Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories
2024
Florian Besnard | Ana Guintard | Cécile Grohs | Laurence Guzylack-Piriou | Margarita Cano | Clémentine Escouflaire | Chris Hozé | Hélène Leclerc | Thierry Buronfosse | Lucie Dutheil | Jeanlin Jourdain | Anne Barbat | Sébastien Fritz | Marie-Christine Deloche | Aude Remot | Blandine Gaussères | Adèle Clément | Marion Bouchier | Elise Contat | Anne Relun | Vincent Plassard | Julie Rivière | Christine Péchoux | Marthe Vilotte | Camille Eche | Claire Kuchly | Mathieu Charles | Arnaud Boulling | Guillaume Viard | Stéphanie Minéry | Sarah Barbey | Clément Birbes | Coralie Danchin-Burge | Frédéric Launay | Sophie Mattalia | Aurélie Allais-Bonnet | Bérangère Ravary | Yves Millemann | Raphaël Guatteo | Christophe Klopp | Christine Gaspin | Carole Iampietro | Cécile Donnadieu | Denis Milan | Marie-Anne Arcangioli | Mekki Boussaha | Gilles Foucras | Didier Boichard | Aurélien Capitan
Abstract Background Dairy cattle breeds are populations of limited effective size, subject to recurrent outbreaks of recessive defects that are commonly studied using positional cloning. However, this strategy, based on the observation of animals with characteristic features, may overlook a number of conditions, such as immune or metabolic genetic disorders, which may be confused with pathologies of environmental etiology. Results We present a data mining framework specifically designed to detect recessive defects in livestock that have been previously missed due to a lack of specific signs, incomplete penetrance, or incomplete linkage disequilibrium. This approach leverages the massive data generated by genomic selection. Its basic principle is to compare the observed and expected numbers of homozygotes for sliding haplotypes in animals with different life histories. Within three cattle breeds, we report 33 new loci responsible for increased risk of juvenile mortality and present a series of validations based on large-scale genotyping, clinical examination, and functional studies for candidate variants affecting the NOA1, RFC5, and ITGB7 genes. In particular, we describe disorders associated with NOA1 and RFC5 mutations for the first time in vertebrates. Conclusions The discovery of these many new defects will help to characterize the genetic basis of inbreeding depression, while their management will improve animal welfare and reduce losses to the industry.
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