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Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance

By Franck Rapaport, Bertrand Boisson, Anne Gregor, Vivien B├ęziat, Stephanie Boisson-Dupuis, Jacinta Bustamante, Emmanuelle Jouanguy, Anne Puel, Jeremie Rosain, Qian Zhang, Shen-Ying Zhang, Joseph G Gleeson, Lluis Quintana-Murci, Jean-Laurent Casanova, Laurent Abel, Etienne Patin

Posted 08 Feb 2020
bioRxiv DOI: 10.1101/2020.02.07.938894

Background: Genetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans. Results: We propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment. Conclusions: These findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.

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