Integrating common and rare genetic variation in diverse human populations
Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and inter...
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| Veröffentlicht in: | Nature (London) 2010-09, Vol.467 (7311), p.52-58 |
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| creator | Altshuler, David M Gibbs, Richard A Peltonen, Leena Dermitzakis, Emmanouil Schaffner, Stephen F Yu, Fuli Bonnen, Penelope E de Bakker, Paul I W Deloukas, Panos Gabriel, Stacey B Gwilliam, Rhian Hunt, Sarah Inouye, Michael Jia, Xiaoming Palotie, Aarno Parkin, Melissa Whittaker, Pamela Chang, Kyle Hawes, Alicia Lewis, Lora R Ren, Yanru Wheeler, David Muzny, Donna Marie Barnes, Chris Darvishi, Katayoon Hurles, Matthew Korn, Joshua M Kristiansson, Kati Lee, Charles McCarrol, Steven A Nemesh, James Keinan, Alon Montgomery, Stephen B Pollack, Samuela Price, Alkes L Soranzo, Nicole Gonzaga-Jauregui, Claudia Anttila, Verneri Brodeur, Wendy Daly, Mark J Leslie, Stephen McVean, Gil Moutsianas, Loukas Nguyen, Huy Zhang, Qingrun Ghori, Mohammed J R McGinnis, Ralph McLaren, William Takeuchi, Fumihiko Grossman, Sharon R Shlyakhter, Ilya Hostetter, Elizabeth B Sabeti, Pardis C Adebamowo, Clement A Foster, Morris W Gordon, Deborah R Licinio, Julio Manca, Maria Cristina Marshall, Patricia A Matsuda, Ichiro Ngare, Duncan Wang, Vivian Ota Reddy, Deepa Rotimi, Charles N Royal, Charmaine D Sharp, Richard R Zeng, Changqing Brooks, Lisa D McEwen, Jean E |
| description | Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called ‘HapMap 3’, includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of ≤5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
Third-generation HapMap
The International HapMap Consortium, established to develop a haplotype map of the human genome describing the common patterns of DNA sequence variation, has now reached its third incarnation. HapMap1, published in 2005 (go.nature.com/gJisDm), contained more than a million SNP (single nucleotide polymorphism) genotypes generated in 269 individuals from four geographically diverse populations. Two years later, HapMap2 (go.nature.com/WttNWX) added more than 2.1 million SNPs to the original map in the same 269 individuals. With the aim of providing a resource for the latest wave of genome-wide studies focused on disease linkages, HapMap3 casts the net wider. About 1.6 million common SNPs were genotyped in 1,184 individuals from 11 global populations, and ten 100-kilobase regions were sequenced in 692 of these individuals.
Here, the analysis of 'HapMap 3' is reported — a public data set of genomic variants in human populations. The resource integrates common and rare single nucleotide polymorphisms (SNPs) and copy number polymorphisms (CNPs) from 11 global populations, providing insights into population-specific differences among variants. It also demonstrates the feasibility of imputing newly discovered rare SNPs and CNPs. |
| doi_str_mv | 10.1038/nature09298 |
| format | Article |
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A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called ‘HapMap 3’, includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of ≤5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
Third-generation HapMap
The International HapMap Consortium, established to develop a haplotype map of the human genome describing the common patterns of DNA sequence variation, has now reached its third incarnation. HapMap1, published in 2005 (go.nature.com/gJisDm), contained more than a million SNP (single nucleotide polymorphism) genotypes generated in 269 individuals from four geographically diverse populations. Two years later, HapMap2 (go.nature.com/WttNWX) added more than 2.1 million SNPs to the original map in the same 269 individuals. With the aim of providing a resource for the latest wave of genome-wide studies focused on disease linkages, HapMap3 casts the net wider. About 1.6 million common SNPs were genotyped in 1,184 individuals from 11 global populations, and ten 100-kilobase regions were sequenced in 692 of these individuals.
