Comparative Analysis of STRs, Mini-STRs and

SNPs for Typing Degraded DNA

MIAN SAHIB ZAR

NATIONAL CENTRE OF EXCELLENCE IN MOLECULAR BIOLOGY,

UNIVERSITY OF THE PUNJAB,

LAHORE, PAKISTAN.

(2014)

Comparative Analysis of STRs, Mini-STRs and SNPs

for Typing Degraded DNA

A thesis submitted to

University of the Punjab

In partial fulfillment of the requirement for the degree of

DOCTOR OF PHILOSOPHY

IN

MOLECULAR BIOLOGY

By

MIAN SAHIB ZAR

SUPERVISORS:

DR. AHMAD ALI SHAHID

(Associate Professor)

DR. MUHAMMAD SAQIB SHAHZAD

(Associate Professor)

NATIONAL CENTRE OF EXCELLENCE IN MOLECULAR BIOLOGY,

UNIVERSITY OF THE PUNJAB,

LAHORE, PAKISTAN.

(2014)

IN THE NAME OF

ALLAH

THE MOST MERCIFUL,

THE MOST BENEFICIENT.

“All humans have the right to be treated with respect, even after

death. Most religious leaders are agree that if the skeleton is of a

deceased human being or animal, then there is no harm in using it for

educational/research purposes. It is the necessity of education that

makes the human skeleton permissible to be used for this purpose, and

the necessity is weighed according to its importance. However, when

the student finishes his/her study, he/she has to cover the skeleton as a

sign of respect for the human being. Leaving it uncovered is contrary

to its honour as the dead should be respected like a live person is.”

(Islamic Perspective).

“Allah has created death and life that He may try which of you is

best in conduct. He is the Mighty, the Most Forgiving.” (Holy

Quran 67:3).

“O mankind, indeed we have created you from male and female and

made you peoples and tribes that you may know one another. Indeed,

the most noble of you in the sight of Allah is the most righteous of

you. Indeed, Allah is Knowing and Acquainted”. (Holy Quran

49:13).

THIS WORK IS DEDICATED TO MY

GREAT

PARENTS

&

GRANDMOTHER

WHO RAISED ME, SUPPORTED ME,

TAUGHT ME AND LOVED ME.

WITHOUT THEIR PRAYERS, GUIDANCE AND

WELL WISHES I WOULD NOT BE WHERE I AM

TODAY.

I

CERTIFICATE

This is to certify that the research work described in the thesis submitted by Mr. Mian

Sahib Zar has been carried out under my supervision. Data/ results reported in this thesis are

duly recorded in the Centre’s official data books. I have personally gone through the raw data

and certify the correctness/authenticity of all results reported herein. I further certify that these

data have not been used in part or full manuscript already or in the process of submission in

partial/complete fulfillment of the award of any other degree from any other institution at home

or abroad. I also certify that enclosed thesis, has been prepared under my supervision and I

endorse its evaluation for the award of Ph. D. degree through the official procedure of the

Centre/University.

In accordance with the rules of the Centre (CEMB), data book No. 949 and 1083 are

declared as un-expendable document that will be kept in the registry of the centre for a minimum

of three years from the date of the thesis defense examination.

Signature of supervisor: _________________

Name of Supervisor: Dr. Ahmad Ali Shahid.

(Associate Professor)

Signature of supervisor: _________________

Name of Supervisor: Dr. Muhammad Saqib Shahzad.

(Associate Professor)

II

DECLARATION

I, Mian Sahib Zar, PhD Scholar (Session: 2010-2014), Centre of Excellence in Molecular

Biology (CEMB) University of the Punjab Lahore, hereby declare that the materials printed in

this thesis entitled “Comparative Analysis of STRs, Mini-STRs and SNPs for Typing

Degraded DNA” is my own work and has not been printed, published and submitted as research

work, or thesis in any university or research institute in Pakistan or abroad. This thesis which is

being submitted for the degree of Ph.D. in the University of the Punjab Lahore does not contain

any material published or written previously by another person.

Dated:

Signature of Deponent

III

ACKNOWLEDGEMENTS

With humblest words, I thank Almighty “Allah”, The most Merciful, The most

Beneficent who bestowed upon me the potential and ability to do this work. I am proud of being

a follower of the Holy Prophet Hazrat Muhammad (PBUH) who is forever a torch of guidance

for humanity.

I am highly obliged to express a profound sense of gratitude to Professor Dr. Tayyab

Husnain, Acting Director, Centre of Excellence in Molecular Biology (CEMB), University of

the Punjab Lahore Pakistan for providing all the necessary facilities for my research at CEMB.

I would like to express my deepest gratitude to my supervisors Dr. Ahmad Ali Shahid

and Dr. Muhammad Saqib Shahzad, who were always available with help and guidance and

for continuous interest, encouragement and kindness throughout all phases of this work.

I also wish to thank to Professor Dr. Kyoung-Jin Shin, Head of the Department of

Forensic Medicine, Yonsei University College of Medicine Seoul South Korea, for giving me the

opportunity to work as an exchange student under his supervision and for managing my research

work accurately and in time with excellent management skills. I am also thankful to Dr. Hwan

Young Lee, Associate Professor in same department. I found her advice invaluable. I benefited

greatly from her knowledge and experience. I am also thankful to Dr. In Seok Yang, Assistant

Professor, and my research fellows who helped me and encouraged me in my research work

from the first day we met in Yonsei University College of Medicine Seoul South Korea. I also

appreciate the generosity and wonderful hospitality of Professor Dr. Woo Ick Young at Yonsei

University College of Medicine Seoul South Korea.

I would also like to owe a special debt of gratitude to Dr. Zia Ur Rahman, Assistant

professor, for their continuing support and guidance during my research work in CEMB. I am

also thankful to Professor Dr. Shahid Jamil Sameeni, Institute of Geology University of the

Punjab Lahore for his help in estimating the age of old skeletal remains using different

archeological and geological approaches. Without his support this project would not have been

possible. Furthermore, I would like to thank Dr. Muhammad Israr (My friend), Assistant

Professor University of Health Sciences Lahore for patiently guiding me through the various

statistical tests, and for providing helpful criticism and feedback throughout the writing process.

This report would not be successful without his acknowledgement. I am also very grateful to my

IV

respected teachers Professor Dr. Shaheen N Khan, Professor Dr. Ikram ul Haq, Dr. Bushra

Rasheed, Dr. Idrees Nasir, Dr. Muhammad Idress Khan, Dr. Sobia, Dr. Mohsin Khan, Dr.

Nadeem, Dr. Zahid Hussain and Dr. Qayum Rao, who always offered words of

encouragement and always believed that I could succeed. My deepest regards to Dr. Zeenath

Hussain, CEO of the Medical Diagnostic Laboratories, Private Limited Lahore for their support,

friendly behavior and providing me excellent guidance to complete my research work. I wish to

sincerely thank to my favorite teachers Professor Dr. Muhammad Aslamkhan, Head of the

Department of Human Genetics and Molecular Biology, University of Health Sciences Lahore

and my M.Phil. Supervisor Dr. Sikander Ali, IIB, GC University Lahore. They have taught me

that there is still much more to learn. I have always admired their intelligence, leadership and

dedication. I am also grateful to my colleagues, Mr. Muhammad Shafeeq (Research Officer),

Mrs. Rukhsana Perveen (Research Officer), Mrs. Uzma (Assistant Research Officer), Mr.

Nauman Gilani (Assistant Research Officer), Nazim Husssain, Shehzad and Adnan Shan for

their support and co-operation in completion of this work. Moreover I would like to thank all the

Scientific, Para scientific and Administrative staff of CEMB especially Imran Arshad Sab

(Assistant Student Coordinator), Mehmood Sab (Senior Admin Officer), Saleem Sab, Khalid

Sab, Ahmad Watto Sab and all others, who had been directly or indirectly helped me in my

research work.

My appreciations are for my friends Muhammad Ilyas, Faidad Khan, Dr. Khitab Gul,

Muhammad Inam, Faiz Ali, Imran Khan, Muhammad Islam Khan, Burhan Ail Shah, Zeeshan

Akber, Fazal Adnan, Sulaiman Afridi, Amjad Ali, Dr. Sulaiman, Dr. Arshad, Niaz Muhammad,

Abrar Hussain, Anwar Khan, Zahoor Khan, Usman Liaqat, Mustafa bhai, Muhammad Shahid

Ansari, Bizzat Hussain, Ihsan Ali, Waqas, Amir Ghafoor, Saeed, Haider, Irfan, Salman, Waris,

Gohar Ali, Imran bhai, Arshad Awan, Sarmad, Hafiz Nisar Muhammad, Abdul Wassay, Imran

Khan, Bahaeldeen, Puspito, Farukh bhai, Zia Ur Rahman, Dawood, Liaqat Ali Khan,

Muhammad Aleem, Malik Adil, Mudassir, Sajjad, Adnan Muzaffar, Salah Ud Din, Bilal Sarwar,

Malik Tanveer, Fazal Bhai, Jawad, Zafar Saleem Sab, Inayat and all CEMBIANS.

I would also like to acknowledge Higher Education Commission (HEC) of Pakistan for

awarding me Indigenous Ph.D. fellowship and six month foreign research fellowship and

supporting a part of this study. I am also thankful to the Centre of Excellence in Molecular

Biology (CEMB) University of the Punjab Lahore and Department of Forensic Medicine,

V

Yonsei University College of Medicine Seoul South Korea for their financial and moral

support. Finally I am thankful to my parents, grandmother, brothers & sisters, whose prayers,

love, guidance and encouragement are always for me. I have no words to capture their sincerity

and inspiration for me.

Mian Sahib Zar

VI

SUMMARY

The primary aim of this study was to investigate various genotyping approaches for

typing old skeletal remains (Degraded DNA samples) and introduce a newly developed in-house

SNaPshot SBE multiplex system for forensic DNA study of old skeletal remains and highlight

the importance of this multiplex system for the identification of individuals at DNA level.

The quality and quantity of human DNA from forensic DNA samples is influenced by

different environmental factors. These factors may cause degradation of DNA which has a

negative impact on the process of DNA amplification especially in case of STR multiplex system

with large amplicon sizes. Therefore, approaches with small amplicon sizes are applied for

typing degraded DNA. Extraction of DNA from old skeletal remains, maximization of DNA

yield and elimination of PCR inhibitors are important issues in forensic DNA studies.

Sometimes, the history and condition of DNA samples are unknown in forensic DNA analysis.

Therefore, an ideal DNA extraction method is required to produce highly purified and high

quality DNA from old and degraded DNA samples. DNA Typing of degraded DNA depends on

the extraction of the small amounts of DNA remaining in old bone samples. There are a wide

range of DNA extraction methods, which depend on alcohol precipitation, spin columns, or silica

columns.

In this study different kinds of human old skeletal remains (Degraded DNA samples)

ranging in age from 100 to 1000 years old, collected from old mass graves of Khyber

Pakhtunkhwa province of Pakistan, were analyzed. DNA extraction was carried out with

modified silica column-based total demineralization extraction method and DNA quantification

was conducted with Quantifiler® Duo-Human DNA Quantification kit (ABI) and the ABI

Prism® 7500-Real Time PCR System (ABI) in duplicate with modified reduced volume

VII

reaction. Three different types of forensic DNA markers: STRs, mini-STRs and SNPs (with

modified protocols) were used for the analysis of degraded DNA samples. Commercially

available kits, AmpFlSTR® Identifiler® and AmpFlSTR® MiniFilerTM

were used for STR and

miniSTR analysis while an in-house SNaPshot SBE multiplex system consists of nine

pigmentation-related SNPs, rs885479 (MC1R), rs26722 (SLC45A2), rs2031526 (DCT),

rs7495174 (OCA2), rs4778241 (OCA2), rs4778138 (OCA2), rs1800414 (OCA2), rs1545397

(OCA2) and rs12913832 (HERC2), was used for SNP studies.

Consensus profiles of each sample were made independently to overcome the stochastic

effects associated with low template or highly degraded DNA typing. Concordance was

determined between AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ STR loci. DNA

profiles obtained with AmpFlSTR® Identifiler®, AmpFlSTR® MiniFiler™ and in-house

SNaPshot SBE multiplex systems were compared. DNA profiles were obtained from minute

quantity of DNA (even from ≤10 pg/µL) in a reliable manner with modified protocols of these

kits which is a significant achievement in this study. The authenticity of the DNA profiles of

bone samples was confirmed by running negative controls along-with these sample using the

Identifiler, MiniFiler and in-house SNaPshot SBE multiplex kits. Finally it was concluded that

DNA typing of old skeletal remains (degraded DNA samples) was improved by using a highly

effective modified silica column-based total demineralization DNA extraction method, modified

protocols of Identifiler, MiniFiler and in-house SNaPshot SBE multiplex systems, optimized

PCR conditions, extended PCR cycles and consensus approaches.

In addition, the minor allelic frequencies of the nine SNPs of the old skeletal remains

were compared with same allelic frequencies of Pakistani (Pathan), CEU, HCB, JPT and YRI

VIII

Populations using HapMap database in order to find out correlation of these samples with

Pakistani (Pathan) and other populations.

IX

ABBREVIATIONS AND SYMBOLS

% Percentage

°C Degrees Celsius

ABI Applied Biosystems Incorporated

bp Base pair

CE Capillary Electrophoresis

CODIS Combined DNA Index System

CT Threshold cycle

ddNTPs Di-deoxy nucleotide triphosphates

dH2O Distilled water

DNA Deoxy Ribonucleic Acid

dNTPs Deoxy Nucleoside Tri Phosphates

EDNAP European DNA Profiling Group

ENFSI European Network of Forensic Science Institutes

Exo Exonuclease

Exo-sap Exonuclease and shrimp alkaline phosphatase

g Gram

h Hour

HWE Hardy-Weinberg Equilibrium

IPC Internal PCR control

Kb Kilo bases

LCN Low copy number DNA

LT DNA Low template DNA

Min Minutes

X

Mini-STRs Mini-Short Tandem Repeats

mL Milliliter

ng Nanogram

PCR Polymerase Chain Reaction

pg Pictogram

POP Performance Optimized Polymer

POP-4 Performance Optimized Polymer with 4% dimethyl polyacrylamide

PTC-200 Peltier Thermal Cycler-200

RFLP Restriction Fragment Length Polymorphism

RFUs Relative Fluorescent Units

rpm Revolution per minute

SAP Shrimp Alkaline Phosphatase

SBE Single Base Extension

SDS Sequence Detection System

Sec Second

SNPs Single Nucleotide Polymorphisms

STRs Short Tandem Repeats

Taq Thermus aquaticus

TE Tris-EDTA

UV Ultraviolet

VNTRs Variable Number of Tandem Repeats

μg Microgram

μL Microliter

μM Micromole

XI

TABLE OF CONTENTS PAGE #

CERTIFICATE I

DECLARATION II

ACKNOWLEDGEMENTS III

SUMMARY VI

ABBREVIATIONS AND SYMBOLS IX

TABLE OF CONTENTS XI

LIST OF FIGURES XIII

LIST OF TABLES XIV

CHAPTER 1 1

INRODUCTION 2

CHAPTER 2 8

REVIEW OF LITERATURE 9

2.1 Deoxyribonucleic Acid (DNA) and Human Genome 9

2.2 DNA Polymorphism 9

2.3 Brief History of DNA Typing 11

2.4 DNA Profiling and Human Skeletal remains 12

2.4.1 Structure and Composition of Human Bones 13

2.4.2 Classification of Human Bones 13

2.5 Process of DNA Degradation 14

2.6 Role of DNA Extraction in DNA Typing 15

2.7 Amplification of degraded DNA 16

2.8 Applications of STRs, mini-STRs and SNPs on degraded DNA samples 17

2.8.1 Short Tandem Repeats Markers (STRs) 17

2.8.2 Application of Mini-STRs on Degraded DNA Samples 19

2.8.3 Single Nucleotide Polymorphisms (SNPs) 20

2.9 Commercial STR, mini-STR and SNP Kits 22

2.9.1 Identifiler™ and Minifiler™ STR Systems 23

2.9.2 SNaPshot™ Multiplex Kit (Minisequencing) 24

2.10 Applications of Capillary Electrophoresis (CE) in DNA Typing 24

2.11 Applications of DNA Typing and Phenotyping 25

CHAPTER 3 27

MATERIALS AND METTHODS 28

3.1 Samples Collection 28

3.2 Cleaning and Pre-treatment and maceration of bone Samples 28

3.3 Extraction of DNA 28

3.4 Quantification of DNA Using Real Time PCR 30

3.5 Amplification of DNA 30

3.5.1 Amplification of Autosomal STRs using AmpFISTR Identifiler PCR

Amplification Kit 30

3.5.2 Amplification of Autosomal STRs using AmpFISTR MiniFiler PCR

Amplification Kit 31

3.5.3 Amplification of SNPs Using In-house SnaPshot SBE Multiplex System 31

3.6 Capillary Electrophoresis (CE) 32

XII

3.7 Data Analysis 33

CHAPTER 4 36

RESULTS 37

4.1 Extraction and Quantification of DNA 37

4.2 Increasing sensitivity of PCR amplification 38

4.3 Effect of environment conditions on DNA quality and profiling of old skeletal

remains 44

4.4 Consensus Approach 47

4.5 Comparative study of STR loci using modified protocols of Identifiler and

MiniFiler STR kits 63

4.6 Comparison of DNA profiles obtained with AmpFlSTR® Identifiler,

AmpFlSTR® MiniFiler and In-house SNaPshot SBE Multiplex Kits from old

Skeletal Remains

71

4.7 Genetic and Phenotypic Association of old skeletal remains with Other

Populations 74

CHAPTER 5 79

DISCUSSION 80

CONCLUSION 90

CHAPTER 6 92

REFERENCES 93

LIST OF PUBLICATIONS 114

XIII

LIST OF FIGURES

Figure 4. 1 Quantification of DNA Using Quantifiler® Duo Human DNA Quantification kit and the ABI

Prism® 7500 Real Time PCR System ........................................................................................................ 37

Figure 4. 2 Partial DNA profile with 28 number of PCR cycles ................................................................ 40

Figure 4. 3 Full DNA profile with 33 number of PCR cycles .................................................................... 41

