) in the mekong delta, vietnam - qut...hypophthalmus) in the mekong delta, vietnam’ bui, thi lien...
TRANSCRIPT
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Impacts of traditional husbandry practices on exploitable levels of
genetic diversity in cultured ‘Tra’ catfish (Pangasianodon
hypophthalmus) in the Mekong Delta, Vietnam’
Bui, Thi Lien Ha
B.Sc, University of Natural Sciences, Vietnam
Biogeosciences
Faculty of Science and Technology FaST
Queensland University of Technology
Brisbane, Australia
Submitted in fulfillment of the requirement of the degree of Master of Science
September 2011
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Abstract
Sutchi catfish (Pangasianodon hypophthalmus) – known more universally by the
Vietnamese name ‘Tra’ is an economically important freshwater fish in the Mekong
Delta in Vietnam that constitutes an important food resource. Artificial propagation
technology for Tra catfish has only recently been developed along the main
branches of the Mekong River where more than 60% of the local human population
participate in fishing or aquaculture. Extensive support for catfish culture in general,
and that of Tra (P. hypophthalmus) in particular, has been provided by the
Vietnamese government to increase both the scale of production and to develop
international export markets. In 2006, total Vietnamese catfish exports reached
approximately 286,602 metric tons (MT) and were valued at 736.87 $M with a
number of large new export destinations being developed. Total value of production
from catfish culture has been predicted to increase to approximately USD 1 billion
by 2020. While freshwater catfish culture in Vietnam has a promising future,
concerns have been raised about long-term quality of fry and the effectiveness of
current brood stock management practices, issues that have been largely neglected
to date.
In this study, four DNA markers (microsatellite loci: CB4, CB7, CB12 and CB13) that
were developed specifically for Tra (P. hypophthalmus) in an earlier study were
applied to examine the genetic quality of artificially propagated Tra fry in the Mekong
Delta in Vietnam. The goals of the study were to assess: (i) how well available levels
of genetic variation in Tra brood stock used for artificial propagation in the Mekong
Delta of Vietnam (breeders from three private hatcheries and Research Institute of
Aquaculture No2 (RIA2) founders) has been conserved; and (ii) whether or not
genetic diversity had declined significantly over time in a stock improvement
program for Tra catfish at RIA2. A secondary issue addressed was how genetic
markers could best be used to assist industry development. DNA was extracted
from fins of catfish collected from the two main branches of the Mekong River inf
Vietnam, three private hatcheries and samples from the Tra improvement program
at RIA2.
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Study outcomes:
i) Genetic diversity estimates for Tra brood stock samples were similar to, and
slightly higher than, wild reference samples. In addition, the relative contribution by
breeders to fry in commercial private hatcheries strongly suggest that the true Ne is
likely to be significantly less than the breeder numbers used; ii) in a stock
improvement program for Tra catfish at RIA2, no significant differences were
detected in gene frequencies among generations (FST=0.021, P=0.036>0.002 after
Bonferroni correction); and only small differences were observed in alleles
frequencies among sample populations.
To date, genetic markers have not been applied in the Tra catfish industry, but in the
current project they were used to evaluate the levels of genetic variation in the Tra
catfish selective breeding program at RIA2 and to undertake genetic correlations
between genetic marker and trait variation. While no associations were detected
using only four loci, they analysis provided training in the practical applications of
the use of molecular markers in aquaculture in general, and in Tra culture, in
particular.
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TABLE OF CONTENTS
Chapter 1. GENERAL INTRODUCTION ............................................................................. 1 1.1. Status of world fisheries and aquaculture ....................................................... 1 1.2. Role of genetics and population genetics in aquaculture ................................ 4 1.3. Genetic improvement - moving from wild to improved culture strains ............. 8 1.4. The Tra catfish culture industry in Vietnam ................................................... 10 1.5. Tra fry cohort production in private hatchery practices in the Mekong Delta . 12 1.6. Genetic marker applications in aquaculture .................................................. 15 1.7. Specific aims of the current study ................................................................. 18
Chapter 2. MATERIALS AND METHODS ........................................................................ 19 2.1. The Tra catfish selective breeding program at RIA2 ..................................... 19 2.2. Propagation of fry at 3 private hatcheries in the Mekong Delta ..................... 20 2.3. Sample collection .......................................................................................... 20 2.4. Genomic DNA extraction ............................................................................... 22 2.5. Genotyping procedures ................................................................................. 22 2.6. Data analysis................................................................................................. 23
Chapter 3. RESULTS ........................................................................................................ 25 3.1. Part A - Characterisation of genetic variation in cultured and wild populations of Tra catfish ........................................................................................................ 25
3.1.1 Pair wise linkage disequilibrium .............................................................. 26 3.1.2. Conformation to HWE results ................................................................ 26 3.1.3 AMOVA analysis of hierarchical differentiation within and among populations ....................................................................................................... 31 3.1.4. Genetic characterization of sampled Tra catfish culture stocks .............. 32
3.2. Part B - Assessment of the relative contribution by breeders to fry cohorts in three private hatcheries in the Mekong Delta ....................................................... 33
3.2.1. Estimation based on the number of males and females in the brood stock .......................................................................................................................... 34 3.2.2. Estimated number of males and females actually contributing to offspring, based on the results of pedigree analyses using CERVUS v3.0 software. ....... 35
Chapter 4. EVALUATION OF THE LEVELS OF GENETIC VARIATION IN THE TRA CATFISH SELECTIVE BREEDING PROGRAM AT RIA2 AND GENETIC CORRELATIONS BETWEEN GENETIC MARKER AND TRAIT VARIATION (% FILLET YIELD). .............................................................................................................................. 39
4.1. Introduction ................................................................................................... 39 4.2. Methods and Materials .................................................................................. 41 4.3. Results .......................................................................................................... 41
4.3.1. Levels of genetic variation in 3 generations in the Tra catfish selective breeding program ............................................................................................. 41 4.3.2. Genetic correlations between genetic markers and a production trait (% fillet yield) .......................................................................................................... 43
Chapter 5. DISCUSSION .................................................................................................. 47 5.1. Characterisation of genetic variation in cultured and wild populations of Tra catfish ................................................................................................................... 47 5.2. The relative contribution by breeders to fry cohorts in three private hatcheries in the Mekong Delta ............................................................................................. 50
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5.3 The levels of genetic variation in the Tra catfish selection breeding program at RIA2 and genetic correlations between genetic marker and trait variation (% fillet yield) ................................................................................................................................. 51 Chapter 6. GENERAL CONCLUSIONS ............................................................................ 52
6.1. Genetic Diversity in selected Tra catfish lines in cultured and a reference wild populations in the Mekong Delta of Vietnam ........................................................ 52 6.2. Individual brood stock contribution to fry cohorts in three private hatcheries in the Mekong Delta ................................................................................................. 53 6.3. Assessment of possible correlations among genotypes and trait quality ...... 54
REFERENCES .................................................................................................................. 55 APPENDICES ................................................................................................................... 62
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List of figures
Figure 1: Diagram of the structure of the catfish selective breeding program at RIA219 Figures 2: Gelscan images of genetic diversity in RIA2 34 brood fish samples (2a)
and from 3 private hatcheries (n=31) (2b) at locus CB 12; gelscan images of allelic diversity in high fillet yield individuals (2c) and of low fillet yield individuals (n= 24) (2d) at locus CB 12. .................................................... 24
Figure 3: Map of Mekong Delta identifying the main areas where Tra catfish are cultured (grey colour) ................................................................................ 34
Figure 4: Ne estimate for Hau brood fish contributions to offspring on day one and day two for individuals confidently assigned to specific parental pairs. ..... 37
Figure 5: Relative allele frequencies at the CB4, CB7, CB12 and CB13 loci in 3 generations of Tra catfish used in the selective breeding program. .......... 42
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List of tables
Table 1: Sample name, sample size, collection date and source of samples for the whole study. ............................................................................................... 21
Table 2: Primer sequence details of the four microsatellite loci screened ............... 23 Table 3: The potential for null alleles for each locus by sample detected using
MICRO-CHECKER..................................................................................... 25 Table 4: Observed and expected heterozygosities (Obs. And Exp, respectively),
probability value (P-value) and standard deviation (sd). Significant deviations from HWE indicated as heterozygote deficiency (def), heterozygote excess (excess) or not significant (ns) after Bonferroni correction. .................................................................................................. 27
Table 5: Microsatellite polymorphism in 7 sample populations of wild and cultured Tra catfish populations. .............................................................................. 30
Table 6: The statistical significance of FST values of population differentiation ...... 31 Table 7: Statistical significance of FST values (the significance of population) among
sample pairs. P values that were significant after Bonferroni correction (α (Bonf) = 0.05/number of test = 0.05/ 21 = 0.002) are highlighted ............... 32
Table 8: Estimation of Ne in three private hatcheries based on the number of male and female brood stock .............................................................................. 35
Table 9: Parentage assignment rate of 3 groups of brood fish and 3 groups of fry . 36 Table 10: Genetic correlations between genetic marker and % fillet yield phenotypic
classes ....................................................................................................... 44
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Statement of Original Authorship
The work contained in this thesis has not been previously submitted for a degree or
diploma at any other higher education institution. To the best of my knowledge and
belief, the thesis contains no material previously published or written by another
person except where due reference is made.
