development of genetic markers to distinguish …
TRANSCRIPT
DEVELOPMENT OF GENETIC MARKERS TO DISTINGUISH BETWEEN HYBRID
AND PUREBRED ANTELOPE POPULATIONS
By
MAMOKOMA CATHRINE MODIBA
Submitted in partial fulfilment of the requirements for the degree
MAGISTER TECHNOLOGIAE: AGRICULTURE
In the
Department of Animal Sciences
FACULTY OF SCIENCES
TSHWANE UNIVERSITY OF TECHNOLOGY
Supervisor: Prof K.A. Nephawe
Co-Supervisors: Dr D.L. Dalton
Prof A. Kotze
November 2016
i
DECLARATION
I, Miss Mamokoma Cathrine Modiba, hereby declare this dissertation with the title
Development of genetic markers to distinguish between hybrid and purebred
antelope populations have been submitted for the M-Tech degree in Agriculture -
Animal Science at the Tshwane University of Technology and it is my own original
work and has not previously been submitted to any other institution of higher
education. I further declare that all sources cited are indicated and acknowledged by
means of a comprehensive list of references.
Signature Date
ii
DEDICATION
This study is dedicated to my late father Masilo Heniel Modiba and my mother
Elizabeth Modiege Modiba. Thank you for building such a strong and wonderful path
for me and for being my support system in all aspects of my life. Moreover you have
constantly showered me with love and showered me with blessings in your every
night prayers.
iii
ACKNOWLEDGEMENT
I would like to say thank you to the Center for Conservation Science at the National
Zoological Gardens of South Africa (NZG) for providing assistance with the project
(from the laboratory work to statistical analysis of data). Thank you to Dr D.L. Dalton
NZG for your patience and support during my study; and for always understanding
my shortfalls as a student by encouraging me to work beyond my limitations. Thank
you for teaching me how to be a patient writer and I know these skills will greatly
serve me in my future research projects.
Thank you to Prof K.A. Nephawe from the Department of Animal Science, Tshwane
University of Technology (TUT), for great supervision and guidance. Thank you for
your vote of confidence in my abilities. Thanks to Prof A. Kotze from the NZG and Dr
B.J. Mtileni from Department of Animal Science (TUT) for mentoring, support and
patience. I am really thankful and appreciate your effort and guidance throughout my
studies.
To Anri van Wyk and Thabang Madisha, how grateful I am that you took the time to
listen to me and helped me with my studies. The opportunity of working with you and
the knowledge you transferred to me was tremendous. I am also extending my
thanks to Clearance Mnisi, the late Rugter Spies and Andries Phukuntsi for making
each and every step of my study very possible and positive.
I humbly appreciate the National Research Foundation (NRF) in collaboration with
the Department of Science and Technology (DST) for providing funding for my
project.
iv
ABSTRACT
Hybridization resulting from anthropogenic actions has been reported for several
species in South Africa. Conservation authorities and game farmers require the
development of a set of markers for the routine identification of pure and hybrid
individuals in antelope species. In this study, diagnostic markers for the detection of
interspecific hybridization between Lechwe and Waterbuck, Gemsbok and Scimitar-
horned Oryx, and Greater Kudu and Nyala were developed. These six species
belong to the sub-family of the Reducinae, Hippotraginae and Trangelaphini in the
Bovidae family, respectively. A total of 28 samples (eight Lechwe, 13 Waterbuck,
three putative hybrids and four animals of unknown purity) were genotyped at 17
microsatellites. Moreover, 43 samples (15 Scimitar-horned Oryx and 24 Gemsbok, of
which three animals were putative hybrids and one sample had unknown purity)
were genotyped at nine microsatellite markers. These were followed by 66 samples
(30 Greater Kudu and 33 Nyala of which two animals were putative hybrids and one
animal was unknown) genotyped at nine microsatellite markers. STRUCTURE was
used to pre-define and cluster individuals, with the most informative clustering found
at K = 2. GenALEX software was used for population diversity estimates. Genetic
diversity was estimated using expected and observed heterozygosity. High genetic
diversity was detected for Waterbuck, Greater Kudu, Nyala, Gemsbok and Scimitar-
horned Oryx in comparison to Lechwe. Bayesian analysis using STRUCTURE
confirmed nine hybrid individuals. AMOVA confirmed a high proportion of
differentiation between the species. Hybridization was observed to be unidirectional
between the male Lechwe and female Waterbuck, while for the Kudu and Nyala,
Gemsbok and Scimitar-horned Oryx it was bidirectional.
v
TABLE OF CONTENTS PAGES
DECLARATION ........................................................................................................... i
DEDICATION .............................................................................................................. ii
ACKNOWLEDGEMENT ............................................................................................. iii
ABSTRACT ................................................................................................................ iv
GLOSSARY ............................................................................................................. xiii
LIST OF ABBREVIATION ......................................................................................... xv
CHAPTER 1 ............................................................................................................... 1
1 GENERAL INTRODUCTION ............................................................................ 1
1.1 Research problem ......................................................................................... 3
1.2 Aim of the study ............................................................................................. 3
1.3 Objectives of the study .................................................................................. 3
1.4 Hypothesis ..................................................................................................... 4
CHAPTER 2 ............................................................................................................... 5
2 LITERATURE REVIEW .................................................................................... 5
2.1 Taxonomic ranking of the Bovidae family ...................................................... 5
2.2.1 Subfamilies within Bovidae ..................................................................... 6
2.2.2 Bovinae ................................................................................................... 6
2.2.1.1 Greater Kudu (Trangelaphus strepsiceros) .............................................. 6
2.2.1.2 Nyala (Trangelaphus angasii) .................................................................. 8
2.2.2 Hippotraginae ............................................................................................. 9
2.2.2.1 Gemsbok (Oryx gazelle) .......................................................................... 9
2.2.2.2 Scimitar-horned Oryx (Oryx dammah) ................................................... 11
2.2.3 Reducinae ................................................................................................. 12
2.2.3.1 Lechwe (Kobus leche) ........................................................................... 12
2.2.3.2 Waterbuck (Kobus ellipsiprymnus) ........................................................ 14
2.3 Historical distribution .................................................................................... 15
2.4 Taxonomy of antelope species included in this study .................................. 16
2.5 Hybridization ................................................................................................ 18
2.5.1 Anthropogenic hybridization...................................................................... 19
2.5.1.1Hybridization without introgression ......................................................... 19
2.5.1.2 Hybridization with introgression ............................................................. 20
2.5.2 Natural hybridization ................................................................................. 21
2.5.2.1 Natural introgression .............................................................................. 21
vi
2.5.2.2 Natural hybrid taxon ............................................................................... 22
2.5.2.3 Natural hybrid zones .............................................................................. 22
2.6 Fitness consequences of hybridization ........................................................ 23
2.7 Hybridization studies in bovids ..................................................................... 23
2.8 Conservation implications of hybridization ................................................... 24
2.9Molecular techniques used in identifying hybrids .......................................... 24
2.9.1 Microsatellite markers ............................................................................... 25
2.9.1.1Cross species markers ........................................................................... 25
2.9.1.2 Species specific markers ....................................................................... 26
2.9.3Mitochondrial Sequencing Markers (mtDNA) ............................................. 26
2.9.3.1 Cytochrome Oxidase I ........................................................................... 26
2.9.3.2 Cytochrome b Oxidase .......................................................................... 27
2.9.4 Single nucleotide polymorphism ............................................................... 27
2.10 Genetic diversity ........................................................................................ 28
CHAPTER 3 ............................................................................................................. 29
3 MATERIALS AND METHODS ........................................................................ 29
3.1 Ethical approval ........................................................................................... 29
3.2 Samples collection ....................................................................................... 29
3.3DNA Isolation ................................................................................................ 31
3.3.1 DNA isolation from whole blood ................................................................ 31
3.3.2 DNA isolation from blood on FTA® ........................................................... 31
3.3.3 DNA isolation from solid tissue ................................................................. 32
3.3.4 DNA isolation from hair samples ............................................................... 32
3.4 Analysis of purity and concentration ............................................................ 32
3.5 Spectrophotometer (Nanodrop) measuring of DNA purity ........................... 33
3.6 Optimisation of cross species markers ........................................................ 33
3.7 Polymerase chain reaction (PCR) and cross species optimization .............. 34
3.8 Allele scoring ............................................................................................... 38
3.9 Mitochondrial sequencing ............................................................................ 38
3.10 Karyotyping analysis .................................................................................. 42
3.11 Reproduction analysis ............................................................................... 42
3.12 Statistical analysis ..................................................................................... 43
3.12.1 Marker description .................................................................................. 43
vii
3.12.2 Hybrid Identification ................................................................................ 43
3.12.3 Mitochondria analysis ............................................................................. 44
CHAPTER 4 ............................................................................................................. 45
4 RESULTS ....................................................................................................... 45
4.1 NanoDrop analysis ...................................................................................... 45
4.1.1Qubit analysis ............................................................................................ 45
4.2 Marker Optimization ..................................................................................... 45
4.3 Allele scoring analysis ................................................................................. 48
4.4 Interspecific hybridization between the Lechwe and Waterbuck ................. 49
4.4.1 Assessing genetic diversity within Lechwe and Waterbuck ...................... 49
4.4.2 Analysis of molecular variance ................................................................. 50
4.4.3 Estimation of allele’s frequency per population ......................................... 52
4.4.4 Population structure of reference populations ........................................... 55
4.4.5 Identification of admixture individuals ....................................................... 57
4.4.6 Mitochondrial analysis .............................................................................. 59
4.5 Interspecific hybridization between Gemsbok and Scimitar-horned Oryx ... 61
4.5.1 Assessing genetic diversity within Scimitar-horned Oryx and Gemsbok ... 61
4.5.2Analysis of molecular variance .................................................................. 62
4.5.3 Estimation of allele frequencies per population......................................... 63
4.5.4 Population Structure of reference populations .......................................... 67
4.5.5 Identification of admixture individuals ....................................................... 68
4.5.6 Mitochondrial analysis .............................................................................. 69
4.6 Interspecific hybridization between the Greater Kudu and Nyala ................ 71
4.6.1 Assessing genetic diversity within Greater kudu and Nyala ...................... 71
4.6.2 Analysis of molecular variance ................................................................. 72
4.6.3 Estimation of allele frequencies per population......................................... 73
4.6.4 Population Structure Analysis ................................................................... 75
4.6.5 Identification of admixture individuals ....................................................... 76
4.6.6Mitochondrial analysis ............................................................................... 80
4.7 Karyotype analysis .......................................................................................... 83
4.8 Reproduction analysis ..................................................................................... 83
CHAPTER 5 ............................................................................................................. 86
5 DISCUSSION ................................................................................................. 86
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5.1 Identification and development of cross species markers ............................ 86
5.2 Assessing Genetic diversity ......................................................................... 86
5.3 Molecular Variance and gene flow ............................................................... 88
5.4 Assessing of hybrid individuals .................................................................... 88
5.5 Mitochondrial analysis ................................................................................. 89
5.6 Reproductive assessment of the hybrid’s fertility ......................................... 89
CHAPTER 6 ............................................................................................................. 91
6 CONCLUSION ............................................................................................... 91
6.1 Conservation management implications ...................................................... 92
REFERENCE ........................................................................................................... 93
ix
LIST OF TABLES PAGES
Table 3.1: Summary of samples collected for hybrid testing .................................... 30
Table 3.2: Polymerase Chain Reaction conditions used for optimisation of
microsatellite markers .............................................................................................. 34
Table 3.3: Cross species microsatellites selected for testing pure animals and
putative hybrids ........................................................................................................ 36
Table 3.4: List of microsatellite markers used according to plexes (Lechwe and
Waterbuck) ............................................................................................................... 37
Table 3.5: The targeted gene regions for hybrid studies .......................................... 39
Table 3.6: Polymerase Chain Reaction conditions for the amplification of regions of
the mitochondrial genome ........................................................................................ 40
Table 3.7: Conditions used for purification and cycle sequencing ............................ 41
Table 4.1: Amplified markers including amplification temperature and product sizes
................................................................................................................................. 47
Table 4.2: Analyses of genetic diversity for Lechwe and Waterbuck ........................ 50
Table 4.3: Analysis of molecular variance within Lechwe and Waterbuck ................ 51
Table 4.4: Analysis of molecular variance between Lechwe and Waterbuck ........... 52
Table 4.5: Allelic frequency per locus per species (Lechwe and Waterbuck) ........... 52
Table 4.6: Inferred individual’s proportion of ancestry (Lechwe and Waterbuck) ..... 58
Table 4.7: Analyses of genetic diversity for Gemsbok and Scimitar-horned oryx ..... 62
Table 4.8: Analysis of molecular variance within Gemsbok and Scimitar Oryx ........ 62
Table 4.9: Analysis of molecular variance between Gemsbok and Scimitar Oryx .... 63
Table 4.10: Allelic frequency per locus per species (Scimitar Oryx and Gemsbok) . 64
Table 4.11: Inferred individual’s proportion of ancestry (Scimitar Oryx and Gemsbok)
................................................................................................................................. 68
Table 4.12: Analyses of genetic diversity in the Greater Kudu and Nyala ................ 72
Table 4.13: Analysis of molecular variance within Greater Kudu and Nyala ............ 72
Table 4.14: Analysis of molecular variance between Greater Kudu and Nyala ........ 72
Table 4.15: Allelic frequency per locus per species (Greater Kudu and Nyala) ........ 73
Table 4.16: Inferred individual’s proportion of ancestry (Kudu and Nyala) .............. 78
x
LIST OF FIGURES PAGES
Figure 2.1: Taxonomic ranking of the Bovidae family showing the family, subfamily
and genus (Gatesy et al., 1992; Feldhammer et al., 2007). ....................................... 5
Figure 2.2: Male Greater Kudu (Peers, 2009) ............................................................ 7
Figure 2.3: Female Greater Kudu (www.flickr.com).................................................... 7
Figure 2.4: Male Nyala (www.natureartists.com) ........................................................ 8
Figure 2.5: Female Nyala (milestravelingteacher.com) .............................................. 9
Figure 2. 6: Male Gemsbok (Wikimedia.org) ............................................................ 10
Figure 2.7: Female Gemsbok (animalcorner.co.uk) ................................................. 10
Figure 2.8: Male Scimitar-horned Oryx (www.arkive .org) ........................................ 11
Figure 2.9: Female Scimitar-horned Oryx (www.imgbucket.com) ............................ 12
Figure 2.10: Male Lechwe (www.wildlife-pictures-online.com) ................................. 13
Figure 2.11: Female Lechwe (www.arkive.org) ........................................................ 13
Figure 2.12: Male Waterbuck (www.sibuya.co.za) ................................................... 14
Figure 2.13: Female Waterbuck (www.atonsafrica.co.za) ........................................ 15
Figure 2.14: Distribution of the Bovidae species (IUCN, 2008) ................................ 16
Figure 4.1: Optimisation results using marker BM415 for Lechwe and Waterbuck .. 46
Figure 4.2: Analysis using GeneMapper® software to score alleles for marker BM415
................................................................................................................................. 48
Figure 4.3: Results from STRUCTURE harvester plots of mean likelihood L(K) and
difference per K value for Lechwe and Waterbuck populations ................................ 56
Figure 4.4: STRUCTURE histogram depicting pure Lechwe and Waterbuck
populations ............................................................................................................... 56
Figure 4.5: STRUCTURE histogram depicting pure Lechwe and Waterbuck
populations as well as putative hybrids and animals of unknown purity. .................. 57
Figure 4.6: Neighbor-Joining Tree generated between the Lechwe, Waterbuck and
Lechwe/Waterbuck ................................................................................................... 59
Figure 4.7: STRUCTURE harvester plots of mean likelihood L(K) and difference per
K value for Scimitar Oryx and Gemsbok populations ............................................... 67
Figure 4.8: STRUCTURE histogram depicting pure Scimitar Oryx and Gemsbok
populations ............................................................................................................... 67
xi
Figure 4.9: STRUCTURE histogram depicting pure Scimitar Oryx and Gemsbok
populations as well as four putative hybrids. ............................................................ 68
Figure 4.10: Neighbor-Joining Tree generated between Gemsbok and Scimitar Oryx
................................................................................................................................. 70
Figure 4.11: STRUCTURE harvester plots of mean likelihood L(K) and difference per
K value for Greater Kudu and Nyala......................................................................... 76
Figure 4.12: STRUCTURE histogram depicting pure Nyala and pure Greater Kudu
individuals. ............................................................................................................... 76
Figure 4.13: STRUCTURE analysis (performed with K = 2) of microsatellite
genotypes of pure Nyala, pure Greater Kudu and hybrid animals. ........................... 77
Figure 4.14: Maximum likelihood tree generated for Greater Kudu, Nyala and Kudu-
Nyala hybrid ............................................................................................................. 81
Figure 4.15: Maximum likelihood tree generated for Greater Kudu, Nyala and Kudu-
Nyala hybrid ............................................................................................................. 81
Figure 4.16: Images recorded during evaluation of eosin/nigrosin smears (t24) taken
at 1000 magnification ............................................................................................... 84
xii
LIST OF ANNEXURES PAGES
Annexure A: Observed Hardy-Weinberg equilibrium, expected heterozygosity and
observed heterozygosity per locus per lechwe and waterbuck sampled population.
............................................................................................................................... 113
Annexure B: Observed Hardy-Weinberg equilibrium, expected heterozygosity and
observed heterozygosity per locus per gemsbok and scimitar horned oryx sampled
population. .............................................................................................................. 115
Annexure C: Observed Hardy-Weinberg equilibrium, expected heterozygosity and
observed heterozygosity per locus per greater kudu and nyala sampled population
............................................................................................................................... 116
xiii
GLOSSARY
Hybridization: interbreeding of individuals from genetically distinct populations,
regardless of the taxonomic status of the population.
Evolution: biology change in the gene pool of a population from generation to
generation by such processes as mutation, natural selection, and genetic drift.
Admixture: the production of new genetic combinations in hybrid populations
through recombination.
Anthropogenic: human influence in nature
Habitat: the natural home or environment of an animal, plant, or other organism
Endangered: seriously at risk of extinction
Microsatellites: a set of short repeated DNA sequences at a particular locus on a
chromosome, which vary in number in different individuals and so can be used for
genetic fingerprinting.
Mitochondrial DNA: an extra nuclear double-stranded DNA found exclusively in
mitochondria that in most eukaryotes is a circular molecule and is maternally
inherited
Homozygous: having a genotype with two of the same alleles for trait
Heterozygous: having a genotype with different alleles and distinct alleles for the
same trait.
Hybrid: offspring of unlike parents
Genotype: genetic constitution of an organism
Introgression: the transfer of genetic information from one species to another as a
result of hybridization between them and repeated backcrossing.
Conservationist: a person who advocates or acts for the protection and
preservation of the environment and wildlife.
Cytogenetic: inheritance in relation to the structure and function of chromosomes.
Reproduction: the production of offspring by a sexual or asexual process.
Herbivorous: animals that get energy from plants and grasses.
Bovidae: is the biological family of cloven-hoofed, ruminant mammals
Pure population: a population in which there has been no hybridization and
therefore contains only individuals from the parental population.
Linkage equilibrium: the random association of alleles at different loci
Linkage disequilibrium: the non-random association of alleles at different loci
xiv
Unidirectional hybridization: mating always occurs between a female of a species
and a male of another species.
Bidirectional hybridization: mating always occurs between a female of a species
and a male of another species functioning in two directions
Null allele: allele that does not produce a functional product, or a mutation in a
primer site that precludes PCR amplification.
Hybrid swamp: a population of individuals that are hybrids by varying number of
generations of backcrossing with parental types and mating among hybrids or a
population that consists of a high percentage of admixed individuals and a lower
percentage of pure individual
xv
LIST OF ABBREVIATION
MtDNA Mitochondrial DNA
IUCN International Union for Conservation of Nature
Km Kilometres
RAPD Random Amplified Polymorphism DNA
AFLP Amplified Fragment Length Polymorphism
SSR Simple Sequence Random
SNPs Single Nucleotide Polymorphisms
ESA Endangered Species Act
PCR Polymerase Chain Reaction
AMOVA Molecular Variance
SAVC South African Veterinary Council
ml millilitre
µl microliter
ºC degree Celsius
min minute
rcf relative centrifuge force
g-DNA genomic DNA
H2O Water
FTA®
Filter paper
DTT Dithiothreitol
RNA Ribonucleic acid.
A260nm/A280 absorbance
nm Nanometer
mm millimetre
UV ultraviolet
dsDNA double-stranded DNA
Cytb Cytochrome C Oxidase
COI Cytochrome Oxidase I
SSRs Simple Sequence Repeats
STRs Short Tandem Repeat
SSLPs Simple Sequence Length Polymorphisms
DMEM Dulbecco’s Modified Eagle’s medium
xvi
µg/ml microgram per millilitre
M Molar
KCl Potassium Chloride
MgCI2 Magnesium Chloride
mM Millimolar
dNTP Deoxyribonucleotide triphosphate
pmol picomole
ddH2O double-distilled water
t time
g gram
h hour
HWE Hardy-Weinberg equilibrium
Na Number of alleles
He Expected heterozygosity
Ho Observed heterozygosity
1
CHAPTER 1
1 GENERAL INTRODUCTION
Hybridization has been extensively discussed on its role on evolution over the years
by evolutionist (Trigo et al., 2008). Hybridization can be a significant source of
variation and has the potential to create new species (Harrison, 1993; Arnold &
Hodges, 1995). This process has been regarded as an important driving force in the
evolution of most species (Arnold & Hodges 1995). The population dynamics of
hybridization are extremely complex; however, the general consensus is that
anthropogenic hybridization has negative impacts on a population. Hybridization can
occur due to changes in species distribution or as a result of alteration of habitat
which may be accelerated due to global change (Brennan et al., 2015) and
intensified by anthropogenic factors (Allendorf et al., 2001). Unintended hybridization
among species poses different threats to previously distinct populations (Robinson et
al., 2015). Negative consequences of hybridization include outbreeding depression
which will result in a reduction of fitness in the hybrid offspring (Burton et al., 2006)
and disruption of local adaptation (Lynch & Walsh, 1998). Interspecific hybridization,
particularly within Bovidae (antelope, cattle, sheep and goats) is not an infrequent
observation (Robinson et al., 2015).
Hybridization in a natural population has been reported in several large mammals
such as the Kob antelope in Northern Uganda (Masembe et al., 2006) and Sable
antelope in Angola (Masembe et al., 2006). Hybridization between the Bontebok
(Damaliscus pygargus pygargus) and Blesblok (Damaliscus dorcas), led to further
endangerment of the Bontebok populations (Van Wyk et al., 2013). In many cases, it
can be difficult to identify a hybrid morphologically (McDevitt et al., 2009) as hybrids
mostly take the appearance of one parent or the other. An example is hybridization
between the male Eland (Taurotragus Oryx) and the female Greater Kudu
(Trangelaphus strepsiceros), in which hybrid offspring phenotypically resemble the
Eland (Jorge et al., 1976).
The use of molecular methods such as microsatellites and mitochondrial DNA
(MtDNA) sequencing have been highly successful in identifying hybrids and have
2
been used in various hybridization studies. Specifically, microsatellites have been
used successfully in hybridization studies between the Common Waterbuck (Kobus
ellipsiprymnus) and Waterbuck (Kobus defassa) (Lorenzen et al., 2006).
