{"doi":"10.1016/j.ajhg.2017.01.026","title":"The Genetic Architecture of Gene Expression in Peripheral Blood","abstract":null,"journal":"The American Journal of Human Genetics","year":2017,"id":592028,"datarank":2.7372126913904173,"base_score":4.442651256490317,"endowment":4.442651256490317,"self_citation_contribution":0.6663976884735476,"citation_network_contribution":2.0708150029168695,"self_endowment_contribution":0.6663976884735476,"citer_contribution":2.0708150029168695,"corpus_percentile":null,"corpus_rank":null,"citation_count":84,"citer_count":67,"citers_with_citation_signal":53,"citers_with_endowment":53,"datacite_reuse_total":2,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1514829,"name":"Alexander Holloway","orcid":null,"position":1,"is_corresponding":false},{"id":1382223,"name":"Allan McRae","orcid":null,"position":2,"is_corresponding":false},{"id":897208,"name":"Jian Yang","orcid":"0000-0003-3281-8803","position":3,"is_corresponding":false},{"id":1514830,"name":"Kerrin Small","orcid":null,"position":4,"is_corresponding":false},{"id":401957,"name":"Jing Zhao","orcid":"0000-0001-5576-644X","position":5,"is_corresponding":false},{"id":1086423,"name":"Biao Zeng","orcid":"0000-0003-1974-5806","position":6,"is_corresponding":false},{"id":374280,"name":"Andrew Bakshi","orcid":"0000-0001-5650-7036","position":7,"is_corresponding":false},{"id":213776,"name":"Andres Metspalu","orcid":"0000-0002-3718-796X","position":8,"is_corresponding":false},{"id":1136375,"name":"Manolis Dermitzakis","orcid":null,"position":9,"is_corresponding":false},{"id":24173,"name":"Greg Gibson","orcid":"0000-0002-5352-5877","position":10,"is_corresponding":false},{"id":1514831,"name":"Tim Spector","orcid":null,"position":11,"is_corresponding":false},{"id":1514832,"name":"Grant Montgomery","orcid":null,"position":12,"is_corresponding":false},{"id":21664,"name":"Tonu Esko","orcid":null,"position":13,"is_corresponding":false},{"id":5308,"name":"Peter M. Visscher","orcid":"0000-0002-2143-8760","position":14,"is_corresponding":false},{"id":12165,"name":"Joseph E. Powell","orcid":"0000-0002-5070-4124","position":15,"is_corresponding":false},{"id":1514828,"name":"Luke R. Lloyd-Jones","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"The Genetic Architecture of Gene Expression in Peripheral Blood","abstract":"We analyzed the mRNA levels for 36,778 transcript expression traits (probes) from 2,765 individuals to comprehensively investigate the genetic architecture and degree of missing heritability for gene expression in peripheral blood. We identified 11,204 cis and 3,791 trans independent expression quantitative trait loci (eQTL) by using linear mixed models to perform genome-wide association analyses. Furthermore, using information on both closely and distantly related individuals, heritability was estimated for all expression traits. Of the set of expressed probes (15,966), 10,580 (66%) had an estimated narrow-sense heritability (h2) greater than zero with a mean (median) value of 0.192 (0.142). Across these probes, on average the proportion of genetic variance explained by all eQTL (hCOJO2) was 31% (0.060/0.192), meaning that 69% is missing, with the sentinel SNP of the largest eQTL explaining 87% (0.052/0.060) of the variance attributed to all identified cis- and trans-eQTL. For the same set of probes, the genetic variance attributed to genome-wide common (MAF > 0.01) HapMap 3 SNPs (hg2) accounted for on average 48% (0.093/0.192) of h2. Taken together, the evidence suggests that approximately half the genetic variance for gene expression is not tagged by common SNPs, and of the variance that is tagged by common SNPs, a large proportion can be attributed to identifiable eQTL of large effect, typically in cis. Finally, we present evidence that, compared with a meta-analysis, using individual-level data results in an increase of approximately 50% in power to detect eQTL.","is_dataset_classified":null,"base_score":4.442651256490317,"endowment":4.442651256490317,"datacite_reuse_total":2,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"28157541","pmcid":"PMC5802995","openalex_id":"https://openalex.org/W2784630408","authors":[],"funders":[{"funder_name":"European Commission","grant_id":"692145","title":"Rise of scientific excellence and collaboration for implementing personalised medicine in Estonia"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1078399","title":"Translating gene discovery for key diseases into clinical outcomes"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1083405","title":"Determining shared genetic control of RNA transcription across 45 human tissue types"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1107599","title":"Control of genome regulation and its role in human disease"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1078037","title":"Neurogenetics and Statistical Genomics"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1083656","title":"Genetics of DNA Methylation and Its Role in Disease Susecptibility"},{"funder_name":"National Health and Medical Research Council (NHMRC)","grant_id":"1046880","title":"CAGE: Consortium for the Architecture of Gene Expression"}],"total_grants":7,"fwci":6.0076,"citation_percentile":0.96374481,"influential_citations":9,"citation_trend":[{"year":2016,"count":2},{"year":2017,"count":4},{"year":2018,"count":10},{"year":2019,"count":6},{"year":2020,"count":10},{"year":2021,"count":7},{"year":2022,"count":8},{"year":2023,"count":13},{"year":2024,"count":10},{"year":2025,"count":9},{"year":2026,"count":5}],"oa_status":"bronze","license":"Elsevier TDM","oa_locations":[{"url":"http://www.cell.com/article/S0002929717300277/pdf","host_type":"journal"},{"url":"http://www.cell.com/article/S0002929717300277/pdf","host_type":"BRONZE"},{"url":"http://www.cell.com/article/S0002929717300277/pdf","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0002929717300277?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0002929717300277?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.ajhg.2017.01.026","host_type":"journal"},{"url":"https://doi.org/10.1016/j.ajhg.2016.12.008","host_type":""},{"url":"http://www.cell.com/article/S0002929716305328/pdf","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/28065468","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/28157541","host_type":""},{"url":"https://espace.library.uq.edu.au/view/UQ:418051","host_type":""},{"url":"https://api.library.uq.edu.au/view/UQ:418051","host_type":""},{"url":"https://dx.doi.org/10.1016/j.ajhg.2016.12.008","host_type":""},{"url":"https://sonar.ch/global/documents/242654","host_type":""},{"url":"http://dx.doi.org/10.1016/j.ajhg.2017.01.026","host_type":""},{"url":"https://doi.org/https://doi.org/10.1016/j.ajhg.2016.12.008","host_type":""}],"fields_of_study":["Genetic Mapping and Diversity in Plants and Animals","Medicine","Biology","0301 basic medicine","03 medical and health sciences","0303 health sciences"],"mesh_terms":[],"keywords":["Expression quantitative trait loci","Genetic architecture","Heritability","Biology","Trait","Gene","Genome-wide association study","Missing heritability problem","Peripheral blood","Genetics","Gene expression","Quantitative trait locus","Expression (computer science)","Computational biology","Evolutionary biology","Genetic variants","Computer science","Single-nucleotide polymorphism","Genotype","Immunology","2716 Genetics (clinical)","Linear mixed models","Quantitative Trait Loci","Inheritance Patterns","610","612","HapMap Project","Polymorphism, Single Nucleotide","Linkage Disequilibrium","576","1311 Genetics","Humans","RNA, Messenger","Genetic Association Studies","Genetic association study","Models, Genetic","Genome, Human","Phenotype","Linear Models"],"sdg_mappings":[{"sdg_number":10,"sdg_label":"10. 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