TY - JOUR T1 - Mapping genetic effects on cellular phenotypes with “cell villages” JF - bioRxiv DO - 10.1101/2020.06.29.174383 SP - 2020.06.29.174383 AU - Jana M. Mitchell AU - James Nemesh AU - Sulagna Ghosh AU - Robert E. Handsaker AU - Curtis J. Mello AU - Daniel Meyer AU - Kavya Raghunathan AU - Heather de Rivera AU - Matt Tegtmeyer AU - Derek Hawes AU - Anna Neumann AU - Ralda Nehme AU - Kevin Eggan AU - Steven A. McCarroll Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/06/29/2020.06.29.174383.abstract N2 - Tens of thousands of genetic variants shape human phenotypes, mostly by unknown cellular mechanisms. Here we describe Census-seq, a way to measure cellular phenotypes in cells from many people simultaneously. Analogous to pooled CRISPR screens but for natural variation, Census-seq associates cellular phenotypes to donors’ genotypes by quantifying the presence of each donor’s DNA in cell “villages” before and after sorting or selection for cellular traits of interest. Census-seq enables population-scale cell-biological phenotyping with low cost and high internal control. We demonstrate Census-seq through investigation of genetic effects on the SMN protein whose deficiency underlies spinal muscular atrophy (SMA). Census-seq quantified and mapped effects of many common alleles on SMN protein levels and response to SMN-targeted therapeutics, including a common, cryptic non-responder allele. We provide tools enabling population-scale cell experiments and explain how Census-seq can be used to map genetic effects on diverse cell phenotypes.HighlightsCensus-seq reveals how inherited genetic variation affects cell phenotypesGenetic analysis of cellular traits in cell villages of >100 donorsCharacterizing human alleles that shape SMN protein expression and drug responsesDevelopment of protocols and software to enable cellular population geneticsCompeting Interest StatementThe authors have declared no competing interest. ER -