Past eQTL studies have mostly focused on one gene at a time. But in the human genome, genes often occur in clusters and tend to be co-regulated by shared mechanisms. So why not consider neighboring genes together when mapping eQTLs? A new preprint tests this idea and introduces a new class of eQTLs: cis-principal component eQTLs (cis-pc eQTLs). These are identified by calculating principal components from the expression of nearby genes and associating those components with genetic variants. Using GTEx data, the authors uncover thousands of genetic signals missed by traditional single-gene approaches. Many of these pcQTLs colocalize with GWAS hits, offering new insights into complex traits. It’s a compelling reminder that genes often work in packs—and understanding disease may sometimes require zooming out to see the bigger regulatory landscape. Paper: Lawrence et al. Focus on single gene effects limits discovery and interpretation of complex trait-associated variants. bioRxiv, 2025