<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Nathan A</submitter><funding>NIAID NIH HHS</funding><funding>NHGRI NIH HHS</funding><funding>NIAMS NIH HHS</funding><pagination>120-128</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9842455</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>606(7912)</volume><pubmed_abstract>Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells&lt;sup>1,2&lt;/sup>. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, indepe</pubmed_abstract><journal>Nature</journal><pubmed_title>Single-cell eQTL models reveal dynamic T cell state dependence of disease loci.</pubmed_title><pmcid>PMC9842455</pmcid><funding_grant_id>U01 HG009379</funding_grant_id><funding_grant_id>R01 AR063759</funding_grant_id><funding_grant_id>U01 HG012009</funding_grant_id><funding_grant_id>U19 AI111224</funding_grant_id><funding_grant_id>T32 AR007530</funding_grant_id><funding_grant_id>T32 HG002295</funding_grant_id><funding_grant_id>P01 AI148102</funding_grant_id><funding_grant_id>R01 AI049313</funding_grant_id><funding_grant_id>UH2 AR067677</funding_grant_id><pubmed_authors>Lecca L</pubmed_authors><pubmed_authors>Nathan A</pubmed_authors><pubmed_authors>Baglaenko Y</pubmed_authors><pubmed_authors>Murray MB</pubmed_authors><pubmed_authors>Raychaudhuri S</pubmed_authors><pubmed_authors>Moody DB</pubmed_authors><pubmed_authors>Ishigaki K</pubmed_authors><pubmed_authors>Price AL</pubmed_authors><pubmed_authors>Valencia C</pubmed_authors><pubmed_authors>Beynor JI</pubmed_authors><pubmed_authors>Luo Y</pubmed_authors><pubmed_authors>Suliman S</pubmed_authors><pubmed_authors>Asgari S</pubmed_authors><pubmed_authors>Amariuta T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-cell eQTL models reveal dynamic T cell state dependence of disease loci.</name><description>Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells&lt;sup>1,2&lt;/sup>. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, indepe</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Jun</publication><modification>2026-05-10T06:54:08.357Z</modification><creation>2025-04-07T03:18:39.466Z</creation></dates><accession>S-EPMC9842455</accession><cross_references><pubmed>35545678</pubmed><doi>10.1038/s41586-022-04713-1</doi></cross_references></HashMap>