Microsatellites are short tandem repeats which are inherited in two copies by an
individual, one from each parent. They can either be homozygous, meaning the
alleles are the same, or heterozygous, meaning that the alleles are different
(Allendorf & Luikart, 2007). A certain genotype can be found exclusively in a certain
population or species (Selkoe & Toonen, 2006). A population or species can
therefore be identified by the unique or private alleles that are found within that
population or species. An exchange of genotypes can therefore be traced between
species or populations. Hybrids can thus be identified if the animal contains
genotypes that are unique to both species. Moreover, mitochondrial DNA
sequencing has given scientists the ability to infer the ancestral history of an
individual or a population as DNA is inherited maternally (Beebee et al., 2005).
According to Masembe et al. (2006), hybridization has been documented in Kenya
between populations of African Oryx using mtDNA control region Cytochrome-b.
MtDNA has also been reported to be used for species identification, taxonomy and
phylogenetic studies (Hurst & Jiggins, 2005).
Hybrid individuals can either be fertile or sterile; an example is that of hybridization
between Red Hartebeest (Alcelaphus buselaphus) and the Blesbok (Damaliscus
dorcas) (Robinson et al., 1991). This crossing is known to produce sterile offspring
(Van Wyk et al., 2013; Grobler & Van der Bank 1995; Rhymer &Simberloff, 1996).
However, there are many cases were hybrid offspring are fertile, the Blue Wildebeest
(Connochaetes taurinus) and Black Wildebeest (Connochaetes gnou) are an
example (Grobler et al., 2005). This may lead to the hybrids mating back and finally
merging with either related siblings or parent species. It may further lead to
distribution of foreign genes in a population which may affect future reproductive
efforts.
The current study involves the testing of molecular techniques to investigate
hybridization between the Lechwe (Kobus leche) and the Waterbuck (Kobus
ellipsipyranmus), the Greater Kudu (Trangelaphus strepsiceros) and the Nyala
3
(Trangelaphus angasii), the Gemsbok (Oryx gazelle) and the Scimitar-horned Oryx
(Oryx dammah). This study is the first report to document the identification of hybrids
in these species.
1.1 Research problem
Hybridization between abundant and endangered wildlife species is of concern as it
is a threat to endangered species (Cordingley et al., 2009a). Hybridization and
introgression in wildlife species may disrupt the local adaptation (Randi, 2008).
Detection of hybridization can be problematic as hybrids may phenotypically
resemble the parental population. Hybrid species do not have taxonomic status,
therefore they are not protected under the Endangered Species Act (ESA) of 1973
that protects pure wildlife (Hedrick, 2009). The current study intends to generate
useful information that may distinguish between hybrid and pure populations of the
aforementioned species. Thus, the study was designed to contribute new knowledge
which would assist conservationists to develop management plans to ensure pure
populations of wildlife species.
1.2 Aim of the study
The main aim of the study was to develop molecular tools in order to characterize
and distinguish between pure and hybrid antelopes. Furthermore, the study intends
to identify a panel of cross species microsatellite markers in order to evaluate
genetic differences between species which could be useful to detect and monitor the
presence of hybrids in antelope populations.
1.3 Objectives of the study
(i) To develop a panel of microsatellite markers to identify F1 hybrids (first
generation), F2 hybrids (second generation) and further backcrosses of various
antelope species.
(ii) To sequence mtDNA regions in the identified hybrid antelope to determine the
direction of hybridization.
4
(iii) To determine the level of genetic structure and amount of genetic variation
between Lechwe (Kobus leche) and Waterbuck (Kobus ellipsiprymnus); Greater
Kudu (Trangelaphus strepsiceros) and Nyala (Nyala angasii); and the Gemsbok
(Oryx gazelle) and Scimitar-horned Oryx (Oryx dammah).
(iv) To use phenotypic characteristics, conventional cytogenetic and clinical
reproductive assessment of the hybrid’s fertility, in order to verify anecdotal
reports of putative hybridization between a male Greater Kudu and a female
Nyala.
1.4 Hypothesis
(i) A panel of microsatellite markers could be developed to identify F1 hybrids (first
generation), F2 hybrids (second generation) and further backcrosses of various
antelope species.
(ii) Regions of mtDNA in the identified hybrid antelope could be sequenced to
determine the direction of hybridization.
(iii) The level of genetic structure and amount of genetic variation could be
determined between Lechwe (Kobus lechwe) and Waterbuck (Kobus
ellipsiprymnus); Greater Kudu (Trangelaphus strepsiceros) and Nyala (Nyala
angasii); and the Gemsbok (Oryx gazelle) and Scimitar-horned Oryx (Oryx
dammah).
(iv) Phenotypic characteristics, conventional cytogenetic and clinical reproductive
assessment of the hybrid’s fertility could be used to verify anecdotal reports of
putative hybridization between a male Greater Kudu and a female Nyala.
5
CHAPTER 2
2 LITERATURE REVIEW
2.1 Taxonomic ranking of the Bovidae family
Antelopes are herbivorous mammals belonging to the family Bovidae and are
members of the Ruminantia suborder (Feldhammer et al., 2007). Their gestation
length varies; in smaller species it is six months while in larger species it is between
eight and nine months (Walther, 1990;Feldhammer et al., 2007; Vaughn et al.,
2013,). The Bovidae family is divided into eight subfamilies that are distributed
across Africa and Eurasia (Figure 2.1). Animals in each subfamily vary in size, coat
colour and morphology. The Bovidae subfamilies are divided into two clades,
namely, Boodontia which consists of only the Bovinae subfamily and Aegodontia
consisting of subfamilies Antilopinae, Cephalophinae, Reducinae, Caprinae,
Aeycerotinae, Hippotraginae and Alcelaphinae (Vaughan et al., 2013; Vrba et al.,
2000).
Figure 2.1: Taxonomic ranking of the Bovidae family showing the family, subfamily and genus (Gatesy et al., 1992; Feldhammer et al., 2007).
6
2.2.1 Subfamilies within Bovidae
2.2.2 Bovinae
The Bovinae subfamily is divided into two families; Trangelaphini and Bovini. In this
genera there are an approximately 24 species containing four horned antelopes, wild
cattle, bison, Asian buffalo and African buffalo (Estes, 1991; Gentry, 2011a;
Shackleton & Harested, 2010a; Shackleton & Harested, 2010b). They are medium
sized to large antelopes and they feed on forage and grassland. The Greater Kudu
(Trangelaphus strepsiceros) and the Nyala (Trangelaphus angasii) species belong to
the Trangelaphus genus within the Trangelaphini family.
2.2.1.1 Greater Kudu (Trangelaphus strepsiceros)
Greater Kudu males (Figure 2.2) are large in size and statute; females (Figure 2.3)
are smaller in size. Males have large horns that are long and spiral at the end. Only
males have a slightly black face with white ring between the eyes and before the lips.
In colour, the body of the Greater Kudu is brown with white rings on the rump.
Normally they scatter during raining season when there is a sufficient food resource
and during the dry seasons they group together when less food is available
(Huffman, 2004). Greater Kudu feed on leaves, grass, shoots, tuber and fruits.
Females are usually seen with their offspring in smaller groups of six to ten
individuals, while males are generally found scattered or in small group. The sexual
maturity of Greater Kudu begins between one to three years, and mating season
starts end of each rainy season. Greater Kudu have a lifespan of approximately
seven to eight years in the wild and are listed as least concern under the
International Union for Conservation of Nature (IUCN)(Reed & Frankham, 2003).
This species is popular amongst trophy hunters. Natural predators in the wild include
lion, leopard and hyena. This species has a chromosome number of 2n=31 (Dalton
et al., 2014).
7
Figure 2.2: Male Greater Kudu (Peers, 2009)
Figure 2.3: Female Greater Kudu (www.flickr.com)
8
2.2.1.2 Nyala (Trangelaphus angasii)
Nyala are slightly grey in colour and only males have horns. They have long bushy
tails and profuse mane hair on the throat. Both male (Figure 2.4) and females
(Figure 2.5) have continuous white stripes on the body. Male are usually tall at the
shoulders and females are much smaller than the males. Both male and female have
dorsal crest hair at the back until to the end of the tail (Estes, 1999). A common
Nyala has 2n=56 chromosome number (O’Brien et al., 2006). This species is
reported to be very selective in terms of their feeding regimes by grazing during rainy
seasons and feeding on forage during dry seasons. Female Nyala reach sexual
maturity at the age of eleven to twelve months and males at the age of eighteen
months (Huffman, 2004). Their gestation length is approximately seven months. The
species are known to live long in captivity. Female Nyala will normally be seen with
their offspring and adult males are always on their own. Their status is of least
concern but the population is threatened by hunting, predators and habitat loss
(IUCN, 2008).
Figure 2.4: Male Nyala (www.natureartists.com)
9
Figure 2.5: Female Nyala (milestravelingteacher.com)
2.2.2 Hippotraginae
The Hippotraginae subfamily consists of the Gemsbok and the Scimitar-horned Oryx,
belonging to the Oryx genus. Members of the Hippotraginae are generally the largest
antelopes that are commonly native in Africa.
2.2.2.1 Gemsbok (Oryx gazelle)
Gemsbok is light brown in colour with lighter patches on the rump. They have long
back tails and are the largest species in the Oryx genus. Both sexes have long
straight horns (Wurster, 1972; Gallagher & Womack, 1992) and distinctively marked
faces. Their chromosome number is reported to be 2n=56 (Cribiu et al., 1990). The
males (Figure 2.6) have bigger shoulders and are tall; females (Figure 2.7) are
slender with dark brown tails. Gemsboks are grazers, feeding on grasses and forbs if
available. Their gestation is approximately eight and half months. The Gemsbok can
survive for long periods without water.
10
Figure 2.6: Gemsbok (Wikimedia.org)
Figure 2.7: Female Gemsbok (animalcorner.co.uk)
11
2.2.2.2 Scimitar-horned Oryx (Oryx dammah)
The Scimitar-horned Oryx’s common name is taken from the backwards facing
curved horns (Newby, 1978). Male Oryx are much larger (Figure 2.8), while females
(Figure 2.9) are medium sized (Bouin, 1950). Their chromosome number is 2n=58
(Wurster, 1972). Both sexes are white in colour with light brown necks. They have
dark patches on the nose and the neck, and they have long tails. The Scimitar-
horned Oryx are grazers that feed on grass and forbs. The females have partially
divided cervix (Kanangawa & Hafez, 1973) and their gestation length is
approximately eight and half months. The Oryx can migrate over a large distance up
to 13000 kilometres (km) per year (Gillet, 1966). The species is currently extinct in
the wild due to habitat loss and hunting (IUCN, 2002).
Figure 2.8: Male Scimitar-horned Oryx (www.arkive .org)
12
Figure 2.9: Female Scimitar-horned Oryx (www.imgbucket.com)
2.2.3 Reducinae
The Reducinae consists of only three genera; Kobus, Redunca and Pelea. They are
valley grazers and found in watery, wet woodland habitats. The Reducinae subfamily
consists of Lechwe and Waterbuck, and mostly consists of medium and large size
antelopes.
2.2.3.1 Lechwe (Kobus leche)
The Lechwe are medium sized antelopes and only males have horns. Male Lechwe
(Figure 2.10) are bigger than females (Figure 2.11) although they both have small
bodies. The Lechwe is golden brown with white bellies and males are darker brown
in colour. Their habitat preference is marshy areas and they feed on aquatic plants.
They rely on water to escape predators. Rams are territorial whereas ewes are
generally observed with their offspring. Gestation is approximately nine months and
their chromosome number is reported to be 2n=48 (Kingswood et al., 2000).
13
Figure 2.10: Male Lechwe (www.wildlife-pictures-online.com)
Figure 2.11: Female Lechwe (www.arkive.org)
14
2.2.3.2 Waterbuck (Kobus ellipsiprymnus)
The Waterbuck are always found in herds of six to ten individuals. Waterbucks are
the largest members of the Kobus genus (Spinage, 1982). They are sexually
dimorphic animals. The males (Figure 2.12) are larger than the females (Figure 2.13)
(Spinage 1982). Males are recognised by their back curved long horns. The diploid
chromosome number ranges from 2n=50-52in Waterbuck. This variation of
chromosomes maybe influenced by centric fusion of the chromosomes that appear
to be forming an abnormally (Lorenzen et al., 2006). They have long necks and short
back legs which supports their body structure. The Waterbuck males claim territory
as early as the age of five. Waterbucks depend on water to survive; thus their habitat
is never far from a water source. They are predominant grazers with their diet
constituting of 70% grazing (Nowak, 1999). The Waterbuck mature slower compared
to other antelope species (Estes, 1991). Maturity starts at the age of six years and
each herd consists of females and offspring. The gestation is approximately seven to
eight months. Waterbuck are of list concern by the International Union of
Conservation for Nature (IUCN, 2008).
Figure 2.12: Male Waterbuck (www.sibuya.co.za)
15
Figure 2.13: Female Waterbuck (www.atonsafrica.co.za)
2.3 Historical distribution
The Bovidae family consists of species that are distributed around the central south
of Africa. The species habitat varies from dry arid regions to wet woodland. The
distribution maps of the species included in this study are indicated in Figure 2.14.
The Kudu Figure 2.14 A) are distributed in Zambia, Sudan, Ethiopia, Chad, Kenya,
Somalia, Zimbabwe, Botswana, Angola, South Africa and Democratic Republic of
Congo (IUCN, 2008). The Nyala are found in Mozambique, Zimbabwe, South Africa,
Zambia and Botswana (Figure 2.14 E). Figure 2.14 D presents Waterbuck’s
distribution in the eastern southern Africa, Zambia, Democratic Republic of Congo,
Ethiopia, Kenya, Namibia, Tanzania and Uganda, Sudan, Botswana and South
Africa (IUCN, 2008). Figure 2.14C presents Lechwe historical distributed in
Botswana, Angola, Zambia and Democratic Republic of Congo (Wilson et al., 2005).
The Gemsbok is distributed in Namibia, Botswana, South Africa and Zimbabwe
(Figure 2.14 B). The Scimitar-horned Oryx are known to be widespread in Sudan on
the Red Sea all the way to Mauritania on the Atlantic coast (Figure 2.14 F). Currently
the only available Scimitar-horned Oryx (Oryx dammah) is in captivity, e.g. Zoos and
16
private land. The Scimitar-horned and Gemsbok are species that hybridize readily
(Dolan, 1996; Gilbert & Woodfine, 2004).
Figure 2.14: Distribution of the Bovidae species (IUCN, 2008)
(# Kudu map (A), Gemsbok map (B), Lechwe map (C), Waterbuck map (D), Nyala map (E), Scimitar-
horned Oryx map (F).
2.4 Taxonomy of antelope species included in this study
The Kudu are divided into two species; the Greater Kudu (Trangelaphus
strepsiceros) and the Lesser Kudu (Trangelaphus imberbis). They further consist of
three known subspecies; Trangelaphus strepsiceros strepsiceros found at the east of
Africa and South Africa, Trangelaphus chora which are distributed at the northeast of
Africa and Trangelaphus cottoni which are found in the Western Sudan ( Meester &
Setzer, 1971). The Lesser Kudu has no known subspecies. Greater Kudu are the
A B C
D E F
17
second largest antelope after the eland and are closely related to the mountain
Nyala (Trangelaphus buxtoni), Bushbuck (Trangelaphus sylraticus), Sitantunga
(Trangelaphus spekii) and the Bongo (Trangelaphus eurycerus). The Nyala
(Trangelaphus angasii) consists of the Mountain Nyala and the Common Nyala and
both species have no subspecies.
The African Oryx is known to have four species, Gemsbok (Oryx gazelle), Scimitar-
horned Oryx (Oryx dammah), Arabian Oryx (Oryx leucoryx) and East African Oryx
(Oryx beisa). The East African Oryx consists of two subspecies namely; Oryx beisa
beisa and the Oryx callotis (Kingdon, 2001). The African Oryx are distributed in
northern Kenya around Samburu, Tsova National Parks and east of Tanzania (East,
1998). The Oryx callotis and the Oryx gazelle were in the same geographical area
and due to their distribution, the Oryx callotis was misidentified as the subspecies of
the Oryx gazelle (Gatesy et al., 1992; Kingdon, 2001). The African Scimitar-horned
Oryx has no known subspecies.
The Lechwe (Kobus leche) consists of three known subspecies; the Black Lechwe
(Kobus leche smitheni) which are distributed around the Bangweulu Basin in
Namibia, the Kafue flats Lechwe (Kobus leche kafuensis) which occur in the Kafue
flats in Zambia (Halternorth, 1963) and the Nile Lechwe (Kobus megaciros) which
occurs in limited areas in the southern Sudan and western Ethiopia.
Another member of the Kobus genus is the Waterbuck consisting of only two
species; the Kobus ellipsiprymnus and the Kobus defassa. The two species are
different but genetically are known to have the same qualities(Lorenzen et al.,2006).
They can be distinguished by appearance where the Waterbuck ellipsiprymnus has a
grey-brown coat and whiten circles ring rump. The Waterbuck defassa is reddish and
with a white encircled ring neck.
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2.5 Hybridization
Hybridization can be defined as “the interbreeding of individuals from what are
believed to be genetically distinct populations, regardless of taxonomic status of
such populations” (Rhymer &Simberloff, 1996). The positive impacts of hybridization
are that it may potentially generate genetic diversity (Anderson & Stebbins, 1954;
Dowling & Secor, 1997; Barton, 2001). In addition, hybridization can lead to rapid
adaptive evolution of a population which may enhance novel adaptive traits
(Lewontin & Birch, 1966). When genes from different species mix they change and
alter the evolutionary process and the speed of speciation between the species
(Grant, 1994; Arnold, 1997; Dowling & Secor, 1997). Hybridization proved to be a
useful tool for conservation of endangered populations, for example the Florida
panther (Feliscon colorcoryi) was interbred with the closely related Texas Puma
(puma concolor stanleyana) to restore the genetic diversity in the highly endangered
Florida Panther (Hedrick, 1995).
The negative impact of hybridization includes the break-up of locally adapted
genotypes in native species resulting in loss of fitness (Rhymer &Simberloff, 1996;
Allendorf et al., 2001). Additionally, in a local population, hybridization can lead to
loss of unique genes as well as morphological and behavioural characteristics. As a
result, hybrids may be unable to adapt to an ever-changing environment (Randi,
2008).Hybridization has led to the extinction of numerous populations and species
(Wolf, Takebayashi & Rieseberg, 2001), a good example is hybridization between
Mexican ducks (Anasdiazi) and introduced Mallard’s ducks in North America.
Hybridization has resulted in the loss of 'Mexican' ducks as they are all considered
as hybrids (Greig, 1980).In addition, the risk of extinction increases when local
populations are introgressed by gene pools from domesticated animals (Lynch
&O’Hely, 2001).
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2.5.1 Anthropogenic hybridization
Anthropogenic hybridization is a human induced activity on nature; encouraged by
translocations of animals into areas where they do not naturally occur and/or due to
habitat modifications (Allendorf et al., 2001). Anthropogenic hybridization as a result
of translocation or reintroduction has been reported in several species. An example
is between the native red deer (Cervus elaphus) which has hybridized with the
introduced sika deer in Scotland (Cervus nippon); genetic analysis indicated
introgression of genes from both sika and red deer (bidirectional hybridization)
(Goodman et al., 1999). Another example is re-introduction of wild boar from central
Europe to Italy which has encouraged hybridization between the subspecies
Susscrofa majori and Susscrofa scrofa. The authors reported a higher percentage of
hybrids observed within breeding station compared to the percentage of hybrids
within free-ranging wild boar populations (Koutsogiannoul et al., 2008).
The formation of wide-ranging areas for creation of new habitats around the world
has the effect of breaking down barriers of isolation between species (Rhymer
&Simberloff, 1996). Anthropogenic factors have influenced the spread of white-tailed
deer (Odocoileus virginianus) into ranges that are formerly occupied by mule deer
(Odocoileus hemionus), which led to the currently occurring hybridization (Carr et al.,
1986; Cronin et al., 1988). In addition, other forms of habitat modification can lead to
hybridization (Rhymer &Simberloff, 1996). For example, the modification of patterns
of water flows may bring species into contact that has been previously
geographically isolated. Allendorf et al. (2001) described two outcomes of
anthropogenic hybridization namely (i) hybridization with introgression (ii)
hybridization without introgression.
2.5.1.1Hybridization without introgression
Hybridization without introgression often occurs without gene flow between
populations whose individuals are hybridizing due to first generation (F1) hybrids
being born sterile due to parental’ chromosome paring problems during meiosis. For
example, hybridization without introgression has been reported between the Red
20
hartebeest (Alcelaphus buselaphus) and the Blesbok (Damaliscus dorcas) which
produces both sterile male and female hybrids (Robinson, 1991). Bull trout
(Salvelinus confluentus) has been reported to hybridize with brook trout (Salvelinus
fontinalis) in Montana but rarely produces offspring beyond the F1 generation (Leary
et al., 1993; Spruell et al. 2001). A common cross between a female horse (Equus
caballus) and a male donkey (Equus African usasinus) produces a sterile mule
(Zong & Fan, 1989).Hybridization without introgression results in wasted
reproductive effort (Allendorf et al., 2001). Thus sterile hybrids are considered as
evolutionary dead-ends because these hybrids reduce the reproductive potential of
populations and can lead to the extinction of species.
2.5.1.2 Hybridization with introgression
Hybridization with introgression is known as the genetic flow between populations
whose individuals hybridize, encouraged by fertile hybrids. Hybridization with
introgression in many cases produces fertile hybrids that may displace one or both
parental taxa through the production of hybrid swarms (Allendorf et al., 2001). Hybrid
swarms consist of individuals that have interbred with other hybrid individuals or with
pure individuals (Allendorf et al., 2001). The individuals from hybrid swarms might
contain most of their genes from one of the parental taxa and are frequently difficult
to distinguish morphologically from their parental taxon (Leary et al., 1993; Brisbin&
Peterson, 2007). This type of hybridization can be defined as widespread
introgression which refers to the existence of both pure and hybrid individuals within
a population. An example includes a study by Kingdon (1997) who suggested that
hybridization between the more widespread Grivet monkeys (Cercopithecus
aethiopsaethiops) with Bale monkey (Cercopithecus djamdjamensis) is a real threat
for the endangered bale monkey. If hybridization is not detected and conservation
measures are not enforced; populations can become complete admixtures where all
individuals are hybrid (Allendorf et al., 2001). An example of complete admixture by
Goodman et al. (1999) indicates that hybridization between red deer and sika
resulted in complete admixture where the entire population consisted of hybrid
individuals. Widespread introgression and complete admixture occur when hybrids
21
are reproductively fertile and mating of these hybrids cannot be avoided, and
backcrossing with either the parental types or other hybrids (Goodman et al., 1999).
2.5.2 Natural hybridization
Natural hybridization is defined as the second contact between two species
populations that have evolved separately over a long period of time (Genovart,
2009). This can be an essential process in the shaping of the evolution in many plant
and animal species (Genovart, 2009). Allendorf et al. (2001) described the three
outcomes of natural hybridization as (i) natural introgression, (ii) hybrid taxon and (iii)
natural hybrid zones. Natural gene flow between different species or populations can
thus be an important source of genetic diversity. However, natural hybridization can
potentially be harmful in lowering density of a population, as high gene flow can
result in loss of locally adapted alleles or genotypes which can result in the reduction
of the fitness of the population within its local environment (Allendorf et al., 2013). An
example of natural hybridization is between the red-legged (Alectoris rufa) and rock
partridges (Alectoris graeca) in the French contact zone (Bernard-Laurent, 1984;
Randi & Bernard-Laurent, 1999). Natural hybrids have also been reported between
endangered species such as blue whales (Balaenoptera musculus) and fin whales
(Balaenoptera physalus) (Arnason et al., 1991).
