"Causal modeling of gene effects in complex traits: from regulators to programs to traits"

Abstract:

Genetic association studies provide a unique tool for identifying causal links from genes to human traits and diseases. However, it is challenging to determine the biological mechanisms underlying most associations, and we lack genome-scale approaches for inferring causal mechanistic pathways from genes to cellular functions to traits. Here I describe our new work aiming to bridge this gap by combining quantitative estimates of gene-trait relationships from loss-of-function burden tests with gene-regulatory connections inferred from Perturb-seq experiments in relevant cell types. By combining these two forms of data, we aim to build causal graphs in which the directional associations of genes with a trait can be explained by their regulatory effects on biological programs or direct effects on the trait. In this talk I will describe a proof-of-concept in which we constructed a map of the gene regulatory hierarchy that jointly controls three partially co-regulated blood traits. We propose that perturbation studies in trait-relevant cell types, coupled with gene-level effect sizes for traits, can bridge the gap between genetics and biology.

Date: Tuesday, April 22, 2025
Time: 2 - 3pm ET
In-Person Location: HESS, 1470 Madison Ave, 2nd Floor, Seminar Room A
Zoom Registration Link
Zoom Meeting ID: 927 6891 4293

Speaker:

Jonathan Pritchard, PhD
Bing Professor of Population Studies
Professor of Genetics and Biology
Co-Director, Center for Computational, Evolutionary and Human Genomics
Member, Bio-X
Stanford University
Pritchard Lab
pritch@stanford.edu

Jonathan Pritchard is a Professor of Biology and Genetics at Stanford University.  He grew up mainly in England, and studied at Penn State, Stanford, and Oxford before joining the faculty of the University of Chicago in 2001. He returned to Stanford to take his current position in 2013. His lab has done wide-ranging research on using genetics to study human population structure, history, and adaptation, as well as on understanding the mechanisms that link genetic variation to variation in gene regulation and complex traits. One of his early contributions was the Structure algorithm for using genetic data to infer population structure and personal ancestry. His current work focuses on the genetic basis of complex traits in humans and on genetic approaches to studying human population history and adaptation.