Figure 4. 4 Negative control obtained with AmpFlSTR® Identifiler™ STR kit ........................................ 42

Figure 4. 5 Negative control obtained with AmpFlSTR® MiniFiler™ STR kit ........................................ 43

Figure 4. 6 Negative Control obtained with In-houseSnaPshot SBE multiplex kit .................................... 44

Figure 4. 7 : Partial DNA profile of 8 STR loci plus amelogenin, obtained with Identifiler kit from 500

years old radius found on the surface of soil and dry area .......................................................................... 45

Figure 4. 8 Partial DNA profile of 2 STR loci plus amelogenin, obtained with Identifiler STR kit from

200 years old radius buried in soil and wet area ......................................................................................... 46

Figure 4. 9 Allelic ladder of AmpFlSTR ® Identifiler TM STR kit ........................................................... 67

Figure 4. 10 Allelic ladder of AmpFlSTR® MiniFilerTM

STR kit .............................................................. 68

Figure 4. 11 Partial DNA profile obtained with AmpFlSTR® Identifiler™ STR kit from bone sample

(FRL 21) ..................................................................................................................................................... 69

Figure 4. 12 Full DNA profile obtained with AmpFlSTR® MiniFiler™ STR kit from bone sample (FRL

21) ............................................................................................................................................................... 70

Figure 4. 13 Comparison of DNA profiles obtained with AmpFlSTR® Identifiler, AmpFlSTR® Minifiler

and in-house SNaPshot SBE Multiplex Kits ............................................................................................... 71

Figure 4. 14 Frequencies of Wild and Mutant Alleles Using nine pigmentation related SNPs across old

skeletal remains ........................................................................................................................................... 75

Figure 4. 15 Association of minor allele frequencies of nine pigmentation related SNPs of old skeletal

remains with same allele of Pakistani (Pathan), CEU, HCB, JPT and YRI Populations ............................ 78

XIV

LIST OF TABLES

Table 2.1 Comparison of STR and SNP markers ....................................................................................... 22

Table 3. 1 Information about the 9 SNPs used in this Study ...................................................................... 33

Table 3. 2 Primers used for amplification of 9 SNPs in this study ............................................................. 34

Table 3. 3 Minisequencing primers used for the detection of the 9 SNPs used in this study ..................... 35

Table 4. 1 Concentration of DNA and CT (Threshold cycle) values of Internal PCR Control (IPC) ……38

Table 4. 2 Consensus DNA profiles produced with AmpFlSTR® Identifiler® STR Kit ........................... 48

Table 4. 3 Consensus DNA profiles produced with AmpFlSTR® MiniFilerTM STR Kit ........................ 55

Table 4. 4 Consensus DNA profiles produced with In-house SnaPshot SBE multiplex kit ....................... 61

Table 4. 5 Concordance and non-concordance of STR Loci Using AmpFlSTR® Identifiler &

AmpFlSTR® MiniFiler STR Kits ............................................................................................................... 64

Table 4. 6 DNA profiles and number of loci successfully genotyped with the AmpFlSTR® Identifiler®

and AmpFlSTR® MiniFiler™ and in-house SnaPshot SBE multiplex Kits from old skeletal remains ..... 73

Table 4. 7 DNA profiles of old skeletal remains for nine pigmentation-related SNPs are unique at least at

one locus ..................................................................................................................................................... 76

Table 4. 8 Information about nine pigmentation-related SNPs, Hardy Weinberg Equilibrium, Minor allelic

frequencies and association of old skeletal remains and other populations (Pakistani, CEU, HCB, JPT and

YRI) ............................................................................................................................................................ 77

1

CHAPTER ONE

2

INRODUCTION

Forensic science is a field that solves legal issues in criminal law as well as in civil cases

(Jobling and Peter Gill, 2004). The availability of DNA samples is very essential for DNA typing

in forensic study. DNA typing is a method in which genetic variations at DNA level is used for

the identification of an individual. DNA typing is used for the identification of human being in

different terrible events like terrorist attacks, mass disasters and crimes. In these situations,

forensic DNA analyst often faces the analysis of highly degraded DNA samples (Alaeddini et al.

2010). DNA samples found at crime scenes or mass disasters may be both qualitatively and

quantitatively inadequate, because they may often contain very low and degraded DNA due to

prolonged exposure to different environmental conditions like heat, light, humidity and

microorganisms (Bender et al., 2004).

It is common in forensic study to encounter highly degraded DNA samples from a variety

of sources. Bones and teeth are often the principal source of evidential material for the

identification of individuals and criminal investigations (Fondevila et al., 2008). Bones and teeth

have the ability to be preserved even if they are buried in soil for long time. Therefore, they are

the best sample sources to be used in anthropology, archeology and DNA forensics for

identification of missing persons, ancient DNA analysis and mass disasters (Loreille et al., 2007,

Seo et al., 2010). Bone is made up of 30% organic (collagen) and 70% inorganic components

(minerals). Organic components such as collagen provide a soft framework to the bones and

inorganic minerals (hydroxyapatite) provide strength and harden the framework. Inorganic

minerals include calcium phosphate, calcium fluoride, calcium hydroxide, calcium citrate and

carbonate (Martin et al., 1998, Piglionica et al., 2012).

3

DNA degradation and contamination are the most prominent problems occur to DNA

analysts during the analysis of old skeletal remains (Alonso et al., 2001). Degradation of human

DNA occurs as a result of both enzymatic (nuclease) and non-enzymatic activity generating

small fragments of DNA (Martin et al., 2006). Small fragments of DNA prevent larger loci from

amplification and act as PCR inhibitors. Degraded DNA may produce stochastic effects which

include allelic drop-in, allelic drop-out, locus drop-out, reduced allelic peak heights and

heterozygote peak imbalance (Diegoli et al., 2012, Grisedale and van Daal, 2014). In addition to

decomposition by microorganisms, the extent of DNA degradation of old skeletal remains

depends on time and environmental conditions (Iwamura et al., 2004). Time accelerates

degradative processes and environmental conditions such as temperature, humidity, pH and soil

chemistry change the rate and aggressiveness of DNA degradation (Burger et al., 1999).

The use of human old skeletal remains for DNA typing is a recent advancement in

forensic sciences. A common problem to DNA analysts is the analysis of old skeletal remains.

Bones vary in their degree of degradation, therefore, if more than one bone is available; the DNA

analysts choose a bone in good condition for DNA typing, because it would contain better DNA

than a more battered bone sample (Vural and Tirpan, 2009).

The contamination of DNA samples with exogenous human DNA is a prominent issue in

DNA analyses (Kemp and Smith, 2005, Anderung et al., 2008, von Wurmb-Schwark et al.,

2008). Therefore proper collection, careful handling and use of compact bone for DNA typing

are preferred to minimize the chances of external contamination (Zehner 2007). Sample

concentration is also an issue, as optimum concentration of bone powder is required to extract

sufficient DNA for DNA typing. Removal of soil debris and other contaminants from the bone

4

surfaces may be very destructive to the samples that must be kept for forensic DNA studies

(Hochmeister et al., 1991, Cattaneo et al., 1995, Hummel et al., 1999).

Extraction and amplification of DNA from old bone samples has great importance in

forensic DNA studies, but the methods used at present are not satisfactory (Kalmar et al., 2000).

The bones and teeth are very difficult to process for DNA extraction. Extraction of DNA from

old skeletal remains is strongly influenced by many factors such as degradation by

environmental exposure, microbial contamination, limited quantity of starting material, presence

of PCR inhibitors, sample age and substrate properties (Hochmeister et al., 1991, Loreille et al.,

2007, Barbaro et al., 2011). Extensive area of the bone sample consists of inorganic minerals

which prevent the extraction of DNA from bone sample. Currently, the DNA extraction

protocols are based on the incubation of bone powder in extraction buffer containing EDTA.

During incubation, EDTA demineralizes the bone sample and inactivates DNAses by chelating

bivalent cations such as Ca++

or Mg

++ (Loreille et al., 2007).

The PCR inhibitors that prevent amplification of DNA from old skeletal remains vary

between burial sites. They originate in the form of fulvic acid, humic acid, tannin, hydroxi-

apatite and polymerase inhibitors from soil, contaminating DNA and degradation in biological

sample (Bourke et al., 1999, Yang et al., 1998). In case of bones, collagen type 1 and maillard

products are the main inhibitors of PCR amplifications (Kalmar et al., 2000).

In DN typing, after DNA extraction, quantification of DNA for all DNA samples is very

necessary (Buckleton 2009). Forensic DNA analysts are often facing problems during the

analysis of old skeletal remains (degraded DNA samples) containing low quantities of template

DNA. Low template DNA refers to any small amount of DNA (≤100–200 pg/ul) present in

degraded DNA sample. More recently, Low template DNA referred to any DNA sample or DNA

5

profile where stochastic effects are present and/or where the alleles detected are below a

laboratory defined stochastic threshold. (Gill et al., 2008, Word 2010, Butler and Hill, 2010).

Genotyping of forensic DNA samples with STR loci produces DNA profiles with high

power of discrimination, yet this approach failed in case of degraded DNA samples (Opel et al.,

2006). The amplicon size of the STR markers that are used for DNA profiling usually ranges

between 100 and 450 base pairs (Buttler et al. 2003). Due to DNA degradation, the longer

fragments often cannot be amplified resulting in partial DNA profiles with lower discrimination

power. There are several approaches to analyze degraded DNA samples having low quantity of

DNA. These are; increasing number of PCR cycles, injecting more DNA, clean-up of the DNA

sample after amplification, using different forensic DNA markers and applying low template

DNA interpretation rules (Buckleton 2009, Bright et al., 2012, Grisedale and van Daal, 2012).

To cope with degraded DNA, most strategies aim at shorter amplicon sizes, like with

mini-STRs or SNPs (Dixon et al., 2006). If the DNA samples become highly degraded,

conventional STR markers fail to amplify, while the use of mini-STRs and SNPs can provide

valuable information (Westen and Sijen, 2009). Currently, research work is going on to improve

DNA typing of old and highly degraded DNA samples using different forensic DNA markers

such as STRs (100-450 bps), mini-STRs (70-283 bps) and SNPs (80-120 bps) (Buttler et al.

2003, ABI MiniFiler kit 2007, Hughes-Stamm et al., 2011). The improvement in these markers

will increase the PCR amplification of highly degraded DNA and discriminating power of the

current approaches (Dixon et al., 2006).

DNA typing is only successful for those persons who are known to forensic investigating

authorities, whereas unknown persons cannot be identified with this approach (Draus-Barini et

al., 2013). Forensic DNA Phenotyping or phenotypic profiling is a type of DNA typing that can

6

identify criminal suspects on the basis of traits such as skin, eye and hair color, gait and

geographical ancestry etc. If appearance information (eye, skin and hair color etc) of an unknown

person are successfully extracted from a DNA sample found in crime scene, this information will

help during investigation of unknown suspects as it will allow reducing the number of potential

suspects with information directly obtained from the crime scene (Dembinski and Picard, 2014).

The new molecular approaches in DNA forensics and advances in molecular biology are

expected to improve the currently available DNA technologies in near future (Kayser and de

Knijff, 2011).

The primary aim of this study was to investigate various modified genotyping approaches

for typing old skeletal remains (Degraded DNA samples) and introduce a newly developed in-

house SNaPshot SBE multiplex system for forensic DNA study of old skeletal remains and

highlight the importance of this multiplex system for the identification of individuals at DNA

level. DNA extraction was carried out with modified silica column-based total demineralization

extraction method from highly degraded old bone samples. PCR amplification was conducted

with modified protocols of STR, mini-STR and SNPs kits to get the most informative DNA

profiles. PCR cycles were increased for increasing the sensitivity of detection. Consensus

profiles of each sample were made independently to overcome stochastic effects associated with

DNA typing of low template and highly degraded DNA. Concordance was determined between

AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ STR loci. DNA profiles obtained with

AmpFlSTR® Identifiler®, AmpFlSTR® MiniFiler™ and in-house SNaPshot SBE multiplex

systems were compared. In addition, the minor allelic frequencies of the nine pigmentation-

related SNPs of the old skeletal remains were compared with same allelic frequencies of

7

Pakistani (Pathan), CEU, HCB, JPT and YRI Populations using HapMap database in order to

find out correlation of these samples with Pakistani (Pathan) and other populations.

8

CHAPTER TWO

9

REVIEW OF LITERATURE

2.1 Deoxyribonucleic Acid (DNA) and Human Genome

Deoxyribonucleic acid (DNA) is double stranded organic polymer which exists within

each cell of human being except red blood cells which have no nucleus. It consists of three

elements; deoxyribose sugar, phosphate group and nitrogenous base. The first two components

of the DNA remain constant in all individuals, while the third component differentiates each

constituent of the polymer and thus helps in discriminating between individuals. Nitrogenous

base consist of one of the four structures; guanine (G), cytosine (C), adenine (A) and thymine

(T). DNA molecule based on the complementarity of the bases, where G pairs with C and A

pairs with T (Luftig and Richey, 2001). In human, DNA is found in nuclei or mitochondria,

called nuclear and mitochondrial DNA, respectively. The total content of the DNA is called

genome which is further divided into mitochondrial (16.5 kbp) and nuclear (3 billion bp) genome

(Lander et al., 2001, Kashyap et al. 2004). Human DNA mostly exists in the nucleus of the cell

which is distributed across the 46 chromosomes in human cells. The human nuclear genome is

made up of coding (5%) and non-coding regions (95%) as shown in figure 2.1. Coding regions

(exons) are highly conserved while non-coding regions (introns) are highly polymorphic (Daniel

and Walsh, 2006).

2.2 DNA Polymorphism

It has been found that human DNA is 99.5% similar between all individuals and only

0.5% varies from individual to individual (Feuk et al., 2006). This variation in DNA provides the

base for human identification purposes and is called DNA polymorphism. DNA polymorphism is

of two types (Kashyap et al. 2004): Polymorphisms in coding regions and polymorphisms in non-

coding regions. Polymorphism in non-coding regions is further divided into two types: sequence

10

polymorphisms and length polymorphisms. Sequence polymorphism is the variation in one or

more bases in the DNA sequence at a particular locus in different individuals (e.g., SNP), while

length polymorphism is the variation in length of DNA at a particular locus in different

individuals. The examples of length polymorphism are minisatellites (VNTR) and microsatellites

(STR & mini-STR) markers (Butler et al., 2007). The location of a DNA marker in the

chromosome is called a locus where alleles are found. Presence of alleles in a genetic locus gives

rise to the genotype of an individual. The combination of genotypes from multiple loci gives rise

to an individual’s DNA profile. Thus, the process of DNA typing involves the determination of

the genotype present at specific locations along the DNA molecule (Butler, 2012).

11

Figure 2. 1 Polymorphic regions in the human genome (adapted from: Kashyap et al., 2004)

2.3 Brief History of DNA Typing

In 1985, Dr. Alec Jeffreys discovered that DNA contains repetitive sequences that vary

from person to person. Those repetitive sequences were called VNTRs (Kirby, 1990). VNTRs

have repeat units that vary in size from 10-100 base pairs. Restriction fragment length

polymorphism (RLFP) technique was used for the analysis of the length variation of VNTRs

(Butler, 2001). The use of VNTRs loci for DNA typing by RFLP analysis was the first accepted

12

DNA analysis method and became the popular method of human identification during the late

1980’s; however, it had several limitations such as it required at least 50 ng of DNA, it could not

be used for degraded DNA samples and it was time consuming and laborious (Siegal et al.

2000). Therefore, it was rarely used for forensic study. While Jeffreys was developing the RFLP

technology, the PCR was discovered by Kary Mullis in 1985. Polymerase chain reaction (PCR)

makes millions of copies of short regions of the DNA. PCR is better suited for forensic DNA

analysis because it is an easier process and it requires a much smaller quantity of DNA for

amplification. It was quickly adopted by the forensic DNA analysts as an alternative approach to

RFLP typing because the use of PCR method made DNA analyses more sensitive, simpler, faster

and more amenable to analyze degraded DNA samples (Budowle, 2000). The first PCR test used

in forensic study was a human leukocyte antigen HLA-DQα (DQA1) locus. It was an

informative test and could be used for trace and degraded samples, but it lacked the

discriminatory power of RFLP typing (Siegal et al. 2000). Both, the RFLP and PCR technology

form the basis of forensic DNA typing.

2.4 DNA Profiling and Human Skeletal remains

Forensic examination of human skeletal remains mainly emphasis on establishing the

DNA profile. DNA profiling is a technique, where DNA is extracted from biological tissues and

analyzed and compared to identify the origin of the particular tissue. This technology has solved

many identification problems such as establishing the identity of individuals, testing

relationships in cases of maintenance, testamentary proceedings and location of extended

families (Kestler and Horsburgh 2002). Creating a DNA profile can be challenging or even

difficult in the case of highly fragmented and degraded DNA samples, as in cases of terrorism or

where sample remains are exposed to harsh and severe environmental conditions for an extended

13

period of time (Hedges et al. 2006). Bones and teeth are mostly used in forensic study as they

have the ability to show resistance to harsh and severe conditions such as high temperature,

humidity and microbial action (Fondevila et al., 2008, Imamoglu et al., 2012).

2.4.1 Structure and Composition of Human Bones

Bone is a complex, calcified, highly organized, living and specialized connective tissue

that forms human skeleton (Nather 2005). The basic structure of human bone is made up of two

components: organic and inorganic. The organic component makes up ~30% of dry bone by

weight and is mostly comprised of collagen (Martin et al., 1998). Collagen is a structural protein

found in the human body and exists in several forms. The inorganic component makes up ~70%

of dry bone by weight and is mainly comprised of a composite of calcium phosphate minerals

(Martin et al. 1998, Piglionica et al., 2012).

