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dc.contributor.authorSanchez, Marie-Pierre
dc.contributor.authorRamayo-Caldas, Yuliaxis
dc.contributor.authorWolf, Valérie
dc.contributor.authorLaithier, Cécile
dc.contributor.authorEl Jabri, Mohammed
dc.contributor.authorMichenet, Alexis
dc.contributor.authorBoussaha, Mekki
dc.contributor.authorTaussat, Sébastien
dc.contributor.authorFritz, Sébastien
dc.contributor.authorDelacroix-Buchet, Agnès
dc.contributor.authorBrochard, Mickaël
dc.contributor.authorBoichard, Didier
dc.contributor.otherProducció Animalca
dc.date.accessioned2020-03-30T06:21:01Z
dc.date.available2020-03-30T06:21:01Z
dc.date.issued2019-07-01
dc.identifier.citationSanchez, Marie-Pierre, Yuliaxis Ramayo-Caldas, Valérie Wolf, Cécile Laithier, Mohammed El Jabri, Alexis Michenet, and Mekki Boussaha et al. 2019. "Sequence-Based GWAS, Network And Pathway Analyses Reveal Genes Co-Associated With Milk Cheese-Making Properties And Milk Composition In Montbéliarde Cows". Genetics Selection Evolution 51 (1). Springer Science and Business Media LLC. doi:10.1186/s12711-019-0473-7.ca
dc.identifier.issn0999-193Xca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/651
dc.description.abstractBackground Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk’s cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows’ genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed. Results Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition. Conclusions By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.ca
dc.format.extent19ca
dc.language.isoengca
dc.publisherBMCca
dc.relation.ispartofGenetics Selection Evolutionca
dc.rightsAttribution 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleSequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cowsca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.subject.udc619ca
dc.identifier.doihttps://doi.org/10.1186/s12711-019-0473-7ca
dc.contributor.groupGenètica i Millora Animalca


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