In vivo and in vitro human gene essentiality estimations capture contrasting functional constraints
Gene essentiality estimation is a popular empirical approach to link genotypes to phenotypes. In humans, essentiality is estimated based on loss-of-function (LoF) mutation intolerance, either from population exome sequencing (in vivo) data or CRISPR-based in vitro perturbation experiments. Both approaches identify genes presumed to have strong detrimental consequences on the organism upon mutation. Are these genes functionally distinct and constrained by having key roles? Do in vivo and in vitro estimations equally recover these constraints? To address these questions, here we integrated disparate genome-scale datasets and compared structural, functional, and evolutionary features of essential genes versus genes with extremely high mutational tolerance and proteome expectation. We found that essentiality estimates do recover functional constraints. However, the organismal or cellular context of estimation leads to functionally contrasting properties underlying the constraint. Our results suggest that depletion of LoF mutations in human populations effectively captures developmental, organismal-level functional constraints not experimentally accessible through CRISPR-based screens. Finally, we identify a new set of genes (OrgEssential), which are intolerant of LoF mutation in vivo but highly tolerant in vitro. These genes drive observed functional constraint differences and have an unexpected preference for nervous system expression.