2.4.2 Classification of Human Bones

The average adult human skeleton is comprised of 206 bones. They are divided into five

types: long, flat, irregular, short and sesamoid (Bass 1995, White and Folkens 2005, White et al.,

2011). Long bones are hollow and tubular, found in the upper and lower extremities (e.g.,

humerus, femur). Flat bones are thin and tabular shaped, found in the cranial vault (e.g., skull,

shoulder, pelvis and rib cage). Irregular bones are bones of various shapes such as bones of the

face and vertebrae. Short bones are cuboidal (e.g., carpals and tarsals). Sesamoid bones are oval

or round bones embedded in tendons (e.g., patella and pisiform). On the basis of porosity, bones

are divided into two types; compact bones and spongy bones (Martin et al., 1998) as shone in

figure 2.2. Compact/Cortical bone is a dense bone with 5-10% porosity that surrounds spongy

bones. Cancellous bone/Spongy bone is a porous, lightweight, honey-comb like structured tissue,

with 75-95% porosity (White et al., 2011).

14

Figure 2. 2 Compact and Spongy Bone (Image Source: http://www.gla.ac.uk)

2.5 Process of DNA Degradation

As described before the major constituents of bone are protein (collagen) and minerals.

Bones and teeth are capable of undergoing microbiological and chemical alteration. Alterations

of bone proteins cause the complete structural and chemical breakdown, responsible of the post

mortem changes in bone. The process of DNA degradation begins a few hours or days after the

death of an organism. Upon exposure to the environment, degradation accompanied in bone

samples due to microbial, biochemical, hydrolytic and oxidative processes (Holland et al., 2003).

DNA degradation begins with autolysis and putrefaction. Most of the degradation occurs during

autolysis when non-bacterial enzymes liberated from the lysosomes digest the DNA template

(Bar et al., 1988, Burger et al., 1999). Putrefaction is the process where anaerobic bacteria

15

decompose proteins. This process is often accompanied by gas production which results in the

foul odor of decaying bodies. DNA degradation occurs at this time due to the presence of

endonucleases. These enzymes decompose the DNA template by shearing it into smaller

fragments. In addition, exonucleases detach one nucleotide after another from the terminal ends,

thus gradually shortening the DNA fragments (Bar et al., 1988). Other chemical processes that

affect DNA degradation over time include hydrolysis and oxidation. The modification and loss

of bases due to hydrolytic and oxidative damage and the absence of specific repair enzymes in

dead cells can result in the loss of the expected DNA fragment during PCR amplification (Burger

et al., 1999).

2.6 Role of DNA Extraction in DNA Typing

Extraction of DNA from old bone samples, maximization of DNA yield and elimination

of PCR inhibitors are important issues in forensic DNA studies. Sometimes, the history and

condition of DNA samples are unknown in forensic DNA study. Therefore, an ideal DNA

extraction method is required to produce highly purified and high quality DNA from old and

degraded DNA samples. DNA Typing of degraded DNA depends on the extraction of the small

amounts of DNA remaining in old bone samples. There are a wide range of DNA extraction

methods, which depend on alcohol precipitation, spin columns, or silica columns. Cattaneo et al.

(1997) compared three different methods for extracting DNA from 43 year old bone samples.

Those methods were the silica-based method, magnetic bead and sodium acetate method. Results

showed that using the silica-based method and magnetic bead method gave the maximum yield

of DNA. Sodium acetate method was also better in maximizing yield of DNA, but PCR

inhibitors were found in its extracts. Davoren et al. (2007) compared two different methods for

extracting DNA from exhumed bones of mass graves. Those were silica column based extraction

16

method and phenol/chloroform extraction method. The silica column based DNA extraction

method gave significant results from DNA typing of old bones than phenol/chloroform

extraction method. Loreille et al. (2007) compared two different extraction methods for DNA

analysis of bones. Those methods were the total demineralization method and the standard DNA

extraction phenol/chloroform methods. Total demineralization method gave maximum quantity

of DNA from degraded skeletal remains. Jakubowska et al. (2012) compared three different

extraction methods for both fresh and old bone samples. These methods were simple organic

phenol/chloroform extraction method, crystal aggregates and total demineralization extraction

method. Total demineralization extraction method was excellent for buried and degraded bone

samples, while simple organic phenol/chloroform extraction method was significant for fresh

bone samples.

2.7 Amplification of degraded DNA

The modern forensic DNA study of human skeletal remains depends on the size/sequence

of PCR products (Bender et al., 2004). Compared with DNA extraction from fresh samples of

saliva and blood, DNA of old bones are generally of shorter length (Bacher and Schumm 1998).

Stochastic effects (allelic dropout, allelic imbalance, increased stutter or non-template addition)

may occur during the amplification of degraded low template DNA (Alaeddini et al., 2010).

Occurrence of stochastic effects could be reduced if quantification of samples indicates that the

concentration of template DNA is more than 200 bp for PCR amplification. Such quantification

of DNA molecules is obtained by using real-time quantitative PCR (Alaeddini et al., 2010).

Optimal template amounts for amplification are typically range from 0.2 to 2 ng of input DNA

molecule with 28-30 PCR amplification cycles (Budowle et al., 2009). One ng of DNA is

considered optimal for most of the commercial DNA amplification kits and 1 ng of DNA is

17

almost equal to six hundred and sixty copies of genomic DNA and when the starting amount of

DNA is < 60 copies, the chances of PCR failures are increased (Alonso et al., 2003).

2.8 Applications of STRs, mini-STRs and SNPs on degraded DNA samples

2.8.1 Short Tandem Repeats Markers (STRs)

Repeated DNA sequences are found throughout the genome of eukaryotic organisms.

Repeat units having 10-100 base pairs sequences and repeated in the genome almost 1000 times,

are referred to as minisatellites or VNTRs markers (Chambers and MacAvoy, 2000). DNA

sequences having 2-6 base pair repeat units and a total amplicon length of less than 500 base

pairs are called microsatellites or STRs. STRs are smaller version of VNTRs that can be

amplified by PCR and maintain their high level of discriminatory power. They are mostly found

in the non-coding regions of DNA molecules (Schneider, 1997, Butler, 2001). One key

advantage of STRs over VNTRs is they can be amplified by PCR. STRs also require only 1 ng of

DNA as compared to the 50 ng required by RFLP analysis (Wickenheiser 2002). STR loci occur

1/15,000 bases in human genome and their rate of mutation is 1/1000. STRs are highly

polymorphic because of two reasons. First, they are randomly distributed throughout the

genome and commonly occurring in non-coding regions and second, they mutate more quickly

than other nuclear regions of the genome. The first STR markers reported were di-repeats

(Weber and May, 1989). STR markers used today for forensic study have at least four bases in

the repeat unit. STR loci offer high discriminatory power and the STR markers allow for

identification of individuals. Allelic ladder is the reference standard used for each STR locus.

Allelic ladders are amplified with the same primers used for amplifying DNA samples. They

provide a comparison standard for analysis of unknown alleles (Sajantila et al., 1992).

STRs are classified into different repeat units, such as mono-, di-, tri-, tetra-, penta- and

hexanucleotides (Fan and Chu 2007). Dinucleotide repeats have two bases in the repeat unit,

18

trinucleotide repeats have three bases, tetranucleotide units have four, pentanucleotide units have

five, and so on. Aside from differing in the length and number of repeat units, STRs also differ in

their repeat patterns. Some STR markers contain simple repeats, wherein the repeat units have

identical length and sequence. Some contain compound repeats, where the repeat units are made

up of two or more simple repeat units. Some contain complex repeats, where the repeat units are

made up of several blocks of variable unit length and intervening sequences (Butler 2001). Some

alleles contain incomplete repeat units called microvariants (e.g. allele 9.3 at the TH01 locus)

can also be found within the STR locus (Puers et al., 1993, Butler 2012). These microvariants are

sometimes called ‘off-ladder’ alleles because they do not size correctly with the alleles present in

the allelic ladder. In 1997, a standardized set of STR markers was developed by forensic DNA

scientists to be used for the identification of human being and was called Combined DNA Index

System (CODIS). In this project 17 STR loci were studied, only 13 of them were selected to be

part of this system. The 13 CODIS STR loci include: TH01, TPOX, FGA, D21S11, CSF1PO,

D7S820, vWA, D18S51, D8S1179, D13S317, D5S818, D16S539, and D3S1358. Among them,

D21S11, D18S51 and FGA are the most polymorphic STR markers while TPOX displays the

tiniest variation between persons (Chakraborty et al., 1999, Butler 2001).

2.8.1.1 Nomenclature of STR markers

If a marker is part of a gene or falls within a gene, the gene name is used for designation.

For example, the TH01 STR marker is a part of human tyrosine hydroxylase gene found on

chromosome 11. The ‘01’ portion of TH01 tells us that the repeat region is located within intron

1 of this gene. Sometimes the prefix HUM- is included at the beginning of a locus name to

indicate that it is from the human genome. Thus, the STR locus TH01 would be correctly listed

as HUMTH01 (Butler, 2005). DNA markers that fall outside of gene regions are designated by

their chromosomal position. For example, the STR marker “D5S818” is example of markers that

19

are not found within gene regions. In this cases, ‘D’ shows DNA, 5 indicates chromosome

number, ‘S’ means that the DNA is a single copy sequence and the final number tells us that it is

the 818th locus described on chromosome 5 (Butler 2001).

2.8.1.2 Application of STRs on Degraded DNA Samples

Short tandem repeats (STRs) are PCR based DNA loci that enabling simultaneous

analysis of multiple loci. Several commercial STR multiplex systems have been developed &

currently accepted within the forensic community (Butler, 2005). Although STR markers are

successfully used in the analysis of DNA, the success of STR amplification is still dictated by the

average size of the template being amplified (Hummel et al., 1999, Alonso et al., 2001). The

amplicon sizes of commercial STR multiplex kits are ranging from 100-450 base pairs (Butler et

al., 2003). When the analysis of degraded DNA is carried out with these kits, the larger sized

amplicons in these kits show lower sensitivity and fall below the detection threshold. In these

situations, allele/locus drop-out take place and give rise to partial genetic profiles (Whitaker et

al., 1995, Takahashi et al., 1997).

2.8.2 Application of Mini-STRs on Degraded DNA Samples

Degraded DNA is mostly characterized by low quantitation and fragmentation. Therefore

conventional STR kits often failed to analyze degraded DNA; but one solution to this problem is

to use smaller PCR products, the so called mini-STRs (Butler 2005, Hughes-Stamm et al., 2011,

Senge et al. 2011). Allelic/locus drop-out occurs during conventional STR analysis (Schneider et

al., 2004). Mini-STRs are achieved by moving the forward and reverse PCR primers in close to

the STR repeat region. Mini-STRs multiplex system was introduced for amplification of degraded

DNA in 2001 (Butler et al., 2003). Mini-STRs were successfully used for the identification of

human remains of the world trade center attack accompanied in 2001. These remains were highly

degraded and fragmented due to intense heat of fire and other environmental factors (Holland et

20

al., 2003). With this system it was possible to amplify smaller PCR products with a greater

success when compared to conventional multiplex systems such as AmpFlSTR® Profiler

Plus. It might be due to the fact that PCR products of mini-STR kits are smaller as compared

to conventional STR kits (Butler et al., 2003).

A large number of forensic DNA studies have shown that analysis of degraded DNA is

improved with smaller sized PCR products, therefore mini-STRs were introduced in forensic

practice since 2005 (Coble and Butler 2005, Severini et al., 2011). In recent years, ENFSI-

EDNAP groups have strongly encouraged the development of new amplification kits for DNA

profiling from degraded DNA samples. New available commercial kits combine amplification

chemistry development with small size loci design to attain greater resistance to inhibitors and

more vigorous and uniform amplification. Opel et al. (2006), Martin et al. (2006) and Massetti et

al. (2009) used PCR multiplexes of mini-STRs to improve DNA profiling of degraded DNA

samples that generated negative/partial DNA profiles with conventional STR kits. The results

showed DNA profiling was improved with mini-STR kits. One of the major disadvantages of

Mini-STR multiplexing is that only few loci can be amplified simultaneously in a single multiplex

reaction as most of loci are of similar size (Butler et al., 2003).

2.8.3 Single Nucleotide Polymorphisms (SNPs)

Single nucleotide polymorphism is a single base (A, G, C or T) sequence variation at a

particular point in the genome (Li et al., 2006). SNPs occur in both exons (coding regions) and

introns (non-coding regions) of the genome. These markers are the most polymorphic sites in the

human genome with approximately 1/1000 base pairs. More than 23 million SNPs have been

reported in the NCBI SNPs database. SNPs are another type of forensic DNA marker that is used

for forensic DNA study (Twyman and Primrose, 2003).

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2.8.3.1 Application of SNPs on Degraded DNA Samples

SNPs are preferred over STRs for typing degraded DNA samples as small size fragments

of DNA are required for SNPs than STRs (Asari et al., 2009). SNPs are more common in human

genome and their mutation rate is lower (1/1000, 000,000) than STRs. Stuttering artifact is

not observed in SNP analysis which makes the interpretation easier (Butler 2005).

However, one drawback of SNPs is that it requires a larger number of loci (50 or more) to obtain

the same level of discriminatory power of STRs (Gill 2001, Gill et al., 2004).

New markers such as mini-STRs and SNPs were used by ENFSI-EDNAP groups to

improve the amplification of degraded DNA instead of to increase the power of discrimination of

conventional STRs. Results indicated that mini-STR markers were more effective DNA markers

(Dixon et al., 2006). Senge et al. (2011) accompanied a comparative study of conventional STRs

and mini-STRs for typing degraded DNA. Results indicated that mini STRs were superior to

conventional STRs. In 2009, a comparison of standard STR profiling was carried out with mini-

STRs and SNPs for typing artificially UV-irradiated degraded DNA samples. Most of the

standard STR markers failed to amplify highly degraded DNA samples, while mini-STRs and

especially SNPs provide valuable information (Westen and Sijen, 2009). Similar kind of study

was carried out by Fondevila et al. (2008) and Hughes-Stamm et al. (2011) for the analysis of

highly degraded DNA. The results indicated that mini-STRs and SNPs analysis produced

significant DNA profiles than conventional STRs.

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Table 2.1 Comparison of STR and SNP markers

Characteristics Short Tandem Repeats

(STRs)

Single Nucleotide Polymorphism (SNPs)

Occurrence in

human genome

1/15 kb 1/1 kb

General

information

High Low (only 20 to 30% as informative as STRs)

Mutation rate 1/1000 1/100 000 000

Marker type Di, tri, tetra, penta-nucleotide

repeat markers with many alleles

Mostly bi-allelic markers with six

possibilities: A/G, C/T, A/T, C/G, T/G, A/C

Number of alleles

per marker

Usually 5 to 20 Typically 2 (some tri-allelic SNPs exist)

Detection methods Gel/capillary electrophoresis Sequence analysis; microchip hybridization

Multiplex

capability

>10 markers with multiple

fluorescent dyes

Difficult to amplify more than 50 SNPs well

(detection of 1000s with microchips)

Amplicon size ≈75 to 400 bp Can be less than 100 bp

Ability to predict

ethnicity

Limited Some SNPs associated with ethnicity

Major advantages

for forensic

application

Many alleles enabling higher

success rates for detecting and

deciphering mixtures

Enabling higher success rates with degraded

DNA samples; low mutation rate may aid

kinship analysis; phenotype prediction

Limitations for

forensic

application

Data interpretation must account

for artifacts such as dye blobs,

stutter, spikes, etc.

Large multiplexing assays required; mixture

resolution issues/interpretation; population

substructure due to low mutation rate.

(Adapted from: Butler 2010, Fundamentals Chapter 12).

2.9 Commercial STR, mini-STR and SNP Kits

There are two major manufacturers of commercial STR, mini-STR, and SNP kits used by

the forensic DNA scientists. These are promega and applied biosystems.

23

2.9.1 Identifiler™ and Minifiler™-STR Systems

Two of the most powerful commercial STR kits used for DNA typing are the

AmpFlSTR® Identifiler™ STR kit (ABI) and the PowerPlex® 16 system (Promega). These STR

kits can amplify 16 STR loci simultaneously. Applied Biosystems included two additional STR

loci D2S1338 and D19S433 plus the gender marker amelogenin beside the 13 core STR loci in

their AmpFlSTR® Identifiler™ kit, while Promega included Penta E and Penta D in their

PowerPlex® 16 system plus the gender marker amelogenin. The Applied Biosystems (ABI)

AmpFℓSTR® Identifiler™ kit amplifies 15 human specific STR markers plus the gender marker

amelogenin in a single reaction. AmpFℓSTR® Identifiler™ kits has amplicon sizes that usually

range from 100-450 base pairs (Butler et al., 2003). In this kit, each primer is fluorescently

labeled with a dye which is attached to the 5′ end of the PCR primer and is detected by passing

through a light source scanner that detects the spectrum of light from the different fluorophores.

This is done through gel capillary electrophoresis, which split up the DNA fragments by size.

Results achieved from kit are seen on an electropherogram. An electropherogram contains a y-

axis, which measures the relative fluorescent units (RFUs), and an x-axis, which measures time

or size of the DNA.

AmpFℓSTR® Identifiler™ works well on a majority of samples encountered in criminal

cases, but it may not produce full human genetic profiles on compromised/degraded DNA

samples. Such samples occur if they are exposed to humidity, heat, UV, environmental

contaminants, such as microbes, soils etc. These elements have the possibility of inhibiting the

PCR process (Butler et al., 2003, Grubwieser et al., 2006). A solution to this problem is to use

small size PCR amplicons (Wiegnad and Kleiber, 2001, Opel et al., 2006). Applied Biosystems

used this mechanism for the PCR system and developed AmpFℓSTR® Minifiler™ STR kit.

Minifier™ STR kit reduces the amplicon size of only the largest eight STR loci in the

24

AmpFℓSTR® Identifiler™ STR kit, as the remainder STR loci in this kit contains smaller

amplicons. Opel et al. (2006) produced full genetic profiles from naturally degraded DNA of

human skeletal remains using MiniFiler™ kit.

2.9.2 SNaPshot™ Multiplex Kit (Minisequencing)

The SNaPshot Multiplex system depends on dideoxy single base extension of unlabeled

oligonucleotide primers (Tully et al., 1996). SNPs detection using SNaPshot Multiplex system

requires SNaPshot™ Multiplex Kit including the master mix with fluorescently dye-labeled

ddNTPs and enzymes, template and primers, GeneScan™ 120 LIZ® Size Standard, Capillary

electrophoresis instruments and GeneMapper® Software. There are six main steps in carrying

out minisequencing. These are amplification of genomic DNA, removal of dNTPs and primers,

primer extension, removal of unincorporated ddNTPs, capillary electrophoresis and data analysis

with GeneMapper software (Morely et al., 1999, Sanchez et al., 2003, Vallone et al., 2004).