2.5.2.1 Natural introgression
Natural hybridization and introgression may lead to the formation of hybrid
phenotypes that are in other cases similar to their parents. It may be difficult for one
to detect introgression based on physical characteristics as backcrossed hybrids
often resemble their parental species. The amount of genetic material from another
parent is normally transferred with each backcross generation, making it impossible
to detect introgression even with genetic techniques (Clack et al., 1998). An example
of natural introgression includes hybridization between the convergent Moorean
22
snails, Partulatainiata and Partulasuturalis, which are distributed on the same
geographic area on the island of Moorea in French Polynesia (Allendorf et al., 2001).
2.5.2.2 Natural hybrid taxon
A hybrid taxon can be described as a historically stable population that due to
inbreeding depression it consists of unique heritable characteristic that comes from
two or more parental taxa. When natural population hybridizes it generates hybrid
individuals that are perceived to have no taxonomic status (Paclt, 1952). There is no
existing evidence that can substantiate the taxonomic status of hybrids. Recent
evidence proposes that all vertebrates might have gone through ancient polyploid; a
process that involved hybridization (Lynch & Conery, 2000). An example of a hybrid
taxon includes the Virgin River round tail chub (Gilaseminude) which is listed as
endangered under the Endangered Species Act of the USA (ESA) (Allendorf et al.,
2001). Hybrid taxon appears to have originated from hybridization between Indian
star tortoises (Geochelone elegans) and giant tortoise (Geochelone robusta) in the
Pleistocene long before human influence in the Colorado River system (De Marais et
al., 1992).
2.5.2.3 Natural hybrid zones
A hybrid zone is a region genetically 'distinct' populations come into contact, mate
and produce hybrids (Barton & Hewitt, 1989). Occurring natural hybrid zones are
found in all major taxa of higher organisms. An example of a natural hybrid zone
between Red and yellow-shafted northern flickers (Colaptes auratus auratus) which
hybridized in the Great Plains of North America narrow where zone extends from
Canada through Texas (USA) and has been historically recorded as stable (Allendorf
et al., 2001). Where hybrids reproduce successful equal to parental types, there is
no assortative mating within the hybrid zone.
23
2.6 Fitness consequences of hybridization
Hybridization may have many effects on fitness of the offspring (Arnold & Martin,
2010). Hybrid progeny may have inferior, superior or similar fitness comparative to
their parents (Arnold &Hodges, 1995; Barton, 2001; Burke & Arnold, 2001). In the
case of hybrid vigor, hybrid progeny has higher fitness than either parental taxa
(Allendorf et al., 2001). Hybrid vigor can be more effectively displayed in many F1
generation hybrids, but can be dissolved in the subsequent generations. Lastly
heterosis may occur in the hybrid progeny whereby deleterious recessive alleles are
protected in hybrids individuals (Allendorf et al., 2001). However, in some cases
hybrids progeny may have lower performance than either parent, due to outbreeding
depression (Lynch & Walsh, 1998). Outbreeding depression occurs when there is
genetic incompatibility between the hybridizing taxa resulting in reduced fitness of a
hybrid to adapt to an environment (Allendorf et al., 2001).
2.7 Hybridization studies in bovids
Several studies on hybridization in bovids have been conducted. Jorge et al. (1975)
reported hybridization between the male Eland (Taurotragus oryx pattersonianus)
and female Kudu (Tragelaphus strepsiceros bea) which resulted in sterile offspring.
Extensive translocation events in the past between subspecies, Bontebok
(Damaliscus pygargus pygargus) and Blesbok (Damaliscus pygargus phillipsi), have
resulted in hybridization between the two subspecies (Van der Walt et al., 2001). In a
similar case, hybridization between Black-wildebeest (Connochaetes gnou) and Blue
Wildebeest (Connochaetes taurinus) has been reported due to trans-location
(Grobler et al., 2005). Hybridization between plain Zebra (Equus burchelli) and Grevy
Zebra (Equus grevy) has been reported since 2004. Hybrid individuals
morphologically appear to be a mix of both the species and the hybridization was
unidirectional (Cordingley et al., 2009). Lastly, hybridization between the Cape
Hartebeest and Blesbok has been reported which resulted in producing a sterile
hybrid (Spear & Chown, 2009).
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2.8 Conservation implications of hybridization
The conservation of pure species was established by the United States of America
Endangered Species Act of 1973 which deemed hybrids of not being worthy of
conservation (O’Brien, 1991). Human interference and the removal of barriers,
translocation or re-introduction of species is a major management problem.
Hybridization without introgression can be wasted reproductive effort, however, it can
still be reversed through removal of all hybrids individuals and non-native species.
What can create species extinction and may be irreversible is hybridization with
introgression where hybrids are fertile which can lead to hybrid vigor where hybrid
fitness is superior. Grobler et al. (2011) suggested the approach of culling all hybrid
individuals to prevent new hybridization activities. The authors suggested that
microsatellite markers should be used to identify pure individuals and translocate
them to a private area. An increase in the pure population size will reduce the
likelihood of a population bottleneck and it will encourage an increase in pure
population size. Pure herds must be maintained with adequate fencing to prevent
overlapping between species (Grobleret al., 2005). An additional approach can be
conducted by providing new management plans in securing the future for the pure
species, by monitoring of hybrids population to assess the fitness of hybrid
individuals and the threat they pose to pure individuals. Management actions should
be allocated directly for conservationists to eliminating a potential threat of
hybridization.
2.9Molecular techniques used in identifying hybrids
Genetic markers are a principle means to study genetic features of an organism.
Since the 1980s, a variety of molecular methods have been developed, including,
Random Amplified Polymorphism DNA (RAPD) (Varghese et al., 1997;
Venkatachalam et al., 2004), Amplified Fragment Length Polymorphism (AFLP)
(Lespinasse et al., 2000), Simple Sequence Random (SSR) (Roy et al., 2004),
Single Nucleotide Polymorphisms (SNPs) (Pootakham et al., 2011), microsatellites
and mitochondria DNA (mtDNA). These markers are developed to study genetic
variation, phylogenetic relationship and genetic linkages (Li et al., 2013). Molecular
25
markers (microsatellites, SNPs and mtDNA) have been used in several hybridization
studies for the detection of hybrid individuals (Scribner et al., 2003).
2.9.1 Microsatellite markers
Microsatellite markers are currently the most popular type of genetic markers for
molecular ecology studies. Microsatellites are known as simple sequence repeats
(SSRs), short tandem repeat (STRs) or simple sequence length polymorphisms
(SSLPs). The tandem repeats of sequence are generally less than 5 base pair (bp)
in length (Bruford & Wayne, 1993). They are highly polymorphic and variable
markers making them useful for assessing population structure, genetic diversity and
inbreeding (Beja-Pereiraet al., 2004). Most commonly used methods for developing
microsatellites markers are cross species markers or species specific markers.
Microsatellites are often used in hybridization studies to provide evidence of
selection (Bos et al., 2008). A hybrid can be detected by an exchange of a unique
genotype between species meaning a hybrid will contain a genotype that is either
one or two species. The use of microsatellites is less time consuming and very
efficient to use.
2.9.1.1Cross species markers
Cross species markers are developed for one specie, and can be used in related
species (Schlotterrer et al., 1991; FitzSimmon et al., 1995; Rico et al., 1996; Gemmel
et al., 1997; Primmer et al., 1996). These microsatellite markers are one of the most
popular markers in ecology studies. They are universal and very transferable from
one species to the next. Cross species markers can be used in closely related taxa
to address studies on population divergence and speciation (Witham et al., 2006).
Grobler et al. (2005) used cross-species markers developed from domestic cattle in
order to identify a number of species-specific alleles in Blue and Black Wildebeest.
The potential success of these marker transfers appear highest in species with long
generation times and mixed breeding (Barbará et al., 2007).
26
2.9.1.2 Species specific markers
These are PCR-based markers of which analysis involves primer sequences that
target the marker regions for amplification (Selkoe & Toonen, 2006). They are
commonly used as sequenced markers, and the primer regions are highly conserved
to an extent that they are invariant within species. They are a specified pair and often
work across wide-range taxonomic groups. These are new primers developed for
each species (Glenn & Schable, 2005). This process of isolating the new
microsatellite markers is faster and less expensive, and reduces the failure rate cost
of new marker isolation in many cases (Glenn &Schable, 2005). They are
recommended in a lot of hybridization studies, an example is the study using
species-specific microsatellite marker to discriminate European Atlantic salmon,
brown trout, and their hybrids (Perrier et al., 2011).
2.9.3Mitochondrial Sequencing Markers (mtDNA)
Mitochondrial DNA represents the genealogy of a certain gene that is presented
maternally. It is of relevance to population and phylogenetic studies and it degrades
slower and evolves faster than nuclear DNA. The animal mitochondrial genome
contains 37 protein coding genes. Analysis of the Cytochrome c Oxidase (Cytb) and
Cytochrome Oxidase I (COI) can be used for barcoding (identification of species)
and in biodiversity studies (Rach et al., 2008). The coding region of the mtDNA has a
higher variable level as compared to the protein-coding genes. An example is a
study using COI and Cytb to detect hybrids in sturgeon populations (Burcea et al.,
2014). The study was able to effectively identify a sturgeon hybrid and also the
maternal ancestry of the individual sturgeon in question.
2.9.3.1 Cytochrome Oxidase I
Cytochrome Oxidase I is the most conserved protein coding genes in the
mitochondrial genome. Cytochrome oxidase has been useful in distinguishing closely
related genera in species identification (Bucklin et al., 1999).Furthermore, there is
evidence that COI sequences are useful in species description and matching
27
boundaries using independent data (Hebert et al., 2003). This region of the mtDNA
genome contains the most leading rate of molecular evolution that is three times
greater than that of 12S or 16S rDNA (Knowlton & Weigt, 1998).
2.9.3.2 Cytochrome b Oxidase
Cytochrome b Oxidase is widely used in studies of divergence at many taxonomic
levels and is considered one of the most useful genes for phylogenetic analysis
(Esposti et al., 1994). It has been suggested as marker of species boundaries in
mammals within the framework of the genetic species (Bradley et al., 2001).
2.9.4 Single nucleotide polymorphism
Information about species genome can be expressed in a complete nucleotide
sequence and those are called Single Nucleotide polymorphism (SNPs). Most of the
differences are due to single base substitution of a nucleotide (Collins et al., 1997).
Advantages of these markers are that they are good resources for mapping complex
genetic traits, cost effective and have high throughput rate. These genetic markers
are used to follow the inheritance patterns of a chromosomal region from generation
to generation (Johnson & Todd, 2000; Risch, 2000). They occur in a coding and non-
coding region of nuclear DNA. They are preferable markers for evolutionary and
population genetics studies and can replace microsatellites markers in studies of
conservation biology. There are several studies using SNPs for assignment of
animals to their country of origin, to determine genetic structure of population and to
identify hybrids within populations. An example is hybridization between the plain
Zebra and the Grevy Zebra using SNPs to determine paternity of hybrids (Cordingley
et al., 2009). SNPs were also used in domestic animals to identify and verify
individuals, parentage and selection of desirable breeding traits (Werner et al.,
2004). However, the disadvantage of SNPs is that they are bi-allelic and thus more
SNPs are required as compared to microsatellites.
28
2.10 Genetic diversity
Genetic diversity is the total number of genetic characteristics in a genetic makeup of
a species. Genetic diversity is one most important aspect in three forms of
biodiversity recognized by the World Conservation Union of Nature (IUCN) as
deserving for conservation (Mc Neely et al., 1990). Genetic diversity is essential for
populations to evolve in regarding to environmental change (Reed & Frankham,
2001). Genetic diversity increases when new individuals are introduced in the
population; then gene flow introduces new polymorphism within a population that
increase population size and generates new genes within a population. In addition,
such a population with higher genetic diversity can adapt easily to changes in
environment due to a higher genetic reservoir (Frankham et al., 2010).
However, a reduced genetic diversity can have several consequences; firstly
inbreeding depression may have a limitation for growth in a population and lower the
probability that influences a population to persist. Secondly, it will limit the ability for a
population to evolve and adapt in change in environment. Thirdly, low genetic
diversity has been seen as bottleneck inclined or a population that is already gone
through bottleneck. There are certain statistical analyses that can allow a study to
measure genetic diversity of a population, those include heterozygosity (a
percentage of heterozygous individuals within a population), allelic diversity (number
of alleles at a locus), and proportion of polymorphic loci (Nei et al., 1975).
29
CHAPTER 3
3 MATERIALS AND METHODS
3.1 Ethical approval
This study was formally approved by the Research Ethics and Science Committee
(RESC) of the National Zoological Gardens of South Africa and by the Tshwane
University of Technology Ethics Committee. The approved project was
“Development and identification of microsatellite marker sets to detect hybridization”
(NZG P10/31).
3.2 Samples collection
Reference samples from pure animals were collected throughout South Africa from
the following species: Lechwe, Waterbuck, Nyala, Kudu, Gemsbok and Scimitar-
horned Oryx. Samples from suspected hybrid individuals were also collected from
Lechwe and Waterbuck, Kudu and Nyala and Gemsbok and Scimitar-horned Oryx.
The samples were allocated unique lab numbers according to species. The sample
collection procedure was conducted in accordance to the guidelines of the South
African Veterinary Council (SAVC) by trained veterinarians. A total number of 137
samples were collected; which includes 80 blood samples, 37 blood on FTA® filter
paper cards (Whatman, NJ, USA), 13 tissue and 7 hair samples, as summarized in
(Table 3.1). A total of 8 Lechwe, 13 Waterbuck, 4 putative hybrid samples and 3
samples of unknown purity were collected. In addition, samples were collected from
24 Gemsbok, 15Scimitar-horned Oryx, 3 putative hybrids and 1 sample of unknown
purity. Lastly, 33 Nyala, 30Greater Kudu, two putative hybrid samples and 1 sample
of unknown purity was also collected.
30
Table 3.1: Summary of samples collected for hybrid testing
Species Collection area Number of samples
Lechwe Limpopo 3
Free State 5
Waterbuck Limpopo 11
Free State 1
Eastern Cape 1
Putative hybrid Free State
Eastern Cape
3
1
Unknown purity Limpopo 3
Scimitar horned Oryx Northern Cape
North West
1
4
Gauteng 10
Gemsbok Northern Cape
Gauteng
Limpopo
16
4
4
Putative hybrid Northern Cape
Gauteng
1
2
Unknown purity Unknown 1
Greater Kudu Gauteng
Free State
3
1
Limpopo 20
Eastern Cape 6
Nyala Unknown 3
Limpopo 30
Putative hybrid Gauteng 2
Unknown purity Unknown 1
Laboratory numbers were used in order to maintain consistency. In the present
study, a panel of cross species markers that could identify pure and hybrid animals
were identified. Furthermore, regions of the mitochondrial genome were sequenced
in order to identify the maternal lineage of hybrid individuals.
31
3.3DNA Isolation
3.3.1 DNA isolation from whole blood
DNA was extracted from blood samples using the ZYMO Genomic DNA™-Tissue
MiniPrep kit, following the manufacturer blood extraction protocol (ZYMO
RESEARCH CORP California, USA). To a 1.5 millilitre (ml) Eppendorf tube, a
volume of 95 microliter (µl) of 2 X Digestion Buffer, 10 µl of Proteinase K and 100 µl
of whole blood was added and vortexed. The mixture was incubated at 55 degrees
Celsius (ºC) for 20 minutes. A volume of 700 µl of Genomic Lysis Buffer was then
added and the mixture was vortexed. This step was followed by centrifugation at 16
000 relative centrifuge force (rcf) for one minute. The supernatant was then
transferred to a Zymo–Spin™ II Column inside a collection tube and centrifuged for
16 000 rcf for one minute. DNA Pre-Wash Buffer, at a volume of 200 µl was added
and the column was centrifuged for 16 000 rcf for 1minute. The flow-through was
discarded and 400 µl of genomic DNA (g-DNA) Wash Buffer was added to the
column before centrifugation for 1 minute. The column was transferred to a new 1.5
ml Eppendorf tube and 50 µl DNA Elution Buffer was added to the column and the
column was centrifuged to elute the DNA.
3.3.2 DNA isolation from blood on FTA®
DNA samples from blood on FTA® were extracted using ZYMO GENOMIC DNA™-
Tissue MiniPrep kit (ZYMO RESEARCH CORP California, USA).The solid tissue
extraction protocol was used. A total of 95 µl of H2O, 95 µl 2x Digestion Buffer and
10 µl of Proteinase K was added to an eppendorf tube with a piece of FTA®.
Following this, the tube was vortexed to mix the solution and was incubated at 55ºC
for 1-2 hours to allow the blood to dissolve from the filter paper into the solution. A
total of 700 µl of Genomic Lysis Buffer was added to the tube and this was mixed
thoroughly by vortexing. The mixture was then centrifuged at 16 000 rcf for one min.
The solution was transferred to a Zymo-spin™ IIC Column in a new collection tube.
Following this step, the column was centrifuged at 16 000 rcf for one minute. A total
of 200 µl of DNA Pre-wash Buffer and 400 µl of g-DNA Wash Buffer was added and
32
the column was centrifuged at 16 000 rcf for one min. Lastly, the spin column was
transferred into a new micro centrifuge tube and 75 µl DNA Elution Buffer was added
prior to centrifugation to elude the DNA.
3.3.3 DNA isolation from solid tissue
DNA samples from solid tissue were extracted using ZYMO GENOMIC DNA™-
Tissue MiniPrep kit (ZYMO RESEARCH CORP California, USA). The solid tissue
extraction protocol was used. Added were 95 µl of H2O, 95 µl 2x Digestion Buffer
and 10 µl of Proteinase K into a 1.5 ml tube which was vortexed and incubated
overnight for the tissue to dissolve. Following this step, similar protocol was followed
as discussed in Section 3.3.2.
3.3.4 DNA isolation from hair samples
DNA from hair samples was extracted using ZYMO GENOMIC DNA™-Tissue
MiniPrep kit (ZYMO RESEARCH CORP California, USA), using the hair extraction
protocol. For this protocol added was 90 µl of H2O, 90 µl 2 x Digestion Buffer, 10 µl
Dithiothreitol (DTT) (1 M) and 10 µl of Proteinase K. The solution was vortexed and
incubated overnight for the hair samples to dissolve. Following this step, similar
protocol was followed as discussed in Section 3.3.2.
3.4 Analysis of purity and concentration
The concentration of the extracted DNA samples was determined using the Thermo
Scientific Qubit™ fluorometer (Thermo Fisher Scientific, Wilmington USA) to quantify
the DNA, RNA and protein. This equipment uses fluorescent dyes to determine the
concentration of nucleic acids and proteins. The kit provides a concentrated assay
reagent, dilution buffer and pre-dilution DNA standard. Tubes of 0.5 µl were prepared
to the equivalent number of samples that were used. The Qubit solution was
prepared by adding a working dilution of 1:200 in a Qubit dsDNA H Buffer, to make a
final concentration volume of 200 µl solution inside a 0.5 µl PCR tube. The dilution
was 198 µl of the solution mixture and 2 µl of DNA sample was then vortexed. The
33
solution was incubated at room temperature for 2 minutes. The machine was
standardized by loading standard 1 and 2, followed by measuring of the DNA
samples to obtain calculated results of DNA concentration.
Formula: Concentration of sample = QF value X(200
𝑥)
3.5 Spectrophotometer (Nanodrop) measuring of DNA purity
The extracted DNA was analyses for purity using a Thermo Scientific NanoDrop™
(Thermo Fisher Scientific, Wilmington, Delaware USA), a tool used to assess
nucleotides, DNA, ribonucleic acid (RNA) and certain protein. The ratio of the
absorbance (A) is set at A260nm/A280nm (Nanometer) to assess the purity of the
DNA samples. The absorbance of the sample at A260nm is represented as it
measures with a conventional 10 millimetre (mm) path. The absorbance at A280nm
may indicate it presence of protein, or other contaminants that absorb strongly at or
near 280. The ultraviolet (UV) represents the general measurement of the
spectrophotometer. The nucleic acid method was used to measure the DNA at
wavelength. All isolated DNA is required to be at a ratio of approximately 1.8-2.0 at
A260/A280, if lower the sample may be contaminated by proteins.
3.6 Optimisation of cross species markers
A total of 30 autosomal cross-species microsatellite markers developed for cattle
(Bos Taurus), goats (Capra aegagrus hircus) and sheep (Ovis aries) were randomly
selected for synthesis by polymerase chain reaction (PCR) amplification. Subsets of
six samples for each species were selected in order to optimise the markers.
Polymerase chain reaction was performed for each primer set. A total of three
Magnesium chloride (MgCl2) concentrations (1.3 mM, 1.5 mM and 2 mM) and six
annealing temperatures (40, 45, 50, 55, 58 and 60) were tested in a 3 × 6 factorial
design that resulted in 18 different combinations of PCR cycles and MgCl2
concentrations. The PCR protocol used to optimize all primer sets is indicated on
(Table3.2). Amplification was achieved using a T100™ Thermal cycler (Thermo
Fisher Scientific, Wilmington USA). PCR products where then subjected to 2%
34
agarose gel (Seakem®) electrophoresis containing gel stain (SYBR® safe) in order to
determine the optimized MgCl2 concentration and annealing temperature. Both 5 µl
of Gene Ruler™ DNA ladder (Thermo Fisher Scientific, Wilmington, Delaware USA)
and 5 µl of each PCR sample were loaded onto the gel. The Gel DOC™ (Bio-Rad
Laboratories Inc.) was used to visualise the amplification product size on the gel.
Table3.2: Polymerase Chain Reaction conditions used for optimisation of microsatellite markers
Steps Cycles steps Temperature Time Number of cycles
Step1 Initial denaturing 95ºC 5 min 1
Denaturing 95ºC 30 sec 30
Step2 Annealing 45-58ºC 30 sec 30
Extension 72ºC 1 min 30
Step3 Final extension 72ºC 60 min 1
Step 4 Hold 4 Overnight 1
# Min = Minute; Sec = Seconds and °C = Degree Celsius
3.7 Polymerase chain reaction (PCR) and cross species optimization
Following PCR optimization, microsatellite markers on Table 3.3 were amplified for
each sample. Of the thirty microsatellites markers that were tested, amplification was
successful for eighteen markers. A total of seventeen markers amplified for Lechwe
and Waterbuck, nine markers amplified for Greater Kudu and Nyala, followed by nine
markers that amplified in Gemsbok and Scimitar-horned Oryx. A panel of eighteen
duplicated autosomal markers was used and plexed according to sizes and
fluorescent label for the Lechwe and Waterbuck, Kudu and Nyala and Gemsbok and
the Scimitar-horned Oryx (Table 3.4). PCR was performed in a 12.5 µl final reaction
master mix in a 0.2 µl PCR tube with a working concentration of 2 x PCR buffer, 2
mM of MgCI2, 2 mM of Deoxyribonucleotide triphosphate (dNTP) mixture,
10picomole (pmol) of the forward and reverse primers, 5-unit of GoTaq® (Flexi
Promega Corporation, Madison, WI, USA) DNA polymerase, containing 50%
Glycerol buffer designed for amplification, 2 µl double-distilled water (ddH2O) and 2.5
35
µl template DNA. The DNA regions were amplified in a T100™ Thermal cycler (Bio-
Rad) following the conditions saved on the Bio-Rad.
