The Sri Lankan Personal Genome Project

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DOI: 10.4038/sljbmi.v2i1.3711
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Abstract
The first Sri Lankan Personal Genome was sequenced heralding the entry of Sri Lanka into the new era of whole genome sequencing. This paper explains the background and the rationale for the project, gives a brief overview of what was found in the Sri Lankan Personal Genome, and discusses the future directions of the project.
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Leading Article
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The Sri Lankan Personal Genome Project: an overview
Prof. Vajira H. W. Dissanayake MBBS, PhD
Professor, Department of Anatomy; Medical Geneticist, Human Genetics Unit, Faculty of Medicine, University
of Colombo, Sri Lanka
E-Mail address: vajirahwd@hotmail.com
Pubudu S. Samarakoon BSc, MSc
Tutor, Biomedical Informatics Course, Postgraduate Institute of Medicine, University of Colombo, Sri Lanka.
Current address: Research Fellow, Department of Medical Genetics, University of Oslo, Norway.
E-Mail address: saneth.samarakoon@gmail.com
Dr. Vinod Scaria MBBS
Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
E-Mail address: vinods@igib.res.in
Ashok Patowary BSc, MSc
Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
E-Mail address: s.sivasubbu@igib.res.in
Dr. Sridhar Sivasubbu PhD
Scientist, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
E-Mail address: s.sivasubbu@igib.res.in
Dr. Rajesh S. Gokhale PhD
Director, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
E-mail address: director@igib.res.in
Sri Lanka Journal of Bio-Medical Informatics 2011;2(1):4-8
DOI: http://dx.doi.org/10.4038/sljbmi.v2i1.3711
Abstract
The first Sri Lankan Personal Genome was sequenced heralding the entry of Sri Lanka into the new era of whole
genome sequencing. This paper explains the background and the rationale for the project, gives a brief overview
of what was found in the Sri Lankan Personal Genome, and discusses the future directions of the project.
Keywords - Sri Lankan Personal Genome Project; Sri Lanka; Genome; Sinhalese; Whole Genome Sequencing
Background
With the completion of the Human Genome Project (HGP)(1,2) and a decade of human
genomics, we are at an interesting juncture in the history of mankind. New technologies have
enabled sequencing of complete human genomes at a fraction of the original cost of what was
spent on the Human Genome Project (HGP). At the same time, these technologies have
significantly improved the scale and the ease of sequencing, and as a result it is now possible
to sequence entire human genomes and understand the genomic make-up of the individual,
with widespread potential applications in healthcare(3).
Major projects worldwide which followed the Human Genome Project, including the
HapMap project(4) and the 1000 genomes project(5), have been cataloguing human genetic
variations at rapid speed. In addition, they have fuelled the growth of technologies and
analytical methods to scan entire genomes for informative genetic markers, aimed at
V. H. W. Dissanayake et al. / Sri Lanka Journal of Biomedical Informatics 2011; 2(1):4-8
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understanding the differences and similarities between individuals. This is the first step
towards understanding genotype-phenotype correlations. Such large studies have been
undertaken by multiple groups from around the world(6). This has resulted in the
identification of a large number markers associated with complex disorders and drug-
response(7). This is just the tip of the iceberg, and many new associations continue to be
reported in scientific literature on a daily basis.
In addition to understanding genetic variations and how they contribute to disease, there has
been a large body of work aimed at understanding other important aspects such as epigenetic
mechanisms and genomic regulation. This was made possible by new genomic tools which
enabled researchers to address questions at a genomic level and developments in
bioinformatics, made possible by the availability of cheaper and faster computers which
made it possible to do large-scale data analysis, and the development of robust algorithms to
mine data and model biological phenomenon on a genomic scale.
The Sri Lankan personal genome
Today any country aspiring to provide its people access to state of the art healthcare cannot
ignore the rapid advances in the field of human genomics. It is imperative at this juncture for
every country to acquire the much-required tools and know-how. In addition, it is also
necessary to create the baseline data for understanding the genetic diversity of its population.
The Sri Lankan Personal Genome Project is the first step in this direction in Sri Lanka, and
marks the entry of Sri Lanka to the exciting field of whole genome sequencing. Sri Lanka is
home to over 20 million people with rich racial, cultural and linguistic diversity(8). The
earliest evidence (34,000 BP) of anatomically modern man in South Asia is found in Sri
Lanka(9). The rich diversity of human populations in the island has been influenced by
migration from the mainland India. Sri Lanka also has a rich heritage in organised medical
care. The hospital at Mihintale (437 367 BC) is the most ancient hospital to be discovered
in the World(10). The Sri Lankan population consists presently of six major populations, the
Sinhalese, Sri Lankan Tamils, Indian Tamils, Moors, Burghers, and Malays(8). It is also home
to other smaller diverse populations like Vaddhas, the descendents of the original inhabitants
of the island who were geographically isolated from other populations, and Kaffirs,
descendents of African slaves brought to the island over 500 years ago.
To understand the genetic diversity of the Sri Lankan populations, and to create the baseline
data for disease association studies, we had earlier created the Sri Lankan Genome Variation
Database(11). This database contains information on Single Nucleotide Polymorphisms
(SNPs) found in Sinhalese, Sri Lankan Tamils and Moors, the three major ethnic groups in
the Sri Lankan population. The database presently contains information including genotype
frequencies of 34 genomic variations encompassing 14 medically important genes. The
database has been designed keeping in mind international standards for describing and
annotating variations, including those of the Human Genome Variation Society (HGVS)(12).
