Abstract

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery.

Highlights

  • The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge

  • This identified two sets of lethal genes: a set of cellular lethal genes essential for both a cell and an organism to survive (cellular lethal (CL)), and a set of developmental lethal genes (DL) that are not essential at the cellular level but where LoF is lethal at the organism level

  • While 35% of genes lethal in the mouse were essential in human cell lines (CL bin), the remaining 65% have not been identified as cell essential and were classified as essential for organism development (DL bin)

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Summary

Introduction

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. One complimentary approach has been to incorporate gene-level information metrics These metrics can help to identify candidate variants in genes not previously associated with disease, which are subsequently confirmed as causative in functional in vitro and in vivo studies. Phenotype comparison between model organisms and clinical descriptions has highlighted new candidate gene–disease associations[10] These successes led us to consider other gene features that could be used to identify human disease genes. The number of observed homozygous LoF mice generated from an intercross between heterozygous parents allows the categorisation of a gene as lethal (~25% of the genes), subviable (~10%) or viable (~65%)[18,21] These findings are consistent with results curated from the scientific literature indicating that approximately one-third of protein-coding genes are essential for organism survival[23]. Other research has reported that orthologues of embryonic lethal LoF mouse genes show an increased association with diseases with high mortality and neurodevelopmental disorders[21,29,30]

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