Genomic insights into the population history and adaptive traits of Latin American Criollo cattle.

Criollo cattle, the descendants of animals brought by Iberian colonists to the Americas, have been the subject of natural and human-mediated selection in novel tropical agroecological zones for centuries. Consequently, these breeds have evolved distinct characteristics such as resistance to diseases and exceptional heat tolerance. In addition to European taurine (Bos taurus) ancestry, it has been proposed that gene flow from African taurine and Asian indicine (Bos indicus) cattle has shaped the ancestry of Criollo cattle. In this study, we analysed Criollo breeds from Colombia and Venezuela using whole-genome sequencing (WGS) and single-nucleotide polymorphism (SNP) array data to examine population structure and admixture at high resolution. Analysis of genetic structure and ancestry components provided evidence for African taurine and Asian indicine admixture in Criollo cattle. In addition, using WGS data, we detected selection signatures associated with a myriad of adaptive traits, revealing genes linked to thermotolerance, reproduction, fertility, immunity and distinct coat and skin coloration traits. This study underscores the remarkable adaptability of Criollo cattle and highlights the genetic richness and potential of these breeds in the face of climate change, habitat flux and disease challenges. Further research is warranted to leverage these findings for more effective and sustainable cattle breeding programmes

Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows

<p>Abstract</p> <p>Background</p> <p>Genome-wide association analysis is a powerful tool for annotating phenotypic effects on the genome and knowledge of genes and chromosomal regions associated with dairy phenotypes is useful for genome and gene-based selection. Here, we report results of a genome-wide analysis of predicted transmitting ability (PTA) of 31 production, health, reproduction and body conformation traits in contemporary Holstein cows.</p> <p>Results</p> <p>Genome-wide association analysis identified a number of candidate genes and chromosome regions associated with 31 dairy traits in contemporary U.S. Holstein cows. Highly significant genes and chromosome regions include: BTA13's <it>GNAS </it>region for milk, fat and protein yields; BTA7's <it>INSR </it>region and BTAX's <it>LOC520057 </it>and <it>GRIA3 </it>for daughter pregnancy rate, somatic cell score and productive life; BTA2's <it>LRP1B </it>for somatic cell score; BTA14's <it>DGAT1-NIBP </it>region for fat percentage; <it>BTA1</it>'s <it>FKBP2 </it>for protein yields and percentage, BTA26's <it>MGMT </it>and BTA6's <it>PDGFRA </it>for protein percentage; BTA18's 53.9-58.7 Mb region for service-sire and daughter calving ease and service-sire stillbirth; BTA18's <it>PGLYRP1</it>-<it>IGFL1 </it>region for a large number of traits; BTA18's <it>LOC787057 </it>for service-sire stillbirth and daughter calving ease; BTA15's <it>CD82</it>, BTA23's <it>DST </it>and the <it>MOCS1</it>-<it>LRFN2 </it>region for daughter stillbirth; and BTAX's <it>LOC520057 </it>and <it>GRIA3 </it>for daughter pregnancy rate. For body conformation traits, BTA11, BTAX, BTA10, BTA5, and BTA26 had the largest concentrations of SNP effects, and <it>PHKA2 </it>of BTAX and <it>REN </it>of BTA16 had the most significant effects for body size traits. For body shape traits, BTAX, BTA19 and BTA3 were most significant. Udder traits were affected by BTA16, BTA22, BTAX, BTA2, BTA10, BTA11, BTA20, BTA22 and BTA25, teat traits were affected by BTA6, BTA7, BTA9, BTA16, BTA11, BTA26 and BTA17, and feet/legs traits were affected by BTA11, BTA13, BTA18, BTA20, and BTA26.</p> <p>Conclusions</p> <p>Genome-wide association analysis identified a number of genes and chromosome regions associated with 31 production, health, reproduction and body conformation traits in contemporary Holstein cows. The results provide useful information for annotating phenotypic effects on the dairy genome and for building consensus of dairy QTL effects.</p

Genomic characteristics of cattle copy number variations

<p>Abstract</p> <p>Background</p> <p>Copy number variation (CNV) represents another important source of genetic variation complementary to single nucleotide polymorphism (SNP). High-density SNP array data have been routinely used to detect human CNVs, many of which have significant functional effects on gene expression and human diseases. In the dairy industry, a large quantity of SNP genotyping results are becoming available and can be used for CNV discovery to understand and accelerate genetic improvement for complex traits.</p> <p>Results</p> <p>We performed a systematic analysis of CNV using the Bovine HapMap SNP genotyping data, including 539 animals of 21 modern cattle breeds and 6 outgroups. After correcting genomic waves and considering the pedigree information, we identified 682 candidate CNV regions, which represent 139.8 megabases (~4.60%) of the genome. Selected CNVs were further experimentally validated and we found that copy number "gain" CNVs were predominantly clustered in tandem rather than existing as interspersed duplications. Many CNV regions (~56%) overlap with cattle genes (1,263), which are significantly enriched for immunity, lactation, reproduction and rumination. The overlap of this new dataset and other published CNV studies was less than 40%; however, our discovery of large, high frequency (> 5% of animals surveyed) CNV regions showed 90% agreement with other studies. These results highlight the differences and commonalities between technical platforms.</p> <p>Conclusions</p> <p>We present a comprehensive genomic analysis of cattle CNVs derived from SNP data which will be a valuable genomic variation resource. Combined with SNP detection assays, gene-containing CNV regions may help identify genes undergoing artificial selection in domesticated animals.</p

Use of haplotypes to identify regions harbouring lethal recessive variants in pigs

Additional file 2: Figure S1. Heatmap of the linkage disequilibrium r 2 values between each of the SNPs located within regions 1.1. and 1.2 on SSC1