MIAN SAHIB ZAR - prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/2327/1/2930S.pdfahmad ali...
Transcript of MIAN SAHIB ZAR - prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/2327/1/2930S.pdfahmad ali...
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).
21
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.
22
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
REFERENCES
Alaeddini, R., Walsh, S.J., Abbas, A. (2010). Forensic implications of genetic analyses from
degraded DNA—A review. Forensic Sci Int Genet, 4(3): 148-157
Alenizi, M.A., Goodwin, W., Hadi, S., Alenizi, H.H., Altamar, K.A., Alsikel, M.S. (2009).
Concordance between the AmpFlSTR MiniFiler and AmpFlSTR Identifiler PCR
amplification kits in the Kuwaiti population. J Forensic Sci, 54(2): 350-352.
Alonso, A., Andelinovic, S., Martin, P., Sutlovic, D., Erceg, I., Huffine, E., de Simon, L.,
Albarran, C., Definis-Gojanovic, M., Fernandez-Rodriguez, A., Garcia, P., Drmic, I.,
Rezic, B., Kuret, S., Sancho, P., Primorac, D. (2001). DNA typing from skeletal
remains: evaluation of multiplex and megaplex STR systems on DNA isolated from
bone and teeth samples. Croat. Med. J, 42: 260-266.
Alonso, A., Martin, P., Albarran, C., Garcia, P., Primorac, D., Garcia, O., Fernandez de
Simon, L., Garcia-Hirschfeld, J., Sancho, M., Fernandez-Piqueras, J. (2003). Specific
quantification of human genomes from low copy number DNA samples in forensic
and ancient DNA studies. Croat Med J, 44 (3): 273–280.
Anderung, C., Persson, P., Bouwman, A., Elburg, R., Gotherstrom, A. (2008). Fishing for
ancient DNA. Forensic Sci Int Genet, 2 (2): 104-107.
Anderung, C., Persson, P., Bouwman, A., Elburg, R., Gotherstrom, A. (2008). Fishing for
ancient DNA. Forensic Sci Int Genet, 2(2): 104-107.
Applied Biosystems. (2007). AmpFlSTR® MiniFiler™ PCR Amplification Kit User's
manual. Foster City, CA : Applied Biosystems.
94
Applied Biosystems. (2008). Quantifiler® Duo DNA quantification kits User’s Manual, PN
4391294 Rev.B.
Asari, M., Watanabe, S., Matsubara, K., Shiono, H., Shimizu, K. (2009). Single nucleotide
polymorphism genotyping by mini-primer allele-specific amplification with universal
reporter primers for identification of degraded DNA. Anal Biochem, 386 (1): 85-90.
Bacher, J., Schumm, J.W. (1998). Development of highly polymorphic pentanucleotide
tandem repeat loci with low stutter. Profiles in DNA, 2(2): 3-6.
Balding, D.J., Buckleton, J. (2009). Interpreting low template DNA profiles. Forensic Sci Int
Genet, 4(1): 1-10.
Bar, W., Kratzer, A., MAchler, M., Schmid, W. (1988). Post mortem stability of DNA.
Forensic Sci. Int, 39(1): 59-70.
Barbaro, A., Cormaci, P., Barbaro, A. (2008). Validation of DNA typing from skeletal
remains using the Invitrogen Charge Switch® Forensic DNA Purification Kit.
Forensic Sci Int Genet, 1(1): 398-400.
Barbaro, A., Cormaci, P., Falcone, G. (2011). Validation of BTATM
lysis buffer for DNA
extraction from challenged forensic samples. Forensic Sci Int Genet. Suppl. 3: e61-
e62.
Bass, W.M. (1995). Human Osteology: A Laboratory and Field Manual. Columbia: Missouri
Archaeological Society; 4th edition, 361 pages.
Bender, K., Farfan, M.J., Schneider, P.M. (2004). Preparation of degraded human DNA
under controlled conditions. Forensic Sci Int Genet, 139: 135-140.
95
Benschop, C.C.G., van der Beek, C.P., Meiland, H.C., van Gorp, A.G.M., Westen,
A.A., Sijen, T. (2011). Low template STR typing: Effect of replicate number and
consensus method on genotyping reliability and DNA database search results.
Forensic Sci Int Genet, 5(4): 316-328.
Bouakaze, C., Keyser, C., Crubézy, E., Montagnon, D., Ludes, B. (2009). Pigment phenotype
and biogeographical ancestry from ancient skeletal remains: inferences from
multiplexed autosomal SNP analysis. Int J Legal Med, 123(4): 315-325.
Bourke, M.T., Scherczinger, C.A., Ladd, C., Lee, H.C. (1999). Naoh treatment to neutralize
inhibitors of taq polymerase. J Forensic Sci. 44 (5): 1046–1050.