36
Table 3.3: Cross species microsatellites selected for testing pure animals and putative hybrids
Primer Forward (5' to 3') Reverses (5'to 3') Colour Size (bp) Reference
TGLA263 CAA GTG CTG GAT ACT ATC TGA CGA TTA AAG CAT CCT CAC CTA TAT ATG C PET 120-170 Bishop et al 1994
OARFCB304 CCC TAG GAG CTT TCA ATA AAG ATT CGG
CGC TGC CAA CTG GGT CAG GG NED 90-190 Buchanan & Crawford 1993
ILST087 AGC AGA CAT GAT GAC TCA GC CTG CCT CTT TTC TTG AGA GC PET 140-200 Bishop et al 1994
MCM527 GTC CAT TGC CTC AAA TCA ATT C AAA CCA CTT GAC TAC TCC CCA A VIC 100-200 Hulmeet al 1994
BM1329 TTG TTT AGG CAA GTC CAA AGT C AAC ACC GCA GCT TCA TCC PET 116-190 Bishop et al 1994
BMS4008 CGG CCC TAA GTG ATA TGT TG GAA GAG TGT GAG GGA AAG ACT G VIC 140-240 Bishop et al 1994
BM3517 GTG TGT TGG CAT CTG GAC TG TGT CAA ATT CTA TGC AGG ATG G NED 100-150 Steffen et al 1993
BM1443 AAT AAA GAG ACA TGG TCA CCG G TCG AGG TGT GGG AGG AAG PET 80-160 Bishop et al 1994
ETH10 GTT CAG GAC TGG CCC TGC TAA CA CCT CCA GCC ACT TTC TTC TC VIC 200-250 Toldoet al 1993
BM2113 GCT GCC TTC TAC CAA ATA CCC CTT CCT GAG AGA AGC AAC ACC VIC 124-146 Sundenet al 1993
BM804 CCA GCA TCA ACT GTC AGA GC GGC AGA TTC TTT GCC TTC TG FAM 120-190 Bishop et al 1994
BM415 GCT ACA GCC CTT CTG GTT TG GAG CTA ATC ACC AAC AGC AAG FAM 130-200 Bishop et al 1994
DIK020 AAG AAA GTC CCT ACC ATG AG AAC CAG TAA TCG TGA GAG GA VIC 120-180 Bishop et al 1994
BM757 TGG AAA CAA TGT AAA CCT GGG TTG AGC CAC CCA AGG AAC C FAM 140-200 Bishop et al 1994
BM203 GGG TGT GAC ATT TTG TTC CC CTG CTC GCC ACT AGT CCT TC FAM 200-250 Bishop et al 1994
MTGT4 GAG CAG CTT CTT TCT TTC TCA TCTT GCT CTT GGA AGC TTA TTG TAT AAAG PET 100-200 Georges & Messy 1992
37
Table 3.4: List of microsatellite markers used according to plexes (Lechwe and Waterbuck)
Species Plexes Locus Dye Size (bp)
Lechwe and Waterbuck Plex 1 ILst87 PET 140-200
OARFCB304 FAM 90-190 BM804 VIC 120-190 BM4008 NED 140-240 Plex 2 ETH10 VIC 200-250 BM2113 FAM 124-146 BM3571 NED 100-150 BM1443 PET 80-160 Plex 3 DIK020 VIC 120-180 BM415 FAM 130-200 MTGT4 PET 100-200 INRA128 NED Plex4 MCM527 VIC 100-200 BM203 FAM 200-250 TGLA263 PET 120-170 Plex 5 BM757 FAM 140-200 BM1329 PET 116-190
Kudu and Nyala Plex 1 SRCRSP8 NED 230-250 BMC3224 FAM 170-200 ILST87 PET 110-160 Plex 2 BM1329 PET 140-165 BM719 VIC 140-155 Plex 3 BM203 FAM 210-240 BM2113 FAM 110-130 Plex 4 OARCP26 FAM 120-190 ETH10 VIC 200-210
Gemsbok and Oryx Plex 1 BMC3224 VIC 180-210 SRCRSP8 NED 220-240 ILST87 PET 135-160 BM2113 VIC 120-130 Plex 2 BM719 VIC 150-160 BM757 FAM 170-180 BM1329 PET 120-160 Plex 3 BM203 FAM 210-240 MCM527 VIC 150-170 OARCP26 FAM 130-150
A volume of 9 µl of GeneScan™ 500 LIZ Applied Biosystems Fluorescence’s and Hi-
Di™ Formamide (Applier Corporation, Foster City, CA, USA) mixture was added to 1
µl of sample and the samples were loaded into a 96 well plate to be analyzed on an
Applied Biosystems®3130xI Genetic Analyzer (Thermo Fisher Scientific, Wilmington
DE. USA).
38
3.8 Allele scoring
GeneMapper® software (Applied Biosystems) was used to analyze the fragments
that were generated during PCR. This software was used to score alleles by
genotype. Genotyping is a process used to determine genetic variants that each
individual possesses. An acceptable allele is scored by a peak that is greater than
1000 RFU. Polymerase chain reaction was conducted using microsatellite markers
consisting of dye-labelled primers (Thermo Fisher Scientific); FAM™ (Blue), VIC®
(Green), PET® (Red) and NED™ (Black). Markers were multiplexed according to the
product size and fluorescent dye. Analysis was conducted using GeneMapper®4.0
software (Applied Biosystems) and a bin builder was created to score alleles. A bin
builder algorithm is designed to enhance the scoring of each allele and those alleles
are assigned to respective bins. GeneMapper®4.0 software (Applied Biosystems) is
able to identify the fragment size of the PCR product for each primer according to the
primer dye.
3.9 Mitochondrial sequencing
Regions of the MtDNA Cytochrome c oxidase (COI) and Cytochrome oxidase (Cytb)
were amplified and sequenced (Table 3.5). The primers used for amplification of the
COI region were LCOI490 5'-GGTCAACAAATCATAAAGATATTGG-3’ and HCO2198
5'-TAAACTTCAGGGTGACCAAAAAATCA-3’ for the Lechwe and the Waterbuck.
The primers used to amplify Cytb region in Gemsbok and Scimitar-horned oryx and
the for Greater Kudu and Nyala L14724 5’CGAAGCTTGATATGAAAACCATCGTTG-
3' and H15495 5’-AAACTGCCAGCCCCTCAAGAATGATATTGTCCTCA-3’. The
selected markers have been reported to be universal in mammals. Sequencing was
conducted using the manufacturer protocol (ZYMO RESEARCH CORP California,
USA). The polymerase chain reaction was performed using THERMO SCIENTIFIC™
DreamTaq with a volume of 12.5 µl per 1 µl of sample. This was followed by adding
of 10 pmol of forward and reverse primer and 9.5 µl of H2O. The PCR product was
amplified in a T100™ Thermal cycler using conditions listed in Table 3.6.
39
Table 3.5: The targeted gene regions for hybrid studies
Gene Forward Sequences Reverse Sequences Reference
COI BatL5310 5'CCTACTCRGCCATTTTACCTATG3' R6036R 5'ACTTCGGGTGTCCAAAGA3' Robinsetal2007
LC01490 5'GGTCAACAAATCATAAAGATATTGG3’ HC02198 5'TAAACTTCAGGGTGACCAAAAAATCA3' Bitanyiet al 2011
Ctyb L14724 5'CGAAGCTTGATATGAAAACCATCGTTG3' H15149 5'AAACTGCCAGCCCCTCAGAATGATATTTGTCCTCA3' Hseishet al2001
D-loop L15925 5' TACACTGGTCTTGTAAACC3' H15915 5'GTCTTGTAAACCTGAAATG3' Schartet al 2006
16S 16SA 5'CGCCTGTTTAACAAAAACAT3' 16SB 5'CTCCGGTTTGAACTCAGATC3' Palumbiet al 1991
40
Table 3.6: Polymerase Chain Reaction conditions for the amplification of regions of
the mitochondrial genome
Steps Cycles steps Temperature Time Number of cycles
Step1 Initial 94ºC 5min 1
Step2
Denaturing 94 ºC 30sec
Annealing 58 ºC 10sec 10
Extension 72 ºC 1min 30
Step 3
Denaturing 94 ºC 30sec
Annealing 55 ºC 30sec 15
Extension 72 ºC 1min 30sec
Step 4
Denaturing 94 ºC 30sec
Annealing 50ºC 30sec 20
Extension 72 ºC 1min 30sec
Step 5 Final extension 72 ºC 10min 1
Step 6 Hold 4 Overnight 1
# Min =Minute, Sec =Seconds and °C= Degree Celsius
Following confirmation of amplification on a 2% agarose gel (Seakem®
)
electrophoresis containing gel stain (SYBR®
safe) samples were purified using 0.25
µl of FastAP™ (Thermosensative alkaline phosphate) and 1µl THERMO
SCIENTIFIC™ Exonuclease. Cycle sequencing was performed with a master mix of
2.25 µl of Big Dye® and Cycle sequencing were conducted using a T100™ Thermal
cycler using the conditions listed in (Table 3.7).
41
Table 3.7: Conditions used for purification and cycle sequencing
Procedure Steps Cycles steps Temperature Time Number of
cycles
Purification Step 1 Initial 37ºC 15 min 1
Step 2 Denature 85ºC 15 min 1
Cycle
sequencing
Step1 Initial
denaturing 94ºC 2 min 1
Denaturing 85ºC 10 sec
Step2 Annealing 50ºC 10 sec 40
Extension 60ºC 2 min 30 sec
Step 4 Hold 4 ºC Overnight 1
# Min =Minute, Sec =Seconds and °C= Degree Celsius
The last step was carried out using ZR DNA Sequencing Clean-Up™ Kit (ZYMO
RESEARCH CORP California, USA), 240 µl of Sequencing Binding Buffer was
added inside a 10 µl of sequencing reaction and the mixture was mixed using
manual pipetting. The mixture was loaded into a Zymo-Spin™ IB Column, which was
placed inside a 2 ml collection tube centrifuged at 16 000 rcf for 30 sec. A total of
300 µl Sequencing Wash Buffer was added to a column. The Zymo-Spin™ IB
Column was placed into a new 1.5 ml tube. A total of 10 µl of the HiDi-Formamide
was added to elute the DNA and the column was centrifuged at 16 000 rcf for 30
sec. The DNA was loaded on an Applied Biosystems®3130xI Genetic Analyzer for
analysis.
42
3.10 Karyotyping analysis
Karyotyping was performed only on the putative Kudu /Nyala hybrid sample.
Fibroblasts were cultured using skin biopsies and established conventional tissue
culture techniques. Cells were grown at 37ºC in Dulbecco’s Modified Eagle’s medium
(DMEM) enriched with 15% bovine fetal serum. Colcemid 0.01 microgram per
millilitre (µg/ml) was added 60 min before harvest. Hypo-tonic treatment 0.075 Molar
(M) of Potassium chloride (KCl) and fixation (3:1; methanol: acetic acid) followed
standard protocols. Air-dried meta-phase preparations were made and stained with
Giemsa.
3.11 Reproduction analysis
The internal and external reproductive organs of a Kudu bull were examined by
means of ultrasonography (Mindray Medical International Ltd.). All of these
procedures were conducted by the reproductive biologists of the National Zoological
Gardens of South Africa. This included palpation of the external and internal organs
to establish the presence of abnormalities. Individual testicular length and
circumference were measured with a calliper. Semen was collected by means of
electro-ejaculation using a portable battery operated (El) Torro electro-stimulator
(Electronic Research Group) following conventional techniques (Crosier et al., 2006).
Samples were evaluated microscopically at a 200 magnification at 37ºC immediately
after collection. Two sets of eosin/nigrosin smears were made. One set was made
immediately (time) (t0) and set two (t24) was made 24 hours after ejaculation. These
smears were examined under oil at 10009 magnifications with phase contrast. For
smears made at t24 the collected ejaculate was kept at 5ºC overnight in an upright
position to allow the formation of sediment. After centrifugation at 300gram (g) for 15
min, aliquots were collected from the bottom of the tubes and a smear was made
and evaluated microscopically. Whole blood samples were centrifuged (300g for 15
min) and recovered serum stored at -20ºC until hormone analysis. Testosterone
concentrations were determined by radioimmunoassay using a Coat-a-Count
commercial kit for total testosterone (Diagnostic Products Corporation) as previously
described (Newell-Fugate et al., 2012).
43
3.12 Statistical analysis
3.12.1 Marker description
MICRO-CHECKER version 2.3.3 (Van Oosterhout et al., 2003-2005) was used for
the processes of identification and isolation using primers and amplification by PCR
that can occur due to the following errors: (i) Null alleles – one or more alleles fail to
amplify during PCR, (ii) Stuttering –changes occur in the allele sizes during PCR, (iii)
Large allele dropout – large alleles do not amplify as efficiently as small alleles.
GenALEX version 6 (Peakell & Smouse, 2006) was used for population analysis to
determine the population variation using genetic markers. It provides frequency-
based F-statistics, heterozygosity, Hardy Weinberg, population assignment,
relatedness and distance-based analyses (Peakell & Smouse, 2006).
Statistical tests were performed in ARLEQUIN version 3.11 (Excoffier et al., 2006)
using microsatellite allele data to provide random association between alleles at a
different locus. The statistical test implemented uses a Monte Carlo to test Hardy-
Weinberg equilibrium theory of ARLEQUIN and it calculates Linkage disequilibrium-
test of non-random association of alleles at different loci. AMOVA was also
performed for different hierarchical analyses of molecular variance to evaluate
population genetic structure. Also pairwise genetic distances FST based genetic
distances were computed.
3.12.2 Hybrid Identification
STRUCTURE version 2.3.4 (Pritchard et al., 2006) was used to identify and confirm
hybrid individuals. This software is a model based Bayesian clustering algorithm that
can infer genetic relationships between populations. STRUCTURE parameters were
set to run for five replicates from K = 1-10, with a run-length of 100,000 repetitions of
Markov Chain Monte Carlo (MCMC), following the burn-in period of 10,000 iterations.
The five values for the estimated Ln (Pr (X\K)) were averaged, from which the
posterior probability were calculated. The average proportion of membership (QI) of
44
individuals to the inferred clusters was determined using the threshold of qI>0.90
(Barilani et al., 2007).
3.12.3 Mitochondria analysis
MEGA6® (Tamura et al., 2013) was used for the alignment of sequences to construct
a phylogenetic tree. The evolutionary history was inferred by using Neighbor-Joining
method (Saitou &Nei, 1987). The percentage of replicate trees in which taxa is
clustered together in the bootstrap test was set to 10000 replicates. The evolutionary
distances model was computed using the Kimura 2-parameter method (Kimura,
1980). BLAST (www.ncbi.nm.nih.gov/blast) was used to confirm and identify the
chromatograms of sequences.
45
CHAPTER 4
4 RESULTS
4.1 NanoDrop analysis
Results for DNA purity and concentration for reference and putative hybrid samples
for Greater Kudu, Nyala, Lechwe, Gemsbok, Scimitar-horned Oryx and Waterbuck
ranged from 0.10 nanogram per microliter (ng/µl) to 14.40 ng/µl. The calculated
absorbance ratio of A260/A280 for purity ranged from 1.8 to 2.23 with one sample
having a ratio of 4.11. Values higher than 2 indicates presence of salts and values
less than 1.8 indicates presence of protein or phenol and contaminants that absorb
strongly at or near 280 nm.
4.1.1Qubit analysis
The results for concentration of the isolated DNA was analysed using the Qubit®
fluorescent dyes, for double stranded DNA. The DNA concentration for samples
ranged from 6.16 ng/ml to 142 nanogram per millimetre (ng/ml).
4.2 Marker Optimization
The results obtained from the gel electrophoresis by optimizing markers for the
Lechwe and Waterbuck at various annealing temperatures ranging from 45ºC to
58ºCand adjusted MgCl2 concentrations were tested 2mM. The optimization for the
following marker BM415 amplified at 55ºC and the product sizes were in the
expected range of 100 to 300 base pairs (bps). Figure 4.1 shows a single fragment
on the agarose gel with primer dimers absent or barely visible. Table 4.1 shows
results of all amplified markers for the Lechwe and Waterbuck, the Kudu and Nyala
and the Gemsbok and Scimitar-horned Oryx and their standard size.
46
Figure 4.1: Optimization results using marker BM415 for Lechwe and Waterbuck
(#Note: Samples shown on the gel electrophoresis indicating Lechwe are represented by LEC,
Waterbuck represented by WTB, and control sample represented by C with adjusted annealing
temperature from 45ºC to 55 ºC and MgCl2 concentration of 2 mM)
N
54ºC DNA ladder
WTB LEC C WTB LEC C WTB LEC C WTB LEC C
45°C 48°C 50°C 55°C
45°C
47
Table 4.1: Amplified markers including the amplification temperature and product sizes
Species Annealing Temperature
Locus Dye Size (bp)
Lechwe and Waterbuck 55ᵒC ILst87 PET 140-200
55ᵒC OARFCB304 FAM 90-190
54ᵒC BM804 VIC 120-190
54ᵒC BM4008 NED 140-240
55ᵒC ETH10 VIC 200-300
55ᵒC BM2113 FAM 124-146
55ᵒC BM3571 NED 100-150
54ᵒC BM1443 PET 80-160
55ᵒC DIK020 VIC 120-180
55ᵒC BM415 FAM 130-200
55ᵒC MTGT4 PET 100-200
58ᵒC INRA128 NED 100-190
55ᵒC MCM527 VIC 100-200
55ᵒC BM203 FAM 200-250
55ᵒC TGLA263 PET 120-170
55ᵒC BM757 FAM 140-200
55ᵒC BM1329 PET 116-190
Kudu and Nyala 45ᵒC SRCRSP8 NED 230-250
45ᵒC BMC3224 FAM 170-200
50ᵒC ILST87 PET 110-160
45ᵒC BM1329 PET 140-165
45ᵒC BM719 VIC 140-155
50ᵒC BM203 FAM 210-240
50ᵒC BM2113 FAM 110-130
50ᵒC OARCP26 FAM 120-190
50ᵒC ETH10 VIC 200-210
Gemsbok and Oryx 45ᵒC BMC3224 VIC 180-210
48ᵒC SRCRSP8 NED 220-240
48ᵒC ILST87 PET 135-160
48ᵒC BM2113 VIC 120-130
50ᵒC BM719 VIC 150-160
48ᵒC BM1329 PET 120-160
45ᵒC BM203 FAM 210-240
50ᵒC MCM527 VIC 150-170
50ᵒC OARCP26 FAM 130-150
48
4.3 Allele scoring analysis
An acceptable allele is represented by a peak between 1000 to 2000 relative
fluorescence units (RFUs). As shown in Figure 4.2 (A), results of genotyping of
marker BM415 displays two alleles 136 and 142 as two peaks. This indicates a
heterozygous individual and shows an individual has inherited two sets of alleles one
from the paternal side and the other from the maternal side. On Figure 4.2 (B) a
single peak is observed which indicates a homozygous individual. Meaning an
individual has inherited one type of allele from both parents.
A.
B.
Figure 4.2: Analysis using Gene Mapper® software to score alleles for marker
BM415
(#Note: A = represent heterozygous individual and B = representative homozygous individual).
49
4.4 Interspecific hybridization between the Lechwe and Waterbuck
4.4.1 Assessing genetic diversity within Lechwe and Waterbuck
Within the reference populations, monomorphic loci, BM2113, TGLA263, BM804,
MCM527, BM415, BM203, DIK020, MTGT4 and OARFCB304, were observed for
Lechwe and BMS4008, ETH10, MCM527 and MTGT4 for Waterbuck. These
markers were excluded from further analysis of genetic diversity as no variations
between alleles were observed.
Probabilities of significance for deviations from Hardy Weinberg equilibrium were
estimated and results are provided in Annexure A. Within the reference Lechwe
populations, two markers (BM3517 and ETH10) were not in HWE in the Limpopo
population and two markers (BM3517 and BM1329) for Free State population. Within
the reference Waterbuck population, two markers (INRA128 and OARFCB304) were
not in HWE. The Lechwe reference population displayed heterozygote deficiency per
locus, meaning lower heterozygosity influenced by the Walhund effect that is when
an organism has two different alleles at a locus.
The number of alleles (Na) ranged from 1 to 2.9, expected (He) ranged from 0.235 -
0.523 and observed (Ho) ranged from 0.382 - 0.550 respectively, with the highest
variation observed in Free State samples (Table 4.2). These values are in line with
other antelope studies of Arabian Oryx measuring genetic diversity using
microsatellites markers, which displayed a low expected heterozygosity (He=0.565)
and a high observed heterozygosity (Ho=0.601) (Arif et al., 2010). In addition, the
study showed that the high level of observed heterozygosity was influenced by
higher density of the Arabian Oryx population (Marshall et al., 1999). Marshall (1999)
also pointed out that though there was loss of genetic variation within the Arabian
Oryx, a significant genetic variation quantity still remains owing to exchanging of the
species among different breeding programs. In most cases observed heterozygosity
was higher than expected heterozygosity, indicating that the population was avoiding
inbreeding via random mating.
50
Within the reference Lechwe population as shown in Table 4.2, Na varied from 1.6 to
2.3, He varied from 0.139 - 0.324 and Ho varied from 0.137 - 0.250 with Free State
samples displaying the lowest heterozygosity. In the Lechwe populations, Ho was
lower than He indicating possible inbreeding (Falconer & Mackay, 1996; Frankham,
1996; Keller & Waller, 2002).
Table 4.2: Analyses of genetic diversity for Lechwe and Waterbuck
Population Area of
collection
Sample
size
Number of
alleles (Na)
Expected
heterozygosity
(He)
Observed
heterozygosity
(Ho)
Waterbuck Eastern Cape 1 1 0.235 0.382
Limpopo 11 2.9 0.523 0.550
Free State 1 1 0.235 0.382
Lechwe Limpopo 3 2.3 0.324 0.250
Free State 5 1.6 0.139 0.137
Linkage disequilibrium was tested using ARLEQUIN version 3.1 (Excoffier et al.,
2006) for the reference populations. Linkage disequilibrium occurs when two genes
are located on the same chromosome and are thus co-inherited. A significant result
(P<0.05) indicates that equilibrium is rejected and provides evidence that loci are in
linkage disequilibrium as observed in Annexure A. Alleles that are in random
association are said to be in linkage equilibrium. The populations were at linkage
equilibrium.
4.4.2 Analysis of molecular variance
FST hierarchical (Wright, 1978) analysis of molecular variance (AMOVA) for
population subdivision was performed using ARLEQUIN version 3.1 (Excoffier et al.,
2006). Variation between sub-species was conducted by dividing the components of
variance into two additives: within individuals and among populations. An FST value
of 0.05 indicates little genetic differentiation; a value between 0.05 and 0.15 indicates
moderate differentiation; a value between 0.15 and 0.25 indicates great
differentiation and values above 0.25 provides evidence of very great genetic
51
differentiation (Wright, 1978; Hartl & Clark, 1997). Hierarchical molecular variance for
two Lechwe population revealed a moderate significant differentiation with
FST=0.1215 (P= 0.0000) (Table 4.3).
Furthermore, FST molecular variance for three Waterbuck subdivided population was
FST = 0.1503 (P = 0.0000) which indicated moderate significant differentiation. When
large populations experience a certain amount of migration they tend to display little
differentiation, whereas small populations that has little migration tend to be highly
differentiated (Holsinger & Wier, 2009). This is influenced by allelic richness, if FST is
small, it means that the allele frequencies within a population are similar; if it is large
it means that the allele frequencies are different (Holsinger & Wier, 2009). Several
studies have demonstrated this concept, molecular variation was estimated amongst
eight Blesbok (Damaliscus pygargus phillipsi) populations with an FST= 0.095
(P=0.000) this revealed a non-significant differentiation, where for the Bontebok
(Damaliscus dorcas dorcas) FST was 0.232 (P= 0.000) indicating high level of genetic
differentiation (Van wyk et al., 2013). However, in the current study, for both Lechwe
and Waterbuck subpopulations, moderate significant differentiation was observed,
providing support that a certain amount of migration within the subdivided sub
population has occurred. Further assessment variation was conducted shown on
(Table 4.4) between the reference Lechwe and Waterbuck populations. An FST=
0.3191 (P=0.000) was observed which revealed significant genetic differentiation.