Signed:
Date: 09/ 09 /2011
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Acknowledgements:
Special thanks to my supervisors Professor Peter Mather and Dr David Hurwood
(Discipline of Biogeosciences, Queensland University of Technology) for their
mentorship and kindness. Thank you to Vincent Chand for laboratory assistance
and technical support. I especially would like to thank my good friend Eleanor
Adamson for all her help and encouragement throughout my time in Australia. I
would also like to thank all my friends in Biogeosciences at QUT.
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Chapter 1. GENERAL INTRODUCTION
1.1. Status of world fisheries and aquaculture
Fish and other aquatic organisms produced in aquaculture have become a major
world food production system that has been called on increasingly to fill the gap
between demand for, and supply of, seafood products for human consumption
(Knibb 2000; Lymbery 2000). Fish produced from culture provide an important
human food resource and can reduce pressure on wild fish stocks in the natural
environment (Lymbery 2000; Primmer, 2005). Aquaculture moreover, is now a key
industry and plays an increasingly important role in global fish production and to
meet rising demand for fish and seafood as many wild fish stocks have declined
over recent decades (Dunham 2000). Under pressure for increased production of
seafood and the need to develop more productive culture strains, many aquaculture
industries are trialling new stock management approaches and attempting to
improve their stock quality (Subasinghe et al. 2000). Development of sustainable
aquaculture production systems that are economically viable and that provide
incomes and livelihoods for poor people in many parts of the globe, is an important
goal in many developing regions around the world.
A number of approaches are being implemented worldwide currently to assist
aquaculture development and to promote a move away from a major reliance on
wild fish resources. They include application of traditional stock improvement
practices (domestication, crossbreeding, hybridisation and artificial selection) that
can deliver more productive culture stocks. This change has required application of
a variety of new technologies including identification of Quantitative Trait Loci
(QTLs), Marker Assisted Selection (MAS) and development and application of
genetic markers among others. The combination of application of traditional
breeding practices with appropriate molecular technologies has been demonstrated
in some aquaculture species to deliver significant productivity increases for culture
industries (Dunham 2000). For example, gene maps are now available for some
important aquaculture species, notably. Channel catfish, tiger shrimp, Japanese
flounder, rainbow trout and Atlantic salmon (Liu 2004).
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Aquaculture Genetics is a relatively new science in many parts of the world, but
where it has been applied it is transforming the performance traits of many cultured
organisms and moving the industry towards enhanced sustainability. For example,
development of the Kansas strain of Channel catfish (Ictalurus punctatus) provides
an excellent example of the potential that applied genetics can offer. This fish is the
oldest domesticated strain of Channel catfish having spent more than a century in
culture. During domestication, growth rates of this strain have increased 3 to 6% per
generation in culture while growth rates of crossbred strains of both Channel catfish
and rainbow trout are 55% and 22% higher, respectively (Dunham 2000). Other
examples include: positive heterosis identified in carp crossbreeds in Israel,
Vietnam, China and Hungary (Moav et al. 1964; Moav and Wohlfarth 1974; Nagy et
al. 1984; Wohlfarth 1993; Hulata 1995); Common carp crossbred lines in Hungary
have shown almost 20% improvement in growth rate compared with pure lines while
a Vietnamese x Hungarian common carp crossbreed is now particularly popular,
due to fast growth and high survival rates under a variety of production
environments; in Bangladesh, a crossing program was instituted for three carp
strains referred to as “Bangladesh”, “Thailand” and “Indonesian” with growth rates
of females from six inter-strain crosses reported to be 23% higher for average
growth rate compared with parental strains (Dunham 2000).
A stock improvement program for European catfish, Silurus glanis, has produced a
culture strain that can tolerate warm water conditions and that can accommodate
mixed diet feeding systems that was achieved via a crossbreeding approach
(Krasznai and Marian 1985). Another example where improved culture lines have
been developed is for walking catfish, Clarias macrocephalus, where improved
tolerance of Aeromonas hydrophila infections was developed by careful application
of a breeding program directed at genes that influence resistance traits (Prarom
1990).
The earliest modern genetic selection program directed at an aquatic species was to
improve survival rate in brook trout (Salvelinus fontinalis), a species that was
susceptible to endemic furunculosis and this program was initiated in the 1920s.
The outcome of this program was to increase survival rate from 2% to 69% after
three generations of artificial selection. Later in 1932, simple selection approaches
were applied to improve the growth rate and fecundity of rainbow trout
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(Oncorhynchus mykiss) in culture (Donaldson and Paul 1957). After 35 years of
direct individual selection, this strain is now widely cultured in the USA and more
widely in other regions across the world (Parsons 1998 cited in Hulata 2000). In
Norway, large stock improvement programs were initiated for Atlantic salmon and
rainbow trout in 1971 and these programs have achieved genetic gains estimated to
be 10 to 15% per generation over the first two generations. Following this, growth
rate and age at sexual maturation traits were targeted from the fifth generation, and
in later generations, disease resistance and meat quality traits were subjected to
artificial selection (Gjedrem 2000). The selected Atlantic salmon culture strain in the
fourth generation showed 77% faster growth rate than control wild fish from the
Namsen River. In 1993, Kirpichnikov reported the outcome of a breeding program in
common carp that employed mass selection to improve resistance to dropsy and
that increased growth rate in Krasnodar in the former Soviet Union (Hulata 2001).
A genetic selection program on gilthead sea bream (Sparus aurata) was also
successful with single-pair offspring groups (full- and half-sibs) employed to improve
production traits (Knibb et al. 1997a). The most widespread fish cultured in Asia
today is a genetically improved strain, the GIFT tilapia (Genetic Improvement of
Farmed Tilapia) and increasingly male hybrid tilapia stocks are also produced widely
(Subasinghe 2000). Several studies have reported, for tilapia strains (Oreochromis
mossambicus, red tilapia, O. aureus and O. niloticus) that mass selection can
improve body weight significantly. Family selection for improved growth rate in the
GIFT Nile tilapia has achieved 77% to 123% improvement with an 11% genetic gain
achieved per generation (Padi 1995).
Carcass quality and percent fillet recovery traits have also been targeted for
improvement in salmonids and catfish (Dunham 1996a). In Thailand, selection for
improved growth rate and disease resistance are currently being trialled for a
number of important native and exotic culture species including pangasiid
freshwater catfish (Pangasius sutchi, syn. of P. hypophthalmus), rohu (Labeo
rohita), Thai walking catfish (Clarias macrocephalus), Java barb (Barbodes
gonionotus), bighead carp (Aristichthys nobilis) and Asian rock oyster (Saccostrea
cucullata) (Dunham 2000). In Australia, genetic improvement programs have been
trialled recently for Pacific oyster (Crassostrea gigas) and Sydney rock oyster
(Saccostrea glomerata). Haley et al. (1975) reported on selection in a related oyster
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species, C. virginica, where adult oysters showed an apparent strong response to
mass selection to improve growth rate (Dunham 2000).
More recently, selection responses reported for body weight at harvest size using a
mass selection approach conducted on Channel catfish (I. punctatus) were high with
genetic gains of 29% for the Kansas strain and 21% for the Marion strain with
associated heritability values of 0.16 and 0.23, respectively (Rezk et al. 2003).
Over the years however, traditional approaches for improving culture stocks have
faced a number of serious challenges with both a decline in the quality of important
production traits and erosion of the response to selection becoming significant
issues for the industry (Knibb 2000; Lymbery 2000). Of increasing interest also are critical concerns about the threats to genetic diversity levels in cultured fish
populations and why there is high risk associated with erosion of exploitable
variation in culture. Understanding the unique attributes of many aquatic species
that make them potentially much more vulnerable to rapid loss of genetic diversity in
culture compared with their terrestrial live stock counterparts will be critical to
developing better breed improvement programs that can assist new aquaculture
industries in many parts of the world.
1.2. Role of genetics and population genetics in aquaculture
Genetic variation or genetic diversity in a population consists of the heritable
information contained in the genome of any population of a species (Kottelat and
Whitten 1996). It describes the diversity of different alleles, or alternative forms of a
given gene that can be found in the target population. Genetic variation implies
presence in individuals in a population of different alleles that if expressed, may
produce a variety of phenotypes. In theory this variation will reflect a population’s
ability to adapt to changes in its environment (Gjedrem 2005). While individuals in a
population cannot predict future environmental change, the more variation that
exists in their collective genomes, the better placed a population will be to adapt to
change if and when it occurs. Thus variable populations will generally respond
better than non-variable ones to environmental change because more exploitable
variation remains.
