Mapping genetic regulation of gene expression to cellular contexts identifies long non-coding RNAs associated with brain disorders.

How genetic variation regulates long non-coding RNA (lncRNA) expression across brain cell types remains poorly understood. A major barrier is the resolution-power trade-off between bulk and single-nucleus expression quantitative trait locus (eQTL) studies. Here, we quantify gene expression from cortical RNA-seq of 2443 individuals using an expanded transcriptome annotation and perform transcriptome-wide interaction eQTL mapping with deconvolution-derived cell-type proportions. Among 17,541 analyzed lncRNAs, we identify 3763 lncRNAs with cellular-context-dependent effects, of which 2,783 (74%) are not annotated by GENCODE. Colocalization with genome-wide association studies (GWAS) of brain-related traits identifies 118 lncRNA-trait colocalization events, approximately two-thirds of which are detectable only after modeling cellular context. Our study establishes a map of cellular-context-dependent genetic regulation in the human brain, providing a basis for nominating lncRNAs with potential roles in mediating genetic risk for brain disorders.