Illuminating links between cis-regulators and trans-acting variants in the human prefrontal cortex

Abstract

Background Neuropsychiatric disorders afflict a large portion of the global population and constitute a significant source of disability worldwide. Although Genome-wide Association Studies (GWAS) have identified many disorder-associated variants, the underlying regulatory mechanisms linking them to disorders remain elusive, especially those involving distant genomic elements. Expression quantitative trait loci (eQTLs) constitute a powerful means of providing this missing link. However, most eQTL studies in human brains have focused exclusively on cis-eQTLs, which link variants to nearby genes (i.e., those within 1 Mb of a variant). A complete understanding of disease etiology requires a clearer understanding of trans-regulatory mechanisms, which, in turn, entails a detailed analysis of the relationships between variants and expression changes in distant genes. Methods By leveraging large datasets from the PsychENCODE consortium, we conducted a genome-wide survey of trans-eQTLs in the human dorsolateral prefrontal cortex. We also performed colocalization and mediation analyses to identify mediators in trans-regulation and use trans-eQTLs to link GWAS loci to schizophrenia risk genes. Results We identified ~80,000 candidate trans-eQTLs (at FDR<0.25) that influence the expression of ~10K target genes (i.e., “trans-eGenes”). We found that many variants associated with these candidate trans-eQTLs overlap with known cis-eQTLs. Moreover, for >60% of these variants (by colocalization), the cis-eQTL’s target gene acts as a mediator for the trans-eQTL SNP's effect on the trans-eGene, highlighting examples of cis-mediation as essential for trans-regulation. Furthermore, many of these colocalized variants fall into a discernable pattern wherein cis-eQTL’s target is a transcription factor or RNA-binding protein, which, in turn, targets the gene associated with the candidate trans-eQTL. Finally, we show that trans-regulatory mechanisms provide valuable insights into psychiatric disorders: beyond what had been possible using only cis-eQTLs, we link an additional 23 GWAS loci and 90 risk genes (using colocalization between candidate trans-eQTLs and schizophrenia GWAS loci). Conclusions We demonstrate that the transcriptional architecture of the human brain is orchestrated by both cis- and trans-regulatory variants and found that trans-eQTLs provide insights into brain-disease biology.

Single-cell genomics and regulatory networks for 388 human brains

“…Previously, groups such as GTEx (Genotype-Tissue Expression), the PsychENCODE Consortium, and ROSMAP (Religious Orders Study and Memory and Aging Project) assembled cohorts large enough to link variants to their effects on gene expression in bulk tissue, generating comprehensive eQTL (expression quantitative trait locus) catalogs for the brain ( 4 – 6 ). Although useful, these tissue-level results do not reflect the specific cell types involved; moreover, they do not provide strong evidence that eQTLs act in cell type–specific fashion ( 7 – 10 ).…”

Single-cell genomics and regulatory networks for 388 human brains

“…S3-S5; ( 20 )). The resource can be summarized at multiple levels: (1) raw data and metadata with a harmonized identifier system for each of the individuals; (2) quantifications of single-cell gene expression (count matrices) with a BICCN-compatible cell-typing system for the PFC; (3) lists of DE genes and differential cell-fractions for various phenotypes; (4) snATAC-seq signal tracks for various cell types and ENCODE-compatible regulatory elements (b-cCREs and scCREs), including lists of validated ones; (5) the variability for each gene and functional category (by individual, cell type, and brain region) and the associated sequence conservation of genes and regulatory elements; (6) a core set of GTEx-compatible scQTLs and other additional sets of QTLs (such as dynamic eQTLs); (7) full GRNs for each cell type, including enhancer-to-gene and TF-to-regulatory element links, and associated files relating each downstream gene to its most significant upstream regulators; (8) cell-to-cell communication networks (expressed as ligand-receptor-by-cell-type matrices); (9) integrative models with code for imputation, perturbation and prioritization of cell-type-specific functional genomics in brain disease; and (10) the resulting prioritized genes, cell types, and cell-to-cell linkages. The brainSCOPE portal also includes visualizer tools for many of the data types (fig.…”

“…Previously, groups such as GTEx (Genotype-Tissue Expression), PsychENCODE, and ROSMAP (Religious Orders Study/Memory and Aging Project) assembled cohorts large enough to link variants to their effects on gene expression in bulk tissue, generating comprehensive eQTL (expression quantitative trait locus) catalogs for the brain (4)(5)(6). While useful, these tissue-level results do not reflect the specific cell types involved; moreover, they do not provide strong evidence that eQTLs act in cell-type-specific fashion (7)(8)(9)(10).…”

Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing

“…Relatedly, the current analyses specifically examined gene expression associated with physically proximal genetic variants (ie, cisregulated expression). As genetic risk for psychiatric disorders consists of many other influences (eg, transregulatory mechanisms; nonsynonymous variation), results should be interpreted as reflecting this specific component of the overall genetic signal. The identification of a drug-gene pair should also not be taken to indicate a pharmacological intervention that directly targets the corresponding gene products.…”