Bright, J.A., McManus, K., Harbison, S., Gill, P., Buckleton., A. (2012). Comparison of
stochastic variation in mixed and unmixed casework and synthetic samples. Forensic
Sci Int Genet, 6(2):180–184.
Buckleton, J. (2009). Validation issues around DNA typing of low level DNA. Forensic Sci
Int Genet, 3(4): 255-260.
Budowle B., Eisenberg A.J., van Daal, A. (2009). Validity of Low Copy Number Typing and
Applications to Forensic Science. Croat Med J. 50(3): 207-217.
Budowle, B. (2000). History and future of DNA typing. Proceedings from the 11th
International Symposium on Human Identification; 8-13; Biloxi, MS.
Burger, J., Hummel, S., Herrman, B., Henke, W. (1999). DNA preservation: A
microsatellite-DNA study on ancient skeletal remains. Electrophoresis, 20(8): 1722-
1728.
96
Burger, J., Hummel, S., Herrmann, B., Henke, W. (1999). DNA preservation: A
microsatellite-DNA study on ancient skeletal remains. Electrophoresis. 20(8): 1722-
1728.
Butler, J.M. (2001). Forensic DNA Typing: Biology and Technology behind STR Markers.
Academic Press, London, 335 pages.
Butler, J.M. (2001). Forensic DNA Typing: Biology and Technology behind STR Markers.
Academic Press, London, 335 pages.
Butler, J.M. (2005). Forensic DNA Typing: Biology, Technology, and Genetics of STR
Markers (2nd
Edition). Elsevier Academic Press, New York, 688 pages.
Butler, J.M. (2010). Fundamentals of Forensic DNA Typing. Elsevier Academic Press, San
Diego, 520 pages.
Butler, J.M. (2012). Advanced Topics in Forensic DNA Typing: Methodology. Elsevier
Academic Press, San Diego, 704 pages.
Butler, J.M. (2012). Advanced Topics in Forensic DNA Typing: Methodology. Elsevier
Academic Press, San Diego, 704 pages.
Butler, J.M., Buel, E., Crivellente, F., McCord, B.R. (2004). Forensic DNA typing by
capillary electrophoresis: using the ABI Prism 310 and 3100 Genetic Analyzers for
STR analysis. Electrophoresis, 25: 1397-1412.
Butler, J.M., Coble, M.D., Vallone P.M. (2007). STRs vs. SNPs: thoughts on the future of
forensic DNA testing. Forensic Sci Med Pathol. 3: 200-205.
97
Butler, J.M., Hill, C.R. (2010). Scientific issues with analysis of low amounts of DNA.
Butler, J.M., Shen, Y., McCord, B.R. (2003). The development of reduced size STR
amplicons as tools for analysis of degraded DNA. J Forensic Sci. 48(5): 1-11.
Caragine, T., Mikulasovich, R., Tamariz, J., Bajda, E., Sebestyen, J., Baum, H., Prinz, M.
(2009). Validation of Testing and Interpretation Protocols for Low Template DNA
Samples Using AmpFlSTR® Identifiler®. Croat Med J, 50(3): 250-267.
Cattaneo, C., Craig, O.E., James, N.T., Sokol, R.J. (1997). Comparison of three DNA
extraction methods on bone and blood stains up to 43 years old and amplification of
three different gene sequences. J Forensic Sci, 42(6): 1126-1135.
Cattaneo, C., Smillie, D.M., Gelsthorpe, K., Piccinini, A., Gelsthorpe, A.R., Sokol, R.J.
(1995). A simple method for extracting DNA from old skeletal material. Forensic Sci.
Int, 74: 167-174.
Chakraborty, R., Stivers, D.N., Su, B., Zhong, Y., Budowle, B. (1999). The utility of short
tandem repeat loci beyond human identification: implications for development of new
DNA typing systems. Electrophoresis, 20(8):1682-1696.
Chambers, G.K., MacAvoy, E.S. (2000). Microsatellites: consensus and controversy. Comp
Biochem Physiol, Part B, 126(4): 455-476.
Coble, MD., Butler, J.M. (2005). Characterization of new miniSTR loci to aid analysis of
degraded DNA. J Forensic Sci. 50(1): 43-53.
98
Cowen, S., Debenham, P., Dixon, A., Kutranov, S., Thomson, J., Way, K. (2011). An
investigation of the robustness of the consensus method of interpreting low-template
DNA profiles. Forensic Sci Int Genet, 5(5): 400-406.
Daniel, R., Walsh, S.J. (2006). The Continuing Evolution of Forensic DNA Profiling - From
STRS to SNPS. Aust J Forensic Sci, 38: 59-74.
