Genome-Wide Identification of Expression Quantitative Trait Loci (eQTLs) in Human Heart
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{"title"=>"Genome-wide identification of expression Quantitative Trait Loci (eQTLs) in human heart", "type"=>"journal", "authors"=>[{"first_name"=>"Tamara T.", "last_name"=>"Koopmann", "scopus_author_id"=>"8628911700"}, {"first_name"=>"Michiel E.", "last_name"=>"Adriaens", "scopus_author_id"=>"24721068600"}, {"first_name"=>"Perry D.", "last_name"=>"Moerland", "scopus_author_id"=>"15065640700"}, {"first_name"=>"Roos F.", "last_name"=>"Marsman", "scopus_author_id"=>"35186321800"}, {"first_name"=>"Margriet L.", "last_name"=>"Westerveld", "scopus_author_id"=>"56178509400"}, {"first_name"=>"Sean", "last_name"=>"Lal", "scopus_author_id"=>"7203074949"}, {"first_name"=>"Taifang", "last_name"=>"Zhang", "scopus_author_id"=>"56137718700"}, {"first_name"=>"Christine Q.", "last_name"=>"Simmons", "scopus_author_id"=>"8063273200"}, {"first_name"=>"Istvan", "last_name"=>"Baczko", "scopus_author_id"=>"6602567705"}, {"first_name"=>"Cristobal", "last_name"=>"Dos Remedios", "scopus_author_id"=>"56033158200"}, {"first_name"=>"Nanette H.", "last_name"=>"Bishopric", "scopus_author_id"=>"7004474058"}, {"first_name"=>"Andras", "last_name"=>"Varro", "scopus_author_id"=>"7004541739"}, {"first_name"=>"Alfred L.", "last_name"=>"George", "scopus_author_id"=>"7402526731"}, {"first_name"=>"Elisabeth M.", "last_name"=>"Lodder", "scopus_author_id"=>"55174619400"}, {"first_name"=>"Connie R.", "last_name"=>"Bezzina", "scopus_author_id"=>"56770964300"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84901340791", "sgr"=>"84901340791", "pui"=>"373160836", "isbn"=>"1932-6203; 1932-6203", "pmid"=>"24846176", "doi"=>"10.1371/journal.pone.0097380"}, "id"=>"46c32ae5-79b7-35c0-b5d2-7998437f7102", "abstract"=>"In recent years genome-wide association studies (GWAS) have uncovered numerous chromosomal loci associated with various electrocardiographic traits and cardiac arrhythmia predisposition. A considerable fraction of these loci lie within inter-genic regions. The underlying trait-associated variants likely reside in regulatory regions and exert their effect by modulating gene expression. Hence, the key to unraveling the molecular mechanisms underlying these cardiac traits is to interrogate variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis. In this study we conducted an eQTL analysis of human heart. For a total of 129 left ventricular samples that were collected from non-diseased human donor hearts, genome-wide transcript abundance and genotyping was determined using microarrays. Each of the 18,402 transcripts and 897,683 SNP genotypes that remained after pre-processing and stringent quality control were tested for eQTL effects. We identified 771 eQTLs, regulating 429 unique transcripts. Overlaying these eQTLs with cardiac GWAS loci identified novel candidates for studies aimed at elucidating the functional and transcriptional impact of these loci. Thus, this work provides for the first time a comprehensive eQTL map of human heart: a powerful and unique resource that enables systems genetics approaches for the study of cardiac traits.", "link"=>"http://www.mendeley.com/research/genomewide-identification-expression-quantitative-trait-loci-eqtls-human-heart-2", "reader_count"=>44, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Researcher"=>9, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>1, "Student > Master"=>8, "Student > Bachelor"=>2, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Researcher"=>9, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>1, "Student > Master"=>8, "Student > Bachelor"=>2, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>9, "Medicine and Dentistry"=>8, "Agricultural and Biological Sciences"=>21, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Chemistry"=>1, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Chemistry"=>{"Chemistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>21}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>9}, "Unspecified"=>{"Unspecified"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>2}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1504131"], "description"=>"<p>The MAF and beta (effect size per copy of the minor allele) for the most significant SNP of each cluster is listed. LD  =  linkage disequilibrium, TSS  =  transcription start site, Chr.  =  chromosome.</p>", "links"=>[], "tags"=>["Evolutionary biology", "population genetics", "genetics", "Heredity", "Quantitative traits", "cardiology", "mathematics", "Statistics (mathematics)", "Biostatistics", "30", "ld-pruned", "snp", "clusters", "materials"], "article_id"=>1031784, "categories"=>["Biological Sciences"], "users"=>["Tamara T. Koopmann", "Michiel E. Adriaens", "Perry D. Moerland", "Roos F. Marsman", "Margriet L. Westerveld", "Sean Lal", "Taifang Zhang", "Christine Q. Simmons", "István Baczkó", "Cristobal dos Remedios", "Nanette H. Bishopric", "András Varró", "Alfred L. George Jr", "Elisabeth M. Lodder", "Connie R. Bezzina"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0097380.t001", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_the_30_most_significant_cis_eQTLs_reported_as_independent_LD_pruned_SNP_clusters_see_Materials_Methods_/1031784", "title"=>"Overview of the 30 most significant <i>cis</i> eQTLs, reported as independent LD-pruned SNP clusters (see Materials & Methods).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-20 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1504129"], "description"=>"<p>An overview of the 4 most significant <i>cis</i> eQTLs: rs11150882 with <i>C17orf97</i> (panel A), rs11158569 with <i>CHURC1</i> (panel B), rs2779212 with <i>ZSWIM7</i> (panel C) and rs2549794 with <i>ERAP2</i> (panel D). On the left of each panel, box-and-whisker plots of mRNA levels for all genotypes. On the right, mean and standard-error plots of mRNA levels for all genotypes are illustrated. Right upper corner gives the association p-value and the gene name.</p>", "links"=>[], "tags"=>["Evolutionary biology", "population genetics", "genetics", "Heredity", "Quantitative traits", "cardiology", "mathematics", "Statistics (mathematics)", "Biostatistics"], "article_id"=>1031782, "categories"=>["Biological Sciences"], "users"=>["Tamara T. Koopmann", "Michiel E. Adriaens", "Perry D. Moerland", "Roos F. Marsman", "Margriet L. Westerveld", "Sean Lal", "Taifang Zhang", "Christine Q. Simmons", "István Baczkó", "Cristobal dos Remedios", "Nanette H. Bishopric", "András Varró", "Alfred L. George Jr", "Elisabeth M. Lodder", "Connie R. Bezzina"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0097380.g001", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_plots_for_top_cis_eQTLs_/1031782", "title"=>"Overview plots for top <i>cis</i> eQTLs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-20 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1504132"], "description"=>"<p>Overview of eQTL effects of reported cardiac electric trait related GWAS SNPs. Only GWAS SNPs reaching genome-wide significance as stated in the original studies (p-value ≤5×10<sup>−8</sup>) and with nominal eQTL association (p≤0.05) are reported. This resulted in 34 independent loci. <i>PRKCA</i> (<i>rs9912468</i>, QRS duration) reaches genome-wide significance (4×10<sup>−8</sup>; represented in bold in table). The beta is defined as the effect size per copy of the minor allele. LD  =  linkage disequilibrium, TSS  =  transcription start site, Chr.  =  chromosome, Y  =  yes, N  =  no.</p>", "links"=>[], "tags"=>["Evolutionary biology", "population genetics", "genetics", "Heredity", "Quantitative traits", "cardiology", "mathematics", "Statistics (mathematics)", "Biostatistics", "snps", "cardiac", "GWAS", "eqtl"], "article_id"=>1031785, "categories"=>["Biological Sciences"], "users"=>["Tamara T. Koopmann", "Michiel E. Adriaens", "Perry D. Moerland", "Roos F. Marsman", "Margriet L. Westerveld", "Sean Lal", "Taifang Zhang", "Christine Q. Simmons", "István Baczkó", "Cristobal dos Remedios", "Nanette H. Bishopric", "András Varró", "Alfred L. George Jr", "Elisabeth M. Lodder", "Connie R. Bezzina"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0097380.t002", "stats"=>{"downloads"=>5, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Look_up_of_SNPs_from_cardiac_GWAS_in_eQTL_data_/1031785", "title"=>"Look-up of SNPs from cardiac GWAS in eQTL data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-20 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1504133", "https://ndownloader.figshare.com/files/1504134", "https://ndownloader.figshare.com/files/1504135"], "description"=>"<div><p>In recent years genome-wide association studies (GWAS) have uncovered numerous chromosomal loci associated with various electrocardiographic traits and cardiac