Here, the analysis of 'HapMap 3' is reported — a public data set of genomic variants in human populations. The resource integrates common and rare single nucleotide polymorphisms (SNPs) and copy number polymorphisms (CNPs) from 11 global populations, providing insights into population-specific differences among variants. It also demonstrates the feasibility of imputing newly discovered rare SNPs and CNPs.</description><identifier>ISSN: 0028-0836</identifier><identifier>EISSN: 1476-4687</identifier><identifier>DOI: 10.1038/nature09298</identifier><identifier>PMID: 20811451</identifier><identifier>CODEN: NATUAS</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/1647/1513/2192 ; 631/208/205/2138 ; 631/208/212 ; 631/208/457/649 ; Algorithms ; DNA Copy Number Variations ; Genetic diversity ; Genetic testing ; Genetic variance ; Genetic variation ; Genetics ; Genome, Human ; Genomics ; Human genome ; Human Genome Project ; Human populations ; Humanities and Social Sciences ; Humans ; multidisciplinary ; Polymorphism, Single Nucleotide ; Population Groups - genetics ; Quality control ; Science ; Science (multidisciplinary)</subject><ispartof>Nature (London), 2010-09, Vol.467 (7311), p.52-58</ispartof><rights>Springer Nature Limited 2010</rights><rights>COPYRIGHT 2010 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Sep 2, 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c676t-b95be9ac32ad644600cebea7f00ea535db288b6dba44e624891fe199db7485113</citedby><cites>FETCH-LOGICAL-c676t-b95be9ac32ad644600cebea7f00ea535db288b6dba44e624891fe199db7485113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/nature09298$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/nature09298$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20811451$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Altshuler, David M</creatorcontrib><creatorcontrib>Gibbs, Richard A</creatorcontrib><creatorcontrib>Peltonen, Leena</creatorcontrib><creatorcontrib>Dermitzakis, Emmanouil</creatorcontrib><creatorcontrib>Schaffner, Stephen F</creatorcontrib><creatorcontrib>Yu, Fuli</creatorcontrib><creatorcontrib>Bonnen, Penelope E</creatorcontrib><creatorcontrib>de Bakker, Paul I W</creatorcontrib><creatorcontrib>Deloukas, Panos</creatorcontrib><creatorcontrib>Gabriel, Stacey B</creatorcontrib><creatorcontrib>Gwilliam, Rhian</creatorcontrib><creatorcontrib>Hunt, Sarah</creatorcontrib><creatorcontrib>Inouye, Michael</creatorcontrib><creatorcontrib>Jia, Xiaoming</creatorcontrib><creatorcontrib>Palotie, Aarno</creatorcontrib><creatorcontrib>Parkin, Melissa</creatorcontrib><creatorcontrib>Whittaker, Pamela</creatorcontrib><creatorcontrib>Chang, Kyle</creatorcontrib><creatorcontrib>Hawes, Alicia</creatorcontrib><creatorcontrib>Lewis, Lora R</creatorcontrib><creatorcontrib>Ren, Yanru</creatorcontrib><creatorcontrib>Wheeler, David</creatorcontrib><creatorcontrib>Muzny, Donna Marie</creatorcontrib><creatorcontrib>Barnes, Chris</creatorcontrib><creatorcontrib>Darvishi, Katayoon</creatorcontrib><creatorcontrib>Hurles, Matthew</creatorcontrib><creatorcontrib>Korn, Joshua M</creatorcontrib><creatorcontrib>Kristiansson, Kati</creatorcontrib><creatorcontrib>Lee, Charles</creatorcontrib><creatorcontrib>McCarrol, Steven A</creatorcontrib><creatorcontrib>Nemesh, James</creatorcontrib><creatorcontrib>Keinan, Alon</creatorcontrib><creatorcontrib>Montgomery, Stephen B</creatorcontrib><creatorcontrib>Pollack, Samuela</creatorcontrib><creatorcontrib>Price, Alkes L</creatorcontrib><creatorcontrib>Soranzo, Nicole</creatorcontrib><creatorcontrib>Gonzaga-Jauregui, Claudia</creatorcontrib><creatorcontrib>Anttila, Verneri</creatorcontrib><creatorcontrib>Brodeur, Wendy</creatorcontrib><creatorcontrib>Daly, Mark J</creatorcontrib><creatorcontrib>Leslie, Stephen</creatorcontrib><creatorcontrib>McVean, Gil</creatorcontrib><creatorcontrib>Moutsianas, Loukas</creatorcontrib><creatorcontrib>Nguyen, Huy</creatorcontrib><creatorcontrib>Zhang, Qingrun</creatorcontrib><creatorcontrib>Ghori, Mohammed