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In aquaculture, where relatively small brood stock populations are often maintained
separately, the genetic constitution of farmed fish stocks can change rapidly over
just a few generations and where populations are small they will tend to lose genetic
variation rapidly (Gjedrem 2005). This is a critical issue in aquaculture, because
achieving genetic gains from a selective breeding program will ultimately depend on
there being sufficient genetic diversity present in the original brood stock (Yu and Li
2007). The amount of genetic variability present in a target population will ultimately
be influenced by diversity levels in the parental stock and the mating system
employed. Genetic variation is essential for population persistence because
populations with higher levels of genetic diversity have greater adaptive potential
and hence provide the best resources for selective breeding programs (Kottelat and
Whitten 1996, Mable and Adam 2007).
Many studies conducted on a variety of different cultured aquatic species including
brown trout – Salmo trutta (Aho et al. 2006), catla – Catla catla (Alam and Islam
2005), rainbow trout – Oncornhynchus mykiss (Pante et al. 2001), black tiger shrimp
– Penaeus monodon (Xu et al. 2001), sole – Solea senegalensis (Porta et al. 2006)
and Pacific white shrimp – Penaeus vannamei (Moss et al. 2008) have reported
ongoing declines in genetic variation over generations during the very early stages
of domestication with some even reporting complete population homozygosity. In
some instances, virtually all of the natural levels of variation can be lost as a result
of poor stock management practices, so this has become an important issue for
aquaculture.
Aquatic species, unlike most terrestrial farmed livestock species, are particularly
vulnerable to rapid loss of genetic diversity because of inherent characteristics that
are very different to their terrestrial counterparts. First, most aquatic species used in
culture are highly fecund, producing large numbers of gametes per individual with
females often capable of producing millions of eggs in a single mating event. While
survival of fertilised eggs in the wild is usually extremely low (90%) in culture. Thus large numbers of offspring can be
generated form even a single mated pair in culture situations. This is important for
hatchery managers because it means that they often require only a few breeders to
generate all the fry or larvae they will need to meet demand. This immediately
creates problems with conserved genetic diversity levels because while fry/larvae
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numbers may be very high (a good outcome for breeders due to the reduced costs
of producing them), diversity can be low compared with equivalent wild-spawned
offspring cohorts where individual survival rates are often very low.
Where effective population size (Ne) is low, genetic drift and inbreeding can rapidly
erode population levels of genetic diversity and change gene frequencies without
regard to their adaptive potential. Ne is defined as "the number of breeding
individuals in an idealized population that would show the same amount of
dispersion of allele frequencies under random genetic drift or the same amount of
inbreeding as the population under consideration” (Hallerman 2003). Another way of
understanding the concept is that effective population size refers to the number of
individuals that contribute genes in equal proportions to the next generation
(Bensten and Gjerde 1994, Doyle et al. 2001, Bensten and Olesen 2002, Yu and Li
2007). Effective population size is usually considered to be a significant parameter
in many population genetics models and in practice effective population size is often
much smaller than observed population size (N) (Brown et al. 2005, Primmer 2005).
As an example, while there are estimated to be 2000 mature individuals of winter
chinook salmon (Oncorhynchus tshawytscha) in the Sacramento River in California,
the Ne of this population has been estimated to be as low as 85 breeding individuals
each reproductive cycle (Bartley et al. 1992). Japanese flounder, Paralichthys
olivaceus, provides another illustration of Ne
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Population genetics is a field of biology that studies the genetic composition of
biological populations (allele frequency distributions) and the changes in genetic
composition that result from evolutionary forces of which natural selection, genetic
drift, mutation and gene flow are considered to be the major ones that influence
gene frequencies in both natural and cultured populations (Hartl and Clark 1997,
Hallerman 2003). Important applications of population genetics in fisheries and
aquaculture have included delineation of wild stock structure, identification of
breeding units, generating theoretical estimates of effective population size,
assessment of inbreeding rate and documenting levels of genetic variation in target
populations (Tave 1993; Gjedrem 2005).
Population genetic methodologies when applied appropriately in aquaculture can
help to address issues associated with negative impacts of animal husbandry
practices that have the potential to severely impact levels of genetic diversity and
hence cause loss of fitness in cultured aquatic populations. The genetic risks
associated with the domestication process employed to produce fish artificially has
also become an important issue in recent times. Many farmed fish strains have
relatively low levels of genetic variation compared with their wild progenitors
(Hansen et al.1997; Yu and Li 2007). If this causes a decline in stock productivity,
then inbreeding depression (where alleles of low fitness may accumulate in the
stock due to combined impacts of genetic drift and inbreeding) has often been
implicated as a major causal factor. The use of only a limited number of broodstock
can potentially lead to high population levels of inbreeding and consequently cause
rapid declines in population genetic diversity levels. This can be reflected in random
changes in frequency or even total loss of critical alleles responsible for important
production traits (Gaffney 2006). The importance of maintaining high levels of
genetic variation in any brood stock is now appreciated more widely and is
considered to be essential for a stock’s long-term sustainability and productivity
(Mustafa 2003). Small effective population size, line breeding or close relative
mating, are all factors that can contribute to increased levels of inbreeding and
ultimately may result in inbreeding depression; therefore, to limit this potential effect,
where possible animal breeders should maintain pedigree records for their brood
stock. This practice, will allow development of strategies that contribute to
maintenance of a sustainable base population for culture (Reisenbichler and Rubin
1999).
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Understanding the individual attributes of aquatic animal species used in culture,
especially their genetic characteristics, will support science and aquaculture to
provide better solutions to current problems. Thus traditional stock improvement
approaches in aquaculture and modern genomics can benefit from population
genetic theory and methodologies that identify, monitor and conserve genetic
diversity in culture lines.
1.3. Genetic improvement - moving from wild to improved culture strains
Genetic stock improvement programs provide a powerful means for enhancing both
preferred qualitative and quantitative traits in any cultured population (Eknath et al.
1998). Stock enhancement in essence, aims to increase the biomass of the target
species with little or no disadvantageous impacts on native gene pools (Ward 2006).
Maintaining genetic quality in fish stock management is now therefore considered to
be a priority for many aquaculture sectors (Lymbery 2000). While in general, stock
improvement can be used to enhance the majority of desirable traits in seed stocks
(Allan 1999), in reality, however, this practice is often difficult and requires long-term
effort from a large number of scientists with access to appropriate technologies,
facilities and adequate financial support (Hulata 2001; Knibb 2000). Genetic
improvement involves making decisions about which individuals to mate (selection)
and how to mate them in the most optimal way (mating systems) (Allan 1999), while
stock improvement is the ability to select brood stock individuals with an appropriate
combination of superior breeding values for selected economic traits (William 1991).
This outcome will result from fully understanding the genetic variation present in a
stock and applying sound breeding practices. Developing genetically improved
stocks however, requires a complex link between theory and practice and so
requires understanding both an individual’s biological and genetic backgrounds. The
objective of selection is to improve the stock genetically by increasing the frequency
of desirable genes (alleles) while decreasing the frequency of less-desirable ones
(Allan 1999). This needs to occur without significantly eroding exploitable genetic
variation levels to a point where any future response to selection may be
compromised. Additionally, while the focus is on optimizing favourable alleles, this
needs to be achieved without increasing the inbreeding rate to a point where
inbreeding depression may result (Davis and Hetzel 2000).
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Genetic improvement programs in farmed aquatic species around the world for the
most part, have been very successful (Knibb 2000). The power of genetic programs
is to change a cultured stock attributes to fit a purpose or production environment.
Records of genetic enhancement activities were evident in terrestrial agriculture
from the time early humans first made the transition from being hunter-gatherers to
farmers and producers. These achievements not only solved problems associated
with obtaining necessary food resources but also reduced the risk of loss of wild
genetic diversity (Booke 1999). In particular, genetic enhancement can provide
solutions to ongoing emergence of pathogens and parasites in high-density culture
that often result in serious new disease outbreaks. Good genetic management and
selection of strains that are resistant to important pathogens have the potential to
address this emerging problem (Chevassus and Dorson 1990). Furthermore, stock
enhancement can open up new profit opportunities for companies and export
industries.
In fisheries and aquaculture, genetic improvement and stock enhancement efforts
continue to create new opportunities (Liao et al. 2004). Increased demand for
aquatic products together with the significant contribution that aquaculture can make
to world food resources makes the role of genetic stock enhancement an emerging
practice in aquaculture, worldwide (Mustafa 2003). A decade ago, genetically
improved fish and shellfish contributed only around 1% to total global aquaculture
production (Gjedrem 2000); of which only a few species made the major contribution
to this component e.g. 75% of Penaeus japonicus farm stock in Australia were
genetically improved (Hulata 2001). According to well-documented records (Hulata
2001), effective aquatic stock enhancement programs are still in the pioneering
stage and only a limited number of species have been addressed intensively to
date, mostly in developed countries especially Atlantic salmon in Norway and
Channel catfish in the USA.