Davoren, J., Vanek, D., Konjhodzic, R., Crews, J., Huffine, E., Parsons, T.J. (2007). Highly
Effective DNA Extraction Method for Nuclear Short Tandem Repeat Testing of
Skeletal Remains from Mass Graves. Croat Med J, 48(4):478-485.
Decorte, R., Liua, C.F., Vanderheydena, N., Cassiman, J.J. (2008). Development of a novel
miniSTR multiplex assay for typing degraded DNA samples. Forensic Sci Int Genet,
1: 112-114.
Dembinski, G.M., Picard, C.J. (2014). Evaluation of the IrisPlex DNA-based eye color
prediction assay in a United States population, Forensic Sci. Int Genet, 9: 111–117.
Diegoli, T.M., Farr, M., Cromartie, C., Coble, M.D., Bille, T.W. (2012). An optimized
protocol for forensic application of the PreCRTM Repair Mix to multiplex STR
amplification of UV-damaged DNA. Forensic Sci. Int. Genet, 6(4):498-503.
Dixon, L.A., Dobbins, A.E., Pulker, H.K., Butler, J.M., Vallone, P.M., Coble, M.D.,
Parson, W., Berger, B., Grubwieser, P., Mogensen, H.S., Morling, N., Nielsen, K.,
Sanchez, J.J., Petkovski, E., Carracedo, A., Sanchez-Diz, P., Ramos-Luis, E., Brion,
M., Irwin, JA., Just, R.S., Loreille, O., Parsons, TJ., Syndercombe-Court, D.,
Schmitter, H., Stradmann-Bellinghausen, B., Bender, K., Gill, P. (2006). Analysis of
99
artificially degraded DNA using STRs and SNPs—results of a collaborative European
(EDNAP) exercise. Forensic Sci Int. 164: 33-44.
Draus-Barini, J., Walsh, S., Popiech, E., Kupiec, T., Glab, H., Branicki, W., Kayser, M.
(2013). Bona fide colour: DNA prediction of human eye and hair colour from ancient
and contemporary skeletal remains. Investigative Genet, 4: 3-17.
Fan, H., and Chu, JY. (2007). A brief review of short tandem repeat mutation. Genomic,
Proteomics and Bioinformatics, 5(1): 7-14.
Feuk, L., Carson, A.R., Scherer, S.W. (2006). Structural variation in the human genome.
Nature reviews Genetics, 7: 85- 97.
Fondevila, M., Phillips, C., Naveran, N., Cerezo, M., Rodriguez, A., Calvo, R., Fernendez,
L.M., . Carracedo, A., Lareu, M.V. (2008). Challenging DNA: Assessment of a range
of genotyping approaches for highly degraded forensic samples. Forensic Sci Int
Genet, 12: 26–28.
Fondevila, M., Phillips, C., Naverán, N., Cerezo, M., Rodríguez, A., Calvo, R., Fernández,
L.M., Carracedo, Á., Lareu, M.V. (2008). Challenging DNA: Assessment of a range
of genotyping approaches for highly degraded forensic samples. Forensic Sci Int
Genet, Supplement Series, 1: 26-28.
Frudakis, T. (2010). Molecular photofitting: Predicting ancestry and phenotype using DNA.
Elsevier, 712 pages.
Gill, P. (2001). An assessment of the utility of single nucleotide polymorphisms (SNPs) for
forensic purposes. Int J Legal Med, 114(4-5): 204-210.
100
Gill, P., Werrett, D.J., Budowle, B., Guerrieri, R. (2004). An assessment of whether SNPs
will replace STRs in national DNA databases-Joint considerations of the DNA
working group of the European Network of Forensic Science Institutes (ENFSI) and
the Scientific Working Group on DNA Analysis Methods (SWGDAM). Science &
Justice, 44(1): 51-53.
Gill, P., Brown, R.M., Fairley, M., Lee, L., Smyth, M., Simpson, N., Irwin, B., Dunlop,
J., Greenhalgh, M., Way, K., Westacott, E.J., Ferguson, S.J., Ford, L.V., Clayton,
T., Guiness, J. (2008). National recommendations of the Technical UK DNA working
group on mixture interpretation for the NDNAD and for court going purposes.
Forensic Sci Int Genet, 2(1): 76-82.
Gill, P., Whitaker, J., Flaxman, C., Brown, N., Buckleton, J. (2000). An investigation of the
rigor of interpretation rules for STRs derived from less than 100 pg of DNA. Forensic
Sci Int, 112(1): 17–40.
Grisedale, k., van Daal, A. (2014). Linear amplification of target prior to PCR for improved
low template DNA results. BioTechniques, 56: 145-147.
Grisedale, K.S., van Daal, A. (2012). Comparison of STR profiling from low template DNA
extracts with and without the consensus profiling method. Investigative Genet,
3(1):14-22.
