Researchers at The Jackson Laboratory (JAX), the Broad Institute of MIT and Harvard, and Yale University, have used artificial intelligence to design thousands of new DNA switches that can precisely control the expression of a gene in different cell types. Their new approach opens the possibility of controlling when and where genes are expressed in the body, for the benefit of human health and medical research, in ways never before possible. 

"What is special about these synthetically designed elements is that they show remarkable specificity to the target cell type they were designed for," said Ryan Tewhey, an associate professor at The Jackson Laboratory and co-senior author of the work with Steven Reilly of Yale, and Pardis Sabeti of the Broad. "This creates the opportunity for us to turn the expression of a gene up or down in just one tissue without affecting the rest of the body."

In recent years, genetic editing technologies and other gene therapy approaches have given scientists the ability to alter the genes inside living cells. However, affecting genes only in selected cell types or tissues, rather than across an entire organism, has been difficult. That is in part because of the ongoing challenge of understanding the DNA switches, called cis-regulatory elements (CREs), that control the expression and repression of genes. 

In a paper published in Nature, Tewhey, Reilly, Sabeti, and their collaborators not only designed new, never-before-seen synthetic CREs, but used the CREs to successfully activate genes in brain, liver or blood cells without turning on those genes in other cell types. 

"The more we learn about the genome, the more we see evidence of the deep influence elements like CREs have on biological function," said Sabeti, who is a core institute member at Broad and a professor at Harvard University and the Harvard T. H. Chan School of Public Health. "By applying machine learning and molecular biology to the logic of when and where CREs work, we can leverage that knowledge using generative AI to build tools for modulating gene expression in new ways experimentally and, perhaps one day, therapeutically."

Although every cell in an organism contains the same genes, not all the genes are needed in every cell, or at all times. CREs help ensure that genes needed in the brain are not used by skin cells, for instance, or that genes required during early development are not activated in adults. CREs themselves are not part of genes, but are separate, regulatory DNA sequences – often located near the genes they control. 

Scientists know that there are thousands of different CREs in the human genome, each with slightly different roles. But the grammar of CREs has been hard to figure out, "with no straightforward rules that control what each CRE does," explained Rodrigo Castro, a computational scientist in the Tewhey lab at JAX and co-first author of the new paper. "This limits our ability to design gene therapies that only effect certain cell types in the human body."

"This project essentially asks the question: 'Can we learn to read and write the code of these regulatory elements?'" said Reilly, who is an assistant professor of genetics at Yale and one of the senior authors of the study. "If we think about it in terms of language, the grammar and syntax of these elements is poorly understood. And so, we tried to build machine learning methods that could learn a more complex code than we could do on our own."