Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Journal Articles Genome Biology Year : 2024

Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories

Aude Remot
Stéphanie Minéry
Clément Birbes
Coralie Danchin-Burge
Frédéric Launay
Sophie Mattalia
Bérangère Ravary
Yves Millemann
Denis Milan

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.
Fichier principal
Vignette du fichier
Besnard2024_GenomeBiology.pdf (3.94 Mo) Télécharger le fichier
Origin Publisher files allowed on an open archive
Licence

Dates and versions

hal-04714371 , version 1 (30-09-2024)

Licence

Identifiers

Cite

Florian Besnard, Ana Guintard, Cécile Grohs, Laurence Guzylack-Piriou, Margarita Cano, et al.. Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories. Genome Biology, 2024, 25 (1), pp.248. ⟨10.1186/s13059-024-03384-7⟩. ⟨hal-04714371⟩
0 View
0 Download

Altmetric

Share

More