{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T03:46:18Z","timestamp":1793245578038,"version":"4.5.0"},"posted":{"date-parts":[[2026,8,14]]},"group-title":"Genetic and Genomic Medicine","reference-count":85,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Human Genome Research Institute","award":["R00HG012222"],"award-info":[{"award-number":["R00HG012222"]}],"id":[{"id":"https:\/\/ror.org\/00baak391","id-type":"ROR","asserted-by":"crossref"}]},{"name":"National Institutes of Health","award":["R01HG014518"],"award-info":[{"award-number":["R01HG014518"]}]},{"name":"EMBO Long Term Postdoctoral Fellowship","award":["EMBO ALTF 424-2022"],"award-info":[{"award-number":["EMBO ALTF 424-2022"]}]},{"name":"Weissman Family MGH Research Scholar Award"},{"name":"Novo Nordisk Foundation","award":["NNF21SA0072102"],"award-info":[{"award-number":["NNF21SA0072102"]}],"id":[{"id":"https:\/\/ror.org\/04txyc737","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Novo Nordisk Foundation","award":["UM1DK126185"],"award-info":[{"award-number":["UM1DK126185"]}],"id":[{"id":"https:\/\/ror.org\/04txyc737","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Novo Nordisk Foundation","award":["RC2 DK144819-01"],"award-info":[{"award-number":["RC2 DK144819-01"]}],"id":[{"id":"https:\/\/ror.org\/04txyc737","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Novo Nordisk Foundation","award":["P30 580 DK040561"],"award-info":[{"award-number":["P30 580 DK040561"]}],"id":[{"id":"https:\/\/ror.org\/04txyc737","id-type":"ROR","asserted-by":"crossref"}]},{"name":"National Institute of Mental Health","award":["R01MH101244"],"award-info":[{"award-number":["R01MH101244"]}]},{"name":"National Institute of Mental Health","award":["R37MH107649"],"award-info":[{"award-number":["R37MH107649"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,9,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Many disease-associated variants are thought to act through gene regulation, yet conventional eQTL mapping explains only a fraction of GWAS loci, potentially because regulatory effects vary across cellular states and environments. We present CASTIE, a scalable Poisson mixed-model framework that directly models sparse single-cell read counts and enables genome-wide testing of genotype-by-context interactions without pre-screening for static effects. Applying CASTIE to 1.2 million peripheral blood mononuclear cells from 982 OneK1K donors identified 3,155 context-dependent eQTL associations, including 2,022 eGenes without detectable static effects. These associations yielded 374 colocalizations across 94 traits, representing 270 unique loci, of which 197 were not recovered using the corresponding static eQTLs. The colocalizations linked trait associations to specific cellular contexts and genes, including\n                  <jats:italic>GCHFR<\/jats:italic>\n                  ,\n                  <jats:italic>RNASET2<\/jats:italic>\n                  and\n                  <jats:italic>ATP1A3<\/jats:italic>\n                  . In adipose-derived mesenchymal stem cells exposed to metabolic stimulations, CASTIE increased eGene discovery by 36 \u2212 92% across cell populations and identified stimulation-dependent regulatory effects at metabolic trait loci. Thus, modeling cellular context reveals disease-relevant regulatory variation beyond static eQTL mapping.\n                <\/jats:p>","DOI":"10.64898\/2026.08.13.26360300","type":"posted-content","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T19:10:21Z","timestamp":1786734621000},"source":"Crossref","is-referenced-by-count":2,"title":["Scalable context-dependent single-cell eQTL mapping reveals disease-relevant regulatory variation beyond static models"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2078-651X","authenticated-orcid":false,"given":"Yijia Christiana","family":"Liu","sequence":"first","affiliation":[{"name":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical 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