Grubwieser, P., Muhlmann, R., Berger, B., Niederstatter, H., Pavlic, M., Parson, W. (2006).
A new miniSTR-multiplex displaying reduced amplicon lengths for the analsis of
degraded DNA. Int J Legal Med, 120(2): 115-120.
101
Hedges, J.E.M., Stevens, R.E., Koch, P.L. (2006). Isotopes in Bones and Teeth. Isotopes in
Paleoenvironmental Research. Springer link, 10: 117-145.
Hill, C.R., Kline, M.C., Duewer, D.L., Butler, J.M. (2010). Strategies for Concordance
Testing. Promega Corporation Web site.
http://www.promega.co.uk/resources/profiles-in-dna/ 2010/strategies-for-
concordance-testing/, 1-11.
Hill, CR., Kline, M.C., Mulero, J.J., Lagace, R.E., Chang, C.W., Hennessy, L.K., Butler,
J.M. (2007). Concordance study between the AmpFlSTR Minifiler PCR amplification
kit and conventional STR typing kits. J Forensic Sci, 52(4): 870-873.
Hochmeister, M.N., Budowle, B., Borer, U.V., Eggmann, U., Comey, C.T., Dirnhofer, R.
(1991). Typing of deoxyribonucleic acid (DNA) extracted from compact bone from
human remains, J. Forensic Sci. 36(6): 1649-1661.
Holland, M.M., Cave, C.A., Holland, C.A., Bille, T.W. (2003). Development of a Quality,
High Throughput DNA Analysis Procedure for Skeletal Samples to Assist with the
Identification of Victims from the World Trade Center Attacks. Croat Med J,
44(3):264-272.
Huel, R., Amory, S., Bilic, A., Vidovic, S., Jasaragic, E., Parsons, T.J. (2012). DNA
Extraction from Aged Skeletal Samples for STR Typing by Capillary
Electrophoresis. Methods Mol Biol, 830: 185-198.
102
Hughes-Stamm, S.R., Ashton, K.J., van Daal A. (2011). Assessment of DNA degradation
and the genotyping success of highly degraded samples. Int J Legal Med, 125(3):
341-348.
Hummel, S., Schultes, T., Bramanti, B., Herrmann, B. (1999). Ancient DNA profiling by
megaplex amplifications. Electrophoresis, 20(8): 1717-1721.
Hummel, S., Herrmann, B. (1994). General Aspects of Sample Preparation. Ancient DNA.
Springer New York, 59-68.
Imamoglu, O., Karapirli, M., Akboyun, N. (2012). Comparison of DNA extraction methods
from teeth samples and evaluation in terms of Forensic Sciences. J For Med, 1: 38-
49.
Iwamura, E.S.M., Soares-Vieira, J.A., Munoz, D.R. (2004). Human identification and
analysis of DNA in bones. Rev. Hosp. Clin. Fac. Med. S. Paulo, 59(6): 383-388.
Jakubowska, J., Maciejewska, A., Pawłowski, R. (2012). Comparison of three methods of
DNA extraction from human bones with different degrees of degradation. Int J Legal
Med, 126(1):173-178.
Jobling, M.A. Gill, P. (2004). Encoded evidence: DNA in forensic analysis. Nature reviews,
genetics, 5: 739-751.
Kaestle, F.A., Horsburgh, K.A. (2002). Ancient DNA in anthropology: methods,
applications, and ethics. American J Phys Anthropol, 35: 92-130.
Kalmar,T., Bachrati, C.Z., Marcsik, A., Rasko, I. (2000). A simple and efficient method for
PCR amplifiable DNA extraction from ancient bones. Nucliec Acid Res. 28(12): i-iv.
103
Kashyap, V., Sitalaximi, T., Chattopadhyay, P., Trivedi, R. (2004). DNA profiling
technologies in forensic analysis. Int J Hum Genet, 4(1): 11-30.
Kayser, M., de Knijff, P. (2011). Improving human forensics through advances in genetics,
genomics and molecular biology. Nature Reviews, Genet, 12: 179-192.
Kemp, B.M., Smith, D.G. (2005). Use of bleach to eliminate contaminating DNA from the
surface of bones and teeth. Forensic Sci Int, 154 (1): 53–61.
Kirby, L.T. (1990). DNA Fingerprinting; Stockton Press: New York, NY, 365 pages.
Kobilinsky, L., Liotti, T.F., & Oeser-Sweat, J. (2005). Genetics, statistics, and databases, in
DNA: Forensic and legal applications, John Wiley & Sons, Inc., Hoboken, NJ, USA,
149-152.