Table 4.3: Analysis of molecular variance within Lechwe and Waterbuck
Population Source of
Variance
Variance
components
Percentage of
variance
FST P-value
Waterbuck Amongst
population
0.339 15.03 0.1503 0.0046
Within Individuals 1.972 87.24
Lechwe Amongst
population
0.280 12.5 0.1215 0.0000
Within Individuals 1.150 87.5
52
Table 4.4: Analysis of molecular variance between Lechwe and Waterbuck
Population FST P value
Lechwe vs. Waterbuck 0.3191 0.0000
4.4.3 Estimation of allele’s frequency per population
The number of alleles per locus ranged from 2 to 13 with the mean number of seven
alleles (Table 4.5).
Table 4.5: Allelic frequency per locus per species (Lechwe and Waterbuck)
Locus
Allele
size Characterization
Lechwe allele
frequency
Waterbuck allele
frequency
ETH10 202 Both 0.300 0.588
204 Waterbuck 0.000 0.147
208 Both 0.550 0.206
210 Lechwe 0.050 0.000
214 Both 0.100 0.059
167 Waterbuck 0.000 0.125
BM2113 177 Both 0.600 0.219
183 Both 0.050 0.156
185 Both 0.050 0.063
189 Both 0.150 0.406
191 Lechwe 0.050 0.000
193 Both 0.100 0.031
134 Both 0.100 0.079
ILST87 140 Both 0.550 0.237
142 Both 0.250 0.447
143 Waterbuck 0.000 0.026
144 Both 0.100 0.132
146 Waterbuck 0.000 0.053
148 Waterbuck 0.000 0.026
146 Waterbuck 0.600 0.265
TGLA263 148 Both 0.250 0.500
151 Lechwe 0.050 0.000
158 Waterbuck 0.000 0.088
166 Both 0.100 0.147
137 Both 0.100 0.263
53
Table 4.5 (Continued…)
Locus
Allele
size Characterization
Lechwe allele
frequency
Waterbuck allele
frequency
BM 804 143 Waterbuck 0.000 0.079
145 Both 0.700 0.211
149 Waterbuck 0.000 0.026
151 Waterbuck 0.000 0.053
153 Both 0.200 0.316
169 Waterbuck 0.000 0.026
173 Waterbuck 0.000 0.026
167 Waterbuck 0.000 0.088
BMS4008 169 Both 0.150 0.324
171 Waterbuck 0.000 0.029
173 Both 0.050 0.059
175 Both 0.300 0.441
177 Lechwe 0.050 0.000
183 Both 0.450 0.059
MCM527 112 Both 1.000 1.000
BM415 130 Both 0.700 0.342
140 Both 0.250 0.368
142 Both 0.050 0.105
144 Waterbuck 0.000 0.026
152 Waterbuck 0.000 0.158
140 Both 0.700 0.263
BM757 146 Waterbuck 0.000 0.026
150 Both 0.150 0.079
156 Both 0.050 0.211
164 Both 0.050 0.053
166 Waterbuck 0.000 0.026
170 Both 0.050 0.105
172 Waterbuck 0.000 0.079
176 Waterbuck 0.000 0.026
178 Waterbuck 0.000 0.026
180 Waterbuck 0.000 0.026
186 Waterbuck 0.000 0.053
190 Waterbuck 0.000 0.026
143 Waterbuck 0.000 0.028
54
Table 4.5 (Continued…)
Locus
Allele
size Characterization
Lechwe allele
frequency
Waterbuck allele
frequency
DIK020 145 Lechwe 0.050 0.000
147 Both 0.800 0.472
153 Both 0.050 0.194
155 Waterbuck 0.000 0.028
157 Both 0.100 0.278
103 Both 0.150 0.088
BM3517 104 Both 0.250 0.088
105 Both 0.100 0.029
106 Lechwe 0.050 0.000
107 Both 0.050 0.147
108 Waterbuck 0.050 0.000
109 waterbuck 0.100 0.000
113 Both 0.050 0.059
114 Waterbuck 0.050 0.000
115 Both 0.050 0.294
116 Waterbuck 0.000 0.088
117 Both 0.100 0.176
119 Waterbuck 0.000 0.029
110 Both 0.050 0.088
BM1443 112 Lechwe 0.100 0.147
114 Waterbuck 0.050 0.441
116 Both 0.650 0.176
118 Both 0.150 0.147
116 Lechwe 0.100 0.000
BM1329 125 Both 0.100 0.147
127 Both 0.800 0.853
211 Both 1.000 0.882
BM203 212 Waterbuck 0.000 0.118
111 Waterbuck 0.000 0.088
MTGT4 113 Both 1.000 0.912
156 Both 0.214 0.118
55
Table 4.5 (Continued…)
Locus
Allele
size Characterization
Lechwe allele
frequency
Waterbuck allele
frequency
INRA128 160 Both 0.214 0.235
162 Both 0.214 0.088
170 Waterbuck 0.000 0.088
176 Both 0.071 0.088
178 Both 0.286 0.265
180 waterbuck 0.000 0.029
182 waterbuck 0.000 0.059
131 waterbuck 0.000 0.053
OARFCB304 135 Both 0.700 0.079
137 Both 0.050 0.105
139 waterbuck 0.000 0.026
141 Both 0.050 0.211
157 waterbuck 0.000 0.026
159 waterbuck 0.000 0.026
161 waterbuck 0.000 0.026
163 waterbuck 0.000 0.053
167 Both 0.050 0.184
169 Both 0.150 0.211
A total of 102 alleles were observed between the two reference populations, with 61
found in both sub-species, eight were private for the Lechwe and 43 were private for
the Waterbuck.
4.4.4 Population structure of reference populations
The results were obtained without USEPOPINFO (0) using the putative population
origin model. The K with the greatest increase in posterior probability (Delta K value)
was identified as the optimum number of sub-populations using STRUCTURE
harvester (Evanno et al., 2005).Figures 4.3 (A) and (B) are results obtained from
STRUCTURE harvester which confirmed a likelihood of two populations (K=2).
56
A.
B.
Figure 4.3: Results from STRUCTURE harvester plots of mean likelihood L(K) and
difference per K value for Lechwe and Waterbuck populations
(#Note: Dataset obtained from STRUCTURE Bayesian containing 28 individuals with (A) representing
Delta K = 2 and (B) representing likelihood distribution as reported by Earl et al., 2012).
The results summarized in Figure 4.4.of the replicate STRUCTURE version 2.3.4
simulations at each value of K were highly consistent. A division of the data set into
two clusters (K = 2) captured the greatest proportion of the data structure with an
average Ln Pr (X|K) (Helen, 2009). STRUCTURE was used to attain an estimate of
an individual’s proportion of ancestry from each of the clusters. Thus at K=2,
STRUCTURE was able to distinguish between two clusters mainly the eight pure
Lechwe and 13 pure Waterbuck.
Pure Lechwe Pure Waterbuck
Figure 4.4: STRUCTURE histogram depicting pure Lechwe and Waterbuck
populations
57
4.4.5 Identification of admixture individuals
The individual coefficient of membership in pure Lechwe varied from q1 = 0.990 to
q1 = 0.997 and in pure waterbuck varied from q1 = 0.961 to q1 = 0.998 (Figure 4.5).
In reported studies, a q1 of less than 0.900 can be used as a threshold in order to
identify hybrid individuals (Barilani et al., 2007). In this study, the q1 values of the
three unknown samples was 0.900, 0.943 and 0.988, thus these animals can be
classified as pure Lechwe and pure Waterbuck (Table 4.6). In regards to the putative
hybrids, three individuals were identified as hybrid due to q1 values less than 0.900
and one individual with q1 value of 0.960 was identified as pure Waterbuck.
Figure 4.5: STRUCTURE histogram depicting pure Lechwe and Waterbuck
populations as well as putative hybrids and animals of unknown purity.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
58
Table 4.6: Inferredindividual’s proportion of ancestry (Lechwe and Waterbuck)
Population q1 Inferred cluster Outcome
Unknown 0.943 Cluster1 Pure lechwe
Pure Lechwe 0.997 Cluster1 Pure lechwe
Pure Lechwe 0.991 Cluster1 Pure lechwe
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Lechwe 0.989 Cluster1 Pure lechwe
Pure Lechwe 0.997 Cluster1 Pure lechwe
Pure Lechwe 0.997 Cluster1 Pure lechwe
Pure Lechwe 0.996 Cluster1 Pure lechwe
Pure Lechwe 0.993 Cluster1 Pure lechwe
Pure Lechwe 0.990 Cluster1 Pure lechwe
Pure Waterbuck 0.994 Cluster2 Pure Waterbuck
Pure Waterbuck 0.994 Cluster2 Pure Waterbuck
Pure Waterbuck 0.998 Cluster2 Pure Waterbuck
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Waterbuck 0.995 Cluster2 Pure Waterbuck
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Putative hybrid* 0.604* Cluster2 Hybrid
Unknown 0.900 Cluster2 Pure Waterbuck
Unknown 0.988 Cluster2 Pure Waterbuck
Putative hybrid* 0.793* Cluster2 Hybrid
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Waterbuck 0.989 Cluster2 Pure Waterbuck
Pure Waterbuck 0.997 Cluster2 Pure Waterbuck
Pure Waterbuck 0.961 Cluster2 Pure Waterbuck
Putative hybrid* 0.965 Cluster2 Pure Waterbuck
Putative hybrid* 0.799* Cluster2 Hybrid
*Represents hybrid individuals with a q1 less than 0.900
59
4.4.6 Mitochondrial analysis
A 460 bp fragment included a portion of the mitochondrial subunit I (Cytochrome
oxidase I) and results had only a total of 456 positions remaining in the final dataset
which conserved sites were C=382 and variable were V=74. The Parsimony-
informative site was pi-36 which means at least two types of nucleotides occur within
a minimum frequency of two populations. The neighbor-joining tree identified two
distinguishable Lechwe (Kobus leche) and Waterbuck (Kobus ellipsiprymnus)
clusters with 100% bootstrap support for each as shown in (Figure 4.6). The putative
hybrids all clustered within the Waterbuck group.
Figure 4.6: Neighbour-Joining Tree generated between the Lechwe, Waterbuck and
Lechwe/Waterbuck
60
(#
Note: Samples were sequenced from subunit I (COI) gene fragments including the root obtained
from Genbank Reedbuck (Redunca redunca). The putative hybrid individuals are indicated in pink and
mother to BB1838 indicated in red).
Cytochrome c oxidase subunit I (COI) is most conserved protein coding genes in the
mitochondrial genomes (Brown, 1985). There is previous work done on COI for
broad taxonomic studies of 11 invertebrate phyla (Folmer et al., 1994) and 11 animal
phyla (Hebert et al., 2003). In addition COI is useful to distinguish closely related
species (Bucklin et al., 1999). Our results show that the interspecific hybridization
observed for the three putative hybrids animals is between male Lechwe and female
Waterbuck. Two of the putative hybrid animals consisted of a mother and her
offspring, both these animals were identified as hybrid based on STRUCTURE and
both clustered with Waterbuck.
61
4.5 Interspecific hybridization between the Gemsbok and Scimitar-horned
Oryx
4.5.1 Assessing genetic diversity within Scimitar-horned Oryx and Gemsbok
Monomorphic loci were excluded from the test as they yielded no significant results.
Monomorphic loci were observed in the North West population for the Scimitar-
horned Oryx (BMC3224, MCM527 and BM719) and for the Gemsbok population
from Gauteng (MCM527 and OARCP26) and for Northern Cape (MCM527).
Bonferroni correction was used for significance testing (Rice 1989). The following
loci deviated from HWE: Gauteng (Scimitar Oryx: loci SRCRSP8, ILST87, BMC3224,
OARCP26 and BM203); Limpopo (Gemsbok: loci SRCRSP8, BM1329, BM2113 and
BM203) as shown in Annexure B. Then data was further analyzed for genotyping
error, null alleles and scoring error using Micro checker (Van Oosterhout et al.,
2004). No evidence of errors was observed for the remaining loci. Furthermore, loci
were tested to determine linkage disequilibrium using ARLEQUIN version 3.1
(Excoffier et al., 2006) for the reference scimitar oryx and gemsbok populations. No
evidence of linkage disequilibrium was observed as shown in Annexure B.
Scimitar Oryx were divided according to the area of collection namely Northern
Cape, North West and Gauteng with the number of alleles (Na) ranging from 2 to 5.4,
expected heterozygosity (He) ranging from 0.366 to 0.628 and observed (Ho) ranged
from 0.444 to 0.722(Table 4.7). The highest variation was observed within the
Gauteng population. Sub population were further divided the gemsbok reference
samples into three populations namely Northern Cape, Gauteng and the number of
alleles (Na) ranging from 2.0 to 5.3, expected (He) ranging from 0.361 to
0.586observed heterozygosity (Ho) ranging from 0.429to 0.630 with the highest
genetic variance within the Northern Cape samples (Table 4.7) However for most of
the populations the observed heterozygosity was higher than expected which
provides evidence that inbreeding is low. Only one population (Gemsbok, Limpopo)
displayed an observed heterozygosity valued lower than expected which may
indicate non-random mating or inbreeding.
62
Table 4.7: Analyses of genetic diversity for Gemsbok and Scimitar-horned oryx Species Population Sample
size Number of alleles per locus (Na)
Expected heterozygosity
(He)
Observed heterozygosity
(Ho)
Scimitar Oryx
Gauteng 10 5.4 0.628 0.643
North West 4 3.0 0.597 0.722
Northern Cape
1 2 0.366 0.444
Gemsbok Gauteng 4 2.000 0.361 0.556 Limpopo 4 2.556 0.463 0.630 Northern
Cape 16
5.333 0.586 0.429 #Samples were obtained from NZG = National Zoological Gardens of South Africa.
4.5.2Analysis of molecular variance
Hierarchical molecular variance results for the two Scimitar oryx population displayed
a high level of genetic differentiation (FST=0.3180; P= 0.0000). The observed high
differentiation between the Scimitar Oryx populations could be influenced by isolation
due to them being kept in captivity. On the other hand, within the Gemsbok
populations a moderate significant differentiation was observed (FST= 0.1384; P=
0.0000) (Table 4.8). Thus, between the Gemsbok populations, migration has
occurred, most likely due to translocation. Genetic differentiation between Scimitar
Oryx and Gemsbok was high (FST= 0.2643; P=0.0000) indicating that these are
genetically distinct species (Table 4.9).
Table 4.8: Analysis of molecular variance within Gemsbok and Scimitar Oryx
Population Source of
variation
Variation
components
Percentage of
variation
FST P-value
Scimitar
Oryx
Amongst
population
1.286 31.81 0.3180 0.0000
Within Individuals 2.725 67.39
Gemsbok Amongst
population
0.443 13.85 0.1384 0.0034
Within Individuals 2.076 66.71
63
Table 4.9: Analysis of molecular variance between Gemsbok and Scimitar Oryx
Population FST P =value
Scimitar Oryx vs Gemsbok 0.2643 0.0000
4.5.3 Estimation of allele frequencies per population
The number of alleles per locus for gemsbok and scimitar oryx ranged from four to
12 alleles with the mean number of six alleles (Table 4.10). An estimated number of
78 alleles were observed between the two reference populations, with 42 alleles
being observed in both species and 18 alleles were identified as private. The results
showed an equal number of private alleles between the two subpopulation.
64
Table 4.10: Allelic frequency per locus per species (Scimitar Oryx and Gemsbok)
Locus Allele size Classification Scimitar Oryx
frequencies
Gemsbok
frequency
SRCRSP8 218 Scimitar Oryx 0.050 0.000
220 Both 0.100 0.135
222 Gemsbok 0.000 0.019
224 Scimitar Oryx 0.250 0.000
228 Gemsbok 0.000 0.058
230 Gemsbok 0.050 0.058
232 Both 0.125 0.077
234 Both 0.325 0.346
236 Both 0.075 0.135
238 Both 0.025 0.115
240 Gemsbok 0.000 0.038
254 Gemsbok 0.000 0.019
ILST87 135 Gemsbok 0.000 0.058
139 Scimitar Oryx 0.025 0.000
140 Scimitar Oryx 0.300 0.000
145 Both 0.225 0.288
147 Both 0.100 0.096
151 Both 0.275 0.135
153 Both 0.025 0.058
155 Both 0.050 0.327
157
Gemsbok
0.000
0.038
BMC3224 182 Scimitar Oryx 0.050 0.000
184 Gemsbok 0.000 0.019
196 Scimitar Oryx 0.375 0.000
198 Both 0.325 0.538
200 Both 0.175 0.250
202 Both 0.050 0.192
204 Both 0.025 0.000
65
Table 4.10 (Continued…)
Locus Allele size Classification Scimitar Oryx
frequencies
Gemsbok
frequency
MCM527 150 Gemsbok 0.000 0.040
156 Both 0.350 0.960
166 Scimitar Oryx 0.500 0.000
170 Scimitar Oryx 0.150 0.000
BM719 150 Scimitar Oryx 0.625 0.000
152 Gemsbok 0.000 0.192
154 Both 0.050 0.327
156 Both 0.300 0.173
158 Both 0.025 0.269
160 Gemsbok 0.000 0.038
BM1329 138 Gemsbok 0.000 0.058
140 Gemsbok 0.000 0.327
142 Both 0.150 0.308
144 Both 0.025 0.058
146 Both 0.025 0.154
150 Both 0.125 0.077
152 Scimitar Oryx 0.025 0.000
154 Scimitar Oryx 0.200 0.000
156 Scimitar Oryx 0.400 0.000
160 Scimitar Oryx 0.050 0.000
162 Gemsbok 0.000 0.019
66
Table 4.10 (Continued…)
Locus Allele size Classification Scimitar Oryx
frequencies
Gemsbok
frequency
BM2113 121 Gemsbok 0.000 0.038
125 Gemsbok 0.125 0.250
127 Scimitar Oryx 0.025 0.000
129 Both 0.200 0.019
131 Both 0.025 0.058
137 Both 0.275 0.019
139 Gemsbok 0.000 0.058
143 Both 0.175 0.308
145 Both 0.075 0.038
147 Both 0.100 0.115
149 Gemsbok 0.000 0.096
OARCP26 129 Scimitar Oryx 0.100 0.000
133 Both 0.150 0.808
134 Both 0.025 0.000
135 Scimitar Oryx 0.150 0.135
137 Both 0.125 0.019
143 Gemsbok 0.000 0.038
145 Scimitar Oryx 0.075 0.000
147 Scimitar Oryx 0.150 0.000
148 Scimitar Oryx 0.025 0.000
149 Scimitar Oryx 0.200 0.000
BM203 226 Scimitar Oryx 0.053 0.000
228 Both 0.105 0.404
230 Both 0.132 0.481
231 Both 0.026 0.000
234 Both 0.289 0.077
236 Both 0.079 0.038
240 Scimitar Oryx 0.289 0.000
266 Scimitar Oryx 0.026 0.000
67
4.5.4 Population Structure of reference populations
The results (Figure 4.7) were obtained without USEPOPINFO=0. STRUCTURE
harvester was used to determine the number of populations (Evanno et al., 2005).
STRUCTURE harvester confirmed a likelihood of two populations Figure4.7 (A) and
(B).
A.
B.
Figure 4.7: STRUCTURE harvester plots of mean likelihood L(K) and difference per
K value for Scimitar Oryx and Gemsbok populations
(#Note: Dataset obtained from STRUCTURE Bayesian containing 39 individuals with (A) representing
Delka K = 2 and (B) representing likelihood distribution as per Earl et al., 2012).
The results summarized in Figure 4.8 of the STRUCTURE simulations at K=2
indicate the division of the data set into two clusters. STRUCTURE was used to
attain an estimate of an individual’s proportion of ancestry from each of the clusters.
Pure Scimitar Oryx Pure Gemsbok
Figure 4.8: STRUCTURE histogram depicting pure Scimitar Oryx and Gemsbok
populations
68
4.5.5 Identification of admixture individuals
Data was further analyzed by including three putative hybrid samples as shown in
Figure 4.9 and Table 4.11 and one sample of unknown purity. The variance of
estimation (q1) for the putative hybrids ranged from 0.53 to 0.70, identifying three
animals as hybrid based on the threshold of q1 = 0.90 as suggested by Barilani et al.
(2007). The sample of unknown purity was identified as Scimitar Oryx.
Figure 4.9: STRUCTURE histogram depicting pure Scimitar Oryx and Gemsbok
populations as well as four putative hybrids.
Table 4.11: Inferred individual’s proportion of ancestry (Scimitar Oryx and Gemsbok)
Population q1 Inferred cluster Outcome
Putative hybrid* 0.53 Cluster 1 Hybrid
Unknown 0.90 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.97 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Putative hybrid* 0.55 Cluster 1 Hybrid
Gemsbok 0.99 Cluster 2 Gemsbok
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
69
Table 4.11 (Continued…)
Population
q1, q2
Inferred cluster
Outcome
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Scimitar Oryx 0.99 Cluster 1 Scimitar Oryx
Putative hybrid* 0.71 Cluster 2 Hybrid
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.97 Cluster 2 Gemsbok
Gemsbok 0.97 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
Gemsbok 0.99 Cluster 2 Gemsbok
* Represents hybrid individualswith a q1 less than 0.900
4.5.6 Mitochondrial analysis
There were a total of 293 positions in the final dataset which conserved sites were
C=358 and variable were V=35 and parsimony-informative site were pi-20. Neighbor-
joining tree identified two distinguishable groups for gemsbok (Oryx gazelle) and
scimitar Oryx (Oryx dammah) populations formed two different groups (Figure 4.10).
The four putative hybrids are identified with a green colour on the phylogenetic tree
in Figure 4.10. The putative hybrid sample that was found to be pure Scimitar Oryx
70
based on STRUCTURE analysis clustered with pure Scimitar Oryx based on
mitochondrial analysis. A total of two hybrid samples clustered with gemsbok
indicating that in both these cases hybridization occurred due to mating of a female
gemsbok and a male scimitar Oryx. One hybrid animal clustered with Scimitar Oryx
indicating that hybridization occurred due to a mating between a female Scimitar
Oryx and a male Gemsbok. Thus, interspecific hybridization in this instance is
bidirectional.
Figure 4.10: Neighbor-Joining Tree generated between Gemsbok and Scimitar
Oryx.
(#Note: The putative hybrid animals are indicated in green text)
71
4.6 Interspecific hybridization between the Greater Kudu and Nyala
4.6.1 Assessing genetic diversity within Greater kudu and Nyala
Monomorphic markers were observed in several populations and were excluded
from the analysis due to them yielding no significant information. Monomorphic loci
were observed in the Greater Kudu populations (BM514, SRSRCP8, ILST87,
BM2113 and ETH10). Loci were tested HWE using Arlequin version 3.1 (Slatkin,
1994a; Lewontin& Kojima, 1960) as shown in Annexure C. In the Greater Kudu
population from Limpopo, one marker (BM719) deviated from HWE. Loci were
further analyzed using MICRO CHECKER (Van Oosterhout et al., 2004) for
genotyping error, null alleles and scoring errors as a possible explanation HWD.
Bonferroni test was also recommended to reduce the chances of gaining false
positive results (Rice, 1986). Departure from HWE might be influenced by
inbreeding, assortative mating and admixture. Linkage disequilibrium was tested
using ARLEQUIN version 3.1 (Excoffier et al., 2006) for the reference Greater Kudu
and Nyala populations. A significant result (P < 0.05) indicates that equilibrium is
rejected and provides evidence that loci are in linkage disequilibrium as observed in
Annexure C.