More recently, a long term and large-scale breeding program was initiated for
Channel catfish (Ictalurus punctatus) and after three generations of selection the
program achieved a 10-20% gain in growth rate per generation (Mahmound et al.
2003). Genetic stock improvement via artificial selection has also been successful in
several other breeding programs including in a cultivated strain of Penaeus
(Litopenaeus) vannamei (Donato et al. 2005), that was then used for stock
enhancement of depleted wild populations (Davenport et al. 1999), There is also a
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long history of stock enhancement in Japan for three finfish species: Japanese
flounder (Paralichthys olivaceus), red sea bream (Pagrus major) and black sea
bream (Acanthopagrus schlegeli) (Fushimi 2001). Moreover, some aquaculture
stock improvement programs in developing countries have achieved positive
outcomes over the past few decades for silver barb (Barbodes gonionotus) selected
for better growth performance in Bangladesh (Hussain et al. 2002) and a
commercial crossbreeding program for common carp in Vietnam (Thien and Thang
1993). Thus, the evidence is clear, where well-designed stock improvement
programs have been implemented for aquatic species, genetic gains can be rapid
and can enhance industry development. Genetic gains from breeding programs for
aquatic species often produce much more rapid gains than equivalent programs in
terrestrial species because genetic variation levels in broodstock are often quite
high as they have only recently been sourced from the wild while terrestrial species
have been domesticated for 100s if not 1000s of generations by humans.
In the current study Pangasianodon hypophthalmus referred to as Tra catfish was
the target species and this species has become a key export industry in Vietnam.
While the Tra catfish culture industry in Vietnam is quite young, it now contributes
significantly to export revenue there, but also the industry is a significant provider of
employment for many poor farmers most importantly, in the Mekong Delta region.
1.4. The Tra catfish culture industry in Vietnam
Two Vietnamese catfish species (Pangasianodon hypophthalmus – Tra) and
(Pangasius bocourti – Basa) are native freshwater fishes that are common and
widely distributed across the Mekong Delta in Vietnam. Both species constitute very
important food fishes in the region (Trong 2007) and occur naturally in both main
branches of the Mekong River. P. hypophthalmus and P. bocourti provide major
protein resources and livelihoods for many rural households particularly during the
flood season. Originally, catfish culture in Vietnam was small-scale and was
generally poorly organized such that most fish were used only for family or local
domestic consumption. Only low quantities were produced in culture and
management of quality was essentially absent. Over a number of decades, a
number of long-term trials were undertaken to close the life cycle of both species in
hatcheries and practices were developed simultaneously by a number of
Vietnamese research institutes, in the south of Vietnam (Mekong Delta) in particular
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by Trinh et al. (2002) that allowed production of catfish fry in sufficient quantities to
support development of a large culture industry. From this simple beginning, culture
of P. hypophthalmus and P. bocourti has gradually become a significant economic
driver and a key income generator for thousands of poor households in the Mekong
Delta.
Covering approximately 40,000 square km and possessing a large young population
of approximately 17 million, the region accounts for 21% of Vietnam’s population
and more than 60% of people participate in fishing there. In 2006, the Vietnamese
fisheries sector accounted for an estimated 6.1% of Gross Domestic Product (GDP)
producing US$ 3.4 billion in export revenue (Nortvedt 2007). Recently, P.
hypophthalmus and P. bocourti were selected to become Vietnam’s aquaculture
product trademark, as cultured catfish has become a major export product.
Following a recent trade war however, the Vietnamese government adjusted
aquaculture export strategies and supported policies for protecting local fish
farmers, processing and export plants. The Vietnamese government has also
recently contributed significantly to, and promoted expansion of, catfish aquaculture
in the Mekong Delta and now sees the industry as playing a major role in social and
economic development for the nation (Monti et al. 2006).
Over recent years, Vietnamese catfish producers have successfully established and
expanded export markets that ensure annual export targets are met. In parallel, the
industry has decreased dependence on the US export market, and has diversified
the variety of available catfish products (Tung et al. 2004). In 2006, the largest
export destinations for Tra and Basa catfish were European countries with export of
123,212 metric tons (MT) worth approximately US$ 343.4 million per annum,
followed by Russia with 42,779 MT estimated value at US$ 83.2 million per annum,
while the American market accepted only 24,281 MT producing US$ 72.9 million per
annum while Australia consumed 10,149 MT valued at US$ 31.0 million per annum.
Thus total catfish exports in 2006 were approximately 286,602 MT valued at a total
of US$ 736.87 million per annum (Nortvedt 2007). Increasing popularity of
Vietnamese catfish in the international aquaculture market reflects recent significant
improvements in product quality. Today more than 60 processing plants have been
developed across the Mekong Delta that produce a variety of catfish products
compared with only eight plants that existed in 1997 (Monti et al. 2006). As a
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consequence, of all fish cultured in Vietnam, catfish now accounts for approximately
80% of exported fish product. Vietnamese catfish production has shown a 36-fold
increase in production since 1997 and this is linked to an increase of 40% in export
of frozen fillets. This now results in a total production of over 825,000 MT
(Lobegeiger 2007), most now going to high value consumers in developed countries
outside Asia.
1.5. Tra fry cohort production in private hatchery practices in the
Mekong Delta Results of a survey by Yen and Trieu (2008) of 30 catfish hatcheries in the Mekong
Delta showed that the majority of brood stock used to produce fry were sourced
from first or second generation domesticated stock. Most hatchery owners possess
only low educational levels rarely above high school level. Initially, most hatchery
owners employed staff with only simple technical training in hatchery techniques
that had been learnt from government extension training programs. From this basic
starting point, practices used in hatcheries were established and now most hatchery
owners undertake their own fry production. In general, two to ten people are
employed in most hatcheries, with the majority being family members. The number
of brood stock held by each hatchery ranges from approximately 100 to over 1000
individuals depending on the hatchery size. For example, one large hatchery in the
Mekong Delta holds approximately 1,700 brood fish (estimated 4 kg each) with a
capacity to produce more than 200 million fry per year (Hung et al. 2008). 47% of
the 30 hatcheries surveyed had collected their brood fish from the wild while 30%
had obtained brood fish from other hatcheries and 23% routinely obtained their
brood fish from both sources. In terms of broodstock management practices,
approximately 73% of hatcheries regularly sourced their brood fish from commercial
grow out ponds, 17% kept their own fry to become brood fish and only 10% of
hatcheries used wild fish to replenish their brood stock supplies (Yen et al. 2008).
While brood stock age varied, most were less than 7 years old while 70% of brood
fish were younger than 5 years because the best reproductive age is 3 to 5 year old
fish with an average weight of 3 to 5 kg. With this approach, brood stocks are
usually replaced every 2 to 3 years. 40% of hatcheries replace brood fish every
year, 60% of the remaining hatcheries have more than two generations of brood fish
while a single hatchery maintains 4 generations of brood fish (Yen and Trieu 2008).
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13
Fish used as brood stock are tagged on their head with a mark and kept separately
in small concrete ponds while two of the 30 hatcheries screened did not tag their
brood stock (Yen and Trieu 2008). Artificial propagation of Tra catfish is carried out
by each farmer where they use sperm from a single male to fertilize 3-5 females
each cycle with an average estimated 120,000 egg/kg female. Some hatcheries mix
the sperm from multiple males to increase their fertilization rate. Almost all of the
hatcheries surveyed produce fry for commercial sale directly, but a few also keep up
to 12.5% for nursing to a larger size before sale. Number of hatchery runs (batches)
varies from 17 to 19 times per year and each brood stock individual is spawned two
to four times per year using a sex ratio of one male to four females. When asked to
comment on fry quality, 70% of Tra hatchery owners considered that fry from
artificial propagation were better or at least of equal quality to fry spawned from wild
brood fish. This is the major reason why 60% of hatchery owners routinely source
their brood fish from their own ponds while only 10% of owners believe that use of
wild fish contributes to better quality fry. A diversity of different breeding practices
have been adopted by hatchery owners from use of only a single pair of fish to
combining batches of fry from multiple crosses to sourcing fry from neighbouring
provinces (Yen and Trieu 2008, Hung et al. 2008). Hatchery owners were surveyed
about issues associated with levels of inbreeding in their hatcheries, with only 40%
responding that they knew that mating related fish can increase the inbreeding rate
and this can affect fry quality; 56% said it was not necessary to consider genetic
relationships among brood fish when producing fry for culture.
