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Massive detection of cryptic recessive genetic defects in livestock mining millions of life trajectories

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Guintard, Ana | Besnard, Florian | Cano, Margarita | Hoze, Chris | Leclerc, Hélène | Boussaha, Mekki | Grohs, Cécile | Barbat, Anne | Fritz, Sebastien | Escouflaire, Clémentine | Rivière, Julie | Péchoux, Christine | Danchin-Burge, Coralie | G., Foucras | Relun, Anne | Plassard, Vincent | Arcangioli, Marie-Anne | Mattalia, Sophie | Boichard, Didier | Capitan, Aurélien

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International audience. A data mining method applied to large-scale genotyping data is proposed to detect recessive loci responsible for increased mortality in cattle and that have remained undetected by previous approaches. It is based on a screen for homozygous haplotype enrichment/depletion in groups of females with different life trajectories. After validation of the results in at risk and control mating, 34 deleterious haplotypes (13 in Holstein, 11 in Montbéliarde, and 10 in Normande) were identified, with frequencies ranging from 1.5 to 7.6%. Profiles of survival curves and causes of mortality differed greatly between loci, with early juvenile, late juvenile and evenly distributed death events. Candidate causal variants were found for fifteen haplotypes. A frameshift mutation of NOA1 and a disruptive inframe deletion of RFC5, affecting two genes with no previous record of live homozygous mutants in mammals, were subject to phenotypical characterization.

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