Genetic Structures of Copy Number Variants Revealed by Genotyping Single Sperm

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2009 Apr 23

PMID 19384415

Citations 1

Authors

Minjie Luo

Xiangfeng Cui

David Fredman

Anthony J Brookes

Marco A Azaro

Danielle M Greenawalt

Guohong Hu

Hui-Yun Wang

Irina V Tereshchenko

Yong Lin

Yue Shentu

Richeng Gao

Li Shen

Honghua Li

Affiliations

Soon will be listed here.

Abstract

Background: Copy number variants (CNVs) occupy a significant portion of the human genome and may have important roles in meiotic recombination, human genome evolution and gene expression. Many genetic diseases may be underlain by CNVs. However, because of the presence of their multiple copies, variability in copy numbers and the diploidy of the human genome, detailed genetic structure of CNVs cannot be readily studied by available techniques.

Methodology/principal Findings: Single sperm samples were used as the primary subjects for the study so that CNV haplotypes in the sperm donors could be studied individually. Forty-eight CNVs characterized in a previous study were analyzed using a microarray-based high-throughput genotyping method after multiplex amplification. Seventeen single nucleotide polymorphisms (SNPs) were also included as controls. Two single-base variants, either allelic or paralogous, could be discriminated for all markers. Microarray data were used to resolve SNP alleles and CNV haplotypes, to quantitatively assess the numbers and compositions of the paralogous segments in each CNV haplotype.

Conclusions/significance: This is the first study of the genetic structure of CNVs on a large scale. Resulting information may help understand evolution of the human genome, gain insight into many genetic processes, and discriminate between CNVs and SNPs. The highly sensitive high-throughput experimental system with haploid sperm samples as subjects may be used to facilitate detailed large-scale CNV analysis.

Citing Articles

Segmental duplication as one of the driving forces underlying the diversity of the human immunoglobulin heavy chain variable gene region.

Pramanik S, Cui X, Wang H, Chimge N, Hu G, Shen L BMC Genomics. 2011; 12:78.

PMID: 21272357 PMC: 3042411. DOI: 10.1186/1471-2164-12-78.

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