Alan B Wells, Nathan Kopp, Xiaoxiao Xu, David R O’Brien, Wei Yang, Arye Nehorai, Tracy L. Adair-Kirk, Raphael Kopan, Joseph D Dougherty
Deeper understanding of the anatomical intermediaries for disease and other complex genetic traits is essential to understanding mechanisms and developing new interventions. Existing ontology tools provide functional annotations for many genes in the genome and they are widely used to develop mechanistic hypotheses based on genetic and transcriptomic data. Yet, information about where a set of genes is expressed may be equally useful in interpreting results and forming novel mechanistic hypotheses for a trait. Therefore, we developed a framework for statistically testing the relationship between gene expression across the body and sets of candidate genes from across the genome. We validated this tool and tested its utility on three applications. First, using thousands of loci identified by GWA studies, our framework identifies the number of disease-associated genes that have enriched expression in the disease-affected tissue. Second, we experimentally confirmed an underappreciated prediction highlighted by our tool: variation in skin expressed genes are a major quantitative genetic modulator of white blood cell count – a trait considered to be a feature of the immune system. Finally, using gene lists derived from sequencing data, we show that human genes under constrained selective pressure are disproportionately expressed in nervous system tissues.