The Kudu samples were divided according to the collection area with the number of
alleles (Na) ranging from 1 to 4.6, expected (He) ranging 0.222 to 0.552 and
observed (Ho) ranged from 0.444 to 0.544 (Table 4.12). The same procedure was
conducted with Nyala samples according to the area of collection. Number of alleles
(Na) ranged from 2.3 to 5.2, expected (He) ranged from 0.350-0.531 and observed
heterozygosity (Ho) ranged from 0.389-0.448(Table 4.12). The Limpopo population
displayed lower observed and a higher expected heterozygosity, which may be an
indication of inbreeding. Gene flow and low inbreeding is suggested in the other
population in previous sections.
72
Table 4.12: Analyses of genetic diversity in the Greater Kudu and Nyala Population Samples
size
Number of
alleles (Na)
Expected
heterozygosity (He)
Observed
heterozygosity (Ho)
Nyala
Limpopo 30 5.2 0.531 0.448
Unknown 3 2.3 0.350 0.389
Greater Kudu
Gauteng
3
3.2
0.484 0.560
Free State 1 0.8 0.222 0.444
Limpopo 20 4.6 0.552 0.544
Eastern Cape 6 3.0 0.429 0.444
4.6.2 Analysis of molecular variance
Hierarchical molecular variance for the two greater Kudu populations revealed a
moderate significant differentiation with FST = 0.1643 (P= 0.0019). Furthermore, FST
molecular variance for the Nyala populations was FST = 0.1875 (P = 0.0000) which
indicated moderate significance (Table 4.13). Analysis by AMOVA as shown in
(below Table 4.14) between of the two populations was high (0.5295; P=0.000)
which confirms the distinction of the two species.
Table 4.13: Analysis of molecular variance within Greater Kudu and Nyala
Population Source of
variance
Components
of variants
Percentage of
variation
FST P.value
Greater Kudu Amongst
population
0.1924 16.44 0.1643 0.0019
Within
individuals
1.0227 87.34
Nyala Amongst
population
0.2614 18.75 0.1875 0.0000
Within
individuals
1.1327 81.25
Table 4.14: Analysis of molecular variance between Greater Kudu and Nyala
Population FST Pvalue
Greater Kudu vs. Nyala 0.5295 0.0000
73
4.6.3 Estimation of allele frequencies per population
In the study presented here; a total of 50 alleles were detected of which 28 are
specific to Nyala, 20 were private in Greater Kudu and five were shared. The
average numbers of alleles are similar in both populations (Table 4.15).
Table 4.15: Allelic frequency per locus per species (Greater Kudu and Nyala)
Locus Allele Classification Greater Kudu
allele frequencies
Nyala allele
frequencies
BM415 118 Greater Kudu 0.023 0.000
122 Greater Kudu 0.273 0.000
124 Both 0.136 0.054
130 Nyala 0.000 0.176
132 Both 0.295 0.041
134 Both 0.023 0.149
136 Both 0.091 0.027
138 Both 0.091 0.014
140 Both 0.068 0.405
150 Nyala 0.000 0.122
152 Nyala 0.000 0.014
SRCRSP8 213 Nyala 0.000 0.025
231 Nyala 0.000 0.025
232 Both 0.306 0.775
234 Both 0.274 0.063
236 Both 0.113 0.100
240 Greater Kudu 0.048 0.000
244 Greater Kudu 0.177 0.000
248 Both 0.065 0.013
252 Greater Kudu 0.016 0.000
ILST87 116 Both 0.633 0.038
118 Both 0.083 0.013
128 Both 0.267 0.013
129 Nyala 0.000 0.038
130 Nyala 0.000 0.654
131 Nyala 0.000 0.013
132 Nyala 0.000 0.115
134 Nyala 0.000 0.090
136 Both 0.017 0.026
74
Table 4.15 (Continued…)
Locus Allele Classification Greater Kudu allele
frequencies
Nyala allele
frequencies
BM719 142 Both 0.500 0.026
150 Greater Kudu 0.138 0.000
152 Both 0.103 0.013
156 Both 0.103 0.064
157 Nyala 0.000 0.192
158 Both 0.017 0.436
159 Nyala 0.000 0.064
160 Both 0.103 0.205
164 Greater Kudu 0.034 0.000
BM1329 159 Nyala 0.000 0.014
141 Both 0.229 0.014
143 Nyala 0.000 0.014
145 Greater Kudu 0.063 0.000
147 Greater Kudu 0.021 0.000
149 Both 0.063 0.041
153 Both 0.083 0.122
155 Both 0.167 0.149
157 Greater Kudu 0.042 0.000
159 Both 0.208 0.595
160 Nyala 0.000 0.054
161 Greater Kudu 0.042 0.000
163 Greater Kudu 0.021 0.000
169 Greater Kudu 0.042 0.000
175 Greater Kudu 0.021 0.000
BM203 218 Both 0.828 0.188
222 Nyala 0.000 0.013
224 Greater Kudu 0.016 0.000
226 Nyala 0.000 0.625
228 Nyala 0.000 0.038
234 Both 0.125 0.138
236 Greater Kudu 0.031 0.000
75
Table 4.15 (Continued…)
Locus Allele Classification Greater Kudu
allele frequencies
Nyala allele
frequencies
BM2113 115 Both 0.984 0.063
120 Nyala 0.000 0.050
121 Both 0.016 0.888
ETH10 200 Both 0.333 0.012
201 Nyala 0.000 0.073
202 Both 0.625 0.037
204 Greater Kudu 0.042 0.000
207 Nyala 0.000 0.024
208 Nyala 0.000 0.659
210 Nyala 0.000 0.159
264 Nyala 0.000 0.037
OARCP26 127 Nyala 0.000 0.238
142 Nyala 0.000 0.013
143 Both 0.040 0.425
145 Nyala 0.000 0.038
148 Nyala 0.000 0.013
149 0.020 0.225
161 Greater Kudu 0.040 0.000
169 Both 0.120 0.013
173 Both 0.640 0.013
175 Both 0.060 0.025
181 Greater Kudu 0.040 0.000
185 Greater Kudu 0.040 0.000
4.6.4 Population Structure Analysis
The results (Figure 4.11) were obtained without USEPOPINFO=0. STRUCTURE
harvester (Figure 4.12) was used to determine the number of populations (Evanno et
al., 2005). Posterior probabilities (Ln) using Bayesian admixture analysis indicated
two distinct clusters (Figure 4.11 A and B). The average proportion of membership
for both pure populations was qI> 0.995.
76
A.
B.
Figure 4.11: STRUCTURE harvester plots of mean likelihood L (K) and difference
per K value for Greater Kudu and Nyala
(#Note: Results are from STRUCTURE Bayesian at delta K=2;Earl et al., 2014)
Pure Nyala Pure Greater Kudu
Pure Greater Kudu
Figure 4.12: STRUCTURE histogram depicting pure Nyala and pure Greater Kudu
individuals.
4.6.5 Identification of admixture individuals
As part of confirming the animal’s hybrid status, the individual assignment of pure
control samples and the putative hybrid was inferred by a Bayesian clustering
analysis using STRUCTURE version 2.3.3 (Pritchard et al., 2010). An a priori value
of K = 2 accounted for the two parental species when we used the genetic admixture
77
analysis and correlated allele frequencies model (Zalapa, 2010) of the programme
STRUCTURE. The study assessed the average proportion of membership (qI) of the
putative hybrid individuals. Two hybrid individuals were identified as shown in Figure
4.13 and Table 4.16. Average proportion of membership ranged from 0.45 to 0.80.
The criterion qI< 0.90 suggested by Barilani et al. (2007) was used to identify
individuals as either pure or hybrid. This criterion was considered adequate for this
study given that the animal could clearly be identified as a hybrid (qI = 0.4).
Figure 4.13: STRUCTURE analysis (performed with K = 2) of microsatellite
genotypes of pure Nyala, pure Greater Kudu and hybrid animals.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
78
Table4.16: Inferred individual’s proportion of ancestry (Kudu and Nyala)
Population q1 Inferred cluster Outcomes
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
Nyala 0.99 Cluster 1 Nyala
79
Table 4.16 (Continued…)
Population q1 Inferred cluster Outcomes
Putative hybrid* 0.77 Cluster 2 Hybrid
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Putative hybrid* 0.57 Cluster 2 Hybrid
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Unknown 0.65 Cluster 2 Hybrid
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
Greater Kudu 0.99 Cluster 2 Greater Kudu
*Represents hybrid individuals with a Q1 less than 0.900
80
4.6.6Mitochondrial analysis
All samples were identified by means of Cytochrome b (Cytb) amplification and
sequence analyses. A 205 bp fragment included a portion of the
mitochondrialcytochrome b (Cytb) gene sequences was acquired from 37
individuals. Blast www.ncbi.nm.nih.gov/blast (National Library of Medicine Rockville
Pike, Bethesda MD, USA) was used to identify species. The rate of variation among
sites was modeled with a gamma distribution shape parameter = 0.12. Analysis
included codon and noncoding positions. All positions with less than 95% site
coverage were eliminated. There were a total of 168 positions in the final dataset
with 243 conserved sites (C), 52 Varaible sites (V) and 29 parsimony-informative
(pi). The neighbor-joining tree as shown in (Figure 4.14) identified two
distinguishable groups namely; Tragelaphus angesii andTragelaphus stepsiceros
populations.
While hybrids clustered within the greater kudu (Tragelaphus stepsiceros) group
indicating that hybridization occurred due to mating between a male Nyala and a
female greater Kudu. This was further suported by phylogenetic analysis using 21
individuals 8 greater kudu and 11 nyala shown on (Figure 4.15) indicated clades for
greater kudu and nyala that included the putative hybrid sample. This hybrid animal
resulted from a mating of a male greater kudu and a female nyala. This type of
hybridization is known as bidirectional hybridization, though based on the
reproductive potential assessment of this individual we consider hybrids to be sterile.
Bidirectional hybridization was also observed between the red deer (Cervus elaphus)
and the sika deer (Cervus nippon) (Slate et al., 1998).
81
Figure 4.14: Maximum likelihood tree generated for Greater Kudu, Nyala and Kudu-
Nyala hybrid
(#Note: Cytb gene fragments in combination with reference samples were acquired from Genbank. All
reference samples are prefixed with relevant Genbank accession numbers, while samples generated
in this study are indicated with NYA.The hybrid sample is indicated in red).
82
Figure 4.15: Neighbor-Joining Tree generated between the Greater Kudu, Nyala
and Kudu/Nyala
(#Note: Samples were sequenced from cytchrome oxidase I (Cytb) gene fragments including the root
obtained from Genbank lowland anoaa (Bubalus depressicornis). The hybrid individuals are indicated
in green).
83
4.7 Karyotype analysis
Meiosis in Greater Kudu males (31, X,t(Y;13) would yield 15,t(Y;13) gametes and in
female Nyala (56,XX), gametes with 28,X. Chromosomes of 50 metaphases were
counted to establish the chromosome number of the putative F1 as 2n = 43
(Supplementary 1). This is consistent with its status as an F1 hybrid. This is further
underscored by the morphology of the hybrid’s chromosomes. The male parent, a
Greater Kudu (2n = 31), has a chromosomal complement that comprises a single
pair of acrocentric autosomes, one unpaired acrocentric autosome (Y2), 13 pairs of
bi-armed autosomes, the submetacentric t(Y;13) fusion chromosome (Y1), and an
acrocentric X (i.e., 31,X,t(Y;13). The female parent, a Nyala (2n = 56), has 26
autosomal pairs that are acrocentric in morphology, one pair that is sub-metacenter
in morphology and two acro- centric X chromosomes (O’Brien et al., 2006) (i.e.,
56,XX). Close inspection of the hybrid’s chromosomes shows 28 acrocentrics (one
inherited from the male Kudu and 27 from the female Nyala), 15 bi-armed
chromosomes (14 inherited from the male Greater Kudu and one from the female
Nyala gamete) in the 2n = 43 complement (Figure 4.16).
4.8 Reproduction analysis
The assessment of the internal reproductive organs on the ultrasound showed no
visible abnormality that interferes with the scrotum test. In addition testes were
shown to be symmetrical; the left testis length measured 5.8 cm with the right testis
length at 6 cm. The collected ejaculate displayed a clear colour and the volume was
estimated at 1.5 ml with a pH 7.5. The eosin/nigrosin smears prepared that were at
(t0) had only a few epithelial cells. However, smears prepared at t24 revealed the
presence of additional epithelial debris and a single abnormal sperm cell as
summarized in (Figure4.16). The ejaculate collected was considered to be
azoospermic and the blood testosterone concentration was 15.79 nmol/l and was
considered to be high. Based on the reproductive potential assessment of this
individual we consider it to be sterile. The immature size of the scrotum, testes and
penis was immediately evident. The size of the testes and penis resembled those of
a juvenile and not a 7 year old bull. Reduction in testes and penis size has similarly
84
been reported in hybrid male Arabian Oryx (Oryx leucoryx; Eljarah et al., 2012). The
authors indicated that the average testis length in the latter measured 5.9 cm, nearly
half of the average measured for bulls under the age of 2 years.
Figure 4.16: Images recorded during evaluation of eosin/nigrosin smears (t24) taken
at 1000 magnification
(#Note: Results represent a series of epithelia cells possibly originated from the epididymal epithelial
cells and squamous epithelial cells possibly derived from desquamation of the preputial epithelium
cell. E, F abnormal spermatozoa showing head, tail and abnormal mid-piece (spermatogenic defect).
G and H loose tail of spermatozoa).
The scrotum circumference measured 14 cm in the hybrid, significantly less that the
average scrotum circumference of 24 cm (Schoeman et al., 1987). The blood serum
testosterone level in the hybrid animal identified in this study was high and is
consistent with reports that the hybrid had been observed mounting cows on the
farm. Studies conducted on the mating performance in Dorper rams indicated that
there was a statistically non-significant correlation between the testis size and
concentration level of plasma testosterone (Schoeman et al., 1987). The immature
85
size of the scrotum, testes and penis was immediately evident. The size of the testes
and penis resembled those of a juvenile and not a 7 year old bull. Reduction in
testes and penis size has similarly been reported in a hybrid Arabian Oryx bull Oryx
leucoryx. (Eljarah et al., 2012).
86
CHAPTER 5
5 DISCUSSION
5.1 Identification and development of cross species markers
A total of 21 one of 30 microsatellites markers were tested and amplification was
successful for the Lechwe and Waterbuck, the Greater Kudu and Nyala, Gemsbok
and the Scimitar-horned Oryx. This included 17 markers that amplified for Lechwe
and Waterbuck, nine markers amplified for Greater Kudu and Nyala, as well as by
nine markers that amplified for Gemsbok and Scimitar-horned Oryx. The type of
marker used are cross species markers, and are known to be less time consuming
and enables the construction of comparative maps between related species. They
can provide information on conservation between species and give an estimate of
the genome average (O’Brien et al., 1993). Out of the 21 amplified markers about
30% were primers paired for cow (Bos Taurus) and 70% were primers from sheep
and goats (Ovis Aries). These types of autosomal cross species markers are
recommended in many hybridization studies and are universal markers developed
for one species that can be used for another.
There are numerous example studies on the use of cross species to detect
hybridization and population structure. A previous study on hybridization between the
Japanese quall (Coturnix Japonica) and the common quall (Coturnix coturnix) used 5
cross species markers to determine hybrid individuals (Barilani et al., 2006). A study
by Dubut et al. (2010) between the European cyprinids using 41 cross species
markers was able to detect hybrid individuals.
5.2 Assessing Genetic diversity
Data collected from autosomal loci were analyzed for Linkage disequilibrium (LD).
When two genes are in linkage disequilibrium, it means that certain alleles of each
gene are inherited together more often than would be expected. This is when a
population has a reduction in the overall heterozygosity due to subpopulation
structure (mixing of two subpopulations with different allele frequency). When two
87
subpopulations have independent allele frequencies, then the overall heterozygosity
is reduced regardless of the subpopulation being in HWE. This can be due to gene
flow between the subpopulations, followed by independent genetic drift in each
subpopulation. According to the results of this study, all sub population were at
linkage equilibrium meaning there was random mating. A departure from HWE has
been widely used for detecting genotype errors (Hosking et al., 2004). Bonferroni
test is also recommended to reduce the chances of gaining false positive results
(Rice, 1986). Besides genotyping error, there are a number of other reasons to
cause a departure from HWE which include; a small population variation and/or
population structure (inbreeding, assortative mating and admixture) (Zhang & Tier,
2009).
Further markers were used to determine genetic diversity by observed (Ho) and
expected (He) heterozygosity; this was calculated by estimating polymorphism
meaning the number of alleles (Na) per locus. A total of 28alleles were specific to
Nyala, 20 were private in Greater Kudu, eight were private for the Lechwe,43 were
private for the Waterbuck and 18 alleles were identified as private in both Gemsbok
and the Scimitar Oryx. This was also reported by Grobler et al.(2004)who found 39
alleles; eight were unique for the Black Wildebeest and 22 were unique for the Blue
Wildebeest. Private alleles are confirmed to be informative in population and genetic
studies, in such areas as molecular ecology and conservation genetics (Petit et al.,
1998; Parker et al., 1999; Fiumera et al., 2000; Neel & Cummings, 2003; Kalinowski,
2004).
Genetic diversity occurs when there is a difference in the number of alleles or
genotypes frequencies between those populations. In this study, there was moderate
to high diversity in all the species except for the Lechwe which exhibited a lower
genetic diversity. This was reported by Yang et al. (2011) were observed
heterozygosity (HO = 0.525) was lower compared to expected heterozygosity (He =
0.552) in 169 individuals of the specie (Equus przewalskiipoliakov) from nine
subpopulations. The authors attributed this to the fact that the population
experienced a severe decline and possible genetic bottleneck. Sample size can
affect the level of genetic diversity; however, this was not the case in this study as
88
the Lechwe reference population displayed lower heterozygosity with a higher
sample size as compared to Waterbuck.
5.3 Molecular Variance and gene flow
Genetic differentiation based on microsatellite data set was high between the
Lechwe and Waterbuck with a 30% difference between the populations, between the
Gemsbok and the Scimitar Oryx with a 20% difference, and between the Greater
Kudu and Nyala with a 50% difference confirming distinct species. When large
populations experience a certain amount of migration they tend to display little
differentiation, whereas small populations that have little migration tend to be highly
differentiated (Holsinger & Wier, 2009). This is influenced by allelic richness, if FST is
small, it means that the allele frequencies within a population are similar; if it is large
it means that the allele frequencies are different (Holsinger & Wier, 2009). Several
studies have demonstrated this concept. Molecular variation was also observed by
van Wyk et al. (2013), who reported an average FST = 0.602 (P=0.0001) revealing a
significant genetic differentiation between pure Bontebok and Blesbok populations
and highlighting that they are genetically distinct. The results of the current study
based on genetic differentiation shows no gene flow between the two species and
that they are genetically distinct.
5.4 Assessing of hybrid individuals
As part of confirming the animal’s hybrid status, the individual assignment of pure
control samples and the putative hybrid was inferred by a Bayesian clustering
analysis. The study identified nine hybrids out of 137 individuals sampled for all
species involved. Average proportion of membership ranged from 0.45 to 0.80. The
criterion qI< 0.90 suggested by Barilani et al. (2007) was used to identify individuals
as either pure or hybrid. This criterion was considered adequate for this study given
that the animal could clearly be identified as a hybrid (qI = 0.4).
89
5.5 Mitochondrial analysis
The current study used two mtDNA gene regions COIfor hybridisation between the
lechwe and waterbuck, and Cytb for the hybridisation between the Gemsbok and
Scimitar Oryx, Greater Kudu and Nyala. This study detected unidirectional
hybridization between female Waterbuck and male Lechwe. A similar study on
detection of natural hybrids in sturgeon populations used the COI gene region and
hybridisation between a female Sterlet (Acipenser ruthenus) and a male Russian
sturgeon (Acipenser gueldenstaedtii) (Burcea et al., 2014). Moreover, bidirectional
hybridization was observed between Gemsbok and Scimitar Oryx as well as Nyala
and Greater Kudu. Slate et al. (1998) also reported bidirectional hybridization
between the red deer (Cervuselaphus) and the sika deer (Cervus nippon), and the
Mongoose lemur (Eulemur mongoz) and the brown lemur (Eulemur fulvus)
(Zaramody & Pastorini, 2001), and also the moor (Macaca maura) and Tonkean
(Macaca tonkeana) (Evans et al., 2001) using Cytb gene region. The mitochondria
analysis showed evidence distinctive clade between Lechwe and Waterbuck, Kudu
and Nyala and Scimitar Oryx and Gemsbok. This was further elaborated by genetic
differentiation between subpopulation.
5.6 Reproductive assessment of the hybrid’s fertility
Based on the reproductive potential assessment for a hybrid between the
Kudu/Nyala the current study considered it to be sterile. The immature size of the
scrotum, testes and penis was immediately evident. The size of the testes and penis
resembled those of a juvenile and not a 7-year-old bull. Reduction in testes and
penis size has similarly been reported in hybrid male Arabian Oryx (Oryx
leucoryx)(Eljarah et al., 2012). The authors indicated that the average testis length in
the latter measured 5.9 cm, nearly half of the average measured for bulls under the
age of 2 years. The scrotum circumference measured 14 cm in the hybrid,
significantly less than the average scrotum circumference of 24 cm (Schoeman et
al., 1987).
90
Observations of sterility are consistent with the meiotic impairment anticipated from
the chromosomal differences between the parental karyotypes. Although some
meiotic activity appears to occur in the greater Kudu x Nyala hybrid. The authors
however indicated that spermatogenesis was disrupted at pachytene (Chandley et
al., 1974). However, further analysis on other sterile hybrids within Tragelaphus
would be required to confirm the occurrence of abnormal spermatozoa.
91
CHAPTER 6
6 CONCLUSION
This study highlighted the significance of using different approaches to assess
hybridization in mammals with specific reference to antelope. The study was able to
successfully identify between pure and hybrid individuals using microsatellite
markers. Furthermore, the study was able to identify first generation backcross
individuals between the Gemsbok and Scimitar Oryx, Waterbuck and Lechwe and
Nyala and Greater Kudu. A clear distinction between pure and hybrid individuals was
possible. The study identified nine hybrids out of 137 individuals sampled for all
species involved. Mitochondrial analysis was also able to assist in the detection of
hybrids and showed the direction of hybridization. Unidirectional hybridization was
identified between female Waterbuck and male Lechwe, whereas bidirectional
hybridization was observed between Gemsbok and Scimitar-horned Oryx as well as
between the Nyala and Greater Kudu. Moderate to high diversity were observed in
all the species except for the Lechwe which exhibited a lower genetic diversity.
Conventional cytogenetic application and clinical reproductive assessment was
further able to confirm the sterility of the hybrid Kudu x Nyala.
Genetic differentiation based on microsatellite data set was high between the
Lechwe and Waterbuck with a 30% difference between the populations. Moreover, a
20% difference was observed between the Gemsbok and the Scimitar Oryx, while a
50% difference was observed between the Greater Kudu and Nyala confirming
distinct species. This was further supported by phylogenetic analysis where
distinctive clades for the Waterbuck, Lechwe, Greater Kudu, Nyala, Gemsbok and
the Scimitar Oryx were observed. Moderate to high differentiation was observed
within the Scimitar Oryx populations, which may indicate evolutionary significant
units within these species due to absence of gene flow. However, this finding
warrants further investigation.
92
6.1 Conservation management implications
In this study, hybridization without introgression was observed between Lechwe and
Waterbuck, Scimitar-horned Oryx and Gemsbok and the Greater Kudu and the
Nyala. Hybridization resulting in sterile offspring has been reported in red Hartebeest
and Blesbok as well as in Eland and Greater Kudu (Robinson et al., 1991; Grobler &
van der Bank, 1995; Rhymer & Simberloff, 1996). Hybridization between different
species may arise due to both species occurring in low numbers resulting in limited
access to conspecific mates. Hybridization without introgression where hybrid
offspring are born sterile leads to wasted reproductive effort which can result in a
reduction in population size.