2.10 Applications of Capillary Electrophoresis (CE) in DNA Typing

Capillary electrophoresis is a methodology used for separation and detection of STR,

mini-STR and SNP alleles in forensic DNA analysis. Capillary electrophoresis consists of three

steps that are injection, separation and detection. The CE systems such as ABI Prism 310, 3100

3130xl, 3500 and 3500xl are commonly used Genetic Analyzers for the analysis of STRs, mini-

STRs and SNPs. The CE system consists of two buffer vials, a narrow glass capillary, two

electrodes, a fluorescence detector, an auto-sampler, a laser excitation source and a computer

(Butler et al., 2004, Butler 2010, Fundamentals Chapter 6). Data obtained from CE is analyzed

with GeneScan® (Applied Biosystems) and Genotyper® (Applied Biosystems) or

GeneMapper® 4.0/GeneMapper® ID (Applied Biosystems) analysis software.

25

2.11 Applications of DNA Typing and Phenotyping

DNA typing is widely used for the identification of human being after terrorist attacks,

crimes, air crashes, fire breakout, automobile and explosive incidents, mass disasters, poisonous

gas attacks, natural events such as earthquake and flood effects and missing person’s

investigations (Alaeddini et al., 2010). Human identification by DNA typing is only successful

for persons who are already known to crime investigators, whereas unknown persons are difficult

to identify with this approach. In such cases forensic DNA phenotyping is applied (Dembinski

and Picard, 2014).

Forensic DNA Phenotyping is a technique in which criminal suspects can be identify on

the basis of traits such as skin, eye and hair color, gait and geographical ancestry etc. An

important factor in identification of human skeletal remains is the documentation of the

externally visible characteristics, such as hair, skin and eye colour. However, if these visible

characteristics are lost, then it would be necessary to use genetic information to divulge these

external visible characteristics (Spichenok et al., 2011). Extraction of externally visible

characteristics (hair, eye and skin color) from a crime scene are expected to be useful during

police investigation in search for unknown suspects as it will allow reducing the number of

potential suspects with information directly obtained from the crime scene (Draus-Barini et al.,

2013).

Pigmentation-related DNA polymorphisms in human being depend on the presence of

melanin which is the main pigment of skin (epidermis), eye (iris) and hair colour (Liu et al.,

2013). The synthesis of melanin relies on multiple genes and factors, such as diseases, drugs, age

and environmental conditions (Lin and Fisher, 2007). Human pigmentation is a polygenic trait

which is influenced by the interaction of different kinds of genes. Recent studies have showed

26

that interaction between HERC2, OCA2, MC1R, SLC45A2 and DCT is responsible for human

pigmentation. Variations in human eye, hair and skin color are the most discriminating and

visible human traits. There are remarkable intra-population variations in human pigmentation

among individuals of different populations. These variations of pigmentation in humans are

mostly due to differences in distribution, type and amount of melanin produced in melanocytes

(Frudakis 2010, Branicki et al., 2009).

27

CHAPTER THREE

28

MATERIALS AND METHODS

3.1 Samples Collection

Twenty four human old bone samples were collected from 100-1000 years old mass

graves of Khyber Pakhtunkhwa province of Pakistan for DNA analysis. Approval for samples

collection was taken from the ethical review committee of the Centre of Excellence in Molecular

Biology University of the Punjab Lahore Pakistan. The samples were photo-documented, labeled

and stored at -20°C till use.

3.2 Cleaning and Pre-treatment and maceration of bone Samples

The bone samples were handled with gloved hands and forceps to avoid contamination.

They were divided into small fragments with a saw and exposed to UV light for 30 minutes. The

bone fragments were treated with Dremel tool, scalpel, surgical blades, distilled water, 10 %

bleach and 95% ethanol to remove contaminated soil, inhibitory substances, and other dirt and

debris. The samples were kept for overnight in a disinfected fume hood and were macerated into

fine powder using surgical scalpel blades, liquid nitrogen, mortar & pestle, abrasives, SPEX

6750 Freezer ⁄ Mill and bench-wise accessories. Bone powder of each sample were transmitted to

15 mL falcon tubes & kept at - 200

C till DNA extraction.

3.3 Extraction of DNA

DNA Extraction was accompanied twice with modified silica column-based complete

demineralization extraction method (Zar et al., 2013). 0.5 g bone powder of each bone sample

was added to a 50 mL falcon tube. Then 15 mL of extraction buffer (0.5 M EDTA and 0.5%

SDS) and 150 µL of 20 mg/mL Proteinase K were added to each tube to dissolve bone powder.

Tubes were mixed well and incubated at 56 C for 48 hours. After first incubation, additional 150

µL of 20 mg/mL Proteinase K was added to each tube and incubated at 56 C for 1 hour. Each

29

tube was centrifuged at 3200 x g for 5 minutes. 7.5 mL of the supernatant was taken from each

tube and added to another 50 mL falcon tube. 38 mL of PB buffer (QIAquick PCR purification

kit, Qiagen) was added to each tube and mixed well. Each tube was centrifuged at 3200 x g for 5

minutes. The mixture of each sample was passed through a QIAamp Blood Maxi column

(Qiagen) using QIAvac 24 Plus connecting system (Qiagen). Maxi columns were cleaned by

pouring 15 mL PE buffer (QIAquick PCR purification kit, Qiagen) in each column. Each column

was placed in a 50 mL collection tube. The tubes were centrifuged at 3200 x g for 5 minutes to

eradicate remaining PE buffer. Collection tubes were discarded and each QIAamp Maxi column

was placed in a new 50 mL falcon tube. 1 mL of nuclease-free double distilled water (ddH2O)

was added to each QIAamp Blood Maxi column (Qiagen). The cap of each tube was closed and

kept for 5 minutes at room temperature. Columns in tubes were centrifuged at 3200 x g for 5

minutes. This step was repeated to attain 2 mL of eluted DNA of each sample. 10 mL of the PB

buffer was added to each tube containing eluted DNA and mixed well. The mixture of each

sample was passed through the QIAamp Mini spin columns (Qiagen) using QIAvac 24 Plus

connecting system (Qiagen). Mini columns were cleaned by pouring 750 µL of PE buffer

(QIAquick PCR purification kit, Qiagen) in each column. Each column was placed in a 2 mL

collection tube. The tubes were centrifuged at 14000 rpm for 3 minutes. Collection tubes were

discarded and each QIAamp Mini column was placed in a 1.5 mL Eppendorf tube. 100 µL of

nuclease-free double distilled water (ddH2O) was added to each QIAamp Mini column and

incubated for 5 minutes at room temperature. Each column in tube was centrifuged at 8000 rpm

for 1 minute. The QIAamp Mini columns were discarded and eluted DNA was stored at -20°C

till use. All extractions were accompanied by negative controls.

30

3.4 Quantification of DNA Using Real Time PCR

Quantification of DNA was conducted with Quantifiler® Duo-Human DNA

Quantification kit (ABI, 2008) and the ABI Prism® 7500-Real Time PCR System (ABI) in

duplicate with modified reduced volume reaction. The quantification reaction was carried out in

a total volume of 12 μL comprising 6.0 μL Quantifiler PCR reaction mix, 5.0 μL Quantifiler

human primer mix and 1 μL DNA extract. 7500 SDS software v 2.0.5 (Applied Biosystems) was

used for Data analysis. The level of PCR inhibitors was determined from the CT value of internal

PCR control (IPC).

3.5 Amplification of DNA

DNA amplification was accompanied twice using standard PCR multiplex kits.

AmpFISTR® Identifiler™ PCR amplification kit (ABI) was used for STR analysis. Mini-STR

analysis was carried out with AmpFISTR® Minifiler™

PCR Amplification kit (ABI) and for

SNPs analysis, in-house SNaPshot SBE multiplex system was used.

3.5.1 Amplification of Autosomal STRs using AmpFISTR Identifiler PCR Amplification

Kit

Amplification of autosomal STRs was conducted twice with AmpFISTR® Identifiler™

STR kit (ABI) with modified reaction mixtures containing 2.0 µL primer mix, 3.8 µL PCR

reaction mix, 1.7 µL dH2O, 2 µL template DNA (≤ 100 pg/µL) and 0.5 µL (5.0 U/µL) of

AmpliTaq Gold DNA Polymerase in a final reaction volume of 10 µL. Thermal cycling was

accompanied on PTC-200 (MJ Research, USA) thermo cycler under the following PCR

conditions: Initial incubation at 95° C for 11 min, dentaturation at 94°C for 1 min, annealing at

59°C for 1 min, extension at 72°C for 1 min and a final extension at 60° C for 60 min with a final

hold at 4°C. The number of PCR cycles was kept 33 during all experiments. PCR amplifications

31

were conducted twice for DNA extracts of each bone sample. Negative controls were run with all

PCR amplification reactions.

3.5.2 Amplification of Autosomal STRs using AmpFISTR MiniFiler PCR Amplification Kit

Amplification of autosomal STRs was conducted twice with AmpFlSTR MiniFiler PCR

Amplification Kit (ABI) with modified reaction mixtures containing of 1.7 µL H2O, 2.0 µL

primer mix, 0.3 µL (5U/µL) AmpliTaq Gold DNA Polymerase, 4.0 µL PCR mix and 2.0 µL

template DNA (≤ 100 pg/µL) in a final reaction volume of 10 µL. Thermal cycling was carried

out on PTC-200 (MJ Research, USA) thermo cycler under the following PCR conditions: Initial

incubation at 95 C for 11 min, dentaturation at 94 C for 20 sec, annealing at 59 C for 2 min,

extension at 72 C for 1 min and a final extension at 60 C for 45 min with a final hold at 4°C.

The number of PCR cycles was kept 33 during all experiments. Negative controls were run with

all PCR amplification reactions.

3.5.3 Amplification of SNPs Using In-house SnaPshot SBE Multiplex System

The in-house SnaPshot SBE multiplex system consists of nine SNPs, rs885479 (MC1R),

rs26722 (SLC45A2), rs2031526 (DCT), rs7495174 (OCA2), rs4778241 (OCA2), rs4778138

(OCA2), rs1800414 (OCA2), rs1545397 (OCA2) and rs12913832 (HERC2). The details of all

markers (SNPs) and primer sequences are listed in Table 3.1-3.3. Genomic DNA was amplified

with multiplex PCR with modified reaction mixtures consisting of 4.4 µL dH2O, 1.0 µL of 10x

Gold STR buffer, 0.6 µL (5U/µL) of AmpliTaq Gold DNA Polymerase, 2.0 µL of 5x primer mix

and 2.0 µL of template DNA (≤ 100 pg/µL) in a final reaction volume of 10 µL. Thermal

cycling was accompanied on PTC-200 (MJ Research, USA) thermo cycler under the following

PCR conditions: Initial incubation at 95 C for 11 min, denaturation at 94 C for 20 sec,

annealing at 60 C for 1 min, extension at 72 C for 30 sec and a final extension at 72 C for 7

min. The number of PCR cycles was kept 38 during all experiments. Negative controls were run

32

with all PCR amplification reactions. The remaining dNTPs and primers were removed by

adding 1.5 µL Exo-SAP-IT (exonuclease and shrimp alkaline phosphatase) enzymes to the 5 µL

of PCR product in a PCR reaction tube. Thermal cycling was accompanied on PTC-200 (MJ

Research, USA) thermo cycler under the following PCR conditions 37 C for 45 min, and 80 C

for 15 min with a single PCR cycle. Primer extension (SBE multiplex reaction) was carried out

by adding 4.0 µL dH2O, 1.0 µL of SnaPshot reaction mix, 2.0 µL of 5x sequencing buffer and 2

µL of 5x primer mix to 1.0 µL of Exo-SAP-treated PCR products in a final reaction volume of

10 µL. Thermal cycling was carried out on PTC-200 (MJ Research, USA) thermo cycler under

the following PCR conditions 96 C for 10 sec, 50 C for 5 sec and 60 C for 30 sec with 25

PCR cycles. After the SNP extension reaction, the SBE products were treated with 1.5 µL

shrimp alkaline phosphatase to remove ddNTPs. Thermal cycling was accompanied on PTC-200

(MJ Research, USA) thermo cycler under the following PCR conditions 37 C for 45 min, and

80 C for 15 min with a single PCR cycle.

3.6 Capillary Electrophoresis (CE)

The analysis of SBE products was carried out with capillary electrophoresis using ABI

Prism® 3130 Genetic analyzer (ABI). Injection mixtures (consisted of 10 μL of Hi-Di formamide

(ABI), 0.2 μL of GeneScan® 500/120-LIZ™ size standard and 1.0 μL of PCR product for each

sample in a final reaction volume of 11.2 µL), were loaded to a 96-well genotyping plate and

covered with the rubber septa. The samples were heated at 95℃ for 5 min to denature DNA into

single stranded DNA and immediately placed on crushed ice for 3 min to stop DNA from

renaturation and injected on the ABI Prism® 3130 Genetic analyzer (ABI).

33

3.7 Data Analysis

Data analysis was conducted with GeneMapper ID software version 3.2 (Life

Technologies). Only the loci showing reliable results were counted. Allele with peak height

above 100 RFU was scored. Consensus DNA profiles were generated with an allele common in

two replicates of each sample (Gill et al., 2000). Allele frequencies of all SNPs were analyzed

with Chi-square Hardy-Weinberg equilibrium test calculator (Rodriguez et al., 2009) and

compared with other populations.

Table 3. 1 Information about the 9 SNPs used in this Study

.Reference

SNP ID

Gene Location Protein SNV

(Alleles)

Phenotype

rs885479

MC1R 16q24.3 Melanocortin 1 receptor

(MCR1)

A/G

Skin color

rs26722 SLC45A2 5p13.3 Membrane-associated

transpoter protein

(MATP)

C/T

Hair color

Skin color

rs2031526

DCT 13q32 dopachrometautomerase

(DCT)

A/G

Skin color

rs7495174

OCA2

15q11.2─15q12 NA+/H+ antiporter or

glutamate transporter

A/G

Eye color

rs4778241

A/C

Eye color

rs4778138

A/G

Eye color

rs1800414

A/G

Eye color

Skin color

rs1545397

A/T

Eye color

rs12913832

HERC2 15q13

Unknown

A/G

Eye color

“Reference SNP ID” refers to the reference sequence identifier given to the SNP in the dbSNP database.“SNV”

stands for single nucleotide variation.

34

Table 3. 2 Primers used for amplification of 9 SNPs in this study

.Gene Reference

SNP ID

Primers Sequence (5′-

3′)

Primer

Length

(bp)

Concentration

(µM)

Amplicon

Size

MC1R rs885479 Forward

GTG GAC CGC

TAC ATC TCC AT

20 0.3

119bp

Reverse AAG AGC GTG

CTG AAG ACG

AC

20 0.3

SLC45A2 rs26722 Forward

CAG GAC CCT

CCA TTG TCA TC

20 0.25

134bp

Reverse TGC ATC TTT

ACC TGT TCA

GCA

21 0.25

DCT rs2031526

Forward

CCT TGA ATT

GCT CTT GAA

AAA CTA A

25 0.8

149bp

Reverse CAG CCC AAT

GAT ACA CTT

TCA TTT AAC

27 0.8

OCA2 rs7495174

Forward

AGG CCC AGG

CGG ACT CAG

18 0.6

128bp

Reverse AGG CAG GGA

GGG TTT ACA

CAG C

22 0.6

OCA2 rs4778241

Forward

GCC ACT CTG

GAA AGC AGT

TT

20 0.5

133bp

Reverse CCA TTT GCG

TGT AGG GTT TT

20 0.5

OCA2 rs4778138

Forward

GCT GTA AAT

TTC CTC CCA

TCA C

22 0.8

116bp

Reverse TCA AAA AGA

AAG TCT CAA

GGG AA

23 0.8

OCA2 rs1800414

Forward

TCG TGA TTC

CAG TTG CGT

AG

20 0.25

135bp

Reverse CCA ACA CTG

TCA GGC ATT

TG

20 0.25

OCA2 rs1545397

Forward

TGG AAT TGG

ATA CTG ACA

ATG GTT G

25 1.0

144bp

Reverse CAT GGG GGA

GAG AGA ATG

ACT CAG

24 1.0

HERC2 rs12913832

Forward

TTG TTC TTC

ATG GCT CTC

TGT GTC TG

26 0.5

108bp

Reverse AGA GAA GCC

TCG GCC CCT

GA

20 0.5

35

Table 3. 3 Minisequencing primers used for the detection of the 9 SNPs used in this study

.Gene Reference

SNP ID

Primer

Direction

Primer

Sequence

(5′-3′) with

t-tail

Primer

Length

with no t-

tail (bp)

Total

Primer

Length

(bp)

Concentration

(µM)

MC1R rs885479 Reverse

(R19-20)

tCC AGA

TGG CCG

CAA CGG CT

19 20 0.8

SLC45A2 rs26722 Forward

(F23-25)

ttG AAT GTA

CGA GTA

TGG TTC

TAT C

23 25 0.15

DCT rs2031526 Reverse

(R22-31)

ttt ttt ttt AAA

TGT CAT

TTG AGG

GTA GGA A

22 31 1.0

OCA-174 rs7495174 Reverse

(R21-38)

ttt ttt ttt ttt ttt

ttA AGG CAA

GTT CCC

CTA AAG GT

21 38 0.2

OCA-241 rs4778241 Reverse

(R19-44)

ttt ttt ttt ttt ttt ttt

ttt ttt tTT GGC

TGG TAG

TTG CAA TT

19 44 0.3

OCA-138 rs4778138 Forward

(F24-50)

ttt ttt ttt ttt ttt ttt

ttt ttt ttC ATC

ACT GAT

TTA GCT

GTG TTC TG

24 50 0.5

OCA-414 rs1800414 Forward

(F21-57)

ttt ttt ttt ttt ttt ttt

ttt ttt ttt ttt ttt ttt

CTG TGG

TTT CTC TCT

TAC AGC

21 57 0.15

OCA-397 rs1545397 Forward

(F29-63)

ttt ttt ttt ttt ttt ttt

ttt ttt ttt ttt ttt

tAA TTT ATC

TTG CAA

AAT TAT

ATC ATT

CAG

29 63 2.0

HERC2 rs12913832 Reverse

(R19-68)

ttt ttt ttt ttt ttt ttt

ttt ttt ttt ttt ttt ttt

ttt ttt ttt ttt tTA

GCG TGC

AGA ACT

TGA CA

19 68 0.15

36

CHAPTER FOUR

37

RESULTS

4.1Extraction and Quantification of DNA

In this study DNA was extracted from old skeletal remains with modified silica columns

based total demineralization extraction method and quantification was carried out by Real Time

PCR with Quantifiler™ Human DUO DNA Quantification kit (Applied Biosystems) and the

ABI Prism® 7500 Sequence Detection System (SDS). Real-time PCR quantification showed that

the DNA was detected in 17 out of 24 old skeletal remains and not detected in 7 samples.