J R</creatorcontrib><creatorcontrib>McGinnis, Ralph</creatorcontrib><creatorcontrib>McLaren, William</creatorcontrib><creatorcontrib>Takeuchi, Fumihiko</creatorcontrib><creatorcontrib>Grossman, Sharon R</creatorcontrib><creatorcontrib>Shlyakhter, Ilya</creatorcontrib><creatorcontrib>Hostetter, Elizabeth B</creatorcontrib><creatorcontrib>Sabeti, Pardis C</creatorcontrib><creatorcontrib>Adebamowo, Clement A</creatorcontrib><creatorcontrib>Foster, Morris W</creatorcontrib><creatorcontrib>Gordon, Deborah R</creatorcontrib><creatorcontrib>Licinio, Julio</creatorcontrib><creatorcontrib>Manca, Maria Cristina</creatorcontrib><creatorcontrib>Marshall, Patricia A</creatorcontrib><creatorcontrib>Matsuda, Ichiro</creatorcontrib><creatorcontrib>Ngare, Duncan</creatorcontrib><creatorcontrib>Wang, Vivian Ota</creatorcontrib><creatorcontrib>Reddy, Deepa</creatorcontrib><creatorcontrib>Rotimi, Charles N</creatorcontrib><creatorcontrib>Royal, Charmaine D</creatorcontrib><creatorcontrib>Sharp, Richard R</creatorcontrib><creatorcontrib>Zeng, Changqing</creatorcontrib><creatorcontrib>Brooks, Lisa D</creatorcontrib><creatorcontrib>McEwen, Jean E</creatorcontrib><creatorcontrib>International HapMap 3 Consortium</creatorcontrib><creatorcontrib>The International HapMap 3 Consortium</creatorcontrib><title>Integrating common and rare genetic variation in diverse human populations</title><title>Nature (London)</title><addtitle>Nature</addtitle><addtitle>Nature</addtitle><description>Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called ‘HapMap 3’, includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of ≤5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
Third-generation HapMap
The International HapMap Consortium, established to develop a haplotype map of the human genome describing the common patterns of DNA sequence variation, has now reached its third incarnation. HapMap1, published in 2005 (go.nature.com/gJisDm), contained more than a million SNP (single nucleotide polymorphism) genotypes generated in 269 individuals from four geographically diverse populations. Two years later, HapMap2 (go.nature.com/WttNWX) added more than 2.1 million SNPs to the original map in the same 269 individuals. With the aim of providing a resource for the latest wave of genome-wide studies focused on disease linkages, HapMap3 casts the net wider. About 1.6 million common SNPs were genotyped in 1,184 individuals from 11 global populations, and ten 100-kilobase regions were sequenced in 692 of these individuals.
Here, the analysis of 'HapMap 3' is reported — a public data set of genomic variants in human populations. The resource integrates common and rare single nucleotide polymorphisms (SNPs) and copy number polymorphisms (CNPs) from 11 global populations, providing insights into population-specific differences among variants. It also demonstrates the feasibility of imputing newly discovered rare SNPs and CNPs.</description><subject>631/1647/1513/2192</subject><subject>631/208/205/2138</subject><subject>631/208/212</subject><subject>631/208/457/649</subject><subject>Algorithms</subject><subject>DNA Copy Number Variations</subject><subject>Genetic diversity</subject><subject>Genetic testing</subject><subject>Genetic variance</subject><subject>Genetic variation</subject><subject>Genetics</subject><subject>Genome, Human</subject><subject>Genomics</subject><subject>Human genome</subject><subject>Human Genome Project</subject><subject>Human populations</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>multidisciplinary</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population Groups - genetics</subject><subject>Quality control</subject><subject>Science</subject><subject>Science 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common and rare genetic variation in diverse human