Lander, E.S., Linton, L.M., Birren, B., Nusbaum, C., Zody, M.C., Baldwin, J., Devon, K.,
Dewar, K., Doyle, M., FitzHugh, W., Funke, R., Gage, D., Harris, K., Heaford, A.,
Howland, J., Kann, L., Lehoczky, J., LeVine, R., McEwan, P., McKernan, K.,
Meldrim, J., Mesirov, J.P., Miranda, C., Morris, W., Naylor, J., Raymond, C., Rosetti,
M., Santos, R., Sheridan, A., Sougnez, C., Stange-Thomann, N., Stojanovic, N.,
Subramanian, A., Wyman, D., Rogers, J., Sulston, J., Ainscough, R., Beck, S.,
Bentley, D., Burton, J., Clee, C., Carter, N., Coulson, A., Deadman, R., Deloukas, P.,
Dunham, A., Dunham, I., Durbin, R., French, L., Grafham, D., Gregory, S., Hubbard,
T., Humphray, S., Hunt, A., Jones, M., Lloyd, C., McMurray, A., Matthews, L.,
Mercer, S., Milne, S., Mullikin, J.C., Mungall, A., Plumb, R., Ross, M., Shownkeen,
R., Sims, S., Waterston, R.H., Wilson, R.K., Hillier, L.W., McPherson, J.D., Marra,
M.A., Mardis, E.R., Fulton, L.A., Chinwalla, A.T., Pepin, K.H., Gish, W.R., Chissoe,
104
S.L., Wendl, M.C., Delehaunty, K.D., Miner, T.L., Delehaunty, A., Kramer, J.B.,
Cook, L.L., Fulton, R.S., Johnson, D.L., Minx, P.J., Clifton, S.W., Hawkins, T.,
Branscomb, E., Predki, P., Richardson, P., Wenning, S., Slezak, T., Doggett, N.,
Cheng, J.F., Olsen, A., Lucas, S., Elkin, C., Uberbacher, E., Frazier, M., Gibbs, R.A.,
Muzny, D.M., Scherer, S.E., Bouck, J.B., Sodergren, E.J., Worley, K.C., Rives, C.M.,
Gorrell, J.H., Metzker, M.L., Naylor, S.L., Kucherlapati, R.S., Nelson, D.L.,
Weinstock, G.M., Sakaki, Y., Fujiyama, A., Hattori, M., Yada, T., Toyoda, A., Itoh,
T., Kawagoe, C., Watanabe, H., Totoki, Y., Taylor, T., Weissenbach, J., Heilig, R.,
Saurin, W., Artiguenave, F., Brottier, P., Bruls, T., Pelletier, E., Robert, C., Wincker,
P., Smith, D.R., Doucette-Stamm, L., Rubenfield, M., Weinstock, K., Lee, H.M.,
Dubois, J., Rosenthal, A., Platzer, M., Nyakatura, G., Taudien, S., Rump, A., Yang,
H., Yu, J., Wang, J., Huang, G., Gu, J., Hood, L., Rowen, L., Madan, A., Qin, S.,
Davis, R.W., Federspiel, N.A., Abola, A.P., Proctor, M.J., Myers, R.M., Schmutz, J.,
Dickson, M., Grimwood, J., Cox, D.R., Olson, M.V., Kaul, R., Raymond, C.,
Shimizu, N., Kawasaki, K., Minoshima, S., Evans, G.A., Athanasiou, M., Schultz, R.,
Roe, B.A., Chen, F., Pan, H., Ramser, J., Lehrach, H., Reinhardt, R., McCombie,
W.R., de la Bastide, M., Dedhia, N., Blocker, H., Hornischer, K., Nordsiek, G.,
Agarwala, R., Aravind, L., Bailey, J.A., Bateman, A., Batzoglou, S., Birney, E., Bork,
P., Brown, D.G., Burge, C.B., Cerutti, L., Chen, H.C., Church, D., Clamp, M.,
Copley, R.R., Doerks, T., Eddy, S.R., Eichler, E.E., Furey, T.S., Galagan, J., Gilbert,
J.G., Harmon, C., Hayashizaki, Y., Haussler, D., Hermjakob, H., Hokamp, K., Jang,
W., Johnson, L.S., Jones, T.A., Kasif, S., Kaspryzk, A., Kennedy, S., Kent, W.J.,
Kitts, P., Koonin, E.V., Korf, I., Kulp, D., Lancet, D., Lowe, T.M., McLysaght, A.,
105
Mikkelsen, T., Moran, J.V., Mulder, N., Pollara, V.J., Ponting, C.P., Schuler, G.,
Schultz, J., Slater, G., Smit, A.F., Stupka, E., Szustakowski, J., Thierry-Mieg, D.,
Thierry-Mieg, J., Wagner, L., Wallis, J., Wheeler, R., Williams, A., Wolf, Y.I.,
Wolfe, K.H., Yang, S.P., Yeh, R.F., Collins, F., Guyer, M.S., Peterson, J., Felsenfeld,
A., Wetterstrand, K.A., Patrinos, A., Morgan, M.J., de Jong, P., Catanese, J.J.,
Osoegawa, K., Shizuya, H., Choi, S. and Chen, Y.J. (2001). Initial sequencing and
analysis of the human genome. Nature, 409: 860-921.
