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bioRxiv · 10.1101/631895

Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis.

Thom, C. S.·Jobaliya, C. D.·Lorenz, K.·Maguire, J. A.·Gagne, A.·Gadue, P.·French, D. L.·Voight, B. F.
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Abstract

Identifying causal variants and genes from human genetics studies of hematopoietic traits are important to enumerate basic regulatory mechanisms underlying these traits, and could ultimately augment translational efforts to generate platelets and/or red blood cells in vitro. To identify putative causal genes from these data, we performed computational modelling using available genome-wide association data sets for platelet traits. Our model identified a joint collection of genomic features enriched at established platelet trait associations and plausible candidate variants. Additional studies associating variation at these loci with change in gene expression highlighted the Tropomyosin 1 (TPM1) among our top-ranked candidate genes. CRISPR/Cas9-mediated TPM1 knockout in human induced pluripotent stem cells (iPSCs) enhanced hematopoietic progenitor development, increasing total megakaryocyte as well as erythroid cell yields. Our findings may help explain human genetics associations and identify a novel genetic strategy to enhance in vitro hematopoiesis.

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Thom, C. S., Jobaliya, C. D., Lorenz, K., Maguire, J. A., Gagne, A., Gadue, P., French, D. L., Voight, B. F.. 2019-05-08. Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis.. https://doi.org/10.1101/631895

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