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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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Published in: | PLoS computational biology 2010-11, Vol.6 (11), p.e1000988-e1000988 |
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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. |
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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.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1000988</identifier><identifier>PMID: 21085617</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Chromosome Mapping ; Computational Biology/Genomics ; Confidence intervals ; Databases, Genetic ; DNA Copy Number Variations ; DNA sequencing ; European Continental Ancestry Group ; Experiments ; Genes ; Genetic aspects ; Genetic Variation ; Genetics and Genomics/Genomics ; Genetics, Population ; Genome ; Genomes ; Genomics - methods ; Genotype ; Humans ; Hybridization ; Methods ; Nucleotide sequencing ; Olfactory receptors ; Oligonucleotide Array Sequence Analysis ; Physiological aspects ; Polymerase Chain Reaction ; Polymorphism, Single Nucleotide ; Principal Component Analysis ; Receptors, Odorant - genetics ; Reproducibility of Results ; Sequence Analysis, DNA ; Software</subject><ispartof>PLoS computational biology, 2010-11, Vol.6 (11), p.e1000988-e1000988</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>Waszak et al. 2010</rights><rights>2010 Waszak et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Waszak SM, Hasin Y, Zichner T, Olender T, Keydar I, et al. (2010) Systematic Inference of Copy-Number Genotypes from Personal Genome Sequencing Data Reveals Extensive Olfactory Receptor Gene Content Diversity. PLoS Comput Biol 6(11): e1000988. doi:10.1371/journal.pcbi.1000988</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c636t-768d203e8b057e1af6db98a1d162676c326e3c2063c9fcb2ecbc30033efc00683</citedby><cites>FETCH-LOGICAL-c636t-768d203e8b057e1af6db98a1d162676c326e3c2063c9fcb2ecbc30033efc00683</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978733/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978733/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,36990,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21085617$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Wasserman, Wyeth W.</contributor><creatorcontrib>Waszak, Sebastian M</creatorcontrib><creatorcontrib>Hasin, Yehudit</creatorcontrib><creatorcontrib>Zichner, Thomas</creatorcontrib><creatorcontrib>Olender, Tsviya</creatorcontrib><creatorcontrib>Keydar, Ifat</creatorcontrib><creatorcontrib>Khen, Miriam</creatorcontrib><creatorcontrib>Stütz, Adrian M</creatorcontrib><creatorcontrib>Schlattl, Andreas</creatorcontrib><creatorcontrib>Lancet, Doron</creatorcontrib><creatorcontrib>Korbel, Jan O</creatorcontrib><title>Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><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. 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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. 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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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21085617</pmid><doi>10.1371/journal.pcbi.1000988</doi><oa>free_for_read</oa></addata></record> |
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subjects | Chromosome Mapping Computational Biology/Genomics Confidence intervals Databases, Genetic DNA Copy Number Variations DNA sequencing European Continental Ancestry Group Experiments Genes Genetic aspects Genetic Variation Genetics and Genomics/Genomics Genetics, Population Genome Genomes Genomics - methods Genotype Humans Hybridization Methods Nucleotide sequencing Olfactory receptors Oligonucleotide Array Sequence Analysis Physiological aspects Polymerase Chain Reaction Polymorphism, Single Nucleotide Principal Component Analysis Receptors, Odorant - genetics Reproducibility of Results Sequence Analysis, DNA Software |
title | Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity |
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