Majority of the degraded old bone samples produced <10 pg/µl DNA from 0.5 g of bone powder

(Zar et al., 2013). In 7 samples, DNA was in the range of 1-10 pg/µL, in 4 samples it was in the

range of 22-69 pg/µL and in 6 samples DNA was in the range of >100 pg/µL (figure 4.1). The

internal PCR control (IPC) assay showed that PCR inhibitors were successfully removed from all

of the extracted DNAs during qPCR, showing CT values of <30 (table 4.1).

Figure 4. 1 Quantification of DNA Using Quantifiler® Duo Human DNA Quantification kit and the ABI

Prism® 7500 Real Time PCR System

38

Table 4. 1 Concentration of DNA and CT (Threshold cycle) values of Internal PCR Control

(IPC)

.S.No Sample ID Type of Bone Quantity of

DNA (pg/µL)

IPC (CT)

1 FRL 1 Humerus 112.5±17.68 28.7±0.13

2 FRL 2 Tibia 5.5±2.12 29.3±0.62

3 FRL 3 Ulna 5.5±0.71 29.3±0.84

4 FRL 4 Metacarpal Not detected 29.3±0.6

5 FRL 5 Tibia 69.5±20.51 29.7±0.25

6 FRL 6 Ulna 104±5.66 29.1±1.06

7 FRL 7 Ulna 22.5±6.36 29.4±0.56

8 FRL 8 Radius 38.5±9.19 29.2±0.88

9 FRL 9 Radius 2.5±2.12 29.8±0.04

10 FRL 10 Skull 117.5±3.54 29.5±0.41

11 FRL 11 Tibia 140.5±7.78 29.2±0.71

12 FRL 12 Femur 171±5.66 29±0.88

13 FRL 13 Ulna 109±12.73 29±0.67

14 FRL 14 Ulna 3.5±2.12 27.8±2.46

15 FRL 15 Radius Not detected 28.4±1.53

16 FRL 16 Femur Not detected 29.5±0.13

17 FRL 17 Tibia 4.5±0.71 29.1±0.55

18 FRL 18 Radius 2±1.41 29.7±0.17

19 FRL19 Femur Not detected 29.8±0.1

20 FRL20 Humerus Not detected 29.8±0.28

21 FRL21 Metacarpal 22±7.07 28.9±0.77

22 FRL22 Fibula Not detected 29.3±0.22

23 FRL23 Radius Not detected 28.5±1.11

24 FRL24 Metacarpal 6.5±6.36 29±0.28

4.2 Increasing sensitivity of PCR amplification

During this study, the extracted DNA was low template (≤100-200 pg/µL) and highly

degraded, therefore, PCR conditions were optimized and the sensitivity of PCR amplification

was increased by extending the number of PCR cycles. For AmpFlSTR® Identifiler® PCR

amplification kit, PCR cycles were extended from standard 28 to 33 to get more informative

DNA profiles from human old skeletal remains. For AmpFlSTR® MiniFilerTM

STR kit and

SNaPshot multiplex kit, PCR cycles were increased from standard 29 to 33 and standard 33 to

38, respectively. During validation studies, it was observed that the amplification of degraded

39

DNA with AmpFlSTR® Identifiler® PCR kit offered promising results by increasing the

number of PCR cycles from standard 28 to 33. Partial DNA profiles (profiles with locus/allele

drop-out) were obtained with standard 28 number of PCR cycles and full DNA profile were

obtained with 33 number of PCR cycles from same old bone samples as shown in figure 4.2 and

figure 4.3, which shows that increasing sensitivity of PCR amplification improve DNA profiling

of old skeletal remains. Therefore extended number of PCR cycles was also used for MiniFilerTM

and in-house SNaPshot SBE multiplex kits. All PCR amplification reactions were accompanied

by negative controls, but no allele/locus drop-in occurred in negative controls with AmpFlSTR®

Identifiler™, AmpFlSTR® MiniFiler™ and in-house SNaPshot SBE multiplex kits as shown in

figure 4.4, 4.5 and 4.6, respectively, and there was no indication of staff contamination by

comparing their DNA profiles against the results obtained from the bones.

40

Figure 4. 2 Partial DNA profile with 28 number of PCR cycles

41

Figure 4. 3 Full DNA profile with 33 number of PCR cycles

42

Figure 4. 4 Negative control obtained with AmpFlSTR® Identifiler™ STR kit

43

Figure 4. 5 Negative control obtained with AmpFlSTR® MiniFiler™ STR kit

44

Figure 4. 6 Negative Control obtained with In-houseSnaPshot SBE multiplex kit

4.3 Effect of environment conditions on DNA quality and profiling of old skeletal remains

In this study the radius of 500 years old, found on the surface of soil and dry mountain

area, produced a partial DNA profile of 8 STR loci plus amelogenin with Identifiler STR kit

(figure 4.7), while a radius of 200 years old, found in buried and wet area, produced a partial

DNA profile of 2 STR loci plus amelogenin as shown in figure 4.8.

45

Figure 4. 7 : Partial DNA profile of 8 STR loci plus amelogenin, obtained with Identifiler kit from 500 years

old radius found on the surface of soil and dry area

46

Figure 4. 8 Partial DNA profile of 2 STR loci plus amelogenin, obtained with Identifiler STR kit from 200

years old radius buried in soil and wet area

47

4.4 Consensus Approach

For each of the degraded old skeletal sample, two replicates were produced

independently. Consensus DNA profiles were created with an allele observed in common from

both replicate reactions of each sample as shown in table 4.2, 4.3, and 4.4. Moreover, in order to

exclude chances of any possibility of internal contamination, DNA profiles of all members of the

laboratory staff were produced with AmpFlSTR® Identifiler®, AmpFlSTR® MiniFilerTM

and

in-house SNaPshot SBE multiplex kits. No match was found for any of the samples analyzed

with same kits.

