Washington University in St. Louis: $7 million to support research into how human genome works

Washington University School of Medicine in St. Louis has received a $7 million grant from the National Institutes of Health (NIH) to help lead national efforts to investigate how variations in the human genome sequence affect how the genome functions. Such information is critical for understanding human health and seeking new ways to treat diseases.

The university will serve as the data and administrative coordinating center for the multicenter project referred to as the Impact of Genomic Variation on Function (IGVF) Consortium.

Nationwide, the NIH is providing about $185 million over five years to the consortium, initiated and funded by the NIH’s National Human Genome Research Institute (NHGRI). NHGRI will fund 25 awards across 30 U.S. research sites.

The Washington University data and administrative center will be led by Ting Wang, the Sanford C. and Karen P. Loewentheil Distinguished Professor of Medicine.

“We’re very good at measuring genomic variation, and Washington University and our McDonnell Genome Institute have been leading that work nationally for decades,” Wang said. “But we still have very little understanding of the functional impact of that genetic variation. One DNA variant or a combination of variants could raise a person’s risk of developing heart disease, Alzheimer’s disease or cancer, for example. This project is a continuation of our long-running genomic research, but now we’re trying to determine how variations in the genome are actually affecting the body.”

Collaborators on the Washington University data center grant include researchers at Northwestern University, the University of California at Santa Cruz, and Carnegie Mellon University.

Wang has a long history of leadership in large genomic research projects at the School of Medicine, including co-leading the university’s contribution to the NIH’s Human Pangenome Reference Sequencing Project, which is tasked with improving the accuracy and diversity of the reference human genome sequence.

The genome sequences of two different people are more than 99.9% identical. But those differences of 0.1% — alternate orders of the As, Cs, Gs and Ts that make up our DNA — combined with environmental and lifestyle factors ultimately shape a person’s overall physical features and disease risk. Researchers have identified millions of human genomic variants that differ across the world, including thousands of disease-associated ones. By combining experimental methods with advanced computer models, the IGVF consortium will identify which variants in the genome are relevant for health and disease — information that will be of critical importance to clinicians.

“Biomedical researchers have recently made remarkable advances in the experimental and computational methods available for elucidating genome function,” said Carolyn Hutter, director of the NHGRI Division of Genome Sciences. “The IGVF consortium will include world leaders in these areas, and together they will leverage these advances to tackle an incredibly challenging and important series of questions related to how genomic variation influences biological function.”

The IGVF consortium will develop a catalog of the results and approaches used in the studies. All information generated by the consortium will be made freely available to the research community via a web portal to assist with future research projects. The web portal will build on the WashU Epigenome Browser, a tool developed by Wang’s team that allows researchers around the world to search and browse genomic data. Because there are thousands of genomic variants associated with disease, and it is not possible to manipulate each variant individually and in each biological setting, consortium researchers also will develop computational modeling approaches to predict the impact of variants on genome function.

The IGVF consortium includes five components: functional characterization centers, regulatory network projects, mapping centers, a data and administrative coordinating center, and predictive modeling projects.