In the true spirit of collaborations and open access to data, the database also accepts
submissions from the research community and thus offers a standard access point to the
spectrum of genetic variations in the population to researchers and clinicians. The resource is
accessible at URL: http://www.hgucolombo.net/slgv/home.htm
As a proof of concept towards the goal of interpreting and analysing complete genome data,
we sequenced a complete genome of an anonymous Sinhalese male of Sri Lankan origin with
both upcountry and low country descent. Sequencing was performed using next-generation
V. H. W. Dissanayake et al. / Sri Lanka Journal of Biomedical Informatics 2011; 2(1):4-8
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sequencing technology, with over 20x coverage of the genome. Analysis of the genome
resulted in the identification of 2,811,918 SNPs, of which 222,739 were novel in comparison
to dbSNP(13) build 131. This accounted for almost 7.9% of entire set of variations in the
genome, pointing to the necessity of having more complete genomes to have a more
comprehensive picture of the spectrum of genetic variations in humans. Analysis also
resulted in the identification of 489,921 insertion-deletion (InDel) events in the genome.
Future directions
The immediate strategic goals of the Sri Lankan Personal Genome Project for 2011-2012 are
to understand in depth, the genetic variations and their potential phenotypic consequences.
Thus, for the years 2011-2012 we articulate our research in terms of three main streams
annotating the genetic variations unique to Sri Lankans, studying the interactions between
genes in relation to disease phenotypes, visualising the annotation of the Sri Lankan genome
via “Sri Lankan Genome Browser” and the “Sri Lankan Genome Variation Database”.
The first Sri Lankan Personal Genome has revealed over 2.8 million single nucleotide
variations of which over 200,000 are unique variations which have hitherto not been
identified in other populations as revealed by comparison with variations collected in the
dbSNP database build 131. We hope that in depth annotation of these variations will provide
crucial insights into some phenotypes which could be specific for the Sri Lankan population.
Coupling this knowledge with associated clinical phenotypes and traits will potentially enable
scientists to generate new hypothesis on the given association. Consequently, these
hypothesis can be validated by specifically genotyping these unique variations in the Sri
Lankan population. Recent advances in the field of bioinformatics and data mining offers the
tools required for the annotation and functional interpretation of SNP data. [For example see
the article by Harendra et al. in this issue of the Journal(14)]. The value of this information can
be further enhanced by comparative studies with data coming from other projects including
the 1000 Genomes Project and other population specific personal genome projects.
Recent advances in genomic technologies have enabled researchers to unravel many a
biological pathway and process at molecular detail. It would be imperative to exploit this data
and perform integrative analysis so as to understand the biological context and functional
consequence of genomic variations. This would include (i) understanding biological
interaction networks including genetic interaction networks and protein interaction networks
from public databases like OMIM and HuGe Navigator, (ii) curation and integration of the
interaction network so as to understand molecular processes of diseases and drug metabolic
pathways, including integrating association data from public repositories and resources to
understand the molecular pathways of biological processes, (iii) integration of the variation
data with the gene interaction network to understand the potential consequences of the
genomic variations which could be modelled and validated in model systems.
To ensure the wide use and ease of interpretation, we have made available the genomic
variations and annotations of the Sri Lankan Personal Genome on the Sri Lankan Genome
Browser, an online genome browser built on the Generic Model Organisms (GMOD)
Gbrowse(15). This would serve as the central hub for exchange of data, visualisation of
genomic variations and their annotations including data that would come out of the Sri
Lankan Personal Genome Project in the future (Figure 1). The resource is freely accessible
online at www.srilankangenome.net.
V. H. W. Dissanayake et al. / Sri Lanka Journal of Biomedical Informatics 2011; 2(1):4-8
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Figure 1. The Sri Lankan Genome Browser provides quick visualization of genomic
variations and would ease the annotation and interpretation of genetic variations.
In the future, we hope to unravel the genetic diversity of Sri Lankan populations by
sequencing more individuals from different racial groups. We also hope to collaborate both
nationally and internationally to assimilate knowledge and expertise and possibly co-create
resources which would enable the interpretation of data and its application in healthcare. This
includes participation in co-creating open resources like OpenPGx (www.openpgx.org) for
interpreting genomic variations and participation in collaborative initiatives aimed at
understanding the diversity of Asian populations. We also recognise that application of
genomics in healthcare would not be possible without educating and involving medical
professionals in genomics research and that this would include educating medical
professionals on analysing and interpreting genomic information and using such information
in their clinical practice.
Declaration of conflicts of interest
The authors declare that they have no conflicts of interest.
Acknowledgement
The Sri Lankan Personal Genome Project was funded by the NOMA Project of the
Postgraduate Institute of Medicine, University of Colombo, Sri Lanka.
References
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the human genome. Nature 409: 860921. doi:10.1038/35057062
2. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, et al. The sequence of the human
genome. Science 291: 13041351. doi:10.1126/science.1058040
3. Green ED, Guyer MS; Charting a course for genomic medicine from base pairs to
bedside. Nature. 2011; 470: 204-13. doi:10.1038/nature09764
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4. The International HapMap Consortium. The International HapMap Project. Nature 2003;
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Polymorphisms (SNPs) in the Heparin-Binding EGF-like Growth Factor (HBEGF) gene
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