48

Table 4. 2 Consensus DNA profiles produced with AmpFlSTR® Identifiler® STR Kit

Sample ID

Loci

Replicates

D8

S11

79

D2

1S1

1

D7

82

0

CSF

1P

O

D3

S13

58

THO

1

D1

3S3

17

D1

6S5

39

D2

S13

38

D1

9S4

33

vWA

TPO

X

D1

8S5

1

AM

EL

D5

S81

8

FGA

FRL 1 Replication #

1

13,

14

29,

32.2

8 10,12 15 6, 9.3 8, 9 12,

13

18 14,

16.2

16, 18 9, 11 13,

21

X 10, 12 20,

24

Replication #

2

13,

14

29,

32.2

8 10,12 15 6, 9.3 8, 9 12,

13

18 14,

16.2

16, 18 9, 11 13,

21

X 10, 12 20,

24

Consensus

Profile

13,

14

29,

32.2

8 10,

12

15 6, 9.3 8, 9 12,

13

18 14,

16.2

16, 18 9, 11 13,

21

X 10, 12 20,

24

FRL2 Replication #

1

13 28

11, 12, 15 12

15,16,17 6

11, 12

9, 11

19, 20 13 14.2 -

14, 16

X, Y - 21

Replication #

2

13 28 11 10, 12

15, 16 -

11, 12

9, 11 20

13, 16, 15 14.2 - 16

X, Y

11, 12 21

Consensus

Profile 13 28 11 12

15, 16 -

11, 12

9, 11 20 13 14.2 - 16

X, Y - 21

FRL3 Replication #

1 - 33.2 11

10, 12

15, 16 9.3

11, 13

11, 12

19, 20 13 17 8 16 X

12, 13

21, 24

Replication #

2 13 33.2

9, 11

10, 12

15, 16

8, 9.3

11, 12

11,12

19, 20 13 17 8 16 X

12, 13 21

Consensus

Profile - 33.2 11

10, 12

15, 16 9.3 11

11, 12

19, 20 13 17 8 16 X

12, 13 21

49

FRL4 Replication #

1 13 30 - -

14, 15 - -

11, 12 -

13.2, 15.2 11 - - X - 23

Replication #

2

- 29, 30 - -

13, 14, 15 - - 11 -

13.2, 15.2 - 7, 8 - X 11 23

Consensus

Profile - 30 - -

14, 15 - - 11 -

13.2, 15.2 - - - X - 23

FRL5 Replication #

1 14, 15

26, 30 12

10, 11

15, 17 9.3

8, 11, 12

11, 13

20, 24

14, 15

18, 19 8, 9

15, 17

X, Y 11

22, 24

Replication #

2 14, 15

26, 30 12

10, 11

15, 17 9.3

8, 12, 13

11, 13

20, 24

14, 15

18, 19 8, 9

14, 15, 17

X, Y 11

22, 24

Consensus

Profile 14, 15

26, 30 12

10, 11

15, 17 9.3

8, 12

11, 13

20, 24

14, 15

18, 19 8, 9

15, 17

X, Y 11

22, 24

FRL6 Replication #

1

10,

15

30.2,

31.2

11 10,

13

16, 17 6, 9 8,

12

11,

12

20,

23

13,

15.2

16, 18 8, 9 13,

17

X 9, 11 19,

21

Replication #

2

10,

15

30.2,

31.2

11 10,

13

16, 17 6, 9 8,

12

11,

12

20,

23

13,

15.2

16, 18 8, 9 13,

17

X 9, 11 19,

21

Consensus

Profile

10,

15

30.2,

31.2

11 10,

13

16, 17 6, 9 8,

12

11,

12

20,

23

13,

15.2

16, 18 8, 9 13,

17

X 9, 11 19,

21

FRL7 Replication #

1

14 30,

32.2

8, 11 12 15, 17 8, 9 8 11 23,

25

13, 14 16, 18 8, 11 13,

17

X, Y 12, 13 21,

22

Replication #

2

14 30,

30.2,

32.2

8, 11 12 15, 17 8, 9 8 11 23,

25

13, 14 16, 18 8, 11 17 X, Y 9, 12,

13

20,21

,22

50

Consensus

Profile

14 30,

32.2

8, 11 12 15, 17 8, 9 8 11 23,

25

13, 14 16, 18 8, 11 17 X, Y 12, 13 21,

22

FRL8 Replication #

1 10, 14

30, 31.2 10

11, 12

14, 18 6, 8

8, 11

8, 11

18, 22

14, 15.2

16, 18

8, 10

17, 19

X, Y

10, 11

20, 24

Replication #

2 10, 14

30, 31.2 10

11, 12

14, 18 6, 8

8, 11

8, 9, 11

18, 22

14, 15.2

16, 18

8, 10

17, 19

X, Y

10, 11

20, 24

Consensus

Profile 10, 14

30, 31.2 10

11, 12

14, 18 6, 8

8, 11

8, 11

18, 22

14, 15.2

16, 18

8, 10

17, 19

X, Y

10, 11

20, 24

FRL9 Replication #

1 15 - - 12 16 - - - - 16 17 - 15 X 12 -

Replication #

2 15 - - -

16, 17 6 11 - -

14.2, 15.2 17 - 15 X 11 -

Consensus

Profile 15 - - - 16 - - - - - 17 - 15 X - -

FRL10 Replication #

1 13,14

28, 30

8, 13 12

17, 19 7, 8

12, 13 13

23, 24

13, 16.2

14, 16 11

13, 14

X, Y

11, 13

20, 25

Replication #

2

14 28, 30

8, 13

10, 12

17, 19 8 12 13

23, 24

13, 16.2

14, 16, 18

11, 12

13, 14

X, Y

11, 12

20, 25

Consensus

Profile 14

28, 30 8,13 12

17, 19 8 12 13

23, 24

13, 16.2

14, 16 11

13, 14

X, Y

11, 12

20, 25

FRL11 Replication #

1 10

28, 30

8, 11

10, 11

16, 18 7, 9

11, 13 12

20, 22

13, 15 17

8, 12

14, 17

X, Y

12, 13

23, 26

51

Replication #

2 10, 15

28, 30

8, 11

10, 11

16, 18 7, 9

11, 13

9, 12

20, 22

13, 15

16, 17

8, 12

14, 15, 17

X, Y

11, 12, 13

23, 26

Consensus

Profile 10

28, 30

8, 11

10, 11

16, 18 7, 9

11, 13 12

20, 22

13, 15 17

8, 12

14, 17

X, Y

12, 13

23, 26

FRL12 Replication #

1 13,16

28, 33.2

11, 12

10, 11

14, 16 6, 9 8

10, 12

19, 24

13, 14

15, 16 8

13, 15

X, Y

10, 13

19, 23

Replication #

2 13, 16

28, 33.2 12

10, 11

14, 16 6, 9 8

10, 12

19, 24

13, 14

15, 16 8

13, 15

X, Y

10, 13

19, 23

Consensus

Profile 13, 16

28, 33.2 12

10, 11

14, 16 6, 9 8

10, 12

19, 24

13, 14

15, 16 8

13, 15

X, Y

10, 13

19, 23

FRL13 Replication #

1 12, 13

30, 30.2

10, 12

12, 13

16, 17 9

8, 10

10, 11

18, 20 15

14, 19 11

14, 15 X

12, 13

19, 24

Replication #

2 12, 13

30, 30.2

10, 12

12, 13

16, 17 9

8, 10

10, 11

18, 20 15

14, 18, 19 11

14, 15 X

12, 13

19, 24

Consensus

Profile 12, 13

30, 30.2

10, 12

12, 13

16, 17 9

8, 10

10, 11

18, 20 15

14, 19 11

14, 15 X

12, 13

19, 24

FRL14 Replication #

1 - - 11 - 18 - 11 12 - 13

17, 18

8, 9, 11 15

X, Y 12 -

Replication #

2 10, 16 -

8,9,11 10 - - 11

8, 11 - 13,16 17 8,9 16

X, Y - -

Consensus

Profile - - 11 - - - 11 - - 13 17 8,9 - X,Y - -

52

FRL15 Replication #

1 17 28 11 - - 6 - 9 - 14 - 8 -

X, Y - 21

Replication #

2 13 - 11.2 - 16 6 13 - -

12, 13 - - - X,Y - 21

Consensus profile - - - - - 6 - - - - - - - X,Y - 21

FRL16 Replication #

1 - - - - 16 - 11 - - - - - - - - 20

Replication #

2 - - - 12 - - - - - - - - - - - 21

Consensus

Profile - - - - - - - - - - - - - - - -

FRL17 Replication #

1 13

28, 33.2 11 11

15, 16 9.3 11

9, 11

17, 20

13, 16 19 -

15, 16

X, Y

11, 12 21

Replication #

2 10, 11, 13

28, 29 8

9.2, 11 17 9.3 11 - -

13, 16

17, 19 - 16 X,Y 12 21

Consensus

Profile 13 28 - 11 - 9.3 11 - -

13, 16 19 - 16 X,Y 12 21

FRL18 Replication #

1 13 - - - 16 - - - 20 11 - - - Y - -

Replication #

2 - 28 11 - - 7 - - 20 11 17 - - Y 12 -

Consensus - - - - - - - - 20 11 - - - Y - -

53

Profile

FRL19 Replication #

1 - - - - 16 - - - - - - - 20 - - -

Replication #

2 - - 10 - - - 11 - - - - - - - 12 -

Consensus

Profile - - - - - - - - - - - - - - - -

FRL20 Replication #

1 - - 10 12 - - - - - - 17 11

14, 18 X - 23

Replication #

2 12 - 11 - - - 12 - - - - - - - - -

Consensus

Profile - - - - - - - - - - - - - - - -

FRL21 Replication #

1 11, 14

28, 32.2 12 11 15 7, 8 12 11 22

13, 14.2

14, 15 8

14, 16

X, Y

11, 12 21

Replication #

2 11, 14

28, 32.2 12 11 15 7, 8

11, 12 - 22

13, 14.2

14, 15 8, 9

14, 15

X, Y

11, 12

21, 23

Consensus

Profile 11, 14

28, 32.2 12 11 15 7, 8 12 - 22

13, 14.2

14, 15 8 14

X, Y

11, 12 21

FRL22 Replication #

1 13, 14

29, 30

8, 11

11, 12

15, 17 9 12 9 19

13, 14

14, 15 10 - X - 24

Replication #

2 14 - - 11 - 8

8, 12 9 25 - 15 10 - X 10 24

54

Consensus

Profile 14 - - 11 - - 12 9 - - 15 10 - X - 24

FRL23 Replication #

1 15 30 8 - - 6 12 - - - - - - - - 20

Replication #

2 14 - - - - - - - - -

14, 18 - - Y - -

Consensus

Profile - - - - - - - - - - - - - - - -

FRL24 Replication #

1

10 29, 31 8 13

15, 16, 17 - 8 - -

13, 15.2

16, 19, 20 - - X

11, 13 22

Replication #

2 10 29,31 8 13

16, 17 - 8 - -

13, 15.2

16, 20 - - X

11, 13 22

Consensus

Profile 10 29,31 8 13

16, 17 - 8 - -

13, 15.2

16, 20 - - X

11, 13 22

55

Table 4. 3 Consensus DNA profiles produced with AmpFlSTR® MiniFilerTM

STR Kit

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL1 Replication # 1

8, 9 8 X 18 29, 32.2

12, 13 13, 21 10, 12 20, 24

Replication # 2

8, 9 8 X 18 29, 32.2

12, 13 13, 21 10, 12 20, 24

Consensus Profile

8,9 8 X 18 29, 32.2

12, 13 13, 21 10, 12 20, 24

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL2 Replication # 1

11,12 11 X, Y 19, 20 26.2, 30, 33.2

9, 11 16 12 21, 24

Replication # 2

11, 12

9, 11 X, Y 20 26.2 9, 11, 12

15, 16 10, 12 21

Consensus Profile

11, 12

11 X, Y 20 26.2 9, 11 16 12 21

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL3 Replication # 1

11 11 X, Y 19, 20 33.2 11, 12 15, 16 10, 12 21, 24

Replication # 2

11, 12

11, 12 X, Y 19, 20 33.2 8, 11, 12

15, 16 10, 11, 12

21

Consensus Profile

11 11 X, Y 19, 20 33.2 11, 12 15, 16 10, 12 21

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL4 Replication # 1

11 10, 11 X 16 30 11 14, 15 10, 11 18.2, 23

Replication # 2

11 10, 11 X 24 30 11, 12 14, 15 10 18.2, 23

Consensus Profile

11 10, 11 X - 30 11 14, 15 10 18.2, 23

Sample Replications D13S D7S82 AML D2S13 D21S1 D16S5 D18S5 CSF1P FGA

56

317 0 38 1 39 1 O

FRL5 Replication # 1

8, 12 11, 12 X, Y 20, 24 26, 30 11, 13 13, 15, 17

10, 11, 12

21, 22, 24

Replication # 2

8, 12 12 X, Y 20, 24 26, 30 9, 11, 13

14, 15, 17

10, 11 22, 24

Consensus Profile

8, 12 12 X, Y 20, 24 26, 30 11, 13 15, 17 10, 11 22, 24

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL6 Replication # 1

8, 12 11 X 20, 23 30.2, 31.2

11, 12 13, 17 10, 13 19, 21

Replication # 2

8, 12 11 X 20, 23 30.2, 31.2

11, 12 13, 17 10, 13 19, 21

Consensus Profile

8, 12 11 X 20, 23 30.2, 31.2

11, 12 13, 17 10, 13 19, 21

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL7 Replication # 1

8 8, 11 X, Y 23, 25 30, 32.2

11 17, 19 12 21, 22

Replication # 2

8 8, 11 X, Y 23, 25 30, 32.2

11 17, 19 12 21, 22

Consensus Profile

8 8, 11 X, Y 23, 25 30, 32.2

11 17, 19 12 21, 22

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL8 Replication # 1

8, 11 10 X, Y 18, 22 30, 31.2

8, 11 17, 19 11, 12 20, 24

Replication # 2

8, 11 10 X, Y 18, 22 30, 31.2

8, 11 17, 19 11, 12 20, 24

Consensus Profile

8, 11 10 X, Y 18, 22 30, 31.2

8, 11 17, 19 11, 12 20, 24

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL9 Replication # 1

11, 12,13

- X 20 30 11, 12, 13

15 10, 11, 12

21

57

Replication # 2

13 - X 25 31.2 11 15 10, 11 -

Consensus Profile

13 - X - - 11 15 10, 11 -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL10 Replication # 1

8, 12, 13

8, 13 X, Y 23, 24 28, 30 13 13, 14 12 20, 25

Replication # 2

12, 13

8, 13 X, Y 23, 24 28, 30 12, 13 13, 14 12 20, 25

Consensus Profile

12, 13

8, 13 X, Y 23, 24 28, 30 13 13, 14 12 20, 25

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL11 Replication # 1

11, 13

8, 11 X, Y 20, 22 28, 30 12 14, 17 10, 11 26

Replication # 2

11, 13

8, 11 X, Y 20, 22 28, 30 9, 12 14, 17 10, 11 26

Consensus Profile

11, 13

8, 11 X, Y 20, 22 28, 30 12 14, 17 10, 11 26

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL12 Replication # 1

8 11, 12 X, Y 19, 24 28, 33.2

10, 12 13, 15 10, 11 19, 23

Replication # 2

8 11, 12 X, Y 19, 24 28, 33.2

10, 12 13, 15 10, 11 19, 23

Consensus Profile

8 11, 12 X, Y 19, 24 28, 33.2

10, 12 13, 15 10, 11 19, 23

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL13 Replication # 1

8, 10 10, 12 X 18, 20 30, 30.2

10, 11 14, 15 12, 13 19, 24

Replication # 2

8, 10 10, 12 X 18, 20 30, 30.2

10, 11 14, 15 12, 13 19, 24

58

Consensus Profile

8, 10 10, 12 X 18, 20 30, 30.2

10, 11 14, 15 12, 13 19, 24

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL14 Replication # 1

11, 12

11, 12 X, Y 26 - - - 11, 12 21, 22

Replication # 2

11 11 X, Y 20 33.2 9 15 10, 12 -

Consensus Profile

11 11 X, Y - - - - 12 -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL15 Replication # 1

12 - X, Y 18, 25 33.2 8, 11 16, 17 10 24

Replication # 2

- - X, Y 20, 23 28 9, 10 16, 17 10 24

Consensus Profile

- - X, Y - - - 16, 17 10 24

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL16 Replication # 1

- - - - 28 - 19 - 24

Replication # 2

- - - - - - - 12 -

Consensus Profile

- - - - - - - - -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL17 Replication # 1

11, 12

11 X, Y 29 28 6 16, 19 11 21

Replication # 2

11 8, 10 X, Y 18 28, 30 11 16 11 21

Consensus Profile

11 - X, Y - 28 - 16 11 21

59

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL18 Replication # 1

- 9, 10 Y 20 32.2, 34

- 15 10 -

Replication # 2

- - Y 20 - - 16 11, 12 24

Consensus Profile

- - Y 20 - - - - -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL19 Replication # 1

11 - X - - - - 12 20

Replication # 2

11 - - 31 10, 11 19 - -

Consensus Profile

- - - - - - - - -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL20 Replication # 1

- 11 X, Y 20 29 6 18 - -

Replication # 2

- 10 X, Y 20 - 8, 10, 12

- - -

Consensus Profile

- - X, Y 20 - - - - -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL21 Replication # 1

12 11, 12 X, Y 22 28, 32.2

9, 12 12, 14 10, 11 21, 22

Replication # 2

11, 12

11, 12 X, Y 22 28, 32.2

9, 12 12, 14 10, 11 21, 22

Consensus Profile

12 11, 12 X, Y 22 28, 32.2

9, 12 12, 14 10, 11 21, 22

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

60

FRL22 Replication # 1

12 8 X 17, 20 - 11 14, 16 11, 12 23

Replication # 2

8, 12 10 X - 33.2 11 16 11 22, 23

Consensus Profile

12 - X - - 11 16 11 23

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL23 Replication # 1

12 - - - 29 - - - 25

Replication # 2

- 11 - - - 9 - 12 20, 21

Consensus Profile

- - - - - - - - -

Sample Replications D13S317

D7S820

AML D2S1338

D21S11

D16S539

D18S51

CSF1PO

FGA

FRL24 Replication # 1

8, 11 8, 9 X 20, 25 29, 31 10, 12 12, 14 12, 13 22, 26

Replication # 2

8, 11 8 X 24, 25 29, 31 10, 12 12, 14, 19

12, 13 22

Consensus Profile

8, 11 8 X 25 29, 31 10, 12 12, 14 12, 13 22

61

Table 4. 4 Consensus DNA profiles produced with in-house SnaPshot SBE multiplex kit

Sample

ID

Replication/

Consensus

Profile

Loci/Markers (9 SNIPs)

MC1R

Skin

Color

SLC45A2

Hair &

Skin

Color

DCT

Skin

Color

OCA174

Eye

Color

OCA241

Eye

Color

OCA138

Eye

Color

OCA414

Eye &

Skin

Color

OCA397

Eye

Color

HERC

2

Eye

Color

FRL1 Replication1 WW WW MtMt WW MtMt Mt/W WW MtMt WW

Replication2 WW WW MtMt WW MtMt Mt/W WW MtMt WW

Consensus Profile

WW WW MtMt WW MtMt Mt/W WW MtMt WW

FRL2 Replication1 W/Mt WW MtMt WW MtMt Mt/W WW MtMt WW

Replication2 W/Mt WW MtMt WW MtMt Mt/W WW MtMt WW

Consensus Profile

W/Mt WW MtMt WW MtMt Mt/W WW MtMt WW

FRL3 Replication1 WW WW MtMt WW WW Mt/W WW MtMt Mt/W

Replication2 WW WW MtMt WW WW Mt/W WW MtMt WW

Consensus Profile

WW WW MtMt WW WW Mt/W WW MtMt WW

FRL4 Replication1 WW WW MtMt WW - WW WW MtMt -

Replication2 W/Mt WW MtMt WW MtMt - WW WW WW

Consensus Profile

WW WW MtMt WW - - WW - -

FRL5 Replication1 WW WW MtMt MtMt WW MtMt WW MtMt WW

Replication2 WW WW MtMt Mt/W WW MtMt WW MtMt WW

Consensus Profile

WW WW MtMt Mt WW MtMt WW MtMt WW

FRL6 Replication1 WW WW MtMt Mt/W MtMt Mt/W WW W/Mt MtMt

Replication2 WW WW MtMt WW MtMt WW WW W/Mt Mt/W

Consensus Profile

WW WW MtMt WW MtMt W WW W/Mt Mt

FRL7 Replication1 WW WW WW Mt/W MtMt MtMt WW MtMt WW

Replication2 WW WW WW Mt/W Mt/W MtMt WW MtMt WW

Consensus Profile

WW WW WW Mt/W Mt MtMt WW MtMt WW

FRL8 Replication1 WW WW MtMt WW Mt/W WW WW MtMt WW

Replication2 WW WW MtMt WW MtMt WW WW MtMt WW

Consensus Profile

WW WW MtMt WW Mt WW WW MtMt WW

FRL9 Replication1 WW WW - MtMt MtMt - WW - -

Replication2 WW WW MtMt Mt/W MtMt Mt/W WW - Mt/W

Consensus Profile

WW WW - Mt MtMt - WW - -

FRL10 Replication1 WW W/Mt WW WW MtMt WW WW WW WW

Replication2 WW W/Mt WW WW MtMt WW WW WW WW

62

Consensus Profile

WW W/Mt WW WW MtMt WW WW WW WW

FRL11 Replication1 W/Mt W/Mt WW MtMt Mt/W Mt/W WW W/Mt WW

Replication2 W/Mt W/Mt WW Mt/W Mt/W Mt/W WW W/Mt WW

Consensus Profile

W/Mt W/Mt WW Mt Mt/W Mt/W WW W/Mt WW

FRL12 Replication1 WW WW Mt/W WW MtMt Mt/W WW MtMt WW

Replication2 WW WW Mt/W WW MtMt Mt/W WW MtMt WW

Consensus Profile

WW WW Mt/W WW MtMt Mt/W WW MtMt WW

FRL13 Replication1 WW MtMt MtMt WW WW WW WW MtMt WW

Replication2 WW MtMt MtMt WW WW WW WW MtMt WW

Consensus Profile

WW MtMt MtMt WW WW WW WW MtMt WW

FRL14 Replication1 WW W/Mt MtMt Mt/W WW - W/Mt MtMt WW

Replication2 WW W/Mt MtMt WW WW WW W/Mt MtMt WW

Consensus Profile

WW W/Mt MtMt W WW - W/Mt MtMt WW

FRL15 Replication1 WW WW MtMt MtMt - WW Mt/W - Mt/W

Replication2 WW WW Mt/W Mt/W MtMt - Mt/W - WW

Consensus Profile

WW WW Mt Mt - - Mt/W - WW

FRL16 Replication1 WW - - Mt/W - MtMt WW - -

Replication2 WW MtMt Mt/W WW MtMt WW - WW

Consensus Profile

WW - - Mt/W - MtMt WW - -

FRL17 Replication1 WW WW MtMt WW MtMt MtMt WW WW WW

Replication2 WW WW MtMt WW MtMt MtMt WW WW WW

Consensus Profile

WW WW MtMt WW MtMt MtMt WW WW WW

FRL18 Replication1 - WW - WW Mt/W Mt/W - W/Mt WW

Replication2 Mt WW - WW - Mt/W Mt/W Mt -

Consensus Profile

- WW - WW - Mt/W - Mt -

FRL19 Replication1 WW W/Mt WW WW - MtMt - - -

Replication2 WW W/ Mt WW MtMt MtMt WW - WW

Consensus Profile

WW W/ Mt - WW - MtMt - - -

FRL20 Replication1 WW WW Mt WW - WW WW - WW

Replication2 WW WW W/ Mt

WW Mt WW Mt WW

Consensus Profile

WW WW Mt WW - - WW - WW

FRL21 Replication1 WW WW Mt/W WW MtMt WW WW MtMt Mt/W

Replication2 WW WW Mt/W WW MtMt WW WW MtMt Mt/W

63

Consensus Profile

WW WW Mt/W WW MtMt WW WW MtMt Mt/W

FRL22 Replication1 WW WW MtMt WW - Mt WW - WW

Replication2 WW WW MtMt WW Mt - WW MtMt WW

Consensus Profile

WW WW MtMt WW - - - - WW

FRL23 Replication1 WW WW MtMt WW - - WW - WW

Replication2 WW - MtMt - - WW WW W/Mt WW

Consensus Profile

WW - MtMt - - - WW - WW

FRL24 Replication1 MtMt W/Mt MtMt Mt/W MtMt Mt/W Mt/W WW WW

Replication2 MtMt W/Mt MtMt Mt/W MtMt Mt/W MtMt WW WW

Consensus Profile

MtMt W/ Mt MtMt Mt/W MtMt Mt/W Mt WW WW

4.5 Comparative study of STR loci using modified protocols of Identifiler and MiniFiler

STR kits

AmpFlSTR® Identifiler STR kit simultaneously amplifies 15 autosomal STR loci

(D8S1179, D21S11, D7820, CSF1PO, D3S1358, THO1, D13S317, D16S539, D2S1338,

D19S433, vWA, TPOX, D18S51, D5S818, FGA) and a sex typing amelogenin marker, while the

AmpFlSTR® MiniFilerTM

PCR amplification kit (ABI) simultaneously amplifies eight mini-STR

loci D13S317, D7S820, D2S1338, D21S11, D16S539, D18S51, CSF1PO, FGA and the sex

typing amelogenin loci, shared with the AmpFlSTR® Identifiler STR kit, but with shorter

amplicons, making it highly successful on degraded DNA. In this study 24 highly degraded old

bone samples were evaluated with both Identifiler and MiniFilerTM

STR kits. Nine STR loci are

common in both AmpFlSTR ® IdentiFiler and AmpFlSTR® MiniFilerTM

STR kits, therefore

concordance and non-concordance was determined on the basis of these common STR loci. Full

concordance between AmpFlSTR® MiniFiler and AmpFlSTR® Identifiler successfully

genotyped STR loci was perceived in 97.10 % (134/138) of the compared STR loci, while

discordant STR loci were 2.90 % (4/138) of the total STR loci due to either or both of allele

64

drop-out or drop-in (Table 4.5). Figure 4.9 and Figure 4.10 represent the allelic ladders for

AmpFlSTR ® Identifiler and AmpFlSTR® MiniFilerTM

STR kits. Comparison of figure 4.11 &

4.12 highlights the ability of MiniFiler™ STR kit to recover locus/allele drop-out which were

not obtained with Identifiler™ kit from same bone sample (Zar et al., 2014).

Table 4. 5 Concordance and non-concordance of STR Loci Using AmpFlSTR® Identifiler

& AmpFlSTR® MiniFiler STR Kits

Sample

ID

Name of

Kits

Loci D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 1 IdentiFiler 8, 9 8 X 18 29, 32.2

12, 13 13, 21

10, 12 20, 24

MiniFiler 8,9 8 X 18 29, 32.2

12, 13 13, 21 10, 12 20, 24

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 2 IdentiFiler 11, 12 11 X, Y 20 28 9, 11 16 12 21

MiniFiler 11, 12 11 X, Y 20 26.2 9, 11 16 12 21

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 3 IdentiFiler 11 11 X 19, 20 33.2 11, 12 16 10, 12, 21

MiniFiler 11 11 X, Y 19, 20 33.2 11, 12 15, 16 10, 12 21

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 4 IdentiFiler - - X - 30 11 - - 23

MiniFiler 11 10, 11 X - 30 11 14, 15 10 18.2, 23

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 5 IdentiFiler 8, 12 12 X, Y 20, 24 26, 30 11, 13 15, 17 10, 11 22, 24

MiniFiler 8, 12 12 X, Y 20, 24 26, 30 11, 13 15, 17 10, 11 22, 24

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 6 IdentiFiler 8, 12 11 X 20, 23 30.2, 31.2

11, 12 13, 17 10, 13 19, 21

MiniFiler 8, 12 11 X 20, 23 30.2, 31.2

11, 12 13, 17 10, 13 19, 21

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 7 IdentiFiler 8 8, 11 X, Y 23, 25 30, 32.2

11

17 12 21, 22

MiniFiler 8 8, 11 X, Y 23, 25 30, 11 17, 19 12 21, 22

65

32.2

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 8 IdentiFiler 8, 11 10 X, Y

18, 22 30, 31.2

8, 11 17, 19 11, 12 20, 24

MiniFiler 8, 11 10 X, Y 18, 22 30, 31.2

8, 11 17, 19 11, 12 20, 24

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 9 IdentiFiler - X - - - 15 - -

MiniFiler 13 - X - - 11 15 10, 11 -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 10 IdentiFiler 12, 13 8, 13 X, Y 23, 24 28, 30 13 13, 14 12 20, 25

MiniFiler 12, 13 8, 13 X, Y 23, 24 28, 30 13 13, 14 12 20, 25

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 11 IdentiFiler 11, 13 8, 11 X, Y 20, 22 28, 30 12 14, 17 10, 11 23, 26

MiniFiler 11, 13 8, 11 X, Y 20, 22 28, 30 12 14, 17 10, 11 26

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 12 IdentiFiler 8 12

X, Y

19, 24 28, 33.2

10, 12 13, 15 10, 11

19, 23

MiniFiler 8 11, 12 X, Y 19, 24 28, 33.2

10, 12 13, 15 10, 11 19, 23

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 13 IdentiFiler 8, 10 10, 12 X 18, 20 30, 30.2