populations</title><author>Altshuler, David M ; Gibbs, Richard A ; Peltonen, Leena ; Dermitzakis, Emmanouil ; Schaffner, Stephen F ; Yu, Fuli ; Bonnen, Penelope E ; de Bakker, Paul I W ; Deloukas, Panos ; Gabriel, Stacey B ; Gwilliam, Rhian ; Hunt, Sarah ; Inouye, Michael ; Jia, Xiaoming ; Palotie, Aarno ; Parkin, Melissa ; Whittaker, Pamela ; Chang, Kyle ; Hawes, Alicia ; Lewis, Lora R ; Ren, Yanru ; Wheeler, David ; Muzny, Donna Marie ; Barnes, Chris ; Darvishi, Katayoon ; Hurles, Matthew ; Korn, Joshua M ; Kristiansson, Kati ; Lee, Charles ; McCarrol, Steven A ; Nemesh, James ; Keinan, Alon ; Montgomery, Stephen B ; Pollack, Samuela ; Price, Alkes L ; Soranzo, Nicole ; Gonzaga-Jauregui, Claudia ; Anttila, Verneri ; Brodeur, Wendy ; Daly, Mark J ; Leslie, Stephen ; McVean, Gil ; Moutsianas, Loukas ; Nguyen, Huy ; Zhang, Qingrun ; Ghori, Mohammed J R ; McGinnis, Ralph ; McLaren, William ; Takeuchi, Fumihiko ; Grossman, Sharon R ; Shlyakhter, Ilya ; Hostetter, Elizabeth B ; Sabeti, Pardis C ; Adebamowo, Clement A ; Foster, Morris W ; Gordon, Deborah R ; Licinio, Julio ; Manca, Maria Cristina ; Marshall, Patricia A ; Matsuda, Ichiro ; Ngare, Duncan ; Wang, Vivian Ota ; Reddy, Deepa ; Rotimi, Charles N ; Royal, Charmaine D ; Sharp, Richard R ; Zeng, Changqing ; Brooks, Lisa D ; McEwen, Jean E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c676t-b95be9ac32ad644600cebea7f00ea535db288b6dba44e624891fe199db7485113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>631/1647/1513/2192</topic><topic>631/208/205/2138</topic><topic>631/208/212</topic><topic>631/208/457/649</topic><topic>Algorithms</topic><topic>DNA Copy Number Variations</topic><topic>Genetic diversity</topic><topic>Genetic testing</topic><topic>Genetic variance</topic><topic>Genetic variation</topic><topic>Genetics</topic><topic>Genome, Human</topic><topic>Genomics</topic><topic>Human genome</topic><topic>Human Genome Project</topic><topic>Human populations</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>multidisciplinary</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Population Groups - genetics</topic><topic>Quality control</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Altshuler, David M</creatorcontrib><creatorcontrib>Gibbs, Richard A</creatorcontrib><creatorcontrib>Peltonen, Leena</creatorcontrib><creatorcontrib>Dermitzakis, Emmanouil</creatorcontrib><creatorcontrib>Schaffner, Stephen F</creatorcontrib><creatorcontrib>Yu, Fuli</creatorcontrib><creatorcontrib>Bonnen, Penelope E</creatorcontrib><creatorcontrib>de Bakker, Paul I W</creatorcontrib><creatorcontrib>Deloukas, Panos</creatorcontrib><creatorcontrib>Gabriel, Stacey 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International HapMap 3 Consortium</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and 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Edition</collection><collection>ProQuest One Psychology</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>University of Michigan</collection><collection>Genetics Abstracts</collection><collection>SIRS Editorial</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nature (London)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Altshuler, David M</au><au>Gibbs, Richard A</au><au>Peltonen, Leena</au><au>Dermitzakis, Emmanouil</au><au>Schaffner, Stephen F</au><au>Yu, Fuli</au><au>Bonnen, Penelope E</au><au>de Bakker, Paul I W</au><au>Deloukas, Panos</au><au>Gabriel, Stacey B</au><au>Gwilliam, Rhian</au><au>Hunt, Sarah</au><au>Inouye, Michael</au><au>Jia, Xiaoming</au><au>Palotie, Aarno</au><au>Parkin, Melissa</au><au>Whittaker, Pamela</au><au>Chang, Kyle</au><au>Hawes, Alicia</au><au>Lewis, Lora R</au><au>Ren, Yanru</au><au>Wheeler, David</au><au>Muzny, Donna Marie</au><au>Barnes, Chris</au><au>Darvishi, Katayoon</au><au>Hurles, Matthew</au><au>Korn, Joshua M</au><au>Kristiansson, Kati</au><au>Lee, Charles</au><au>McCarrol, Steven