Hybridization can lead to outbreeding depression by lowering fitness in offspring that
can influence the survival of the hybrids (Rhymer, 2006). Lower survival of the hybrid
results in lower chances of the individuals to cope with environmental changes. Even
if hybrids do survive, they may be sterile or the offspring of one cross or the other
may be sterile. Hybridization has a negative impact, often overlooked but important
and can lead to the decline of species due to genetic dilution (Rhymer, 2006). Once
hybridization occurs, the risk of genetic extinction depends on the offspring
adaptation. Wolf et al. (2001) argued that “hybridization is the most progressive
genetic threat to endangered species, and even species extinction can occur in less
than five generations”. Hybridization with or without introgression can lead to the
extinction of rare species (Rhymer, 2006).
93
REFERENCE
ALLENDORF, F. W. LEARY, R. F. SPRUELL, P. & WENBURG, J. K. 2001. The
problems with hybrids: Setting conservation guidelines. Trends in Ecology and
Evolution, 16: 613–622.
ALLENDORF,F.W.& LUIKART, G. 2007. Conservation and the Genetics of
Populations. Management Volume 97.
ALDEN, P.C., ESTES, R.,D. SCHLITTER, D. MCBRIDE, B. 1995. National Audubon
Society Field Guide to African Wildlife. New York: Chanticleer Press Edition.
ANDERSON, E. & STEBBINS JR.G. L.1954. Hybridization as an Evolutionary
Stimulus. Evolution, 8:378–388.
ARIF, I. A, KHAN, H. A, SHOBRAK, M., HOMAIDAN, A. A AL, SADOON, M. A.L. &
FARHAN, A. H. AL. 2010. Measuring the genetic diversity of Arabian Oryx using
microsatellite markers: implication for captive breeding. Genes & Genetic
Systems, 85: 141–145.
ARNOLD, M. L. 1997. Natural hybridization and evolution. Oxford University press
page 232.
ARNOLD, M. L., & HODGES, S. A. 1995. Are natural hybrids fit or unfit relative to
their parents? Trends in Ecology & Evolution, 10:67–71.
ARNASON, U., SPILLIAERT, R., PALSDOTTIR, A., & ARNASON, A. 1991.
Molecular identification of hybrids between the two largest whale species, the
blue whale (Balaenoptera musculus) and the fin whale (B. physalus). Hereditas,
115: 183-189.
BARBARÁ, T., PALMA-SILVA, C., PAGGI, G. M., BERED, F., FAY, M. F., & LEXER,
C. 2007. Cross-species transfer of nuclear microsatellite markers: Potential and
limitations. Molecular Ecology, 16: 3759–3767.
94
BARILANI, M. DEREGNACOURT, S. GALLEGO, S. GALLI, L. MUCCI, N. PIOMBO,
R. PUIGCERVER, M. RIMONDI, S. RODRIGUES-TEIJERO, J., D. SPANO, S.&
RANDI, E. 2005. Dectection hybridization in wild (Coturnix c. coturnix)and
domesticated (Coturnix c.japonica) qual population . Biological . Conservation,
126:445-455.
BARILANI, M. SFOUGARIS, A. GIANNAKOPOULOS, A. MUCCI, N., TABARRONI,
C., & RANDI, E. 2007. Detecting introgressive hybridisation in rock partridge
populations (Alectoris graeca) in Greece through Bayesian admixture analyses
of multilocus genotypes. Conservation Genetics, 8:343-354.
BARTON, N.,H. & HEWITT, G.,M. 1989 Adaptation, speciation and hybrid zones.
Nature 341:497–503
BARTON, N., H. 2001. The role of hybridization in evolution. Molecular Ecology,
10:551–568.
BEEBEE, T., J., C.& GRIFFITHS, R., A. 2005. The amphibian decline crisis: A
watershed for conservation biology? Biological Conservation, 125:271–285.
BEJA-PEREIRA, A., ZEYL, E., OURAGH, L., NAGASH, H., FERRAND, N.,
TABERLET, P., & LUIKART, G. 2004. Twenty polymorphic microsatellites in two
of North Africa’s most threatened ungulates: Gazella dorcas and Ammotragus
lervia (Bovidae; Artiodactyla). Molecular Ecology Notes, 4:452–455.
BIRUNGI, J., & ARCTANDER, P. 2000. Large sequence divergence of mitochondrial
DNA genotypes of the control region within populations of the African antelope,
kob (Kobus kob). Molecular Ecology, 9:1997–2008.
BISHOP, M. D., KAPPES, S. M., KEELE, J. W., STONE, R. T., SUNDEN, S. L. F.,
HAWKINS, G., A. &BEATTIE, C., W. 1994. A genetic linkage map for cattle.
Genetics, 136:619–639.
95
BITANYI, S., JORNSTAD, B., G. ERNEST,E., M. NESJE, M. KUSILUKA, L., J.
KEYYU, J., D. MDEGELA, R., H. & ROED, K., H.2011. Species identication of
Tanzanian antelopes using DNA barcoding. Molecular ecologyresources,
11:442-449.
BOS, D. H., GOPURENKO, D., WILLIAMS, R. N., & DEWOODY, J. A. 2008.
Inferring population history and demography using microsatellites, mitochondrial
DNA, and major histocompatibility complex (MHC) genes. Evolution, 62:1458–
BRADLEY, R. D., & BAKER, R. J. 2001. A test of the genetic species concept:
cytochrome-b sequences and mammals. Journal of Mammalogy, 82: 960–973.
BRENNAN, A.,C. WOODWARD,G. SEEHAUSEN, O.MUÑOZ-FUENTES, V..
MORITZ, C., GUELMAMI, A. ABBOTT, R., J.&EDELAAR, P. 2015.
"hybridization due to changing species distributions: adding problems or
solutions to conservation of biodiversity during global change?." Evolutionary
Ecology Research 16: 475-491.
BRISBIN, I. L., & PETERSON, A. T. (2007). Playing chicken with red junglefowl:
Identifying phenotypic markers of genetic purity in Gallus gallus. Animal
Conservation, 10:429–435.
BROWN, W., M. 1985.The mitochondrial genome of animals. In Molecular
Evolutionary Genetics , R.J.Maclntyre edition. New York:Plenum Press.
page.95-130.
BRUFORD, M. W., & WAYNE, R. K. 1993. Microsatellites and their application to
population genetic studies. Current opinion in genetics & development, 3: 939-
943.
BUCHANAN, F., C. ADAMS, L., J. LITTLEJOHN, R., P. MADDOX, J., F
&CRAWFORD , A., M. 1994. Determination of evolutionary relationship among
sheep breeds using microsatellites. Genomics, 22:397-403.
BUCKLIN, A., GUARNIERI, M., HILL, R. S., BENTLEY, A. M., & KAARTVEDT, S.
1999. Taxonomic and systematic assessment of planktonic copepods using
96
mitochondrial COI sequence variation and competitive, species-specific PCR. In
Molecular Ecology of Aquatic Communities Springer Netherlands page. 239-
254.
BURCEA, A., FLORESCU, I. E., DUDU, A., GEORGESCU, S. E., & COSTACHE, M.
2014. Molecular Methods for the Detection of Natural Hybrids in Sturgeon
Populations. Transylvanian Review of Systematical and Ecological Research,
16: 65–72.
BURKE, J. M., & ARNOLD, M. L. 2001. G Enetics and the F Itness of H Ybrids.
Annual Review of Genetics, 35:31–52.
CARR, S. M., BALLINGER, S. W., DERR, J. N., BLANKENSHIP, L. H., & BICKHAM,
J. W. 1986. Mitochondrial DNA analysis of hybridization between sympatric
white-tailed deer and mule deer in west Texas. Proceedings of the National
Academy of Sciences of the USA, 83: 9576–9580.
CHANDLEY,A.,C.JONES,R.DOTT, H.,M. ALLEN,W.,R. SHORT, R.,V. 1974. Meiosis
in interspecific equine hybrids: I. The mule (E.assinus E. caballus) and hinny (E.
caballus E. asinus).Cytogenet Cell Genetics 13:330–334
CHOWN, S. L., SPEAR, D., LEE, J. E., & SHAW, J. D. 2009. Animal introductions to
southern systems: lessons for ecology and for policy. African Zoology, 44: 248-
262.
CORDINGLEY, J. E., SUNDARESAN, S. R., FISCHHOFF, I. R., SHAPIRO, B.,
RUSKEY, J., & RUBENSTEIN, D. I. 2009. Is the endangered Grevy’s zebra
threatened by hybridization? Animal Conservation, 12: 505–513.
COLLINS, F. S., GUYER, M. S., & CHAKRAVARTI, A. 1997. Variations on a theme:
cataloging human DNA sequence variation. Science, 278:1580-1581.
CRIBIU, E. P., ASMONDÉ, J. F., DURAND, V., GRETH, A, & ANAGARIYAH, S.
1990. Robertsonian chromosome polymorphism in the Arabian oryx (Oryx
leucoryx). Cytogenetics and Cell Genetics, 54 :161–163.
97
CRONIN, M. A., VYSE, E. R., & CAMERON, D. G. 1988. Genetic relationships
between mule deer and white-tailed deer in Montana. The Journal of Wildlife
Management, 320-328.
CROSIER,A.,E.PUKAZHENTHI,B.,S.HENGHALI,J.,N.HOWARDJ.,G.DICKMANA,J.
&MARKER L .2006. Cryopreservation of spermatozoan from wild born Namibian
cheetah (Acinonyx jubatus) and influence ofglycerol on cryosurvival.
Cryobiology 52:169–181
DALTON, D. L., TORDIFFE, A., LUTHER, I., DURAN, A., VAN WYK, A. M.,
BRETTSCHNEIDER, H., Oosthuizen,A. Modiba, C. &KOTZÉ, A. 2014.
Interspecific hybridization between greater kudu and nyala. Genetica, 142: 265–
271.
DEGLI ESPOSTI, M., DE VRIES, S., CRIMI, M., GHELLI, A., PATARNELLO, T., &
MEYER, A. 1993. Mitochondrial cytochrome b: evolution and structure of the
protein. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1143:243-271.
DEMARAIS, B.D., DOWLING, T.E., DOUGLAS, M.E., MINCKLEY, WL, & MARSH,
P.C. 1992. Hybrid origin of Gila seminuda (Pisces: Cyprinidae): implications for
evolution and conservation. Proceedings of the National Academy of Science,
89: 2747- 2751.
DOLAN, J.M. 1966: Notes on the scimitar-horned oryx Oryx dammah (Cretzschmar,
1826. International Zoo Yearbook 6: 219-229.
DOWLING, T. E., & SECOR, C. L. 1997. the Role of Hybridization and Introgression
in the Diversification of Animals. Annual Review of Ecology and Systematics, 28
:593–619.
DUBUT, V. SINAMA, M. MARTIN, J., F. MEGLECZ, E. FERNANDEZ, CHAPPAZ, R.
GILLES, A. & COSTEDOAT, C. 2010. Cross-species amplification of 41
microsatellite in European Cyprinids:a toolfor evolution ,population genetics and
hybridisation studies. BMC research notes 3: 1.
98
EARL D., A. VONHOLDT B.,M. 2012.Structure harvester: a website and program for
visualizing structure output and implementing the Evanno method. Conservation
Genet Resources 4:359–361.
EAST R. 1998 African antelope database 1998. IUCN/SSC Antelope Specialist
Group Report.
ELJARAH A. A,.L-ZGHOUL M.,B, JAWASREH K, ABABNEH M, ALSUMADI M,&
ALHALAH A 2012 Characterization of male reproductive anatomy of the
endangered Arabian oryx (Oryx leucoryx). Theriogenology 78:159–164
EVANNO, G. REGNAUT, S.& GOUDET, J. 2005. Dectecting the number of clusters
of individual using the software STRUCTURE: a simulation study. Molecular
ecology , 14: 2611-2620.
EVANS, B. J., SUPRIATNA, J., & MELNICK, D. J. 2001. Hybridization and
population genetics of two macaque species in Sulawesi, Indonesia. Evolution;
International Journal of Organic Evolution, 55:1686–1702.
ESPOSTI , D.,M.GHELLI, A. RATTA, M. CORTES,D.& ESTORNELL,E.1994.
Natural substances (acetogenins) from the family Annonaceae are powerful
inhibitors of Mitochondrial NADH dehydrogenase (Complex I).Biochemical
Journal, 301:161-167.
ESTES, R. 1991. The behavior guide to African mammals: including hoofed
mammals, carnivores, primates. Berkeley, CA: University of California Press.
EXCOFFIER , L., G. LAVAL, G. & SCHNEIDER, S. ARLEQUIN version 3.1:a
software for population genetic data analysis . Computational and molecular
population genetics laboratory, Institution of Zoology, University of Berne ,
Switzerland .
FALCONER, D. S., & MACKAY, T. F. C. 1996. Introduction to Quantitative Genetics,
4th edition. Longman Science and Technology, Harlow, UK.
99
FRANKHAM, R., BALLOU, J.D. & BRISCOE, D.A. 2010. Introduction to conservation
genetics. 2nd edition. United Kingdom, Cambridge University Press.
FELDHAMER, G.A., DRICKAMER, L.C., VESSEY, S.H., MERRITT, J.F.
&KRAJEWSKI, C. 2007. Mammalogy: Adaptation, Diversity. Ecology, page,643.
FITZSIMMONS, N.N., MORITZ, C. & MOORE, S.S. 1995. Conservation and
dynamics of microsatellite loci over 300 million years of marine turtle evolution.
Molecular Biology and Evolution, 12: 432-440.
FIUMERA, A. C., PARKER, P. G., & FUERST, P. A. 2000. Effective population size
and maintenance of genetic diversity in captive‐bred populations of a lake
Victoria cichlid. Conservation Biology, 14:886-892.
FOWLER, M. E., & MILLER, R. E. 2008. Zoo and wild animal medicine: current
therapy Volume. 6. Elsevier Health Sciences.
GALLAGHER, D. S., & WOMACK, J. E. 1992. Chromosome conservation in the
Bovidae. The Journal of Heredity, 83: 287–298.
GATESY, J., YELON, D., DES, R., & VRBA, E. S. 1992. Based on Mitochondrial
Ribosomal DNA Sequences , 9:433–446.
GEMMELL, N.J., ALLEN, P.J., GOODMAN, S.J. & REED, J.Z. 1997. Interspecific
microsatellite markers for the study of pinniped populations. Molecular Ecology,
6: 661-666.
GLENN, T. C., & SCHABLE, N. A. 2005. Isolating microsatellite DNA loci. Methods
in enzymology, 395:202-222.
GENOVART, M. 2009. Natural hybridization and conservation. Biodiversity and
Conservation, 18:1435–1439.
GENTRY, A. 1994. "Artiodactyla" (On-line). Encyclopedia Britannica Online.
AccessedJune102015athttp://www.britannica.com/EBchecked/topic/37203/artio
dactyl/51680/Areas-of-distribution.
100
GENTRY, A. 2011. Bovidae. Pp. 363-465 in T Harrison, ed. Paleontology and
Geology of Laetoli: Human Evolution in Context. Volume 2: Fossil Hominins and
the Associated Fauna. New York, NY: Springer.
GEORGES,M. & MASSEY, J.1992. Polymorphic DNA markers in Bovidae. World
Intellectual Property Organisation, Geneva. WO publication.No. 92/13120.
GILLET, H. 1966. The scimitar oryx and the addax in the Tchad Republic (Part I).
African Wild Life, 20:103-115.
GILBERT, T., GILBERT, T., WOODFINE, T., & WOODFINE, T. 2003. The biology,
husbandry and conservation of scimitar-horned oryx Oryx dammah. The
Biology, Husbandry and Conservation of Scimitar-Horned Oryx Oryx Dammah.,
Unpaginated.
GOODMAN, S. J., BARTON, N. H., SWANSON, G., ABERNETHY, K., &
PEMBERTON, J. M. 1999. Introgression through rare hybridization: A genetic
study of a hybrid zone between red and sika deer (genus Cervus) in Argyll,
Scotland. Genetics, 152:355–371.
GRANT, P. R. 1994. Population variation and hybridization: Comparison of finches
from two archipelagos. Evolutionary Ecology, 8:598–617.
GREIG, J.,L. 1980. Duck hybridization : a threat to species intergrity. Bokmakierie
32:88-89.
GROBLER, J. P., HARTL, G. B., GROBLER, N., KOTZE, A., BOTHA, K., &
TIEDEMANN, R. 2005. The genetic status of an isolated black wildebeest
(Connochaetes gnou) population from the Abe Bailey Nature Reserve, South
Africa: Microsatellite data on a putative past hybridization with blue wildebeest
(C-taurinus). Mammalian Biology, 70: 35–45.
GROBLER JP, RUSHWORTH I, BRINK JS, BLOOMER P, KOTZE A & REILLY B
2011. Management of hybridization in an endemic species:decision making in
the face of imperfect information in the case of the black wildebeest-
Connochaetes gnou. Europe Journal Wildlife 57:997–1006
101
GROBLER, J. P., & VAN DER BANK, F. H. 1995. Allozyme divergence among four
representatives of the subfamily Alcelaphinae (family: Bovidae). Comparative
Biochemistry and Physiology ,112:303–308.
HALTENORTH, T., 1963. Classification of Mammals: Artiodactyla. Handbook of
Zoology, 8 (32), page.1- 167th
HARRISON, R. G. 1993. Hybrid zones and the evolutionary process. Oxford
University Press on Demand.
HARTL, D. L., CLARK, A. G., & CLARK, A. G. 1997. Principles of population
genetics Volume. 116. Sunderland: Sinauer associates.
HEBERT, P. D., CYWINSKA, A., & BALL, S. L. 2003. Biological identifications
through DNA barcodes. Proceedings of the Royal Society of London B:
Biological Sciences, 270:313-321.
HEDRICK, P. W. 1995. The Florida Gene Flow and Genetic Restoration: Panther as
a Case Study. Conseravtion Biology, 9: 996–1007.
HEDRICK, P. W. 2009. Conservation genetics and North American bison (Bison
bison). Journal of Heredity, 100: 411–420.
HOLSINGER, K. E., & WEIR, B. S. 2009. Genetics in geographically structured
populations: defining, estimating and interpreting FST. Nature ReviewsGenetics,
10: 639-650.
HOSKING, L., LUMSDEN, S., LEWIS, K., YEO, A., MCCARTHY, L., BANSAL, A., &
XU, C. F. 2004. Detection of genotyping errors by Hardy–Weinberg equilibrium
testing. European Journal of Human Genetics, 12: 395-399.
HUANG, N.,E. LINACRE, A.& LEE, J., C. 2001. Cytochrome b gene for species
identification of the conservation animals. Forensic Science International, 122:7-
18.
HUFFMAN, B.2004. Ultimate ungulate fact sheet on Bongo (Tragelaphus eurycerus).
www.ultimateungulate.com. Accessed on May 15, 2016.
102
HULME , D., J.SILK J, P., REDWIN, J., M. BARENDSE,W.& BEH, K., J. 1994. Ten
polymorphic ovine microsatellites . Animal Genetcis, 25:434-435.HSIESH, H.,
M. CHIANG, H., L. TSAI, L., C. LAI, S.,Y.
HURST, G. D. D., & JIGGINS, F. M. 2005. Problems with mitochondrial DNA as a
marker in population, phylogeographic and phylogenetic studies: the effects of
inherited symbionts. Proceedings. Biological Sciences / The Royal Society,
272:1525–1534.
IUCN, 2008. "IUCN Red List of Threatened Species" (On-line). Mammals. Accessed
April 12, 2015 at http://www.iucnredlist.org/initiatives/mammals.
JOHNSON, G. C., & TODD, J. A. 2000. Strategies in complex disease mapping.
Current opinion in genetics & development, 10: 330-334.
JOLLEY, K. A., WILSON, D. J., KRIZ, P., MCVEAN, G., & MAIDEN, M. C. J. 2005.
The influence of mutation, recombination, popula7tion history, and selection on
patterns of genetic diversity in Neisseria meningitidis. Molecular Biology and
Evolution, 22:562–569.
JORGE, W., BUTLER, S., & BENIRSCHKE, K. 1976. Studies on a male eland× kudu
hybrid. Journal of reproduction and fertility, 46:13-16.
JOSHI, D., CHOOCHOTE, W., & MIN, G. S. 2009. Short report: Natural hybrid
between Anopheles kleini and Anopheles sinensis. American Journal of Tropical
Medicine and Hygiene, 81:1020–1022.
KALINOWSKI, S. T. 2004. Counting alleles with rarefaction: private alleles and
hierarchical sampling designs. Conservation. Genetics. 5: 539-543.
KANAGAWA, H., & HAFEZ, E. S. E. 1973. Morphology of cervix uteri of Rodentia,
Carnivora and Artiodactyla. Cells Tissues Organs, 84:118-128
KELLER, L. F., & WALLER, D. M. 2002. Inbreeding effects in wild populations.
Trends in Ecology & Evolution, 17: 230-241.
103
KIMURA, M. 1980. A simple method for estimating evolutionary rates of base
substitutions through comparative studies of nucleotide sequences. Journal of
molecular evolution, 16:111-120.
KIMURA, M., & OHTA, T.2014. Protein polymorphism as a phase of molecular
evolution. Essential Readings in Evolutionary Biology, 229, 234.
KINGDON, J.1997. The Kingdon field guide to African mammals, Academic
Press,London.
KINGDON J. 2001. The Kingdon Field Guide to African Mammals, Academic Press,
San Diego.
KINGSWOOD, S. C., KUMAMOTO, A T., CHARTER, S. J., HOUCK, M. L., &
BENIRSCHKE, K. 2000. Chromosomes of the antelope genus Kobus
(Artiodactyla, Bovidae): karyotypic divergence by centric fusion rearrangements.
Cytogenetics and Cell Genetics,
KNOWLTON, N. & WEIGT, L. A. 1998. New dates and new rates for divergence
across the Isthmus of Panama. Proc. R. Soc. London. 265:2257–2263.
KENYA WILDLIFE SERVICE (KWS). 2008. Conservation and management strategy
for Grevy’s zebra (Equus grevyi) in Kenya 2007-2011. Kenya: Kenya Wildlife
Service
LEARY R.,F. ALLENDORF F., W. FORBES S.,H.1993. Conservation genetics of bull
trout in the Columbia and Klamath River Drainages. Conservation . Biology.,
7:856–865.
LEWONTIN, R. C., & KOJIMA, K. I. 1960. The evolutionary dynamics of complex
polymorphisms. Evolution, 458-472.
LEWONTIN, R. C., & BIRCH, L. C. 1966. Hybridization as a Source of Variation for
Adaptation to New Environments. Evolution, 20: 315–336.
LESPINASSE, D., RODIER-GOUD, M., GRIVET, L., LECONTE, A., LEGNATE, H.,
& SEGUIN, M. A. 2000. A saturated genetic linkage map of rubber tree (Hevea
104
spp.) based on RFLP, AFLP, microsatellite, and isozyme markers. Theoretical
and Applied Genetics, 100:127-138.
LORENZEN, E. D., SIMONSEN, B. T., KAT, P. W., ARCTANDER, P., &
SIEGISMUND, H. R. 2006. Hybridization between subspecies of waterbuck
(Kobus ellipsiprymnus) in zones of overlap with limited introgression. Molecular
Ecology, 15: 3787–3799.
LI, DEJUN, ZHIHUI XIA, ZHI DENG, XIANGHONG LIU, AND FUYING FENG. 2013.