10, 11 14, 15 12, 13

19, 24

MiniFiler 8, 10 10, 12 X 18, 20 30, 30.2

10, 11 14, 15 12, 13 19, 24

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 14 IdentiFiler 11 11 X, Y - - - - - -

MiniFiler 11 11 X, Y - - - - 12 -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 15 IdentiFiler - - X,Y - - - - - 21

MiniFiler - - X, Y - - - 16, 17 10 24

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 16 IdentiFiler - - - - - - - - -

MiniFiler - - - - - - - - -

66

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 17 IdentiFiler 11 - X, Y - 28 - 16 11 21

MiniFiler 11 - X, Y - 28 - 16 11 21

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 18 IdentiFiler - - Y 20 - - - - -

MiniFiler - - Y 20 - - - - -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 19 IdentiFiler - - - - - - - - -

MiniFiler - - - - - - - - -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 20 IdentiFiler - - - - - - - -

MiniFiler - - X, Y 20 - - - - -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 21 IdentiFiler 12 12 X, Y 22 28, 32.2

- 14 11 21

MiniFiler 12 11, 12 X, Y 22 28, 32.2

9, 12 12, 14 10, 11 21, 22

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 22 IdentiFiler 12 - X - - 9 - 11 24

MiniFiler 12 - X - - 11 16 11 23

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 23 IdentiFiler -

-

- - - -

-

-

-

MiniFiler - - - - - - - - -

D13S317 D7S820 AMEL D2S1338 D21S11 D16S539 D18S51 CSF1PO FGA

FRL 24 IdentiFiler 8 8 X

-

29, 31

-

-

13

22

MiniFiler 8, 11 8 X 25 29, 31 10, 12 12, 14 12, 13 22

67

Figure 4. 9 Allelic ladder of AmpFlSTR ® Identifiler TM STR kit

68

Figure 4. 10 Allelic ladder of AmpFlSTR® MiniFiler

TM STR kit

69

Figure 4. 11 Partial DNA profile obtained with AmpFlSTR® Identifiler™ STR kit from bone sample (FRL

21)

70

Figure 4. 12 Full DNA profile obtained with AmpFlSTR® MiniFiler™ STR kit from bone sample (FRL 21)

71

4.6 Comparison of DNA profiles obtained with AmpFlSTR® Identifiler, AmpFlSTR®

MiniFiler and In-house SNaPshot SBE Multiplex Kits from old Skeletal Remains

In present study, twenty four old skeletal remains containing low template and degraded

DNA were analyzed with modified protocols of AmpFlSTR® Identifiler™, AmpFlSTR®

MiniFiler™ and in-house SNaPshot SBE multiplex kits for DNA typing. Among them, 9 full

DNA profiles, 11 partial profiles and 4 no profiles were produced with Identifiler STR kit, 13

full DNA profiles, 8 partial and 3 no profiles with MiniFiler kit and 14 full DNA profiles, 10

partial DNA profiles and zero no profiles were produced with in-house SNaPshot SBE multiplex

system from low template DNA samples among the 24 tested as shown in figure 4.13.

Figure 4. 13 Comparison of DNA profiles obtained with AmpFlSTR® Identifiler, AmpFlSTR® Minifiler and

in-house SNaPshot SBE Multiplex Kits

Full, partial and no profiles were made on the basis of the number of loci successfully

genotyped with the AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ and in-house

SNaPshot SBE multiplex kits as shown in table 4.6. Comparison of DNA profiles obtained with

72

AmpFlSTR® Identifiler™, AmpFlSTR® MiniFiler™ and in-house SNaPshot SBE multiplex kits

from old skeletal remains (degraded DNA samples) revealed that more significant DNA profiles

were obtained with MiniFiler and in-house SNaPshot SBE multiplex kits as compared to

Identifiler™ STR kit.

73

Table 4. 6 DNA profiles and number of loci successfully genotyped with the AmpFlSTR® Identifiler® and AmpFlSTR®

MiniFiler™ and in-house SNaPshot SBE multiplex Kits from old skeletal remains

Sample ID Identifiler STR

Loci

Minifiler STR

Loci

SnaPshot

SNP Loci

Sample ID Identifiler

STR Loci

Minifiler

STR Loci

SnaPshot

SNP Loci

FRL (1) 16/16 9/9

9/9

FRL (13) 16/16 9/9

9/9

FRL (2) 13/16 9/9

9/9

FRL (14) 6/16 4/9

8/9

FRL (3) 15/16 9/9

9/9

FRL (15) 3/16 4/9

6/9

FRL (4) 6/16 8/9

5/9

FRL (16) 0/16 0/9

4/9

FRL (5) 16/16 9/9

9/9

FRL (17) 11/16 6/9

9/9

FRL (6) 16/16 9/9

9/9

FRL (18) 3/16 2/9

4/9

FRL (7) 16/16 9/9

9/9

FRL (19) 0/16 0/9

4/9

FRL (8) 16/16 9/9

9/9

FRL (20) 0/16 2/9

6/9

FRL (9) 5/16 5/9

5/9

FRL (21) 15/16 9/9

9/9

FRL (10) 16/16 9/9

9/9

FRL (22) 8/16 6/9

5/9

FRL (11) 16/16 9/9

9/9

FRL (23) 0/16 0/9

4/9

FRL (12) 16/16 9/9

9/9

FRL (24) 11/16 9/9

9/9 Identifiler Kit: Full DNA Profile (16/16 STR Loci), Partial DNA Profile (<16/16 STR Loci), No Profile (0/16 STR Loci).

Minifiler Kit: Full DNA Profile (9/9 STR Loci), Partial DNA Profile (<9/9 STR Loci), No Profile (0/9 STR Loci).

SnaPshot multiplex Kit: Full DNA Profile (9/9 SNP Loci), Partial DNA Profile (<9/9 SNP Loci), No Profile (0/9 SNP Loci).

74

4.7 Genetic and Phenotypic Association of old skeletal remains with Other Populations

In this study, we have selected 9 SNPs that are associated with skin, eye and hair color

and analyzed their frequencies in old skeletal remains collected from old mass graves of

Pakistan. Among them, five SNPs rs7495174 (OCA2), rs4778241 (OCA2), rs4778138 (OCA2),

rs1545397 (OCA2), rs12913832 (HERC2) are used for the eye color detection of an individual,

two SNPs rs885479 (MC1R), rs2031526 (DCT) detect the skin color, one SNP rs26722

(SLC45A2) is used for prediction of both skin and hair coloration and one SNP rs1800414

(OCA2) is used for both eye and skin coloration. All SNPs are bi-allelic. The two alleles of each

SNP were represented by ‘W’ (wild type) and ‘Mt’ (mutant type) alleles. Allelic frequencies of

both wild type (W) and mutant type (Mt) alleles were determined as show in figure 4.14. Allele

frequencies and other parameters for these SNPs are given in Table 4.8. All SNPs were

polymorphic across old skeletal remains. Seven SNPs [rs885479 (MC1R), rs26722 (SLC45A2),

rs2031526 (DCT), rs7495174 (OCA2), rs4778241 (OCA2), rs4778138 (OCA2), rs1545397

(OCA2)] in total nine were under Hardy-Weinberg Equilibrium (p > 0.001) and only two

[rs1800414 (OCA2), rs12913832 (HERC2)] were not under Hardy Weinberg Equilibrium. The

minor allele frequencies (MAFs) of all SNPs [rs885479 (MC1R), rs26722 (SLC45A2),

rs2031526 (DCT), rs7495174 (OCA2), rs4778241 (OCA2), rs4778138 (OCA2), rs1800414

(OCA2), rs1545397 (OCA2) and rs12913832 (HERC2)] across old skeletal remains were 0.107,

0.178, 0.25, 0.21, 0.25, 0.428, 0.071, 0.285 and 0.071, respectively. The minor allelic

frequencies of each SNP of old skeletal remains were compared with same allelic frequencies of

Pakistani (Pathan) and four other populations (CEU, HCB, JPT, YRI) using HapMap database

(http://www.ncbi.nlm.nih.gov/SNP/) as shown in figure 4.15. The results indicated that the old

skeletal remains analyzed in this study for 9 pigmentation-related SNPs were genetically more

75

closer to Pakistani (Pathan) population than the other populations that prove that all of the

skeletal remains really belonged to Pakistani individuals (Figure 4.15). Comparison of the minor

allelic frequencies of the nine SNPs of old skeletal remains also showed correlation

(concordance and discordance) of these SNPs with other populations as shown in table 4.8. All

full DNA profiles obtained with 9 pigmentation-related SNPs were unique at least at one locus

which confirms the authenticity of the results obtained with in-house SNaPshot SBE Multiplex

kit as shown in table 4.7. Even though the application and importance of these SNPs will be

further verified in future by association study in Pakistani population using large number of

DNA samples, this study might provide potential SNP markers for forensic DNA study of old

skeletal remains.

Figure 4. 14 Frequencies of Wild and Mutant Alleles Using nine pigmentation related SNPs across old

skeletal remains

76

Table 4. 7 DNA profiles of old skeletal remains for nine pigmentation-related SNPs are

unique at least at one locus

Sample

ID MC1R SLC45A2 DCT OCA174 OCA241 OCA138 OCA414 OCA397 HERC2

FRL1 WW WW MtMt WW MtMt Mt/W WW MtMt WW

FRL2 W/Mt WW MtMt WW MtMt Mt/W WW MtMt WW

FRL3 WW WW MtMt WW WW Mt/W WW MtMt WW

FRL5 WW WW MtMt Mt WW MtMt WW MtMt WW

FRL6 WW WW MtMt WW MtMt WW WW W/Mt MtMt

FRL7 WW WW WW Mt/W MtMt MtMt WW MtMt WW

FRL8 WW WW MtMt WW MtMt WW WW MtMt WW

FRL10 WW W/Mt WW WW MtMt WW WW WW WW

FRL11 W/Mt W/Mt WW Mt Mt/W Mt/W WW W/Mt WW

FRL12 WW WW Mt/W WW MtMt Mt/W WW MtMt WW

FRL13 WW MtMt MtMt WW WW WW WW MtMt WW

FRL17 WW WW MtMt WW MtMt MtMt WW WW WW

FRL21 WW WW Mt/W WW MtMt WW WW MtMt Mt/W

FRL24 MtMt W/ Mt MtMt Mt/W MtMt Mt/W Mt WW WW

77

Table 4. 8 Information about nine pigmentation-related SNPs, Hardy Weinberg Equilibrium, Minor allelic frequencies and

association of old skeletal remains and other populations (Pakistani, CEU, HCB, JPT and YRI)

Information about SNPs Old Skeletal Remains from Pakistan HapMap

Correlation SNP ID

Reported

gene Location

Phenotyp

e

Major

Allele

(A)

Minor

Allele

(B)

MAF HWE

No. of

genotypes

(AA/AB/BB)

Pakistani CEU HCB JPT YRI

rs885479 MC1R 16q24.3 Skin color G A 0.107 5.5 (12/1/1) 0.10 0.100 0.640 0.733 0.009 Major in

HCB & JPT

rs26722 SLC45A2 5p13.3 Hair color

Skin color C T 0.178 1.02 (10/3/1) 0.16 0.004 0.407 0.372

0.049

Minor in all

rs2031526 DCT 13q32 Skin color A G 0.25 9.17 (10/1/3) 0.30 0.858

0.200 0.125 0.933 Major in

CEU & YRI

rs7495174

OCA2

15q11.2-

15q12

Eye color G A 0.21 4.64 (10/2/2) 0.25 0.951 0.349 0.320 0.841 Major in

CEU & YRI

rs4778241 Eye color C A 0.25 9.17 (10/1/3) 0.30 0.159 0.791 0.820 0.580

Major in

HCB, JPT &

YRI

rs4778138 Eye color G A 0.428 0.22 (5/6/3) 0.45 0.894 0.279 0.283 0.270 Major in

CEU only

rs1800414 Eye color

Skin color A G 0.071 14 (13/0/1) 0.05 0.00 0.628

0.552

0.00 Major in

HCB & JPT

rs1545397 Eye color T A 0.285 5.92 (9/2/3) 0.20 0.950 0.089 0.011 1.000 Major in

CEU & YRI

rs12913832 HERC2 15q13 Eye color A G 0.071 14 (13/0/1) 0.06 0.792 0.00 0.00 0.00

Monomorphic

in JPT &

YRI. Major in

CEU

78

Figure 4. 15 Association of minor allele frequencies of nine pigmentation related SNPs of old skeletal remains with same allele of Pakistani (Pathan),

CEU, HCB, JPT and YRI Populations

79

CHAPTER FIVE

80

DISCUSSION

The most fundamental methods upon which DNA typing from old skeletal remains

depends are: DNA extraction, quantification and typing methods. Extraction of DNA from

old skeletal remains, maximization of DNA yield and elimination of PCR inhibitors are

important issues in forensic DNA studies (Barbaro et al., 2008). Sometimes, the history and

condition of DNA samples are unknown in forensic DNA analysis. Therefore, an ideal DNA

extraction method is required to produce highly purified and high quality DNA from old and

degraded DNA samples. The extraction methods mostly concentrated on purifying extracted

DNA with silica columns and decalcifying old bone sample with EDTA for the analysis of

degraded DNA samples (Anderung et al., 2008).

In this study a modified silica column based total demineralization DNA extraction

method has been used for the removal of PCR inhibitors and recovery of clean and pure

DNA from old skeletal remains. It might be due to the fact that complete demineralization

followed by silica binding is highly successful for the extraction and recovery of DNA

profiles from degraded old skeletal remains (Huel et al., 2012). Quantification was carried

out by Real Time PCR with Quantifiler™ Human DUO DNA Quantification kit (Applied

Biosystems) and the ABI Prism® 7500 Sequence Detection System (SDS). Real-time PCR

quantification showed that the DNA was detected in 17 samples in total 24 old skeletal

remains. Majority of the degraded old samples produced <10 pg/µl DNA from 0.5 g of bone

powder. In 7 samples, DNA was in the range of 1-10 pg/µL, in 4 samples it was in the range

of 22-69 pg/µL and in 6 samples the DNA was in the range of >100 pg/µL (figure 4.1). In 7

samples DNA was not detected, probably due to the fact that the samples were very old and

highly degraded. Sometime quantification results of degraded DNA samples may be

81

unreliable, because samples having low or nil quantity of DNA may give full or partial DNA

profiles and significant quantification results may give partial or nil DNA profiles (Buckleton

2009). The internal PCR control (IPC) assay showed that PCR inhibitors were successfully

removed from all of the extracted DNAs during qPCR, showing CT values of <30 (table 4.1).

It might be due to the reason that using a highly effective silica-based total demineralization

DNA extraction method improved DNA quantification and removal of PCR inhibitors (Lee

et al., 2010). Similar kinds of findings have been reported by Huel et al. (2012). In contrast,

Rucinski et al. (2012) have described that silica-based extraction method does not improve

the quality and quantity of DNA for DNA typing of human skeletal remains as compared to

standard organic extraction method while Cattaneo et al. (1995) reported that standard

organic extraction (phenol/chloroform extraction) method is not always satisfactory for the

extraction of DNA from old skeletal remains.

During this study, the extracted DNA was low template and highly degraded,

therefore PCR conditions were optimized and the sensitivity of PCR amplification was

increased by extending the number of PCR cycles. For AmpFlSTR® Identifiler® PCR

amplification kit, PCR cycles were extended from standard 28 to 33 to get more informative

DNA profiles from human old skeletal remains. During validation studies, it was observed

that the amplification of degraded DNA with AmpFlSTR® Identifiler® PCR kit offered

promising results by increasing the number of PCR cycles from standard 28 to 33 in PCR

reaction as shown in figure 4.2 and figure 4.3. It might be due to the fact that increase in the

sensitivity of PCR amplification permits DNA profiles to be more informative from old and

highly degraded DNA samples (Puch-Solis et al., 2013). The success rate of these samples

was not further improved by additional number of PCR cycles, therefore, 33 number of PCR

82

cycles was considered optimal for these samples. In contrast to the present findings,

Sundquist and Bessetti (2005) reported that 32 number of PCR cycles allows extraction and

amplification of DNA from minute/degraded DNA samples and produce useful DNA

profiles. Dixon et al. (2004) reported that allele recovery for larger STR loci could be

enhanced by increasing the number of PCR cycles from standard 28 cycles to 30-36 cycles.

Gill et al. (2000) and Romanini et al. (2011) described that sensitivity of PCR amplification

is improved by raising the number of PCR cycles from standard 28 to 34 for typing old

skeletal remains (<100 pg/µl DNA) using AmpFlSTR® Identifiler® PCR amplification kit.

For AmpFlSTR® MiniFilerTM

STR kit and SNaPshot multiplex kit, PCR cycles were

increased from standard 30 to 33 and standard 33 to 38, respectively. It might be due to the

fact that low template DNA can successfully be amplified with raising the PCR cycling

conditions (Romanini et al., 2011). Decorte et al. (2008) reported that using mini-STR

multiplex assay produced reproducible DNA profiles from < 30 pg/µL DNA when number of

PCR cycles was enhanced from standard 30 to 34. Bouakaze et al. (2009) increased the

number of PCR cycles from standard 33 to 37 for autosomal SNP analysis of ancient skeletal

remains. The authenticity of the DNA profiles of bone samples was confirmed by running

negative controls along-with these sample using the Identifiler, MiniFiler and in-house

SNaPshot SBE multiplex kits. No allele or locus drop-in occurred in negative controls

produced with AmpFlSTR® Identifiler™, AmpFlSTR® MiniFiler™ and in-house SNaPshot

SBE multiplex kits as shown in figure 4.4, 4.5 and 4.6, respectively.

