Ray Laboratory

The Ray lab studies the mechanisms that contribute to variation in human immune responses. In particular, we determine how genetic variants and non-coding regulatory regions alter immune responses and confer autoimmune disease susceptibility. With a focus on T cells, we prioritize likely disease-causal genetic variants and enhancers, and, in human and mouse systems, we dissect their mechanisms of action. Understanding the mechanisms of inherited autoimmune disease susceptibility will inform efforts for personalized therapies and disease prevention.

Prioritizing and validating autoimmune disease-causal variants

Autoimmune diseases have strong genetic etiologies, but we still know very little about how genetic variants promote autoimmunity. We study the actions of disease-associated genetic variants, focusing on those that occur outside of genes, for their effects on gene expression, cellular function, and models of disease.

Genome-wide association studies have associated hundreds of genetic loci with commonly acquired autoimmune diseases. However, the genetic variants that contribute to autoimmunity in each locus are mostly unknown. This is because disease contributing variants are often in tight linkage disequilibrium with many non-contributing variants, and 90% of disease-associated variants are in non-coding regions, making their actions on gene expression and cellular processes difficult to measure. One clue for how disease variants promote disease is their enrichment in gene regulatory regions called enhancers.

Since only a fraction of the thousands of disease-associated variants are likely to drive disease, we use observational and perturbational techniques to prioritize them for mechanistic dissection, including whether a variant is in a putative enhancer, if ablating that enhancer’s activity alters gene expression, and if the variant is capable of modulating expression and chromatin accessibility in an allele-specific fashion. We then validate prioritized variants through engineering them into the genomes of relevant cell types and mice to test their effects on cellular and physiological processes.

Mapping T cell regulatory regions genome-wide

However, while efforts to identify regions that are likely to regulate gene expression in particular cell types have been widely successful, the vast majority of these regions do not have a verified target gene (or genes) nor a context for their activity.

Since autoimmune disease-associated genetic variants are enriched in immune cell regulatory regions, these regions are likely key in driving autoimmunity. Millions of putative regulatory regions have been mapped through assaying chromatin accessibility, histone modifications, and 3-D chromatin conformation. However, despite the wealth of publicly available data for many cell types, we are still in the early stages of predicting how they operate—1) their strength and directionality on gene expression are still poorly predicted, and 2) connecting regulatory regions to the genes they regulate remains an extraordinary challenge. To address this, a major focus of the lab is to connect these regions to T cell gene expression and function at baseline and in activation states, with the goal of finding the ones that influence aberrant T cell activation.

Chromatin state in autoimmunity

Chromatin state provides hints about the regulatory capacity of a given genomic region. Hundreds of cell types have been profiled for their chromatin state in healthy people, but we still lack the same information for autoimmune patients. A major aim of the lab is to map the chromatin states of immune cells from autoimmune patients and their relatives to better understand new regions of importance particular to disease state.

Chromatin state, determined through assaying histone modifications and chromatin accessibility, helps to highlight important regions of the genome that have regulatory capacity. One goal in the lab is to combine chromatin state data from autoimmune patients with transcription factor binding and motif information to reveal mechanisms for disease pathogenesis and better pinpoint genetic variants that contribute to disease risk.