14 research outputs found

    Human and mouse essentiality screens as a resource for disease gene discovery

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    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. Discovery of causal variants for monogenic disorders has been facilitated by whole exome and genome sequencing, but does not provide a diagnosis for all patients. Here, the authors propose a Full Spectrum of Intolerance to Loss-of-Function (FUSIL) categorization that integrates gene essentiality information to aid disease gene discovery

    Nat Genet

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    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.Comment in : Genetic differential calculus. [Nat Genet. 2015] Comment in : Scaling up phenotyping studies. [Nat Biotechnol. 2015

    The Negative Affect of an Appalachian Dialect

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    In this Autoethnography, the author tells a personal narrative about how growing up in rural Appalachia shaped her personal growth and identity. She draws from personal experiences and her struggles with having an Appalachian accent in a professional world. In researching for this work, the author draws on scholarship on Appalachian stereotypes (Massey 2007), the Appalachian Dialect (Mehring 2006), the tragic disappearance of the Appalachian identity (Grenoble 2012). This Autoethnography highlights personal experiences with negative stereotypes in Appalachia, and adds to the growing field of study on Appalachian identity

    Author Correction: EMPReSS: standardized phenotype screens for functional annotation of the mouse genome

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    International audienceCorrection to: Nature Genetics, published online 1 November 2005.In the version of this article initially published, members of the Eumorphia Consortium appeared in the Supplementary Information but were not included in the main article. The full list of members appears below
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