"Development,characterization, genetic diversity and cross-species/genera
transferability of ILP markers in rubber tree (Hevea brasiliensis)", Genes &
Genomics,
LOWE, V., & GARDINER, A. 1974. A re-examination of the subspecies of red deer
(Cervus elaphus) with particular reference to the stocks in Britain. Journal Of
Zoology, 174:185–201.
LYNCH, M., & O’HELY, M. 2001. Captive breeding and the genetic fitness of natural
populations. Conservation Genetics, 2:363–378.
LYNCH, M., & WALSH, B. 1998. Genetics and analysis of quantitative traits, 980.
LYNCH, M., & CONERY, J. S. 2000. The evolutionary fate and consequences of
duplicate genes. Science, 290: 1151-1155.
MASEMBE, C., MUWANIKA, V. B., NYAKAANA, S., ARCTANDER, P., &
SIEGISMUND, H. R. 2006. Three genetically divergent lineages of the Oryx in
eastern Africa: Evidence for an ancient introgressive hybridization. Conservation
Genetics, 7:551–562.
MARSHALL, T. C., SUNNUCKS, P., SPALTON, J. A., GRETH, A., & PEMBERTON,
J. M. 1999. Use of genetic data for conservation management: the case of the
Arabian oryx. Animal Conservation, 2: 269-278.
MCDEVITT, A. D., MARIANI, S., HEBBLEWHITE, M., DECESARE, N. J.,
MORGANTINI, L., SEIP, D.,MUSIANI, M. 2009. Survival in the Rockies of an
105
endangered hybrid swarm from diverged caribou (Rangifer tarandus) lineages.
Molecular Ecology, 18:, 665–679.
MCNEELY, J. A., K. R. MILLER, W. V. REID, R. A. MITTERMEIER, AND T. B.
WERNER. 1990. Conserving the world’s biological diversity. IUCN, World
Resources Institute, Conservation International, WWF-US, and the World Bank,
Washington, DC.
MEETSER H.M J.SETZER. 1971. Setzer H.M . 1971. City of Washington:
Simithsonian Institution Press.
NEEL, M. C., & ELLSTRAND, N. C. (2003). Conservation of genetic diversity in the
endangered plant Eriogonum ovalifolium var. vineum (Polygonaceae).
Conservation Genetics, 4:337-352.
NEI M, MARUYAMA T, CHAKRABORTY R 1975 The bottleneck effect and genetic
variability in populations. Evolution, 29:1–10.
NEWBY, J. . 1978. Scimitar-horned Oryx – the End of the Line ?, 14(03), 219–221.
NEWELL-FUGATE, A. NOTHLING,J. BERTSCHINGER, H.2012. Seasonal changes
in steroid hormone profiles, body weight, semen quality and the reproductive
tract in captive wild dogs (Lycaon pictus) in South-Africa. Gen Comp Endocrinol
178:272–281
NOWAK, R. M. 1999. Walker's Mammals of the World Volume. 1. JHU Press.
O'BRIEN, S., J. WOMACK, J., E. LYONS, L.,A. MOORE,K.,J. JENKINS, N.,A. &
COPELAND, N.,G. 1993. Anchored reference loci for comparative genome
mapping animals . Nature genetics, 3:103-112.
O’BRIEN S.J. MENNINGER JC, NASH WG 2006 Atlas of mammalian
chromosomes. John Wiley & Sons, Hoboken
PACLT, J. 1952. Hybrids and Taxonomy. Taxon, 1: 117-118.
106
PARKER, K. M., SHEFFER, R. J., & HEDRICK, P. W. 1999. Molecular variation and
evolutionarily significant units in the endangered Gila topminnow. Conservation
Biology, 13: 108-116.
PEAKALL, R. O. D., & SMOUSE, P. E. 2006. GENALEX 6: genetic analysis in Excel.
Population genetic software for teaching and research. Molecular ecology notes,
6(1), 288-295.
PERRIER, C., GRANDJEAN, F., LE GENTIL, J., CHERBONNEL, C., & EVANNO, G.
2011. A species-specific microsatellite marker to discriminate European Atlantic
salmon, brown trout, and their hybrids. Conservation Genetics Resources,
3:131-133.
PETIT, R., EL MOUSADIK, A. AND PONS, O. 1998. Identifying populations for
conservation on the basis of genetic markers. ? Conservation. Biology. 12: 844-
855.
PITRA, C., VAZPINTO, P., O’KEEFFE, B. W. J., WILLOWS-MUNRO, S., JANSEN
VAN VUUREN, B., & ROBINSON, T. J. 2006. DNA-led rediscovery of the giant
sable antelope in Angola. European Journal of Wildlife Research, 52: 145–152.
PRIMMER, C.R., MOLLER, A.P. & ELLEGREN, H. 1996. A wide-range survey of
cross-species microsatellite amplification in birds. Molecular. Ecology., 5:365–
378.
PRITCHARD, J. K. 2010. Documentation for structure software : Version 2 . 3. In
Practice, 6: 321–326.
POOTAKHAM, W., CHANPRASERT, J., JOMCHAI, N., SANGSRAKRU, D.,
YOOCHA, T., THERAWATTANASUK, K., & TANGPHATSORNRUANG, S.
2011. Single nucleotide polymorphism marker development in the rubber tree,
Hevea brasiliensis (Euphorbiaceae). American journal of botany, 98:337-338.
RACH, J. DESALLE, R. SARKAR, I.,N. SCHIERWATER,B. & HADRYS, H. 2008.
Character-based DNA barcording allows discrimination of genera, species and
107
population in Odonata. Proceeding of the Royal Society of London Boilogical
Sciences, 275:237- 247.
RANDI, E. 2008. Detecting hybridization between wild species and their
domesticated relatives. Molecular Ecology, 17:285–293.
RANDI, E., & BERNARD-LAURENT, A. 1999. Population genetics of a hybrid zone
between the Red-legged partridge and Rock partridge. Population Genetics,
116: 324–337.
REED, D. H., & FRANKHAM, R. 2003. Correlation between Fitness and Genetic
Diversity\rCorrelación entre Adaptabilidad Diversidad Genética. Conservation
Biology, 17: 230–237.
RHYMER, J.M.SIMBERLOFF,D.1996. Extinction By Hybridization and Introgression.
Annual Review of Ecology and Systematics, 27:83–109.
RHYMER, J. M. 2006. S33-4 Extinction by hybridization and introgression in anatine
ducks. Acta Zoological Sinica, 52: 583-585.
RICE, W. R. 1989. Analyzing tables of statistical tests. Evolution, 43:223-225.
RICO, C., RICO, I. & HEWITT, G. 1996. 470 million years of conservation of
microsatellite loci among fish species. Proc. R. Social. London, B, Biology.
Science, 263:549–557.
RISCH, N. J. 2000. Searching for genetic determinants in the new millennium.
Nature, 405: 847-856.
ROBINS, J., H. HINGSTON,M. MATISOOSMITH, E., L ROSSH., A. 2007.
Identification Rattus species using mitochondrial DNA. Molecular Ecology
Notes, 7:717-729.
ROBINSON, T. J., MORRIS, D. J., & FAIRALL, N. 1991. Interspecific hybridization in
the bovidae: Sterility of Alcelaphus buselaphus ?? Damaliscus dorcas F1
progeny. Biological Conservation, 58: 345–356.
108
ROBINSON, T. J., H. CERNOHORSKA, E. SCHULZE,AND A. &DURAN-PUIG.
2015. "Molecular cytogenetics of tragelaphine and alcelaphine interspecies
hybrids: hybridization, introgression and speciation in some African antelope",
Biology Letters.
ROY, C. B., NAZEER, M. A., & SAHA, T. 2004. Identification of simple sequence
repeats in rubber (Hevea brasiliensis). Current Science-Bangalore-, 87:807-810.
SAITOU, N. & NEI, M. 1987 The neighbor‐joining method: a new method for
reconstructing phylogenetic trees. Molelacur. Biology. Evolution., 4: 406–425
SCHLÖTTERER C, AMOS W, &TAUTZ D. 1991. Conservation of polymorphic
simple sequence loci in cetacean species. Nature, 354:63–65.
SCHWARTZ, M. K., PILGRIM, K. L., MCKELVEY, K. S., LINDQUIST, E. L., CLAAR,
J., J.LOCH, S., & RUGGIERO, L. F. 2004. Hybridization between Canada lynx
and bobcats: Genetic results and management implications. Conservation
Genetics, 5: 349–355.
SCHOEMAN S.,J. MAREE C. &COMBRINK G.,C. 1987. The relationship between
testis size and stimulated plasma testosterone concen- trations and its influence
on mating performance in Dorper rams. South Africa Journal Animal Science
17:64
SCRIBNER, K. T., WARRILLOW, J. A., LEAFLOOR, J. O., PRINCE, H. H., INMAN,
R. L., LUUKKONEN, D. R., & FLEGEL, C. S. 2003. Genetic methods for
determining racial composition of Canada Goose harvests. The Journal of
wildlife management, 122-135.
SELKOE, K. A., & TOONEN, R. J. 2006. Microsatellites for ecologists: A practical
guide to using and evaluating microsatellite markers. Ecology Letters, 9:615–
629.
SHACKLETON, D., A. HARESTED. 2010. "Bovidae (Antelopes, cattle, bison,
buffaloes, goats, and sheep)" (On-line). Grzimek's Animal Life. Accessed April
14, 2015 at http://animals.galegroup.com.
109
SLATE, J., COLTMAN, D. W., GOODMAN, S. J., MACLEAN, I., PEMBERTON, J.
M., & WILLIAMS, J. L. 1998. Bovine microsatellite loci are highly conserved in
red deer (Cervus elaphus), sika deer (Cervus nippon) and Soay sheep (Ovis
aries). Animal Genetics, 29(June), 307–315.
SLATKIN, M. 1994. An exact test for neutrality based on the Ewens sampling
distribution. Genet. Res., 64:71–74.
SUNDEN, S., L., F, T.STONE, M.,D. BISHOP,S. , M. KAPPES, J.,W. KEELE &
BEATTIE, G., W. 1993."A highly polymorphic bovine microsatellite locus
BM2113". Animal Genetics 1:69-69.
SPEAR, D., & CHOWN, S. L. 2009. The extent and impacts of ungulate
translocations: South Africa in a global context. Biological Conservation, 142:
353-363.
SPINAGE C., A.1982. A Territorial Antelope: The Uganda Waterbuck. Academic
Press, London and New York.
SPRUELL P, BARTRON M, KANDA N, ALLENDORF F.,W. 2001. Detection of
hybrids between bull trout (Salvelinus confluentus) and brook trout (Salvelinus
fontinalis) using PCR primers complementary to interspersed nuclear elements.
Copia, 4:1093–1099.
STEFFEN , P. EGGEN, A. STRANZINGER G. FRIES, R. DIETZ A., B.WOMACK,J.,
E. 1993.Isolation and mapping of polymorphic microsatellites in cattle. Animal
Genetics, 24:121-124.
TAMURA, KOICHIRO, GLEN STECHER, DANIEL PETERSON, ALAN FILIPSKI,
AND SUDHIR KUMAR. 2013."MEGA6: molecular evolutionary genetics analysis
version 6.0." Molecular biology and evolution 30: 2725-2729.
TAYLOR C.,R. SPINAGE C.,A. LYMAN C.,P.1969. Water relations of the waterbuck,
an East African antelope. American Journal of Physiology, 217:630–634.
110
TOLDO , S., S. FRIES, R. STEFFEN, P.. NIEBERG, H.,L. BARENDSE, W..
WOMACK, J., E. HETZEL, D.,J., S. & STRANZINGER, G. 1993. Physically
mapped , cosmid-derived microsatellite markersas anchor locion bovin
chromosomes. Mammalian Genome, 4:720-727.
TRIGO T., C. FREITAS T.,R.,O. KUNZLE,R G. CARDOSO L. SILVA J.,C., R.
JOHNSON W.,E. O’BRIEN S., J.BONATTO S.,L., E. IZIRIK, E. 2008. Inter-
species hybridization among Neotropical cats of the genus Leopardus, and
evidence for an introgressive hybrid zone between L. geoffroyi and L. tigrinus in
southern Brazil. Molecular Ecology 17: 4317–4333.
VAN DER WALT, J. M., NEL, L. H., & HOELZEL, A. R. 2001. Characterization of
major histocompatibility complex DRB diversity in the endemic South African
antelope Damaliscus pygargus: a comparison in two subspecies with different
demographic histories. Molecular Ecology, 10: 1679-1688.
VAN OOSTERHOUT C.HUTCHINSON W.,F.WILLS D.,P.,M.SHIPLEY P. 2004.
Micro-checker: software for identifying and correcting genotyp- ing errors in
microsatellite data. Molecular Ecology Notes 4:535–538.
VAN WYK, A. M., KOTZÉ, A., RANDI, E., & DALTON, D. L. 2013. A hybrid dilemma:
A molecular investigation of South African bontebok (Damaliscus pygargus
pygargus) and blesbok (Damaliscus pygargus phillipsi). Conservation Genetics,
14:589–599.
VARGHESE, Y. A., KNAAK, C., SETHURAJ, M. R., & ECKE, W. 1997. Evaluation of
random amplified polymorphic DNA (RAPD) markers in Hevea brasiliensis.
Plant Breeding, 116: 47-52.
VAUGHAN, T.A., RYAN, J.M. AND CZAPLEWSKI, N.J. 2013. Mammalogy. Jones &
Bartlett Publishers.
VERNESI, C., CRESTANELLO, B.PECCHIOLI, E., TARTARI, D.CARAMELLI, D.
HAUFFE, H.& BERTORELLE, G. 2003. The genetic impact of demographic
decline and reintroduction in the wild boar (Sus scrofa): A microsatellite
analysis. Molecular Ecology, 12:585–595.
111
VENKATACHALAM, P., PRIYA, P., AMMA, C. S., & THULASEEDHARAN, A. 2004.
Identification, cloning and sequence analysis of a dwarf genome-specific RAPD
marker in rubber tree [Hevea brasiliensis (Muell.) Arg.]. Plant cell reports, 23:
327-332.
WALTHER, F. 1990. Bovids. in S Parker, ed. Grzimek's Encyclopedia of Mammals,
Vol. 5, 1 Edition. New York: McGraw-Hill Publishing Company. Page. 288-324,
338-339, 354-355, 432-433, 444-445, 460-461, 482-483
WERNER, F. A. O., DURSTEWITZ, G., HABERMANN, F. A., THALLER, G.,
KRÄMER, W., KOLLERS, S., & FRIES, R.2004. Detection and characterization
of SNPs useful for identity control and parentage testing in major European
dairy breeds. Animal genetics, 35: 44-49.
WHITHAM, T. G., BAILEY, J. K., SCHWEITZER, J. A., SHUSTER, S. M.,
BANGERT, R. K., LEROY, C. J., ... & FISCHER, D. G. 2006. A framework for
community and ecosystem genetics: from genes to ecosystems. Nature
Reviews Genetics, 7: 510-523.
WOLF, D. E., TAKEBAYASHI, N., & RIESEBERG, L. H. 2001. Predicting the risk of
extinction through hybridization. Conservation Biology, 15: 1039–1053.
WURSTER, D. H. 1972. Sex-chromosome translocations and karyotypes in bovid
tribes. Cytogenetic and Genome Research, 11: 197-207.
WRIGHT, S. 1978. Evolution ant the Genetics of Populations. Vol 4. Variability within
and among natural populations. Chicago, University of Chicago Press.
YANG, Z., & RANNALA, B. 2012. Molecular phylogenetics: principles and practice.
Nature Reviews Genetics, 13:303-314.
ZALAPA, J., E. 2010. The extent of hybridization and its impact on genetic diversity
and population structure of an invasive tree, Ulmus pumila(Ulmaceae)",
Evolutionary Application, 03.
112
ZARAMODY, A, & PASTORINI, J. 2001. Indications for hybridisation between red-
fronted lemurs (Eulemur fulvus rufus) and mongoose lemurs (E. mongoz) in
northwest Madagascar. Lemur News, 6:28–31.
ZHANG, Y. D., & TIER, B. 2009. Population stratification, not genotype error, causes
some SNPs to depart from Hardy-Weinberg Equilibrium. In Proc. Association.
Advmt. Animal Breeding and Genetics Volume. 18, page. 243-246.
ZONG, E., & FAN, G. 1989. The variety of sterility and gradual progression to fertility
in hybrids of the horse and donkey. Heredity, 62: 393-406.
113
Annexure A:Observed Hardy-Weinberg equilibrium, expected heterozygosity and observed heterozygosity per locus per lechwe and waterbuck sampled
population
Population
ETH10
BM2113
ILST87
TGLA263
BM804
BMS4008
MCM527
BM415
BM757
DIK020
BM3517
BM1443
BM13291
BM203
MTGT4
INRA 128
OARFCB3
04
Lechwe Limpopo
Expected (He)
0.428 0.464 0.607 0.464 0.428 0.857 * 0.428 0.464 0.250 0.821 0.750 * * * 0.857 0.785
Observed (Ho)
0.000 0.250 0.500 0.250 0.000 0.750 * 0.000 0.250 0.250 0.250 0.750 * * * 0.500 0.500
P.value **0.042 0.141 0.430 0.144 0.142 0.654 * 0.141 0.143 1.000 **0.028 0.658 * * * 0.121 0.312
Freestate Expected (He)
0.166
*
0.166
*
*
0.439
*
*
*
*
0.787
0.166
0.303
*
*
0.600
*
Observed (Ho)
0.166 * 0.166 * * 0.500 * * * * 0.333 0.166 0.000 * * 1.000 *
P.value 1.000 * 1.000 * * 1.000 * * * * **0.014 1.000 **0.091 * * 0.399 *
Waterbuck Limpopo Expected (He)
0.489
0.721
0.663
0.587
0.649
0.680
*
0.729
0.827
0.738
0.793
0.643
0.323
*
0.147
0.781
0.849
Observed (Ho)
0.461 0.833 0.615 0.307 0.615 0.923 * 0.923 0.923 0.615 0.769 0.615 0.230 * 0.153 0.538 0.769
P.value 0.525 0.525 0.083 *0.024 0.281 0.112 * 0.646 0.922 0.209 0.210 0.251 0.374 * 1.000 *0.000 *0.000
FreestateExpected (He)
* 1.000 0.933 1.000 1.000 * * 0.866 0.933 0.600 1.000 1.000 1.000 0.533 * 0.833 0.933
Observed (Ho)
* 1.000 1.000 1.000 1.000 * * 1.000 1.000 0.666 1.000 1.000 1.000 0.000 * 1.000 1.000
P.value * 1.000 1.000 1.000 1.000 * * 0.465 1.000 1.000 1.000 1.000 1.000 0.200 * 1.000 1.000
114
**Represent values that are less than (P<0.05) which are not at hardy Weinberg, * markers that were monomorphic and excluded in test.
Eastern Cape Expected (He)
0.500
0.833
0.833
0.833
0.500
*
0.666
0.833
0.500
0.500
1.000
0.500
*
*
0.500
1.000
0.500
Observed (Ho)
0.500 1.000 1.000 0.1000 0.500 * 0.000 1.000 0.500 0.500 1.000 0.500 * * 0.500 1.000 0.500
P.value 1.000 1.000 1.000 1.000 1.000 * 0.333 1.000 1.000 1.000 1.000 1.000 * * 1.000 1.000 1.000
115
Annexure B:Observed Hardy-Weinberg equilibrium, expected heterozygosity and observed heterozygosity between Gemsbok and Scimitar Oryx
Population SRCRSP8 ILST87 BMC3224 MCM527 BM719 BM1329 BM2113 OARCP26 BM203
Scimitar Oryx Gauteng
Expected (He) 0.716 0.732 0.695 0.500 0.261 0.624 0.738 0.833 0.730 Observed (Ho) 0.642 1.000 0.642 0.500 0.071 0.500 0.718 0.785 0.928 P.value **0.001 **0.010 **0.004 0.124 0.004 0.114 0.194 **0.010 **0.078
Northern Cape Expected (He)
1.000 1.000 0.500 0.500 0.833 0.833 0.833 0.500 0.833
Observed (Ho) 1.000 1.000 0.500 0.500 0.500 0.500 1.000 0.500 1.000 P.value 1.000 1.000 1.000 1.000 0.332 0.331 1.000 1.000 1.000
North West Expected (He)
0.642 0.464 * * * 0.535 0.785 0.571 0.800
Observed (Ho) 0.750 0.500 * * * 0.750 0.500 0.500 1.000 P.value 1.000 1.000 * * * 1.000 0.310 1.000 1.000
Gemsbok Gauteng Expected (He) 0.666 0.500 0.833 * 0.500 0.833 0.500 * 0.500 Observed (Ho) 1.000 0.500 1.000 * 0.500 1.000 0.500 * 0.500 P.value 1.000 1.000 1.000 * 1.000 1.000 1.000 * 1.000
Northern Cape Expected (He)
0.866 0.600 0.533 * 0.333 0.733 0.733 0.600 0.600
Observed (Ho) 1.000 1.000 0.666 * 0.333 0.666 1.000 0.333 0.666 P.value 1.000 0.399 1.000 * 1.000 1.000 1.000 0.199 1.000
Limpopo Expected (He)
0.809 0.793 0.630 0.097 0.711 0.771 0.752 0.221 0.616
Observed (Ho) 0.619 0.761 0.714 0.100 0.476 0.428 0.238 0.142 0.380 P.value **0.047 0.232 0.169 1.000 0.105 **0.000 0.000 0.311 **0.008
**Represent values that are less than (P<0.05) which are not at hardy Weinberg, * markers that were monomorphic and excluded in test.
116
Annexure C:Observed Hardy-Weinberg equilibrium, expected heterozygosity and observed heterozygosity between Greater kudu and Nyala
Population BM415 SRSRSP8 ILST87 BM719 BM1329 BM203 BM2113 ETH10 OARCP26 Greater Kudu
Limpopo Expected (He) 0.768 0.323 0.378 0.520 0.631 0.480 0.440 0.301 0.682 Observed (Ho) 0.720 0.250 0.434 0.400 0.636 0.480 0.040 0.280 0.766 P.value 0.318 0.613 1.000 0.001 0.712 0.815 1.000 1.000 0.338
Freestate Expected (He)
* * * 1.000 * * * * 1.000
Observed (Ho) * * * 1.000 * * * * 1.000 P.value * * * 1.000 * * * * 1.000
Gauteng Expected (He)
0.333 * 0.667 0.333 0.333 0.333 * 1.000 1.000
Observed (Ho) 0.333 * 0.733 0.333 0.333 0.333 * 0.600 0.600 P.value 1.000 * 1.000 1.000 1.000 1.000 * 0.399 0.401
Eastern Cape Expected (He)
1.000 * 0.500 1.000 * 0.500 * 0.500 *
Observed (Ho) 1.000 * 0.500 0.833 * 0.333 * 0.500 * P.value 1.000 * 1.000 1.000 * 0.335 * 1.000 *
Nyala Limpopo Expected (He)
0.691
0.608
0.125
0.741
0.833
*
*
0.525
0.591
Observed (Ho) 0.625 0.875 0.125 0.625 0.750 * * 0.625 0.375 P.value 0.590 0.328 1.000 1.000 0.880 * * 1.000 0.050
Unknown Expected (He)
0.633 0.751 0.712 0.441 0.866 0.294 * 0.666 0.500
Observed (Ho) 0.750 0.777 0.555 0.250 0.875 0.333 * 1.000 0.500 P.value 0.022 0.120 0.140 0.015 0.240 1.000 * 1.000 1.000
**Represent values that are less than (P<0.05) which are not at hardy Weinberg, * markers that were monomorphic and excluded in test.