Insertion-deletions burden in copy number polymorphisms of the Tibetan population.
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Date
2014-04
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Abstract
BACKGROUND: Many studies have been conducted to
identify either insertions-deletions (inDels) or copy number
variations (CNVs) in humans, but few studies have been
conducted to identify both of these forms coexisting in the
same region.
AIMS AND OBJECTIVES: To map the functionally
significant sites within human genes that are likely to
influence human traits and diseases.
MATERIALS AND METHODS: In this report, we
describe an inDel map in the 1051 Tibetan CNV regions
obtained through CNV genotyping using Affymetrix
Genome-wide single nucleotide polymorphism 6.0 chip.
InDel polymorphisms in these copy number polymorphism
regions were identified with a computational approach using
the 2500 deoxyribonucleic acid sequences obtained from
the 1000 Genome Project.
RESULTS: The study identified a total of 95935 inDels that
range from 1 bp to several bps in length which were found
scattered across regulatory regions, exons and in introns
of genes underlying the CNVs. A study on the distribution
of inDels revealed that the majority of inDels were found
in coding regions of the genome than the noncoding,
while within the genes, inDels in intron regions were more
followed by exonic regions and finally the regulatory regions.
CONCLUSION: Study of inDels in CNV regions contribute
to the enhanced understanding of the role played by the
two variations and their collective influence on the genome.
Further, a collection of these inDel genetic markers will aid
in genetic mapping, further understanding of the phenotypic
variability, identification of disease genes and in detecting
novel CNVs.
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Keywords
Copy number variations, insertions‑deletions, insertions‑deletions burden, Tibet
Citation
Veerappa Avinash M, Vishweswaraiah Sangeetha, Lingaiah Kusuma, Murthy N Megha, Suresh Raviraj V, Belur Keshava, Ramachandra Nallur B, Tejaswini , Patel Niveditha B, Supriya Gowda P K. Insertion-deletions burden in copy number polymorphisms of the Tibetan population. Indian Journal of Human Genetics. 2014 Apr-Jun ; 20 (2): 166-174.