During field sampling of brood stock from three private hatcheries in the Hong Ngu
district of Dong Thap Province, specific details of practices in hatcheries were
documented. Two hatchery owners possessed high school level training and the
third was a local aquaculture official. Each produced fry in their hatcheries
themselves and employed 3-5 of their relatives (to assist). Assistants in hatcheries
were also employed elsewhere as teachers or rice farmers or were otherwise
unemployed. Each hatchery had approximately 500 to 1,000 brood stock cages
along the river or brood stock were held in earthen ponds behind houses. No
information was available however, about the number of brood stock used regularly
for spawning, or whether all fish were used to produce fry. Common practice was to
initiate artificial propagation using 40-80 female and 5-10 male brood fish for each
cycle. Before each batch, brood stocks were selected based on visual inspection; if
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they possessed good phenotypes and were healthy. For the initial spawning in each
batch, hatchery owners used about 10-15 quality fish with an average weight of 2-3
kg/individual that were ready to spawn. All eggs were collected from 10-15 females
into a plastic basket and combined with milt from 2-3 males. A single female was
used for 3 to 4 repeat spawns per year and after 2-3 years; individuals were
replaced. In some instances, hatchery managers employed brood fish from other
hatcheries or even wild fish obtained from Cambodia. Most hatchery owners were
quite secretive about their practices and often will not cooperate with government
officials or volunteer information because they think it is not essential and do not like
their business practices being scrutinised. Only a very few owners were interested
in genetic or inbreeding issues with their stocks or saw the relevance of these
issues to their operations.
Provision of appropriate support can allow cultured catfish from Vietnam to become
as well-known an aquaculture brand as has been achieved for Norwegian salmon.
Recent strategies employed in the Mekong Delta industry have increased the catfish
breeding area to 10,200 ha with 1,900 fish cages to be introduced by late 2010 with
a total capacity now exceeding 860,000 MT in output. Export targets predict a
potential production of 230,000 MT of Tra and Basa catfish fillet, earning 600 million
USD in 2010 and this is forecast to increase to 460,000 MT with an estimated
turnover of 1.2 billion USD by 2020 (TheFishSite). There are many reasons why the
catfish culture industry in Vietnam has expanded so rapidly including: the industry
has addressed specific demands from foreign consumers, Pangasius catfish culture
makes an important contribution to household incomes and Vietnam’s export
income has grown and increased employment opportunities in the Mekong Delta.
Improving the quality and productivity of Tra and Basa aquaculture is now seen as a
significant opportunity for Vietnam and if issues are addressed appropriately this will
allow the industry to continue to expand. Currently, virtually nothing is known
however, about how existing management practices of cultured catfish stocks in
Vietnam are impacting levels of genetic diversity. Understanding what impacts (if
any) have occurred will allow better breeding practices to be designed in the future,
if they prove necessary.
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1.6. Genetic marker applications in aquaculture
Exploiting advanced genetic marker technologies can be useful at three levels for
management of aquatic species: i) for detecting simple inherited traits; ii) finding loci
that affect variation in quantitative traits; and iii) for assisting with optimizing
selective breeding outcomes based on marker assisted selection. Examples where
markers have applications in aquaculture include: gene mapping, identification of
sex, individual identification and parentage assignment, population genetic
applications, detecting effects of selection and trans-genesis (Lo Presti 2009).
For example, the basic objective of gene mapping studies is to elucidate the location
of functional genes responsible for important performance and production traits
(Davis and Hetzel 2000; Liu 2006). The position of gene loci encoding simple
inherited characteristics can be located in the genome of a target species by
analysing correlations between allelic variation in families that co-segregate with
markers after linkage analysis (Georges 1998 cited in Davis and Hetzel 2000). Once
identified, gene markers allow screening of parents and progeny and development
of a diagnostic test such as the simple genetic markers used widely for human
disease diagnostics (Hartl and Clark 1997). Many genomics projects have used
microsatellite markers to develop aquaculture databases for target species. For
example, in Europe, there are a number of genetic improvement programs that have
developed more than 100 microsatellite markers for species such as common carp
(Cyprinus carpio), approximately 1,700 microsatellites for Atlantic salmon (Salmo
salar), and more than 250 microsatellites for European sea bass (Dicentrarchus
maximus). Other important species in European aquaculture include flat oyster,
lobster, and Atlantic cod where more than 50 microsatellite markers are available for
each species (Blohm et al. 2006). A very large and long-term project is applying
genetic markers (based on microsatellites) to developing a saturated linkage map
for Channel catfish (Ictalus punctatus). Several hundred microsatellite markers have
been developed over the recent decade for both Channel and blue catfish families
by Liu et al. (2006) and these will contribute to the resulting linkage map. Another
study of Channel catfish developed 293 microsatellite markers to add to the growing
genetic linkage map (Geoffrey et al. 2001). To date, two genetic linkage map
frameworks have been published for the species. The first map developed by
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16
Waldbieser et al. (2001) was established using Channel catfish intra-specific
resource families, and the other was initiated by Liu et al. (2003) using Channel
catfish X blue catfish inter-specific families (Liu 2006). Linkage maps for salmonids
are also under construction with over 228,000 bacterial artificial chromosome (BAC)
clones fingerprinted from Atlantic salmon (Liu 2006). Tilapia, oysters, shrimps and
striped bass are other species where concentrated efforts are being made to map
each species’ entire genome (Liu 2006).
Identification of sex of cultured individuals can also be important in some aquatic
species because one sex may perform better when produced in monosex culture
stocks, an example being culture of all-male freshwater prawn (Macrobrachium
rosenbergii) (Sagi et al. 1998) or Nile tilapia (Oreochromis niloticus niloticus)
(Angienda et al. 2000). Discrimination of phenotypic sex can be quite difficult in the
early larval stages for many aquatic species, but molecular genetics has proven to
be very effective at addressing the problem via detection of sex-linked DNA markers
in different species (Devlin and Nagahama 2002).
For individual identification and parentage assignment, genetic markers can not only
solve problems associated with physical tags that are often difficult or even
impossible to apply in juveniles or farmed molluscs etc. but also significantly
decrease the cost and time required to keep different families in separate ponds, a
process that also limits the number of animals available for selection (Lymbery
2000, Bentsen and Olesen 2002, Liu and Crodes 2004). In parentage analysis,
genetic markers can identify individuals effectively using distinct genotypes from
allelic diversity and allele frequency data. Once genetic information is available for
parental pairs (sires and dams) and their offspring, breeders can construct simple
pedigrees (Martinez 2007). Individual identification combined with pedigree data,
allow the researcher to identify individuals and their genetic relationships to select
those with the best breeding values (Bentsen and Olesen 2002). This can help to
estimate selection response and to optimise breeding parameters (Zhang et al.
2006).
In selection programs, molecular markers can be used to identify genetically
superior individuals; this process is referred to as marker assisted selection (MAS).
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MAS or genome wide marker assisted selection (G-MAS) is a selection process in
which specific candidate genes are identified based on genotypes using molecular
markers (Liu and Crodes 2004) and results from the use of gene markers linked to
QTLs in genetic improvement programs (Davis and Hetzel 2000). To employ MAS,
researchers need to have a clear and high-density linkage map and to understand
comprehensively the number of QTLs that affect each phenotypic characteristic,
their mode of inheritance and potential interactions of different QTLs on traits and
the economic characteristics of the traits studied (Poompuang and Hallerman 1997
cited in Liu and Crodes 2004). MAS in general, is applied mostly to traits that are
otherwise difficult or expensive to measure and QTLs are loci that exert a major
influence on important quantitative traits. Many commercially important traits that
show continuous variation (quantitative traits) are generally influenced by a group of
genes of small additive effect (Falconer 1989). In genetic improvement programs,
QTLs are evaluated as complementary to breeding value estimates of genetic merit
(Davis and Hetzel 2000). QTLs are usually detected by combined analysis of
phenotypes with linked marker maps and they have been applied in a number of
aquaculture stock improvement programs because of their capacity to assist animal
breeders to reach specific breeding goals.
Some examples where molecular genetic approaches have been broadly applied in
genetic improvement programs include Appleyard and Ward (2005), who reported
that 8 microsatellite markers were useful in a mass selection program for Pacific
oyster (Crassostrea gigas) in Australia and New Zealand. Similarly, MacAvoy et al.
(2008) published 49 microsatellite primer sets for a selective breeding program in
the New Zealand GreenshellTM mussel (Perna canaliculus). Asian aquaculture
researchers have also contributed recently to world genetic databases. Eleven
microsatellites were developed to estimate kinship for brood stock management in
Japanese flounder (Paralichthys olivaceus) to minimise risk of inbreeding (Sekino et
al. 2004), while Wang et al. (2006) used 240 microsatellites to screen 24
chromosomes in the karyotype of Asian sea bass (Lates calcarifer), known locally
as Barramundi in Australia. They mapped 5 significant and 24 putative QTLs that
influenced individual body weight. A four-way tilapia cross in Israel also initiated a
linkage map for QTL studies of this important culture species. 20 microsatellites
were found to be associated with two significant QTL traits, one for cold tolerance
and the other for individual growth rate (Moen et al. 2004).