A</au><au>Nemesh, James</au><au>Keinan, Alon</au><au>Montgomery, Stephen B</au><au>Pollack, Samuela</au><au>Price, Alkes L</au><au>Soranzo, Nicole</au><au>Gonzaga-Jauregui, Claudia</au><au>Anttila, Verneri</au><au>Brodeur, Wendy</au><au>Daly, Mark J</au><au>Leslie, Stephen</au><au>McVean, Gil</au><au>Moutsianas, Loukas</au><au>Nguyen, Huy</au><au>Zhang, Qingrun</au><au>Ghori, Mohammed J R</au><au>McGinnis, Ralph</au><au>McLaren, William</au><au>Takeuchi, Fumihiko</au><au>Grossman, Sharon R</au><au>Shlyakhter, Ilya</au><au>Hostetter, Elizabeth B</au><au>Sabeti, Pardis C</au><au>Adebamowo, Clement A</au><au>Foster, Morris W</au><au>Gordon, Deborah R</au><au>Licinio, Julio</au><au>Manca, Maria Cristina</au><au>Marshall, Patricia A</au><au>Matsuda, Ichiro</au><au>Ngare, Duncan</au><au>Wang, Vivian Ota</au><au>Reddy, Deepa</au><au>Rotimi, Charles N</au><au>Royal, Charmaine D</au><au>Sharp, Richard R</au><au>Zeng, Changqing</au><au>Brooks, Lisa D</au><au>McEwen, Jean E</au><aucorp>International HapMap 3 Consortium</aucorp><aucorp>The International HapMap 3 Consortium</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating common and rare genetic variation in diverse human populations</atitle><jtitle>Nature (London)</jtitle><stitle>Nature</stitle><addtitle>Nature</addtitle><date>2010-09-02</date><risdate>2010</risdate><volume>467</volume><issue>7311</issue><spage>52</spage><epage>58</epage><pages>52-58</pages><issn>0028-0836</issn><eissn>1476-4687</eissn><coden>NATUAS</coden><abstract>Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called ‘HapMap 3’, includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of ≤5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
Third-generation HapMap
The International HapMap Consortium, established to develop a haplotype map of the human genome describing the common patterns of DNA sequence variation, has now reached its third incarnation. HapMap1, published in 2005 (go.nature.com/gJisDm), contained more than a million SNP (single nucleotide polymorphism) genotypes generated in 269 individuals from four geographically diverse populations. Two years later, HapMap2 (go.nature.com/WttNWX) added more than 2.1 million SNPs to the original map in the same 269 individuals. With the aim of providing a resource for the latest wave of genome-wide studies focused on disease linkages, HapMap3 casts the net wider. About 1.6 million common SNPs were genotyped in 1,184 individuals from 11 global populations, and ten 100-kilobase regions were sequenced in 692 of these individuals.
Here, the analysis of 'HapMap 3' is reported — a public data set of genomic variants in human populations. The resource integrates common and rare single nucleotide polymorphisms (SNPs) and copy number polymorphisms (CNPs) from 11 global populations, providing insights into population-specific differences among variants. It also demonstrates the feasibility of imputing newly discovered rare SNPs and CNPs.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>20811451</pmid><doi>10.1038/nature09298</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0028-0836 |
| ispartof | Nature (London), 2010-09, Vol.467 (7311), p.52-58 |
| issn | 0028-0836 1476-4687 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3173859 |
| source | MEDLINE; SpringerLink Journals; Nature Journals Online |
| subjects | 631/1647/1513/2192 631/208/205/2138 631/208/212 631/208/457/649 Algorithms DNA Copy Number Variations Genetic diversity Genetic testing Genetic variance Genetic variation Genetics Genome, Human Genomics Human genome Human Genome Project Human populations Humanities and Social Sciences Humans multidisciplinary Polymorphism, Single Nucleotide Population Groups - genetics Quality control Science Science (multidisciplinary) |
| title | Integrating common and rare genetic variation in diverse human populations |
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