Previous studies have shown that environmental factors such as humidity,

temperature, soil pH, UV irradiation, passage of time and microorganisms cause the

degradation of DNA molecule in bone tissues (Zink et al., 2002). Therefore it is difficult to

83

predict DNA quality and profiling from age and appearance of bone samples only. In this

study the radius of 500 years old, found on the surface of soil and dry mountain area,

produced a partial DNA profile of 8 STR loci plus amelogenin with Identifiler STR kit, while

a radius of 200 years old, found in buried and wet area, produced a partial DNA profile of 2

STR loci plus amelogenin as shown in figure 4.7 and figure 4.8, respectively. It might be due

to the fact that the DNA of bone sample, buried and exposed to harsh environmental

conditions such as heat, humidity and microorganisms, was adversely affected by these

factors (Bender et al., 2004, Vural and Tirpan, 2009). Butler (2005) and Willerslev and

Cooper (2005) reported that humidity and hydrolytic damage accelerate the fragmentation of

DNA molecule. Hummel and Herrmann (1994) suggested that microorganisms such as fungi

and bacteria are the main sources of contamination in buried bone samples that invade on the

bone tissues, compete for PCR primers during PCR amplification, and give rise to the lack of

successful PCR amplification.

The interpretations of DNA profiles become very difficult when analyzing old

skeletal remains with low template (≤100-200 pg/µL) or highly degraded DNA

(Gill et al., 2000). In fact, by simply extending the number of PCR cycles, the

quantity of amplified product increases, but the stochastic effects (allele drop-in, drop-out,

high stutter, peak height imbalance etc.) in the resulting DNA profiles increase as well

(Benschop et al., 2011). According to DNA interpretation rules, consensus approach

was used for producing more reliable and reproducible DNA profiles (Caragine et

al., 2009). For each of the degraded old skeletal sample, two replicates were produced

independently. Consensus DNA profiles were created with an allele observed in common

from both replicate reactions of each sample as shown in tables 4.2, 4.3 and 4.4. Similar

84

approach has been used by Cowen et al. (2011) for low template DNA samples. Moreover, in

order to exclude chances of any possibility of internal contamination, DNA profiles of all

members of the laboratory staff were produced with AmpFlSTR® Identifiler®, AmpFlSTR®

MiniFilerTM

and in-house SNaPshot SBE multiplex kits. No match was found for any of the

samples analyzed with same kits.

Concordance and non-concordance estimations are important to determine

allelic/locus dropout or drop-in or null alleles in a data obtained from AmpFlSTR®

Identifiler® and AmpFlSTR® MiniFilerTM

STR kits (Hill et al., 2010). After evaluation of

old skeletal remains with AmpFlSTR® Identifiler® PCR Amplification Kit, the attention

was focused on AmpFlSTR® MiniFilerTM

STR kits (small amplicon size) to improve the

success rate of DNA profiling for these samples encountered with AmpFlSTR® Identifiler®

PCR Amplification Kit, because the problem linked with degraded DNA samples is the

fragmentation of DNA template, and primers with smaller amplicon size increase the

probability of gaining a good DNA profile from shorter DNA fragments. AmpFlSTR®

Identifiler STR kit simultaneously amplifies 15 autosomal STR loci (D8S1179, D21S11,

D7820, CSF1PO, D3S1358, THO1, D13S317, D16S539, D2S1338, D19S433, vWA, TPOX,

D18S51, D5S818, FGA) and a sex determining amelogenin marker, while the AmpFlSTR®

MiniFilerTM

PCR amplification kit (ABI) simultaneously amplifies eight mini-STR loci

D13S317, D7S820, D2S1338, D21S11, D16S539, D18S51, CSF1PO, FGA and the sex

determining amelogenin loci, shared with the AmpFlSTR® Identifiler STR kit, but with

shorter amplicons, making it highly successful on degraded DNA. The most significant

challenge to interpretation in DNA profiling of highly degraded DNA samples arises when

85

either or both of allele drop-in and drop-out create discordances (Balding and Buckleton,

2009).

In this study 24 highly degraded old bone samples were evaluated with both

Identifiler and MiniFilerTM

STR kits. Nine STR loci are common in both AmpFlSTR ®

Identifiler and AmpFlSTR® MiniFilerTM

STR kits, therefore concordance and non-

concordance was determined on the basis of these common STR loci. Full concordance

between AmpFlSTR® MiniFiler and AmpFlSTR® Identifiler successfully genotyped STR

loci was perceived in 97.10 % (134/138) of the compared STR loci, while discordant STR

loci were 2.90 % (4/138) of the total STR loci due to either or both of allele drop-out or drop-

in (Table 4.5 ). Similar kinds of findings (99.7% and 99.88% concordance), have been

reported by Hill et al. (2007) and Alenizi et al. (2009), respectively, for typing fresh blood

samples using AmpFlSTR® MiniFiler and AmpFlSTR® Identifiler STR kits, while in the

present study old skeletal remains have been used. Oh et al. (2012) have investigated eight

human femurs (200-400 years old) for comparative analysis of STRs and mini-STRs loci,

while in the present study 24 different kinds of old skeletal remains have been used. Figure

4.9 and Figure 4.10 represent the allelic ladders for AmpFlSTR ® Identifiler and

AmpFlSTR® MiniFilerTM

STR kits. Comparison of figure 4.11 & 4.12 highlights the ability

of MiniFiler™ STR kit to recover more informative DNA profiles than Identifiler™ STR kit

from same bone sample. Similar kinds of findings have been reported by Mulero et al.

(2008).

Forensic DNA analysts are facing problems during the analysis of degraded DNA

samples. A variety of methods have been developed to avoid difficulty in obtaining valuable

86

DNA information from degraded DNA samples. These methods include STRs, mini-STRs

and single nucleotide polymorphism (SNP) analysis (Pang and Cheung 2007). In the present

study, twenty four old skeletal remains containing low template DNA were analyzed with

modified protocols of AmpFlSTR® Identifiler™, AmpFlSTR® MiniFiler™ and SNaPshot

multiplex kits for DNA typing. Among them, 9 full DNA profiles, 11 partial DNA profiles

and 4 no profiles were produced with Identifiler kit, 13 full DNA profiles, 8 partial and 3 no

profiles with MiniFiler kit and 14 full DNA profiles, 10 partial DNA profiles and zero no

profiles were produced with in-house-SNaPshot SBE multiplex system from low template

DNA samples among the 24 tested as shown in figure 4.13. Full DNA profiles may be

probably produced due to increasing number of PCR cycles, optimizing PCR conditions and

absence of PCR inhibitors, while partial and nil DNA profiles were produced probably due to

low and nil quantity of DNA and highly fragmentation of DNA template. Full, partial and no

profiles were made on the basis of the number of loci successfully genotyped with the

AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ and in-house SNaPshot SBE

multiplex kits as shown in table 4.6. Comparison of DNA profiles obtained with

AmpFlSTR® MiniFiler™, AmpFlSTR® Identifiler™ and SNaPshot multiplex kits from old

skeletal remains (degraded DNA samples) revealed more complete profiles with MiniFiler

and SNaPshot multiplex kits as compared to Identifiler™ STR kit. Similar kinds of findings

have been reported by Westen and Sijen (2009) that in case of highly degraded DNA

samples, most of the conventional STRs fail to amplify, while mini-STRs and SNPs provide

useful information. It might be due to the fact that the primers of the mini- STR and SNP loci

as compared to conventional STR loci yield smaller amplicons (Oh et al., 2012). Wiegand

and Kleiber (2001) described that use of mini-STRs in amplification of degraded DNA

87

samples produce more valuable DNA profiles as compared to conventional STR loci. Senge

et al. (2011) reported that mini-STRs are better than standard STRs for typing DNA samples

with minute amounts of degraded DNA. Asari et al. (2009) reported that autosomal SNPs are

preferred over conventional STRs for typing degraded DNA samples because they require

small fragments of DNA than STRs. Budowle et al. (2009) stated that the amplicons size for

SNPs may be shorter than those for conventional STRs and mini-STRs. Thus, amplification

may be more vigorous for SNPs and stochastic affects may be less than for larger amplicons

of STRs and mini-STRs. Our results also showed that in-house SNaPshot SBE multiplex

system is more sensitive than conventional STR kits, succeeding in all presented cases to

yield a profile with less than 10 pg/µL of DNA.

Most of haplotypes are common in all human beings; however, their frequencies may

vary among different populations. In humans, there is a wide range of eye, skin and hair

pigmentation, within same as well as different populations (Mukherjee et al., 2013).

Therefore, analysis of SNPs from various populations is necessary for detection of

pigmentation related SNPs.

In this study, we have selected 9 SNPs that are associated with skin, eye and hair

color and analyzed their frequencies in old skeletal remains collected from old mass graves

of Pakistan. Among them, five SNPs rs7495174 (OCA2), rs4778241 (OCA2), rs4778138

(OCA2), rs1545397 (OCA2), rs12913832 (HERC2) are used for the eye color detection of an

individual, two SNPs rs885479 (MC1R), rs2031526 (DCT) detect the skin color, one SNP

rs26722 (SLC45A2) is used for prediction of both skin and hair coloration and one SNP

rs1800414 (OCA2) is used for both eye and skin coloration. All SNPs are bi-allelic. The two

alleles of each SNP were represented by ‘W’ (wild type) and ‘Mt’ (mutant type) alleles.

88

Allelic frequencies of both wild type (W) and mutant type (Mt) alleles were determined as

show in figure 4.14. Allele frequencies and other parameters for these SNPs are given in

Table 4.8. All SNPs were polymorphic across old skeletal remains. Seven SNPs [rs885479

(MC1R), rs26722 (SLC45A2), rs2031526 (DCT), rs7495174 (OCA2), rs4778241 (OCA2),

rs4778138 (OCA2), rs1545397 (OCA2)] in total nine were under Hardy-Weinberg

Equilibrium (p > 0.001) and only two [rs1800414 (OCA2), rs12913832 (HERC2)] were not

under Hardy Weinberg Equilibrium. When the allele frequencies are not under Hardy-

Weinberg Equilibrium (p > 0.001), the population may be under environmental forces that

cause some alleles to deviate from HWE. The main reasons of deviation from HWE may be

selection, inbreeding and population sub-structure (Butler, 2005). Deviation from Hardy-

Weinberg equation indicates that the HWE cannot exactly determine allele/genotype

frequencies for the population of interest. Therefore, when there is highly significant

deviation from Hardy-Weinberg equation (HWE), the allele frequency database should not

be used to calculate the frequency of a genetic profile in a population (Kobilinsky et al.,

2005).

The minor allele frequencies (MAFs) of all SNPs [rs885479 (MC1R), rs26722 (SLC45A2),

rs2031526 (DCT), rs7495174 (OCA2), rs4778241 (OCA2), rs4778138 (OCA2), rs1800414

(OCA2), rs1545397 (OCA2) and rs12913832 (HERC2)] across old skeletal remains were

0.107, 0.178, 0.25, 0.21, 0.25, 0.428, 0.071, 0.285 and 0.071, respectively. The minor allelic

frequencies of each SNP of old skeletal remains were compared with same allele of Pakistani

(Pathan) and four other populations (CEU, HCB, JPT, YRI) using HapMap database

(http://www.ncbi.nlm.nih.gov/SNP/) as shown in figure 4.15. The International HapMap

Project has been developed in 2002. The ambition of this project was to find out the common

89

patterns of DNA sequence variation in the human genome (The International HapMap

Consortium 2003). This project was based on 270 individuals from four different sources:

JPT (Japanese in Tokyo, Japan), CHB (Han Chinese in Beijing, China), YRI (Yoruba in

Ibadan, Nigeria) and CEU (CEPH Utah residents with ancestry from northern and western

Europe). Our results indicated that the old skeletal remains analyzed in this study for 9

pigmentation-related SNPs were genetically more closer to Pakistani (Pathan) population

than the other populations that proves that all of the old skeletal remains really belonged to

Pakistani individuals (Figure 4.15). Comparison of the minor allelic frequencies of the nine

SNPs of old skeletal remains also showed correlation (concordance and discordance) of these

SNPs with other populations as shown in table 4.8. The purpose of this study was to find out

the far and close association of these old skeletal remains with other populations. Similar

kind of study has been reported by Lim and Oh (2013). All full DNA profiles obtained with 9

pigmentation-related SNPs were unique at least at one locus which confirms the authenticity

of the results obtained with in-house SNaPshot SBE Multiplex kit as shown in table 4.7.

Even though the application and importance of these SNPs will be further verified in

future by association study in Pakistani population using large number of DNA samples, this

study might provide potential SNP markers for forensic DNA study of old skeletal remains.

In addition, this study presents a newly developed assay for known polymorphic sequences

related to physical traits of forensic interest. The study is one of the trending ones in current

forensic research and the assays arrangement has been carefully designed and thoroughly

tried with highly challenging DNA, succeeding in all presented cases to yield a DNA profile.

90

CONCLUSION

DNA samples collected from crime scene are often inadequate, degraded and

contaminated with PCR inhibitors, leading to poor DNA amplification and prohibiting the

production of successful DNA profiles. Therefore it is important in DNA typing, to ensure

that degraded and inadequate amount of DNA found in forensic DNA samples, can be used

in an effective and efficient way to produce reliable and more informative DNA profiles. In

this study, we have improved DNA typing of old skeletal remains using different forensic

approaches. We have proved that modified silica based total demineralization extraction

method successfully extract DNA from old bone samples and remove PCR inhibitors, as a

result, improves DNA profiling of degraded old skeletal remains. In addition improvement in

DNA typing of old skeletal remains was carried out with modified protocols of PCR

conditions, extended PCR cycles and consensus approaches using Identifiler®, MiniFiler™

and in-house SNaPshot SBE multiplex kits. Promising results were obtained from this study

and it was concluded that DNA profiles can be obtained from minute quantity of DNA (even

form ≤10 pg/µL) in a reliable manner.

This study also highlights a comparative study of STR loci with modified protocols of

AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ STR Kits for typing old skeletal

remains collected from 100-1000 years old mass graves of Pakistan. Comparison showed that

AmpFlSTR® MiniFiler™ kit promoted the recovery of locus/alleles that failed to type with

the AmpFlSTR® Identifiler™ kit. Further this study concentrate on the production of

valuable DNA profiles from old skeletal remains using a newly developed in-house

SNaPshot SBE multiplex system with extended PCR cycles and modified reaction mixture

and highlight the importance of 9 pigmentation-related SNPs across old skeletal remains and

their correlation with other populations. Finally comparison of DNA profiles obtained with

91

AmpFlSTR® Identifiler™, AmpFlSTR® MiniFiler™ and in-house SNaPshot multiplex kits

from old skeletal remains revealed that significant DNA profiles were obtained with

MiniFiler and in-house SnaPshot kits as compared to Identifiler™ kit during the analysis of

degraded DNA samples. In addition the aim of this study was to introduce an in-house

SNaPshot SBE multiplex system for forensic DNA study of old skeletal remains and

highlight the importance of this multiplex system for the identification of individuals at DNA

level. The results proved that in-house SNaPshot SBE multiplex system was more sensitive

than conventional STR kits, succeeding in all presented cases to yield a DNA profile from

old skeletal remains.

Considering these points in the present study, it is recommendable for forensic DNA

experts to strongly consider modified protocols of Identifiler, MiniFiler and newly developed

in-house SNaPshot SBE multiplex systems for typing degraded and old skeletal remains. The

presented assays would be a very interesting asset in forensic casework.

92

CHAPTER SIX

93

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LIST OF PUBLICATIONS

Research Papers Published On My Thesis Work

Mian Sahib Zar*, Ahmad Ali Shahid, Muhammad Saqib Shahzad, Kyoung-Jin

Shin, Hwan Young Lee, Muhammad Israr, Tayyab Husnain (2014). Comparative

study of STR loci for typing old skeletal remains with modified protocols of

AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ STR Kits. Australian

Journal of Forensic Sciences. DOI:10.1080/00450618.2014.925976.

Mian Sahib Zar*, Ahmad Ali Shahid, Muhammad Saqib Shahzad, , Kyoung-Jin

Shin, Hwan Young Lee, Muhammad Israr, Eun Hye Kim, Zia-ur-Rahman,

Tayyab Husnain (2013). Forensic DNA Typing of Old Skeletal Remains Using

AmpFlSTR®Identifiler® PCR Amplification Kit. Journal of Forensic Research.

5 (1): 211-216.

Mian Sahib Zar*, Ahmad Ali Shahid, Muhammad Saqib Shahzad, Kyoung- Jin

Shin, Hwan Young Lee, Sang-Seob Lee, Muhammad Israr, Eun Young Lee,

Galina Kulstein, Peter Wiegand, Tayyab Husnain (2014). DNA Typing and

Phenotyping of old skeletal remains using in-house SNaPshot SBE Multiplex

system. (Submitted).

OTHER PUBLICATIONS:

Mian Sahib Zar*, Ahmad Ali Shahid and Muhammad Saqib Shahzad (2013). An

Overview of Crimes, Terrorism and DNA Forensics in Pakistan. Journal of

Forensic Research. 4 (4): 201-202.

Muhammad Israr, Ahmad Ali Shahid, Ziaur Rahman, Mian Sahib

Zar, Muhammad Saqib Shahzad, Tayyab Husnain, Celine Pfeifer, Peter Wiegand

115

(2014). Development and characterization of a new 12-plex ChrX miniSTR

system. International Journal of Legal Medicine. 128 (3): 1-4.

Rukhsana Perveen, Ziaur Rahman, Muhammad Saqib Shahzad, Muhammad Israr,

Muhammad Shafique, Muhammad Adnan Shan, Mian Sahib Zar, Muhammad

Iqbal, Tayyab Husnain (2014). Y-STR Haplotype Diversity in Punjabi Population

of Pakistan. Forensic Science International: Genetics. 9: e20–e21.

Niaz M. Achakzai, Z. Rahman, M.S. Shahzad, S. Daud, M.S. Zar, M. Israr, T.

Husnain, Sascha Willuweit, Lutz Roewer. (2012). Y-chromosomal STR analysis

in the Pashtun population of Southern Afghanistan. Forensic Science

International: Genetics. 6(4): e103–e105.

Ilyas M, Shahzad M.S, Israr M, Shafeeq M, Zar M.S, Ali A, Rahman Z and

Husnain T. “Y-chromosomal STR Haplotype Profiling in Yousafzai's living in

Swat Valley Pakistan”. Published in Proceedings of the 22nd

Congress of the

International Academy of Legal Medicine (IALM), pp. 357-363. July 5-8, 2012,

Istanbul, Turkey.