Integrative analysis of low- and high-resolution eQTL
The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. Power and genetic resolution are heavily affected by the study population: whereas recombinan...
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| Veröffentlicht in: | PloS one 2010-11, Vol.5 (11), p.e13920-e13920 |
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| creator | Loguercio, Salvatore Overall, Rupert W Michaelson, Jacob J Wiltshire, Tim Pletcher, Mathew T Miller, Brooke H Walker, John R Kempermann, Gerd Su, Andrew I Beyer, Andreas |
| description | The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. Power and genetic resolution are heavily affected by the study population: whereas recombinant inbred (RI) strains yield greater statistical power with low genetic resolution, using diverse inbred or outbred strains improves genetic resolution at the cost of lower power. In order to overcome the limitations of both individual approaches, we combine data from RI strains with genetically more diverse strains and analyze hippocampus eQTL data obtained from mouse RI strains (BXD) and from a panel of diverse inbred strains (Mouse Diversity Panel, MDP). We perform a systematic analysis of the consistency of eQTL independently obtained from these two populations and demonstrate that a significant fraction of eQTL can be replicated. Based on existing knowledge from pathway databases we assess different approaches for using the high-resolution MDP data for fine mapping BXD eQTL. Finally, we apply this framework to an eQTL hotspot on chromosome 1 (Qrr1), which has been implicated in a range of neurological traits. Here we present the first systematic examination of the consistency between eQTL obtained independently from the BXD and MDP populations. Our analysis of fine-mapping approaches is based on 'real life' data as opposed to simulated data and it allows us to propose a strategy for using MDP data to fine map BXD eQTL. Application of this framework to Qrr1 reveals that this eQTL hotspot is not caused by just one (or few) 'master regulators', but actually by a set of polymorphic genes specific to the central nervous system. |
| doi_str_mv | 10.1371/journal.pone.0013920 |
| format | Article |
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Power and genetic resolution are heavily affected by the study population: whereas recombinant inbred (RI) strains yield greater statistical power with low genetic resolution, using diverse inbred or outbred strains improves genetic resolution at the cost of lower power. In order to overcome the limitations of both individual approaches, we combine data from RI strains with genetically more diverse strains and analyze hippocampus eQTL data obtained from mouse RI strains (BXD) and from a panel of diverse inbred strains (Mouse Diversity Panel, MDP). We perform a systematic analysis of the consistency of eQTL independently obtained from these two populations and demonstrate that a significant fraction of eQTL can be replicated. Based on existing knowledge from pathway databases we assess different approaches for using the high-resolution MDP data for fine mapping BXD eQTL. Finally, we apply this framework to an eQTL hotspot on chromosome 1 (Qrr1), which has been implicated in a range of neurological traits. Here we present the first systematic examination of the consistency between eQTL obtained independently from the BXD and MDP populations. Our analysis of fine-mapping approaches is based on 'real life' data as opposed to simulated data and it allows us to propose a strategy for using MDP data to fine map BXD eQTL. Application of this framework to Qrr1 reveals that this eQTL hotspot is not caused by just one (or few) 'master regulators', but actually by a set of polymorphic genes specific to the central nervous system.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0013920</identifier><identifier>PMID: 21085707</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acids ; Algorithms ; Analysis ; Animals ; Artificial chromosomes ; Bioinformatics ; Biotechnology ; Central nervous system ; Chromosome 1 ; Chromosome Mapping - methods ; Chromosomes, Mammalian - genetics ; Computational Biology/Systems Biology ; Computational Biology/Transcriptional Regulation ; Consistency ; Data processing ; Databases, Genetic ; Drug therapy ; Female ; Gene expression ; Gene Expression Profiling ; Gene mapping ; Genes ; Genetic diversity ; Genetic transcription ; Genetics and Genomics/Complex Traits ; Genetics and Genomics/Gene Expression ; Genetics and Genomics/Population Genetics ; Genome - genetics ; Genomes ; Genomics ; Haplotypes ; High resolution ; Hot spots ; Inbreeding ; Male ; Mapping ; Methods ; Mice ; Mice, Inbred Strains ; Population (statistical) ; Population studies ; Proteins ; Quantitative genetics ; Quantitative trait loci ; Quantitative Trait Loci - genetics ; R&D ; Recombinant ; Regulators ; Research & development ; Studies ; Transcription</subject><ispartof>PloS one, 2010-11, Vol.5 (11), p.e13920-e13920</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>2010 Loguercio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Loguercio et al. 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-cc6136813584722a4085f04caaf668b7313594676577dfcb3a9d4deee12ef4573</citedby><cites>FETCH-LOGICAL-c691t-cc6136813584722a4085f04caaf668b7313594676577dfcb3a9d4deee12ef4573</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/PMC2978079/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978079/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21085707$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Aziz, Ramy K.</contributor><creatorcontrib>Loguercio, Salvatore</creatorcontrib><creatorcontrib>Overall, Rupert W</creatorcontrib><creatorcontrib>Michaelson, Jacob J</creatorcontrib><creatorcontrib>Wiltshire, Tim</creatorcontrib><creatorcontrib>Pletcher, Mathew T</creatorcontrib><creatorcontrib>Miller, Brooke H</creatorcontrib><creatorcontrib>Walker, John R</creatorcontrib><creatorcontrib>Kempermann, Gerd</creatorcontrib><creatorcontrib>Su, Andrew I</creatorcontrib><creatorcontrib>Beyer, Andreas</creatorcontrib><title>Integrative analysis of low- and high-resolution eQTL</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. 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| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2010-11, Vol.5 (11), p.e13920-e13920 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1295201452 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Acids Algorithms Analysis Animals Artificial chromosomes Bioinformatics Biotechnology Central nervous system Chromosome 1 Chromosome Mapping - methods Chromosomes, Mammalian - genetics Computational Biology/Systems Biology Computational Biology/Transcriptional Regulation Consistency Data processing Databases, Genetic Drug therapy Female Gene expression Gene Expression Profiling Gene mapping Genes Genetic diversity Genetic transcription Genetics and Genomics/Complex Traits Genetics and Genomics/Gene Expression Genetics and Genomics/Population Genetics Genome - genetics Genomes Genomics Haplotypes High resolution Hot spots Inbreeding Male Mapping Methods Mice Mice, Inbred Strains Population (statistical) Population studies Proteins Quantitative genetics Quantitative trait loci Quantitative Trait Loci - genetics R&D Recombinant Regulators Research & development Studies Transcription |
| title | Integrative analysis of low- and high-resolution eQTL |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T13%3A26%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Integrative%20analysis%20of%20low-%20and%20high-resolution%20eQTL&rft.jtitle=PloS%20one&rft.au=Loguercio,%20Salvatore&rft.date=2010-11-10&rft.volume=5&rft.issue=11&rft.spage=e13920&rft.epage=e13920&rft.pages=e13920-e13920&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0013920&rft_dat=%3Cgale_plos_%3EA473834858%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1295201452&rft_id=info:pmid/21085707&rft_galeid=A473834858&rft_doaj_id=oai_doaj_org_article_e1e6da615c0c494e9bd37ca5ba88ea12&rfr_iscdi=true |