GWA analysis for milk production traits in dairy sheep and genetic support for a QTN influencing milk protein percentage in the LALBA gene

Genome-wide SNP scan in a porcine Large White×Minzhu intercross population reveals a locus influencing muscle mass on chromosome 2

A high-density single nucleotide polymorphism (SNP) array containing 62 163 markers was employed for a genome-wide association study (GWAS) to identify variants associated with lean meat in ham (LMH, %) and lean meat percentage (LMP, %) within a porcine Large White×Minzhu intercross population. For each individual, LMH and LMP were measured after slaughter at the age of 240±7 days. A total of 557 F2 animals were genotyped. The GWAS revealed that 21 SNPs showed significant genome-wide or chromosome-wide associations with LMH and LMP by the Genome-wide Rapid Association using Mixed Model and Regression-Genomic Control approach. Nineteen significant genome-wide SNPs were mapped to the distal end of Sus Scrofa Chromosome (SSC) 2, where a major known gene responsible for muscle mass, IGF2 is located. A conditioned analysis, in which the genotype of the strongest associated SNP is included as a fixed effect in the model, showed that those significant SNPs on SSC2 were derived from a single quantitative trait locus. The two chromosome-wide association SNPs on SSC1 disappeared after conditioned analysis suggested the association signal is a false association derived from using a F2 population. The present result is expected to lead to novel insights into muscle mass in different pig breeds and lays a preliminary foundation for follow-up studies for identification of causal mutations for subsequent application in marker-assisted selection programs for improving muscle mass in pigs.

Application of selection mapping to identify genomic regions associated with dairy production in sheep

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of "dairy breeds." This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep.

Within- and across-breed genomic predictions and genomic relationships for Western Pyrenees dairy sheep breeds Latxa, Manech, and Basco-Béarnaise

Genotypes, phenotypes and pedigrees of 6 breeds of dairy sheep (including subdivisions of Latxa, Manech, and Basco-Béarnaise) from the Spain and France Western Pyrenees were used to estimate genetic relationships across breeds (together with genotypes from the Lacaune dairy sheep) and to verify by forward cross-validation single-breed or multiple-breed genetic evaluations. The number of rams genotyped fluctuated between 100 and 1,300 but generally represented the 10 last cohorts of progeny-tested rams within each breed. Genetic relationships were assessed by principal components analysis of the genomic relationship matrices and also by the conservation of linkage disequilibrium patterns at given physical distances in the genome. Genomic and pedigree-based evaluations used daughter yield performances of all rams, although some of them were not genotyped. A pseudo-single step method was used in this case for genomic predictions. Results showed a clear structure in blond and black breeds for Manech and Latxa, reflecting historical exchanges, and isolation of Basco-Béarnaise and Lacaune. Relatedness between any 2 breeds was, however, lower than expected. Single-breed genomic predictions had accuracies comparable with other breeds of dairy sheep or small breeds of dairy cattle. They were more accurate than pedigree predictions for 5 out of 6 breeds, with absolute increases in accuracy ranging from 0.05 to 0.30 points. They were significantly better, as assessed by bootstrapping of candidates, for 2 of the breeds. Predictions using multiple populations only marginally increased the accuracy for a couple of breeds. Pooling populations does not increase the accuracy of genomic evaluations in dairy sheep; however, single-breed genomic predictions are more accurate, even for small breeds, and make the consideration of genomic schemes in dairy sheep interesting.

A post-GWAS replication study confirming the PTK2 gene associated with milk production traits in Chinese Holstein

Our initial genome-wide association study (GWAS) demonstrated that two SNPs (ARS-BFGL-NGS-33248, UA-IFASA-9288) within the protein tyrosine kinase 2 (PTK2) gene were significantly associated with milk production traits in Chinese Holstein dairy cattle. To further validate if the statistical evidence provided in GWAS were true-positive findings, a replication study was performed herein through genotype-phenotype associations. The two tested SNPs were found to show significant associations with milk production traits, which confirmed the associations observed in the original study. Specifically, SNPs lying in the PTK2 gene were also detected by sequencing 14 unrelated sires in Chinese Holsteins and a total of thirty-three novel SNPs were identified. Thirteen out of these identified SNPs were genotyped and tested for association with milk production traits in an independent resource population. After Bonferroni correction for multiple testing, twelve SNPs were statistically significant for more than two milk production traits. Analyses of pairwise D' measures of linkage disequilibrium (LD) between all SNPs were also explored. Two haplotype blocks were inferred and the association study at haplotype level revealed similar effects on milk production traits. In addition, the RNA expression analyses revealed that a non-synonymous coding SNP (g.4061098T>G) was involved in the regulation of gene expression. Thus the findings presented here provide strong evidence for associations of PTK2 variants with dairy production traits and may be applied in Chinese Holstein breeding program.

