Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel compu...

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Autores principales:	Sebastian M Waszak, Yehudit Hasin, Thomas Zichner, Tsviya Olender, Ifat Keydar, Miriam Khen, Adrian M Stütz, Andreas Schlattl, Doron Lancet, Jan O Korbel
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/55e67763b13046bab013d5e4fd461399
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spelling	oai:doaj.org-article:55e67763b13046bab013d5e4fd4613992021-11-18T05:51:56ZSystematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.1553-734X1553-735810.1371/journal.pcbi.1000988https://doaj.org/article/55e67763b13046bab013d5e4fd4613992010-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21085617/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95-99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.Sebastian M WaszakYehudit HasinThomas ZichnerTsviya OlenderIfat KeydarMiriam KhenAdrian M StützAndreas SchlattlDoron LancetJan O KorbelPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 6, Iss 11, p e1000988 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Sebastian M Waszak Yehudit Hasin Thomas Zichner Tsviya Olender Ifat Keydar Miriam Khen Adrian M Stütz Andreas Schlattl Doron Lancet Jan O Korbel Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
description	Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95-99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.
format	article
author	Sebastian M Waszak Yehudit Hasin Thomas Zichner Tsviya Olender Ifat Keydar Miriam Khen Adrian M Stütz Andreas Schlattl Doron Lancet Jan O Korbel
author_facet	Sebastian M Waszak Yehudit Hasin Thomas Zichner Tsviya Olender Ifat Keydar Miriam Khen Adrian M Stütz Andreas Schlattl Doron Lancet Jan O Korbel
author_sort	Sebastian M Waszak
title	Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
title_short	Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
title_full	Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
title_fullStr	Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
title_full_unstemmed	Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
title_sort	systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/55e67763b13046bab013d5e4fd461399
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Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.

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