arrhythmia predisposition. A considerable fraction of these loci lie within inter-genic regions. The underlying trait-associated variants likely reside in regulatory regions and exert their effect by modulating gene expression. Hence, the key to unraveling the molecular mechanisms underlying these cardiac traits is to interrogate variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis. In this study we conducted an eQTL analysis of human heart. For a total of 129 left ventricular samples that were collected from non-diseased human donor hearts, genome-wide transcript abundance and genotyping was determined using microarrays. Each of the 18,402 transcripts and 897,683 SNP genotypes that remained after pre-processing and stringent quality control were tested for eQTL effects. We identified 771 eQTLs, regulating 429 unique transcripts. Overlaying these eQTLs with cardiac GWAS loci identified novel candidates for studies aimed at elucidating the functional and transcriptional impact of these loci. Thus, this work provides for the first time a comprehensive eQTL map of human heart: a powerful and unique resource that enables systems genetics approaches for the study of cardiac traits.</p></div>", "links"=>[], "tags"=>["Evolutionary biology", "population genetics", "genetics", "Heredity", "Quantitative traits", "cardiology", "mathematics", "Statistics (mathematics)", "Biostatistics", "quantitative", "loci"], "article_id"=>1031786, "categories"=>["Biological Sciences"], "users"=>["Tamara T. Koopmann", "Michiel E. Adriaens", "Perry D. Moerland", "Roos F. Marsman", "Margriet L. Westerveld", "Sean Lal", "Taifang Zhang", "Christine Q. Simmons", "István Baczkó", "Cristobal dos Remedios", "Nanette H. Bishopric", "András Varró", "Alfred L. George Jr", "Elisabeth M. Lodder", "Connie R. Bezzina"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0097380.s001", "https://dx.doi.org/10.1371/journal.pone.0097380.s002", "https://dx.doi.org/10.1371/journal.pone.0097380.s003"], "stats"=>{"downloads"=>11, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genome_Wide_Identification_of_Expression_Quantitative_Trait_Loci_eQTLs_in_Human_Heart_/1031786", "title"=>"Genome-Wide Identification of Expression Quantitative Trait Loci (eQTLs) in Human Heart", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-05-20 02:51:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1504130"], "description"=>"<p>An overview of 4 GWAS <i>cis</i> eQTLs: rs9912468 with <i>PRKCA</i> (panel A), rs7912445 with <i>GNB4</i> (panel B), rs8049607 with <i>LITAF</i> (panel C) and rs6882776 with <i>NKX2-5</i> (panel D). On the left of each panel, box-and-whisker plots of mRNA levels for all genotypes. On the right, mean and standard-error plots of mRNA levels for all genotypes are illustrated. Right upper corner gives the association p-value and the gene name.</p>", "links"=>[], "tags"=>["Evolutionary biology", "population genetics", "genetics", "Heredity", "Quantitative traits", "cardiology", "mathematics", "Statistics (mathematics)", "Biostatistics", "overview", "cardiac", "GWAS"], "article_id"=>1031783, "categories"=>["Biological Sciences"], "users"=>["Tamara T. Koopmann", "Michiel E. Adriaens", "Perry D. Moerland", "Roos F. Marsman", "Margriet L. Westerveld", "Sean Lal", "Taifang Zhang", "Christine Q. Simmons", "István Baczkó", "Cristobal dos Remedios", "Nanette H. Bishopric", "András Varró", "Alfred L. George Jr", "Elisabeth M. Lodder", "Connie R. Bezzina"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0097380.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_eQTL_overview_plots_for_4_cardiac_trait_GWAS_candidate_genes_/1031783", "title"=>"eQTL overview plots for 4 cardiac trait GWAS candidate genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-20 02:51:07"}

PMC Usage Stats | Further Information

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Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Computational biology", "average_usage"=>[341, 529]}, {"subject_area"=>"/Biology and life sciences/Evolutionary biology", "average_usage"=>[333]}]}
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Net::HTTPInternalServerError

Source
Scopus
Time
2019-09-07 18:10:12 UTC
Target URL
https://api.elsevier.com/content/search/index:SCOPUS?query=DOI(10.1371%2Fjournal.pone.0097380)
Trace

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/app/jobs/source_job.rb:35:in `perform'