Identification of quantitative trait loci underlying milk traits in Spanish dairy sheep using linkage plus combined linkage disequilibrium and linkage analysis approaches

In this study, 2 procedures were used to analyze a data set from a whole-genome scan, one based on linkage analysis information and the other combing linkage disequilibrium and linkage analysis (LDLA), to determine the quantitative trait loci (QTL) influencing milk production traits in sheep. A total of 1,696 animals from 16 half-sib families were genotyped using the OvineSNP50 BeadChip (Illumina Inc., San Diego, CA) and analysis was performed using a daughter design. Moreover, the same data set has been previously investigated through a genome-wide association (GWA) analysis and a comparison of results from the 3 methods has been possible. The linkage analysis and LDLA methodologies yielded different results, although some significantly associated regions were common to both procedures. The linkage analysis detected 3 overlapping genome-wise significant QTL on sheep chromosome (OAR) 2 influencing milk yield, protein yield, and fat yield, whereas 34 genome-wise significant QTL regions were detected using the LDLA approach. The most significant QTL for protein and fat percentages was detected on OAR3, which was reported in a previous GWA analysis. Both the linkage analysis and LDLA identified many other chromosome-wise significant associations across different sheep autosomes. Additional analyses were performed on OAR2 and OAR3 to determine the possible causality of the most significant polymorphisms identified for these genetic effects by the previously reported GWA analysis. For OAR3, the analyses demonstrated additional genetic proof of the causality previously suggested by our group for a single nucleotide polymorphism located in the α-lactalbumin gene (LALBA). In summary, although the results shown here suggest that in commercial dairy populations, the LDLA method exhibits a higher efficiency to map QTL than the simple linkage analysis or linkage disequilibrium methods, we believe that comparing the 3 analysis methods is the best approach to obtain a global picture of all identifiable QTL segregating in the population at both family-based and population-based levels.

Genome-wide association studies for growth and meat production traits in sheep

BACKGROUND

Growth and meat production traits are significant economic traits in sheep. The aim of the study is to identify candidate genes affecting growth and meat production traits at genome level with high throughput single nucleotide polymorphisms (SNP) genotyping technologies.

METHODOLOGY AND RESULTS

Using Illumina OvineSNP50 BeadChip, we performed a GWA study in 329 purebred sheep for 11 growth and meat production traits (birth weight, weaning weight, 6-month weight, eye muscle area, fat thickness, pre-weaning gain, post-weaning gain, daily weight gain, height at withers, chest girth, and shin circumference). After quality control, 319 sheep and 48,198 SNPs were analyzed by TASSEL program in a mixed linear model (MLM). 36 significant SNPs were identified for 7 traits, and 10 of them reached genome-wise significance level for post-weaning gain. Gene annotation was implemented with the latest sheep genome Ovis_aries_v3.1 (released October 2012). More than one-third SNPs (14 out of 36) were located within ovine genes, others were located close to ovine genes (878bp-398,165bp apart). The strongest new finding is 5 genes were thought to be the most crucial candidate genes associated with post-weaning gain: s58995.1 was located within the ovine genes MEF2B and RFXANK, OAR3_84073899.1, OAR3_115712045.1 and OAR9_91721507.1 were located within CAMKMT, TRHDE, and RIPK2 respectively. GRM1, POL, MBD5, UBR2, RPL7 and SMC2 were thought to be the important candidate genes affecting post-weaning gain too. Additionally, 25 genes at chromosome-wise significance level were also forecasted to be the promising genes that influencing sheep growth and meat production traits.

CONCLUSIONS

The results will contribute to the similar studies and facilitate the potential utilization of genes involved in growth and meat production traits in sheep in future.