<HashMap><database>EGA</database><scores/><additional><omics_type>Genomics</omics_type><dataset_type>Ilumina HumanHap550-2v3_B-Beadstudio</dataset_type><full_dataset_link>https://ega-archive.org/datasets/EGAD00000000027</full_dataset_link><sample_count>176</sample_count><description>EGA dataset EGAD00000000027</description><repository>EGA</repository><title>Title not provided</title><pubmed_abstract>MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression.</pubmed_abstract><pubmed_abstract>Studies correlating genetic variation to gene expression facilitate the interpretation of common human phenotypes and disease. As functional variants may be operating in a tissue-dependent manner, we performed gene expression profiling and association with genetic variants (single-nucleotide polymorphisms) on three cell types of 75 individuals. We detected cell type-specific genetic effects, with 69 to 80% of regulatory variants operating in a cell type-specific manner, and identified multiple expressive quantitative trait loci (eQTLs) per gene, unique or shared among cell types and positively correlated with the number of transcripts per gene. Cell type-specific eQTLs were found at larger distances from genes and at lower effect size, similar to known enhancers. These data suggest that the complete regulatory variant repertoire can only be uncovered in the context of cell-type specificity.</pubmed_abstract><pubmed_title>Common regulatory variation impacts gene expression in a cell type-dependent manner.</pubmed_title><pubmed_title>Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts.</pubmed_title><pubmed_authors>Borel Christelle C, Deutsch Samuel S, Letourneau Audrey A, Migliavacca Eugenia E, Montgomery Stephen B SB, Dimas Antigone S AS, Vejnar Charles E CE, Attar Homa H, Gagnebin Maryline M, Gehrig Corinne C, Falconnet Emilie E, Dupré Yann Y, Dermitzakis Emmanouil T ET, Antonarakis Stylianos E SE</pubmed_authors><pubmed_authors>Dimas Antigone S AS, Deutsch Samuel S, Stranger Barbara E BE, Montgomery Stephen B SB, Borel Christelle C, Attar-Cohen Homa H, Ingle Catherine C, Beazley Claude C, Gutierrez Arcelus Maria M, Sekowska Magdalena M, Gagnebin Marilyne M, Nisbett James J, Deloukas Panos P, Dermitzakis Emmanouil T ET, Antonarakis Stylianos E SE</pubmed_authors></additional><is_claimable>false</is_claimable><name>EGAD00000000027</name><description>eQTL data for European newborns</description><dates><updated>2017-07-26 15:39:24</updated></dates><accession>EGAD00000000027</accession><cross_references><TAXONOMY>9606</TAXONOMY><pubmed>21147911</pubmed><pubmed>19644074</pubmed><EGA>EGAC00001000105</EGA><EGA>EGAS00000000056</EGA></cross_references></HashMap>