ArticleData in brief2025
Whole genome short read data from 567 bulls of 14 breeds provides insight into genetic diversity of French cattle.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- An inherited SLC25A12-related recessive form of congenital porencephaly in Limousin cattle.Genetics, selection, evolution : GSE · 2026Article
- LRP4-Related Lethal Syndromic Form of Syndactyly in Limousin Cattle.Animal genetics · 2026Article
- Pangenome-based association testing between a structural variant located upstream of the KIT gene and head depigmentation across a diverse panel of cattle breeds.Genetics, selection, evolution : GSE · 2026Article
- Comprehensive detection of structural variations in long and short reads dataset of French cattle.Scientific reports · 2025Article
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Authors and funding
20 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Technological developments in high-throughput sequencing and advances in bioinformatic analysis allowed to sequence and study a very large number of genomes from a single species (cattle). Analyzing this data set enabled to generate the corresponding genomic variant database, especially for single nucleotide polymorphisms (SNPs) and small insertion or deletion (Indels) variations. These variants and genotypes allowed to better characterize the genetic diversity of these breeds. In this work, we sequenced 567 bulls from 14 different breeds (Holstein, Montbéliarde, Normande, Brown Swiss, Simmental, Abondance, Tarentaise, Vosgienne, Blonde d'Aquitaine, Charolaise, Limousine, Aubrac, Flamande, Parthenaise). Each sample was sequenced at an approximately 15x depth on the Illumina Novaseq6000 platform. We detected 34,252,080 variants, 25,115,987 of which were already known in the Ensembl variation database version 110 and 9,136,093 were absent and were considered as novel variants. This data set represents a useful resource for the community to better identify SNPs or indels such as mutation anticipation and provides new insights into bovine genetic diversity.
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