These switches could potentially be used in a variety of applications, from treating genetic diseases to optimizing tissue regeneration.
By analyzing vast amounts of DNA data, the AI model was able to uncover patterns that humans couldn’t easily identify.Researchers at The Jackson Laboratory , the Broad Institute of MIT and Harvard, and Yale University have achieved a breakthrough in gene control through artificial intelligence .
The novel approach uses AI to design synthetic DNA switches, known as cis-regulatory elements , which can precisely regulate gene activity in specific tissues or cell types.A key challenge in genetic engineering has been the ability to control where and when genes are expressed in living organisms. While gene-editing technologies like CRISPR have made it easier to modify genes, ensuring that these alterations only impact the desired tissues or cells has been difficult. The team behind this study sought to address this by creating synthetic DNA sequences that act as precise on-off switches for gene expression, thus providing greater control over genetic interventions. “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, co-senior author of the study. “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.”Every cell in the body contains the same genetic code, but not all genes are active in every cell. Regulatory DNA elements, like CREs, function as control switches, making sure the right genes are activated in the right cells at the right time. The challenge, however, has been deciphering the “grammar” of these sequences—understanding the rules that govern how they work. To overcome this hurdle, the team employed deep learning, a branch of AI, to train a model capable of predicting CRE activity. By analyzing vast amounts of DNA data, the AI model was able to uncover patterns that humans couldn’t easily identify. The results allowed researchers to better understand how the arrangement of sequences within CREs affects gene activation, paving the way for the design of synthetic CREs with highly specific functions. Using a platform called CODA , the researchers were able to design thousands of novel CREs that can control gene expression in selected cell types. A graphical representation of how cis-regulatory elements work to turn genes on or off and open possibilities for personalized medicine.and mice. In one striking example, a synthetic CRE successfully activated a fluorescent protein in the livers of developing zebrafish but nowhere else in the body. This level of precision could be a game-changer for therapies that require gene expression in one specific tissue, without impacting others.are activated, these AI-designed CREs could potentially be used in a variety of therapeutic applications, from treating genetic diseases to optimizing tissue regeneration.switches could be employed in biomanufacturing or to develop advanced treatments for a range of conditions, offering more effective ways to manipulate genes with unprecedented precision.. “Such tools will be valuable for basic research but also could have significant biomedical implications where you could use these elements to control gene expression in very specific cell types for therapeutic purposes.”Srishti studied English literature at the University of Delhi and has since then realized it's not her cup of tea. She has been an editor in every space and content type imaginable, from children's books to journal articles. She enjoys popular culture, reading contemporary fiction and nonfiction, crafts, and spending time with her cats. With a keen interest in science, Srishti is particularly drawn to beats covering medicine, sustainability, gene studies, and anything biology-related.
Deep Learning Genetic Code Human DNA Sequencing Regulatory Genes
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