Proceedings of the National Academy of Sciences · 2016 · 36 citations · 46 references
Engineering specific cellular behaviors can impact biomedicine and biotechnology, and globally modifying gene expression states is one strategy to achieve desired phenotypes, with systematic benchmarks accelerating progress. The paper introduces a broadly applicable algorithm for transcriptome engineering that designs transcription factor deletions or overexpressions to shift cells toward a gene expression state linked to a desired phenotype. The authors also present an approach to benchmark and validate these algorithms.
Significance The ability to engineer specific behaviors into cells would have a significant impact on biomedicine and biotechnology, including applications to regenerative medicine and biofuels production. One way to coax cells to behave in a desired way is to globally modify their gene expression state, making it more like the state of cells with the desired behavior. This paper introduces a broadly applicable algorithm for transcriptome engineering—designing transcription factor deletions or overexpressions to move cells to a gene expression state that is associated with a desired phenotype. This paper also presents an approach to benchmarking and validating such algorithms. The availability of systematic, objective benchmarks for a computational task often stimulates increased effort and rapid progress on that task.
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