To understand how genes affect human health, researchers need to go beyond variants in the DNA sequence, and dive into the switches, or enhancers, that control when and where a gene is expressed in the body. Now, researchers at La Jolla Institute for Immunology have created 3D maps of how enhancer sequences and genes interact in several types of immune cells. This work advances the understanding of individual risk for diseases from asthma to cancer and even COVID-19.

“The difference is within us,” said Vivek Chandra, PhD, an instructor at La Jolla Institute for Immunology. “We can get infected by the same bacteria or viruses, but the ways our diseases progress can be very different.”

The research is published in Nature Genetics in the paper, “Promoter-interacting expression quantitative trait loci are enriched for functional genetic variants.

The scientists used a genome-wide mapping technique to map the target genes for important DNA sequences called enhancers that serve as a specific switch to turn a gene on in a cell-specific manner. They knew that no matter how far away an enhancer was, it would need to find a way to be physically near the promoter it controls. The team’s new 3D maps showed how enhancers on one part of a DNA strand actually loop around to meet promoters.

“People have found a lot of these switches, but it hasn’t been easy to know which switch is connected to which gene,” said Pandurangan Vijayanand, MD, PhD, associate professor at La Jolla Institute for Immunology and co-senior author of the new study.

More specifically, using H3K27ac HiChIP assays, the team mapped expression quantitative trait loci (eQTLs) overlapping active cis-regulatory elements that interact with their target gene promoters (promoter-interacting eQTLs, pieQTLs) in five common immune cell types. The approach, the authors noted, allowed them “to identify functionally important eQTLs and show mechanisms that explain their cell-type restriction.”

“Nobody has done this mapping, either technically or analytically, to this precision in immune cells,” said Vijayanand.

In addition, the team also devised an approach to eQTL discovery that relies on HiChIP-based promoter interaction maps as a structural framework for deciding which SNPs to test for association with gene expression.

To their surprise, the researchers linked genes to enhancers very far away in the DNA sequences. Thinking at a molecular scale, for some of the genes, the enhancers appear miles away. “To date, fewer than a handful of examples of such ultra-long distance connections have been discovered and validated,” said Chandra, who performed genome editing experiments (CRISPR) that validated some of the discoveries in the paper. More specifically, they validated the functional role of pieQTLs using reporter assays, CRISPRi, dCas9-tiling guides, and Cas9-mediated base-pair editing.

The study shows that variations in the enhancer sequences can actually disable the “switch” leading to problems in turning on the right gene in the right cell type. With their new maps, researchers can predict whether DNA sequence changes in these switches will increase disease risk in a person.

The researchers uncovered that some “turned off” promoter sequences—previously thought to do nothing—are actually switching on genes far away in the DNA sequence. “They might be connected to other genes that you would never expect,” said Ferhat Ay, PhD, an assistant professor of computational biology at La Jolla Institute for Immunology.

“Going forward, we can apply this framework to understand cell types involved in many different diseases,” added Ay.

This discovery means that researchers may need to change how they think of gene regulation. When researchers uncover a genetic variant linked to a disease, they usually go looking for the nearby gene. Now, they’ll need to use different tools to hunt for potential target genes scattered through the genome. The team’s findings in immune cells will be openly available online through the DICE (Database of Immune Cell Expression, Expression of quantitative trait loci and Epigenomics) database.

“People working on all kinds of diseases are completely rethinking how they find variants and the genes they associate with,” said Ferhat.

The new study also shows how this same approach can be used on other cell types. “The next steps are endless,” said Vijayanand.

Previous articleAdaptive Clues from Microbial Mosaics in Your Mouth
Next articleEpigenetic Regulator Mll1 Linked to Most Severe Forms of Colon Cancer