University of Washington
Cole Trapnell, Jay Shendure
A decade after the completion of the human genome project, the function of the vast majority of the 20,000 human genes remains largely unknown. Although forward genetic screens can coarsely implicate hundreds of genes in having some role in a phenotype, this almost always is the end of the story, rather than the beginning. There are at least two critical challenges to experimentally analyzing a gene. First, the phenotype measured upon perturbing a gene usually is based on cell growth or survival and therefore provides few or no clues about that gene’s molecular role. Second, perturbing a single gene often has no phenotypic effect because other genes buffer against the change. Two investigators from the University of Washington plan to develop a new paradigm, combinatorial forward genetics (CFG), which addresses both challenges at once. CFG aims to broadly capture the molecular consequences of perturbing thousands of genes in a multitude of combinations by evaluating the resulting signatures of cell states in a high-throughput manner. To analyze the data from the CFG experiments, the team will implement “deep neural algorithms” which can recognize features of increased complexity. While the risks are substantial, CFG has the potential to revolutionize the understanding of the human genome by markedly accelerating the discovery of sets of genes that functionally collaborate, e.g. in signaling pathways, as molecular machines, or for cellular reprogramming. Knowledge of such interactions will be invaluable in advancing the understanding of each gene’s role in human biology and disease.
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