Lee, H.Y., Park, M.J., Kim, N.Y., Sim, J.E., Yang, W.I., Shin, K.J. (2010). Simple and
highly effective DNA extraction methods from old skeletal remains using silica
columns. Forensic Sci Int Genet, 4(5): 275-80.
Li, L., Li, CT., Li, R.Y., Liu, Y., Lin, Y., Que, T.Z., Sun, M.Q., Li, Y. (2006). SNP
genotyping by multiplex amplification and microarrays assay for forensic application.
Forensic Sci Int, 162(1-3): 74-79.
Lim, J.E., Oh, B. (2013). Allelic Frequencies of 20 Visible Phenotype Variants in the Korean
Population. Genomics Inform, 11(2): 93-96.
Lin, J.Y., Fisher, D.E. (2007). Melanocyte biology and skin pigmentation. Nature, 445: 843-
850.
Liu, F., Wen, B., Kayser, M. (2013). Colorful DNA polymorphisms in humans. Semin Cell
Devl Bio. 24(6-7): 562-575.
106
Loreille, O.M., Diegoli, T.M., Irwin, J.A., Coble, M.D., Parsons, T.J. (2007). High efficiency
DNA extraction from bone by total demineralization. Forensic Sci Int Genet, 1: 191-
195.
Loreille, O.M., Diegoli, T.M., Irwin, J.A., Coble, M.D., Parsons, T.J. (2007). High efficiency
DNA extraction from bone by total demineralization. Forensic Sci Int Genet, 1(2):
191-195.
Loreille, O.M., Diegoli, TM., Irwin, J.A., Coble, M.D., Parsons, T.J. (2007). High efficiency
DNA extraction from bone by total demineralization. Forensic Sci. Int. Genet, 1(2):
191-195.
Luftig, M.A., Richey, S. (2001). DNA and Forensic Science. New England Law Review,
35(3): 609-613.
Martın, P., Garcia, O., Albarran, C., Garcıa, P., Alonso, A. (2006). Application of mini-STR
loci to severely degraded casework samples. International Congress Series 1288,
522–525.
Martin, R.B., Burr, D.B., Sharkey, N.A. (1998). Skeletal Tissue Mechanics. New York:
Springer, 1: 1-292.
Massetti, S,. Severini, S., Lanciaa, M., Coletti, A., Carnevali, E., Bacci, M., Faa A., D’Aloja,
E. (2009). Allele frequencies of six miniSTR loci (D10S1248, D14S1434,D22S1045,
D4S2364, D2S441, D1S1677) in two Italian populations. Forensic Sci Int Genet,
Suppl. 2, 367-368.
107
Morley, J.M., Bark, J.E., Evans, C.E., Perry, J.G., Hewitt, C.A., Tully, G. (1999). Validation
of mitochondrial DNA minisequencing for forensic casework. Int J Legal Med.
112(4): 241-248.
Mukherjee, M., Mukerjee, S., Sarkar-Roy, N., Ghosh, T., Kalpana, D., Sharma, A.K. (2013).
Polymorphisms of four pigmentation genes (SLC45A2, SLC24A5, MC1R and
TYRP1) among eleven endogamous populations of India. J Genet, 92(1): 135-139.
Mulero JJ, Chang, C.W., Lagac, R.E., Wang, D.Y., Bas, J.L., McMahon, T.P., Hennessy,
L.K. (2008). Development and Validation of the AmpFlSTR MiniFilerTM
PCR
Amplification Kit: A MiniSTR Multiplex for the Analysis of Degraded and⁄or PCR
Inhibited DNA. J Forensic Sci, 53(4): 838-852.
Nather, A. (2005). Bone Grafts and Bone Substitutes: Basic Science and Clinical
Applications. World Scientific Publishing Company, Incorporated, Medical - 592
pages.
Oh, C.S., Lee, S.J., Park, J.B., Lee, S.D., Seo, S.B., Kim, H.Y., Kim, J., Kim, Y.S., Shin,
D.H. (2012). Autosomal Short Tandem Repeat analysis of ancient DNA by coupled
use of mini- and conventional STR Kits. J Forensic Sci, 57(3):820-825.
Opel, K.L., Chung, D.T., Drabek, J., Tatarek, N.E., Jantz, L.M., McCord, B.R. (2006). The
Application of Miniplex Primer Sets in the Analysis of Degraded DNA from Human
Skeletal Remains. J Forens Sci, 51(2): 351–356.
