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

A better understanding of the genetic mechanisms regulating hematopoiesis are necessary, and could augment translational efforts to generate red blood cells (RBCs) and/or platelets . Using available genome-wide association data sets, we applied a machine-learning framework to identify genomic features enriched at established platelet trait associations and score variants genome-wide to identify biologically plausible gene candidates. We found that high-scoring SNPs marked relevant loci and genes, including an expression quantitative trait locus for (). CRISPR/Cas9-mediated knockout in human induced pluripotent stem cells (iPSCs) unexpectedly enhanced early hematopoietic progenitor development. Our findings may help explain human genetics associations and identify a novel genetic strategy to enhance hematopoiesis, increasing RBC and MK yield.