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Currently, much effort and cooperation worldwide is directed at developing QTL
maps or MAS for specific aquaculture species. In Channel catfish, rainbow trout and
tilapias, QTL markers for growth, feed conversion efficiency, tolerance to bacterial
disease, spawning time, embryonic developmental rates and cold tolerance have all
been reported (LaPatra et al. 1993, 1996). In trout and salmon, a candidate DNA
marker linked to infectious haematopoietic necrosis (IHN) disease resistance was
also identified recently (Houston et al. 2008). Thus, genetic markers can assist
animal breeders to improve the quality of their culture stocks.
1.7. Specific aims of the current study
There were four aims in the current study:
i. To assess the genetic status of cultured Tra catfish (Pangasianodon
hypophthalmus) populations in the Mekong Delta of Vietnam,
ii. To evaluate the levels of genetic variation in the Tra catfish selective breeding
program at RIA2 after 3 generations and to estimate the effective population size
and other related genetic parameters in this population.
iii. To assess the percent contribution by individual breeders to fry cohorts and to
estimate effective population size and inbreeding coefficients in three private
hatcheries in the Mekong Delta,
iv. To trial genetic correlations between genetic markers and an important
production trait (fillet yield).
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Chapter 2. MATERIALS AND METHODS
2.1. The Tra catfish selective breeding program at RIA2
A selective breeding program for Tra catfish commenced at the Research Institute
for Aquaculture No 2 (RIA2), Ho Chi Minh City, in 2001. Brood stock used were
obtained as fry produced from wild parents sourced from three private hatcheries–
Truong, Duong, and Ro (WP – TDR). After brood stock were raised for 3 years
(2004), fish were mated as families and tagged for breeding selection at RIA2. The
parental generation was referred to as the ‘P’ generation.
The selective breeding program at RIA2 was initiated to improve fillet yield in 2004.
In 2005, when F1 individuals were 8 months old, the average time to market size, all
individuals were measured. Each fish was measured for total length, weight, and
body depth. Following this, 30 individuals were chosen at random from a sample of
100 fish from each family and individuals were euthanized by professional filleters at
the Angiang catfish-processing plant to assess fillet metrics per family. After filleting,
each individual was weighed for total fillet yield and remaining body components.
Figure 1: Diagram of the structure of the catfish selective breeding program at RIA2
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2.2. Propagation of fry at 3 private hatcheries in the Mekong Delta
In private hatcheries in the Mekong Delta, broodstock are selected as breeders
based on their individual growth performance. In some instances brood stock are
also sourced directly from the wild or are domesticated fish obtained from the
hatchery. Breeders are selected at approximately 2 years of age when they weigh
approximately 3 kg (Yen and Trieu 2008). Of the three hatcheries examined here,
two-employed wild caught brood stock from a local river (Khanh and Hau) while the
third hatchery employed only domesticated stock (Nam). For each fry propagation
cycle, approximately 40 females and 10 males were separated to become brood
stock for artificial spawning. Sperm from two or three males were employed
commonly to fertilize eggs combined from 8 females. Spawns were then pooled
together into a few large batches (depending on the number of eggs produced).
After hatching, newly spawned fry resulting from multiple batches were combined
automatically into a large single circular nursery tank. Samples for the current study
were then collected randomly on the first and second days after fry had hatched. On
the second day, remaining fry were sold to farmers. Samples of fins from all brood
stock individuals and a random sample of whole larvae from brood-tanks were
collected and stored in 70% ethanol at 4°C prior to DNA extraction and genetic
analysis.
2.3. Sample collection
Two groups of samples were available:
Group A (RIA 2 group): The first group comprised individuals from the catfish
selective breeding program at RIA2. This group consisted of 48 founder individuals
collected form the wild in 2001 (WP called TDR); 34 offspring from P (F1) that
contributed to reproduction events in 2005; and 120 selected individuals (F2) that
included 48 high fillet yield individuals, 48 low fillet yield individuals and 24 random
individuals (Controls) in 2006. In addition, 27 individuals were collected from the wild
as a reference sample of wild diversity levels and these individuals were sourced
from two branches of the lower Mekong River (HW: Hau River Wild = 20 fingerlings
and TW: Tien River Wild = 7 samples) in 2008 and 2009, respectively (see Table 1).
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A small piece of fin tissue was removed from each adult fish and samples stored in
70% ethanol at 4°C prior to DNA extraction.
Group B (Private hatcheries group): The second group comprised individuals from
three private hatcheries: Hau, Nam and Khanh owned by smallholders in one of the
two main branches of the Mekong River and (Tien River) that produced fry cohorts
for commercial culture that were chosen for the study in 2008. Sampling was
conducted during fry propagation periods. Eggs were mass hatched in 100 litre
containers and fry were transferred to a 3000 litre tank for nursing; 200 larvae were
sampled on the first and second days (100 each day) after hatching and samples
fixed in 70% ethanol at 4°C prior to DNA extraction. A total of 31 samples of
parental individuals and 600 fry from 3 hatcheries were sampled for the study.
Details of the sampling (Table 1) are presented below.
Table 1: Sample name, sample size, collection date and source of samples for the
whole study.
Sample name Abbreviation Place
Year
n
RIA 2 group (A)
Wild Parents TDR Tien River - wild 2001 47
F1 RIA2 RIA2 - domestic 2005 34
F2 - High fillet H RIA2 - selection 2006 48
F2 - Low fillet L RIA2 - selection 2006 48
F2 - Random R RIA2 - selection 2006 24
Wild reference HW Hau River – wild offspring 2009 20
Wild reference TW Tien River – wild adult 2008 7
Hatcheries group (B)
Hau brood HB Tien River 2008 10
Hau offspring H1 and H2 196
Nam brood NB Domestic 2008 10
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Nam offspring N1 and N2 196
Khanh brood KB Tien River 2008 11
Khanh offspring K1 and K2 196
2.4. Genomic DNA extraction
Total genomic DNA was extracted from all mature brood stock individuals from
approximately 50mg of caudal fin tissue using a standard salt procedure, as
described in the QUT Ecological genetics laboratory manual, a procedure adapted
from Miller et al. (1988).
Total genomic DNA was also extracted from first day, and second day old larvae
using a Chelex procedure (QUT Ecological genetics laboratory manual 2004). This
procedure required that whole larvae were digested overnight at 55°C in 100 μl of
10% Chelex 20mg/ml Proteinase K.
2.5. Genotyping procedures Multi-locus microsatellite genotypes were obtained for each sample individual via
polymerase chain reaction (PCR) amplification using four microsatellite primer sets
purchased from a Thai commercial company (DNA Technology Laboratory, BIOTEC
– Kasetsart University - Thailand) with support from RIA2. Primers were specifically
designed for P. hypophthalmus. Four dinucleotide repeat loci (CB4, CB7, CB12 and
CB13, Table 2) of the ten loci available for Tra catfish were polymorphic and were
screened in the samples available here. PCR amplifications were performed in 10 μl
volumes reaction mixtures containing 1 μl approximately 50 ng of extracted P.
hypophthalmus DNA template, 1 μl of 10X reaction buffer [500 mM KCl, 200 mM
Tris-HCl (pH 8.4)], 1.5 mM MgCl2, 2.5 mM of each DNTP, 5 pM of each primer, 0.5
units of Taq DNA polymerase (Promega, Madison, WI). Thermal cycling was carried
out as follows: initial denaturation at 95oC for 4 min, followed by 30 cycles consisting
of 30 sec denaturising at 95oC, 30 sec annealing at the optimized annealing
temperature (see Table 2), 30 sec extension at 72oC, with a final extension of 10
min at 72oC.
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Table 2: Primer sequence details of the four microsatellite loci screened
Locus Sequence Primer Annealing
Temp (oC) Forward (5’…………………………→3’) Reverse (5’……………………→3’)
CB4 CCA CAT CCT TAT CAC CCT GAA C ACA ATA CAG AGA AAT CCC CAA GG 55
CB7 GAA CAT CCA CAA ACA CAT CAC AC ACT TTC CCG GAG TAA TCG TTG 55
CB12 GCG ATA GAG ACA GAG AGT CAT GG ATC TGG GTC AAA ATG ATT GGA AC 55
CB13 GTG TGT CAA GTT GGG ATC ATG G CTC CAT TTA CAG ACC ATC CGT AG 55
2.6. Data analysis PCR amplified products were screened in acrylamide gels using a Gel-Scan-3000
(Corbet Research) genotyper. Genotypes were scored using One D-scan version
2.05 software (Scanalytics, Inc., 1998). Data were then stored in MSExcel format
(2003). For the pre-data analysis step, allelic data were checked for presence of null
alleles (signified by an excess of homozygotes), large allele drop out (preferential
amplification of small alleles) or incorrect scoring due to stutter bands (created by
slippage during PCR extension) using MICROCHECKER software version 2.2.3
(Van Oosterhout et al. 2004). Microsatellite polymorphisms were quantified by
assessing genetic diversity parameters and how diversity was partitioned within and
among samples: observed (Ho) and expected (He) heterozygosity; inbreeding
coefficients (FIS) and genetic differentiation among samples (FST), using ARLEQUIN
v3.1 software (Schneider et al., 2000). Statistical significance of F statistics was
determined using a non-parametric permutation process incorporating 100
iterations. Allelic richness (An) was estimated using FSTAT v2.9.3 (Goudet 1995).