Pang B.C.M., Cheung B.K.K. (2007). One-step generation of degraded DNA by UV
irradiation. Anal Biochem, 360(1):163-165.
108
Piglionica, M., De Donno, A., Baldassarra, S.L., Santoro, V., Scorca, A., Introna,
F., Dell'Erba, A. (2012). Extraction of DNA from bones in cases where expectations
for success are low. Am J Forensic Med Pathol, 33(4): 322-327.
Puch-Solis, R., Rodgers, L., Mazumder, A., Pope, S., Evett, I., Curran, J., Balding, D. (2013).
Evaluating forensic DNA profiles using peak heights, allowing for multiple donors,
allelic dropout and stutters. Forensic Sci Int Genet, 7(5): 555-563.
Puers, C., Hammond, H.A., Jin, L., Caskey, C.T., Schumm, J.W. (1993). Identification repeat
sequence heterogeneity at the polymorphic short tandem repeat locus
HUMTH01[AATG]n and reassignment of alleles in population analysis by using a
locus-specific allelic ladder. Am J Hum Genet, 53(4): 953-958.
Rodriguez, S., Gaunt, T.R., Day, L.N.M. (2009). Hardy-Weinberg Equilibrium Testing of
Biological Ascertainment for Mendelian Randomization Studies. Am J Epidemiol.
169(4): 505–514.
Romanini, C., Ferrer, M.R., Catelli, M.L., Vullo, C. (2011). A comparison of AmpFlSTR
IdentifilerTM
Kit versus AmpFlSTR Identifiler PlusTM
Kit in challenging bone
samples by using normal and increased PCR cycle number. Forensic Sci Int Genet, 3:
e514-e515.
Rucinski, C., Malaver, A.L., Yunis, E.J., Yunis, J.J. (2012). Comparison of two methods for
isolating DNA from human skeletal remains for STR analysis. J Forensic Sci, 57(3):
706-712.
109
Sajantila, A., Puomilahti, S., Johnsson, V., Ehnholm, C. (1992). Amplification of
reproducible allele markers for amplified fragment length polymorphism analysis.
Biotechniques, 12(1): 16-22.
Sanchez, J.J., Borsting, C., Hallenberg, C., Buchard, A., Hernandez, A., Morling, N. (2003).
Multiplex PCR and minisequencing of SNPs—a model with 35 Y chromosome SNPs.
Forensic Sci Int, 137(1): 74-84.
Schneider, P.M. (1997). Basic issues in forensic DNA typing. Forensic Sci Int, 88(1): 17-22.
Schneider, PM., Bender, K., Mayr, WR., Parson, W., Hoste, B., Decorte, R., Cordonnier,
J., Vanek, D., Morling, N., Karjalainen, M., Marie-Paule Carlotti, C., Sabatier, M.,
Hohoff, C., Schmitter, H., Pflug, W., Wenzel, R., Patzelt, D., Lessig,
R., Dobrowolski, P., O'Donnell, G., Garafano, L., Dobosz, M., De Knijff, P., Mevag,
B., Pawlowski, R.,Gusmao, L., Conceicao Vide, M., Alonso Alonso, A., García
Fernandez, O., Sanz Nicolas, P., Kihlgreen, A., Bar, W., Meier, V., Teyssier,
A., Coquoz, R., Brandt, C., Germann, U., Gill, P., Hallett, J., Greenhalgh, M. (2004).
STR analysis of artificially degraded DNA-results of a collaborative European
exercise. Forensic Sci Int, 139(2-3): 123-134.
Senge, T., Madea, B., Junge, A., Rothschild, M.A., Schneider, P.M. (2011). STRs, mini
STRs and SNPs – A comparative study for typing degraded DNA. Leg Med, 13(2):
68-74.
Seo, S.B., Zhang, A., Kim, H.Y., Yi, JA., Lee, H.Y., Shin, D.H., Lee, S.D. (2010). Technical
Note Efficiency of Total Demineralization and Ion-Exchange Column for DNA
Extraction from Bone. American J. of Phys. Anthropol. 141:158–162.
110
Severini, S., Lancia, M., Massetti, S., Coletti, A., Carlini, L., Carnevali, E. (2011). Analysis
of severely compromised skeletal remains by the use of the latest generation kits.
Forensic Sci Int Genet, Suppl. 3, e115-e116.
Siegal, J.A., Saukko, P.J., Knupfer, G.C. (2000). Encyclopedia of Forensic Sciences. Vol. 2.
London: Academic Press.
Spichenok, O., Budimlija, Z.M., Mitchell, A.A., Jenny, A., Kovacevic, L., Marjanovic,
D., Caragine, T., Prinz, M., Wurmbach, E. (2011). Prediction of eye and skin color in
diverse populations using seven SNPs. Forensic Sci Int Genet, 5(5): 472-478.
