BackgroundMastitis is a major disease of dairy cattle occurring in response to environmental exposure to infective agents with a great economic impact on dairy industry. Somatic cell count (SCC) and its log transformation in somatic cell score (SCS) are traits that have been used as indirect measures of resistance to mastitis for decades in selective breeding. A selective DNA pooling (SDP) approach was applied to identify Quantitative Trait Loci (QTL) for SCS in Valdostana Red Pied cattle using the Illumina Bovine HD BeadChip.ResultsA total of 171 SNPs reached the genome-wide significance for association with SCS. Fifty-two SNPs were annotated within genes, some of those involved in the immune response to mastitis. On BTAs 1, 2, 3, 4, 9, 13, 15, 17, 21 and 22 the largest number of markers in association to the trait was found. These regions identified novel genomic regions related to mastitis (1-Mb SNP windows) and confirmed those already mapped. The largest number of significant SNPs exceeding the threshold for genome-wide significant signal was found on BTA 15, located at 50.43-51.63 Mb.ConclusionsThe genomic regions identified in this study contribute to a better understanding of the genetic control of the mastitis immune response in cattle and may allow the inclusion of more detailed QTL information in selection programs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-014-0106-7) contains supplementary material, which is available to authorized users.
Copy number variants (CNVs) are an important source of genomic structural variation, recognized to influence phenotypic variation in many species. Many studies have focused on identifying CNVs within and between human and livestock populations alike, but only few have explored population-genetic properties in cattle based on CNVs derived from a high-density SNP array. We report a high-resolution CNV scan using Illumina’s 777k BovineHD Beadchip for Valdostana Red Pied (VRP), an autochthonous Italian dual-purpose cattle population reared in the Alps that did not undergo strong selection for production traits. After stringent quality control and filtering, CNVs were called across 108 bulls using the PennCNV software. A total of 6,784 CNVs were identified, summarized to 1,723 CNV regions (CNVRs) on 29 autosomes covering a total of ~59 Mb of the UMD3.1 assembly. Among the mapped CNVRs, there were 812 losses, 832 gains and 79 complexes. We subsequently performed a comparison of CNVs detected in the VRP and those available from published studies in the Italian Brown Swiss (IBS) and Mexican Holstein (HOL). A total of 171 CNVRs were common to all three breeds. Between VRP and IBS, 474 regions overlapped, while only 313 overlapped between VRP and HOL, indicating a more similar genetic background among populations with common origins, i.e. the Alps. The principal component, clustering and admixture analyses showed a clear separation of the three breeds into three distinct clusters. In order to describe the distribution of CNVs within and among breeds we used the pair VST statistic, considering only the CNVRs shared to more than 5 individuals (within breed). We identified unique and highly differentiated CNVs (n = 33), some of which could be due to specific breed selection and adaptation. Genes and QTL within these regions were characterized.
The Aosta Red Pied (Valdostana Pezzata Rossa (VRP)), the Aosta Black Pied (Valdostana Pezzata Nera (VBP)) and the Aosta Chestnut (Valdostana Castana (CAS)) are dual-purpose cattle breeds (meat and milk), very well adapted to the harsh environmental conditions of alpine territories: their farming is in fact characterized by summer pasture at very high altitude. A total of 728 individuals were genotyped with the GeenSeek Genomic Profiler® (GGP) Bovine 150K Illumina SNP chip as a part of the DUALBREEDING-PSRN Italian-funded research project. The genetic diversity among populations showed that the three breeds are distinct populations based on the FST values, ADMIXTURE and Principal Component Analysis (PCA) results. Runs of Homozygosity (ROH) were obtained for the three populations to disclose recent autozygosity. The genomic inbreeding based on the ROH was calculated and coupled with information derived from the F (inbreeding coefficient) and FST parameters. The mean FROH values were low: CAS = 0.06, VBP = 0.05 and VRP = 0.07, while the average F values were −0.003, −0.01 and −0.003, respectively. The annotation and enrichment analysis, performed in the identified most frequent ROH (TOP_ROH), showed genes that can be linked to the resilience capacity of these populations to harsh environmental farming conditions, and to the peculiar characteristics searched for by farmers in each breed.
This study aimed to exploit the genetic components of cow fighting ability in Valdostana breed. Data from 41 knockout competitions in three different weight categories (WC) performed over two years were used. Two different variables to express fighting ability were considered: 1) a “placing score” (PS) dependent on the position reached in each WC, and 2) a “relative placing score” (RPS), calculated as relative position within WC. A complete data set (COMP) accounting for all fights (n=7157) or a reduced data set (REDU) considering only the best annual PS or RPS for each cow (n=4563), were also compared through ANOVA, REML variance components’ estimates and EBVs’ correlation. The PS in the COMP showed the highest R2 (0.44), and h2 resulted 0.163. The PS in the REDU showed a lower R2 (0.25), similar h2 value (0.189), but higher repeatability than PS in the COMP (0.373 vs. 0.294). The RPS variable in both data sets gave similar genetic parameters, but the R2 models resulted very low (0.02-0.04). The use of the PS variable and the COMP seems the most promising system to evaluate cow fighting ability in Valdostana breed, and a substantial genetic component for this ability seems to exist
We used genome-wide SNP data from 18 local cattle breeds from six countries of the Alpine region to characterize population structure and identify genomic regions underlying positive selection. The geographically close breeds Evolèner, Eringer, Valdostana Pezzata Nera, and Valdostana Castana were found to differ from all other Alpine breeds. In addition, three breeds, Simmental, and Original Braunvieh from Switzerland and Pinzgauer from Austria built three separate clusters. Of the 18 breeds studied, the intra-alpine Swiss breed Evolèner had the highest average inbreeding based on runs of homozygosity (F ROH ) and the highest average genomic relationship within the breed. In contrast, Slovenian Cika cattle had the lowest average genomic inbreeding and the lowest average genomic relationship within the breed. We found selection signatures on chromosome 6 near known genes such as KIT and LCORL explaining variation in coat color and body size in cattle. The most prominent selection signatures were similar regardless of marker density and the breeds in the data set. In addition, using available high-density SNP data from 14 of the breeds we identified 47 genome regions as ROH islands. The proportion of homozygous animals was higher in all studied animals of local breeds than in Holstein and Brown Swiss cattle, the two most important commercial breeds in the Alpine region. We report ROH islands near genes related to thermoregulation, coat color, production, and stature. The results of this study serve as a basis for the search for causal variants underlying adaptation to the alpine environment and other specific characteristics selected during the evolution of local Alpine cattle breeds.
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