Exact P-values that test for conformity of genotypes to Hardy–Weinberg proportions
and linkage equilibrium were estimated using a Markov chain method (1000
dememorization steps, 1000 batches, 1000 iterations per batch) using ARLEQUIN.
Estimates of levels of genetic variation in three generations of Tra catfish used in
the selective breeding program at RIA2 and pedigree analysis of hatchery juveniles
were undertaken using CERVUS v3.0 (Kalinowski 2007) software employing
10000 cycles. In all analyses, levels of significance for multiple tests were corrected
using Bonferroni adjustment (Rice, 1989). With exact P value for all experimental
tests set at α = 0.05; after Bonferroni, α (Bonf) = 0.05/ number of tests.
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib33
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Effective population size (Ne) of hatchery stocks from three rivers were estimated
using two methods: i) estimation based on the number of males and females in the
brood stock (Hartl and Clark, 1997) and ii) number of males and females that
actually contributed to offspring, based on results from the pedigree analysis
(parentage assignment) using CERVUS v3.0 software. Assessment of genetic
correlations between genetic markers and production trait (% fillet yield) were
assessed using GENECLASS v2.0. software (Piry et al. 2004). Representative
examples of microsatellite Gelscan images are presented in Figures 2 a-d.
Figures 2: Gelscan images of genetic diversity in RIA2 34 brood fish samples (2a)
and from 3 private hatcheries (n=31) (2b) at locus CB 12; gelscan
images of allelic diversity in high fillet yield individuals (2c) and of low
fillet yield individuals (n= 24) (2d) at locus CB 12.
2a 2b
2c 2d
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib14
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Chapter 3. RESULTS
3.1. Part A - Characterisation of genetic variation in cultured and wild
populations of Tra catfish
The pairwise linkage disequilibrium results from the sampled populations are
presented in Appendix 1. Initial analysis of the raw data assessed presence of null
alleles, linkage disequilibrium and sample conformation to Hardy Weinberg
Equilibrium (HWE). The four microsatellite loci (CB4, CB7, CB12 and CB13)
screened in the Tra catfish samples showed amplified fragments that ranged in size
from 195 to 277bp. Individual sample amplification success ranged from 88 to 95%
across the four loci with observed number of alleles per locus ranging from 2 (Locus
CB7) to 10 (Locus CB12) MICROCHECKER analysis indicated that null alleles were
present in high frequency at two loci; CB4 and CB 12 (>50%) (Table 3).
Table 3: The potential for null alleles for each locus by sample detected using
MICRO-CHECKER.
locus CB4 CB7 CB12 CB13
population
Wild no no yes no
TDR no no yes yes
RIA2 yes no yes yes
Fillet yes yes no yes
Hau yes no yes no
Nam yes no yes yes
Khanh yes no yes yes
Average expected number of homozygotes at locus CB4 and CB12 were 14.5 and
7.5, respectively while average observed homozygotes at these loci were 24.8 and
16.7, respectively. In most instances, visualization of gel images of the two loci
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suggested that null alleles were a likely reason for higher than expected
homozygotes numbers at the two loci in most sampled populations.
3.1.1 Pair wise linkage disequilibrium
Pair wise linkage disequilibrium analysis using an exact P value (α = 0.05), after
Bonferroni correlation (α Bonf = 0.05/75 = 0.0007) showed no evidence for
significant linkage disequilibrium among the four loci (P< 0.0007). This result
indicates that the four loci screened in the Tra samples examined here provided
independent assessments of genetic diversity in the sample populations. A
complete statistical summary of the linkage disequilibrium results are presented in
table 4.
3.1.2. Conformation to HWE results
Table 4 presents expected and observed heterozygosity estimates and exact P
values for Hardy Weinberg Equilibrium (HWE) tests (α = 0.05), after Bonferroni
correction (α Bonf = 0.05/60 = 0.0008). A substantial number of tests revealed
significant deviations from HWE. In most cases this was in the form of heterozygote
deficiency, however several instances of heterozygote excess were also observed.
While these data could be used to infer a serious problem with null alleles, there is
strong evidence from the different broodstock samples and wild population sample
that this is unlikely to be the case. Out of the 16 HWE tests for H Brood, N Brood, K
Brood and the wild sample, only two indicated heterozygote deficiency. It is more
likely that the result seen here for the offspring reflect non-random mating in the
broodstock (a function of the breeding protocols used in the hatcheries), differential
contribution of breeders and/or differential survival of fry from particular crosses.
(Tave 1994).
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Table 4: Observed and expected heterozygosities (Obs. And Exp, respectively),
probability value (P-value) and standard deviation (sd). Significant
deviations from HWE indicated as heterozygote deficiency (def),
heterozygote excess (excess) or not significant (ns) after Bonferroni
correction. Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from
HWE
H1
CB4 0.52083 0.72818 0.00006 0.00002 def
CB7 0.00000 0.60929 0.00000 0.00000 def
CB12 0.88542 0.67828 0.00000 0.00000 excess
CB13 0.67708 0.67294 0.00000 0.00000 excess
H2
CB4 0.71875 0.65211 0.09747 0.00079 ns
CB7 0.62500 0.52285 0.06969 0.00080 ns
CB12 0.42708 0.53916 0.00000 0.00000 def
CB13 0.72917 0.70370 0.14440 0.00122 ns
H Brood
CB4 0.50000 0.78947 0.11528 0.00082 ns
CB7 0.60000 0.51053 0.43256 0.00140 ns
CB12 0.50000 0.84737 0.01231 0.00031 ns
CB13 0.80000 0.78947 0.17228 0.00145 ns
N1
CB4 0.25532 0.65588 0.00000 0.00000 def
CB7 0.54255 0.58078 0.00000 0.00000 def
CB12 0.51685 0.68152 0.00000 0.00000 def
CB13 0.75532 0.72193 0.00000 0.00000 excess
N2
CB4 0.62637 0.67245 0.00386 0.00019 def
CB7 0.63441 0.58983 0.18024 0.00106 ns
CB12 0.58889 0.79963 0.00000 0.00000 def
CB13 0.74468 0.68819 0.00000 0.00000 excess
N Brood
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Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from HWE
CB4 0.50000 0.66842 0.26167 0.00124 ns
CB7 0.70000 0.59474 0.49094 0.00151 ns
CB12 0.60000 0.62105 0.19733 0.00088 ns
CB13 0.80000 0.60526 0.81148 0.00100 ns
K1
CB4 0.63441 0.64940 0.79725 0.00139 ns
CB7 0.62766 0.67306 0.11780 0.00085 ns
CB12 0.57778 0.79081 0.00000 0.00000 def
CB13 0.68085 0.61230 0.03387 0.00064 ns
K2
CB4 0.21277 0.61617 0.00000 0.00000 def
CB7 0.65625 0.62778 0.79531 0.00130 ns
CB12 0.35065 0.79611 0.00000 0.00000 def
CB13 0.69565 0.78326 0.00000 0.00000 def
K Brood
CB4 0.90909 0.65801 0.13736 0.00089 ns
CB7 0.63636 0.49784 1.00000 0.00000 ns
CB12 0.54545 0.73593 0.07103 0.00080 ns
CB13 0.90909 0.71429 0.56921 0.00135 ns
Wild
CB4 0.25926 0.47799 0.00151 0.00011 ns
CB7 0.59259 0.64570 0.28614 0.00140 ns
CB12 0.22222 0.72816 0.00000 0.00000 def
CB13 0.66667 0.81551 0.00769 0.00023 ns
TDR
CB4 0.57143 0.70711 0.01556 0.00037 ns
CB7 0.54545 0.59953 0.12716 0.00121 ns
CB12 0.50000 0.85829 0.00000 0.00000 def
CB13 0.55556 0.79526 0.00000 0.00000 def
Ria2
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Pop/Locus Obs.Het Exp.Het P-value s.d Dev. from HWE
CB4 0.14706 0.64311 0.00000 0.00000 def
CB7 0.47059 0.58824 0.00376 0.00015 ns
CB12 0.43750 0.66964 0.00358 0.00016 ns
CB13 0.35294 0.77217 0.00000 0.00000 def
High
CB4 0.39535 0.57346 0.00396 0.00020 ns
CB7 0.52174 0.71261 0.00402 0.00019 ns
CB12 0.64444 0.87241 0.00000 0.00000 def
CB13 0.64103 0.76190 0.00060 0.00007 def
Low
CB4 0.27083 0.63136 0.00000 0.00000 def
CB7 0.66667 0.64320 0.97791 0.00045 ns
CB12 0.65909 0.76959 0.04750 0.00026 ns
CB13 0.48936 0.78609 0.00000 0.00000 def
Random
CB4 0.08696 0.53816 0.00000 0.00000 def
CB7 0.43478 0.61836 0.04401 0.00057 ns
CB12 0.52381 0.83624 0.00000 0.00000 def
CB13 0.34783 0.76715 0.00000 0.00000 def
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Table 5: Microsatellite polymorphism in 7 sample populations of wild and cultured Tra catfish populations.