Sundquist, T., Bessetti, J. (2005). Identifying and Preventing DNA Contamination in a DNA-
Typing Laboratory. Promega Corporation. Profiles in DNA, 8(2): 11-13.
Takahashi, M., Kato, Y., Mukoyama, H., Kanaya, H., Kamiyama, S. (1997). Evaluation of
five polymorphic microsatellite markers for typing DNA from decomposed human
tissues - correlation between the size of the alleles and that of the template DNA.
Forensic Sci Int, 90(1-2): 1-9.
Tully, G., Sullivan, K.M., Nixon, P., Stones, R.E., Gill, P. (1996). Rapid detection of
mitochondrial sequence polymorphisms using multiplex solid-phase fluorescent
minisequencing. Genomics, 34(1): 107-113.
Twyman, R.M., Primrose, S.B. (2003). Techniques patents for SNP genotyping.
Pharmacogenomics, 4(1): 67-79.
111
Vallone, PM., Just, R.S., Coble, M.D., Butler, J.M., Parsons, T.J. (2004). A multiplex allele-
specific primer extension assay for forensically informative SNPs distributed
throughout the mitochondrial genome. Int J Legal Med, 118(3): 147–157.
von Wurmb-Schwark, N., Heinrich, A., Freudenberg, M., Gebuhr, M., Schwark, T. (2008).
The impact of DNA contamination of bone samples in forensic case analysis and
anthropological research. Leg Med. 10 (3): 125-130.
Vural, H.C., Tirpan, A.A. (2009). Comparison and Development of a rapid extraction method
of DNA from ancient human skeletal remains of Turkey. The Internet J Bio
Anthropol. 4(1): 3.
Weber, JL., May, P.E. (1989). Abundant class of human DNA polymorphisms which can be
typed using the polymerase chain reaction. Am J Hum Genet, 44(3): 388-396.
Westen, A.A., Sijen, T. (2009). Degraded DNA sample analysis using DNA repair enzymes,
mini-STRs and (tri-allelic) SNPs. Forensic Sci Int Genet, Suppl. Series 2(1): 505-507.
Whitaker, J.P., Clayton, T.M., Urquhart, A.J., Millican, E.S., Downes, T.J., Kimpton, C.P.,
Gill, P. (1995). Short tandem repeat typing of bodies from a mass disaster: high
success rate and characteristic amplifications patterns in highly degraded samples.
BioTechniques, 18(4): 670-677.
White, T.D., Black, M.T., Folkens, P.A. (2011). Human Osteology. Elsevier Academic Press,
3rd
Edition, 662 pages.
White, T.D., Folkens, P.A. (2005). The human Bone Manual. Elsevier Academic Press; 1st
edition, 488 Pages.
112
Wickenheiser, R.A. (2002). Trace DNA: a review, discussion of theory, and application of
the transfer of trace quantities of DNA through skin contact. J Forensic Sci, 47(3):
442-450.
Wiegand, P., Kleiber, M. (2001). Less is more - length reduction of STR amplicons using
redesigned primers. Int J Legal Med, 114: 285-287.
Willerslev, E., Cooper, A. 2005. Ancient DNA. Proc R Soc Bio, 272: 3-16.
Word, C. (2010). What is LCN?—Definitions and Challenges. Promega Corporation Web
site.
Yang, D.Y., Eng, B., Waye, J.S., Dudar, J.C., Saunders, S.R. (1998). Improved DNA
extraction from ancient bones using silica based spin columns. Am J Phys Anth,
105(4): 539–543.
Zar, M.S., Shahid, A.A., Shahzad, M.S., Shin, K.J., Lee, H.Y., Israr, M., Kim, E.H., Rahman,
Z.U., Husnain, T. (2013). Forensic DNA Typing of Old Skeletal Remains Using
AmpFlSTR®Identifiler® PCR Amplification Kit. J Forensic Res, 5(1): 211-216.
Zar, M.S., Shahid, A.A., Shahzad, M.S., Shin, K.J., Lee, H.Y., Israr, M., Husnain, T. (2014).
Comparative study of STR loci for typing old skeletal remains with modified
protocols of AmpFlSTR® Identifiler® and AmpFlSTR® MiniFiler™ STR Kits.
Australian J Forensic Sci. DOI:10.1080/00450618.2014.925976.
Zehner, R. (2007). “Foreign” DNA in tissue adherent to compact bone from tsunami victims.
Forensic Sci Int Genet. 1 (2): 218-222.
113
Zink, AR., Reischl, U., Wolf, H., Nerlich, A.G. (2002). Molecular analysis of ancient
microbial infections. FEMS Microbiol Lett, 213(2): 141-147.
114
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.