Group/ Locus
A An
CB4 P A An
CB7 P A An
CB12 P A An
CB13 P Average gene
diversity Average
number of alleles
Hau Brood (n=10)
5 5.00 0.13 3 3.00 0.42 7 7.00 0.01 6 6.00 0.17 0.73 +/- 0.45 5.30 +/- 1.48
Nam Brood (n=10)
4 4.00 0.26 4 4.00 0.48 6 6.00 0.18 4 4.00 0.82 0.62 +/- 0.39 4.50 +/- 0.87
Khanh Brood (n=10)
4 3.91 0.13 3 2.99 1.00 6 5.72 0.07 4 3.91 0.56 0.65 +/- 0.40 4.25 +/- 1.09
Wild 1
(n=20)
3 3.54 0.01 4 3.36 0.65 6 4.64 0.00 6 5.68 0.01 0.64 +/- 0.38 4.75 +/- 1.29
Wild 2
(n=7)
4 3.54 0.09 2 3.36 0.44 3 4.64 0.02 4 5.68 0.46 0.63 +/- 0.40 3.25 +/- 0.83
Founder
(TDR n=45)
3 3.75 0.02 4 2.99 0.12 10 7.58 0.00 6 5.55 0.00 0.68 +/- 0.47 5.75 +/- 2.68
RIA2 Brood (n=34)
3 2.99 0.00 6 4.02 0.00 6 4.53 0.00 5 4.74 0.00 0.67 +/- 0.42 5.00 +/- 1.23
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3.1.3 AMOVA analysis of hierarchical differentiation within and among
populations
ARLQUIN 3.1 software was used to assess hierarchical differentiation among
sample populations at two levels; within and among populations employing analysis
of molecular variance (AMOVA). AMOVA allows estimation of the statistical
significance of FST values between sample pairs, i.e. the significance of population
differentiation. The following settings; 100 permutations for significance with 10000
steps were employed in the Markov chain.
Table 6: The statistical significance of FST values of population differentiation
Source of variation d.f Percentage of variation
Among samples 6 7.41
Within samples 267 92.59
FST = 0.0741, P < 0.0000 +/- 0.0000
The results show that the majority of variation present was evident within
populations (92.6 %) while only 7.4% variation was evident among populations.
Variation among populations however, was highly significant (P
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Table 7: Statistical significance of FST values (the significance of population) among
sample pairs. P values that were significant after Bonferroni correction (α
(Bonf) = 0.05/number of test = 0.05/ 21 = 0.002) are highlighted
P values →
FST ↓ Hau
Brood
Nam
Brood
Khanh
Brood
Wild Wild 2 TDR RIA2
Hau Brood - 0.000 0.0270 0.000 0.0270 0.1351 0.0811
Nam Brood 0.0668 - 0.000 0.0090 0.000 0.000 0.000
Khanh Brood 0.0477 0.1009 - 0.000 0.0090 0.000 0.000
Wild 0.1098 0.0623 0.1404 - 0.000 0.000 0.000
Wild 2 0.7060 0.1706 0.0599 0.1184 - 0.0090 0.0180
TDR 0.0236 0.0819 0.0557 0.0951 0.0776 - 0.0360
RIA2 0.0406 0.1435 0.0834 0.1232 0.0770 0.0212 -
Genetic variation among parents representing the 6 populations (average gene
diversity ranged from 0.62 – 0.73 and average number of alleles per locus ranged
from 4.25 – 5.75). Allelic richness (An) across the sampled populations was highest
at the CB12 locus (10 alleles) and lowest at the CB7 locus (2 alleles) (Table 5).
3.1.4. Genetic characterization of sampled Tra catfish culture stocks
Microsatellite polymorphism was quantified by estimating gene diversity within
samples (FIS) and between samples (FST), observed (Ho) and expected (He)
heterozygosity, and estimating level of differentiation among stocks. Seven
populations were available for comparisons of genetic differentiation among sample
populations (Table 7). Brood stock samples were available from 3 private hatcheries
namely: the Hau and Khanh brood stocks and Nam hatcheries of which the Nam
hatchery had developed the first domesticated brood stock in the Mekong Delta
region. The TDR as sourced from wild fish and the first domesticated generation
from the TDR brood fish at RIA2 were used for the selective breeding program. Wild
1 and Wild 2 were wild caught individuals collected from the Tien and Hau River as
a wild reference for comparison of genetic diversity levels in culture stocks.
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Parameters for genetic variation (Table 5) in 6 sample populations of Tra catfish in
culture and wild are presented as mean number of alleles per locus (A), allelic
richness (An), observed heterozygosity (Ho), expected heterozygosity (He) and
average gene diversity. For wild Tra catfish, these values showed A = 3.25–4.75;
allelic richness, An = 3.3–5.6; observed heterozygosity, Ho = 0.15–0.71; expected
heterozygosity, He = 0.3–0.82 and average gene diversity = 0.64, and hatchery
samples showed A = 4.25–5.75; An = 2.99–7.58; Ho = 0.14–0.91; He = 0.49–0.82.
3.2. Part B - Assessment of the relative contribution by breeders to fry
cohorts in three private hatcheries in the Mekong Delta
The majority of Tra brood stock examined in the current study was sampled from the
main Mekong River in Dong Thap Province (RIA2 founder and 3 private hatcheries).
Dong Thap Province in the Mekong River Delta is recognised as the premier region
(An Giang, Can Tho and Vinh Long and Hau Giang) for Tra catfish culture in
Vietnam. P. hypophthalmus culture has become a major industry in the south of
Vietnam because there is abundant supply of fresh water available year-round. In
2006, this province produced 300,000 MT of catfish that contributed 37.5% to the
total production of catfish from aquaculture in Vietnam. The industry in this province
also employs approximately 40,000 people of the 1.6 million people who live in the
region (Phuong et al. 2007). In 2007, 87 catfish hatcheries were operational in Dong
Thap Province, producing more than 4.4 billion fry per year constituting the majority
of catfish seed supplied to the industry across the whole Mekong Delta.
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Figure 3: Map of Mekong Delta identifying the main areas where Tra catfish are
cultured (grey colour)
The current experiment was designed to estimate the effective population size (Ne)
of fish in a closed system and follow them from spawning to hatching. For example,
at the Hau hatchery for the first spawn, eggs from 8 female fish and sperm from 2
males were pooled and hatched as a single composite cohort. On the first day, 100
fry were sampled randomly followed by a second sample of fry (n = 100) on day two
before remaining fry were sold to farmers. The design employed to estimate Ne had
to be suitable to fit into commercial hatchery practices employed on farms while
allowing molecular assessment and analysis of the relative contributions by parents
that potentially contributed to the fry cohorts.
3.2.1. Estimation based on the number of males and females in the
brood stock
According to Hartl and Clark (1997), to ensure the highest Ne during spawning,
under ideal conditions all brood stock should contribute equally to offspring.
However, Ne will be substantially less than N if there is unequal representation of
the sexes and Ne will be impacted more by the rare sex. A simple statistic for
estimating Ne is where:
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4SGKB98-3&_user=62921&_coverDate=08%2F01%2F2008&_rdoc=1&_fmt=full&_orig=search&_cdi=4972&_sort=d&_docanchor=&view=c&_searchStrId=1173002344&_rerunOrigin=scholar.google&_acct=C000005418&_version=1&_urlVersion=0&_userid=62921&md5=d2e514892737afdee954b175a7408245#bib14
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with Nm and Nf being the numbers of male and female brood stock,
respectively.Table 8 provides estimates of Ne for the three private hatcheries using
this method. While the Ne estimates are all less than the total numbers of brood
stock in each case, there is no insight into the relative contributions of each breeder.
Unequal contribution will lead to a further decline in approximation of the true Ne
and therefore needs to be assessed in order to provide a more realistic estimate.
Table 8: Estimation of Ne in three private hatcheries based on the number