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Aim of this study was to analyse the genetic background of milk Fourier transform infrared (FTIR) spectra in dairy sheep. Individual milk FTIR spectra, with 1060 wavenumbers each, were available for 793 adult Sarda breed ewes genotyped at 45,813 SNP. The absorbance values of each wavenumber was analysed using a linear mixed model that included dim class, parity and lambing month as fixed effects and flock-test date and animal as random effects. The model was applied to estimate variance components and heritability and to perform a genome-wide association study for each wavenumber. Average h 2 of wavenumbers absorbance was 0.13 ± 0.08, with the largest values observed in the regions associated with the characteristic bonds of carbonylic and methylenic groups of milk fat (h 2  = 0.57 at 1724-1728 cm -1 ; and h 2  = 0.34 at 2811-2834 cm -1 , respectively). The absorbance values of wavenumbers were moderately correlated with the estimated heritabilities. After the Bonferroni correction, a total of nine markers were found to be significantly associated with 32 different wavenumbers. Of particular interest was the SNP s63269.1, mapped on chromosome 2, that was found to be associated with 27 wavenumbers. Genes previously found to be related to traits of interest (e.g. disease resistance, milk yield and quality, cheese firmness) are located close to the significant SNP. As expected, the heritability estimated for the absorbance of each wavenumbers seems to be associated with the related milk components., (© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.)

Natural adaptation and artificial selection have shaped the genome of modern livestock breeds. Among SNP-based metrics that are used to detect signatures of selection at genome-wide level, runs of homozygosity (ROH) are getting increasing popularity. In this paper, ROH distribution and features of a sample of 823 Sarda breed ewes farmed at different levels of altitude are analysed to investigate the effect of the environment on the patterns of homozygosity. A total of 46,829 (33,087 unique) ROH were detected. OAR2 exhibited the largest average number of ROH per animal. The most frequent ROH (OAR27, 38.9-44.2 Mb) was shared by 327. ROH length was statistically affected (p < 0.001) by both the altitude and temperature of the place where the flock was located. The highest probability of a SNP falling in a ROH was observed for hill ewes, whereas the smallest one for mountain. A total of 457 SNP exceeded the 99th percentile of the ROH count per SNP distribution and were considered significant. These markers mapped in eight chromosomes and they clustered into 17 ROH islands, where 80 candidate genes were mapped. Results of this study highlighted differences in the ROH distribution and features among sheep farmed in flocks located at different levels of altitude, confirming the role of environmental adaptability in shaping the genome of this breed., (© 2022 Wiley-VCH GmbH.)

Genomic information allows for a more accurate calculation of relationships among animals than the pedigree information, leading to an increase in accuracy of breeding values. Here, we used pedigree-based and single-step genomic approaches to estimate variance components and breeding values for β-hydroxybutyrate milk content (BHB). Additionally, we performed a genome-wide association study (GWAS) to depict its genetic architecture. BHB concentrations within the first 90 days of lactation, estimated from milk medium infrared spectra, were available for 30,461 cows (70,984 records). Genotypes at 42,152 loci were available for 9,123 animals. Low heritabilities were found for BHB using pedigree-based (0.09 ± 0.01) and genomic (0.10 ± 0.01) approaches. Genetic correlation between BHB and milk traits ranged from -0.27 ± 0.06 (BHB and protein percentage) to 0.13 ± 0.07 (BHB and fat-to-protein ratio) using pedigree and from -0.26 ± 0.05 (BHB and protein percentage) to 0.13 ± 0.06 (BHB and fat-to-protein ratio) using genomics. Breeding values were validated for 344 genotyped cows using linear regression method. The genomic EBV (GEBV) had greater accuracy (0.51 vs. 0.45) and regression coefficient (0.98 vs. 0.95) compared to EBV. The correlation between two subsequent evaluations, without and with phenotypes for validation cows, was 0.85 for GEBV and 0.82 for EBV. Predictive ability (correlation between (G)EBV and adjusted phenotypes) was greater when genomic information was used (0.38) than in the pedigree-based approach (0.31). Validation statistics in the pairwise two-trait models (milk yield, fat and protein percentage, urea, fat/protein ratio, lactose and logarithmic transformation of somatic cells count) were very similar to the ones highlighted for the single-trait model. The GWAS allowed discovering four significant markers located on BTA20 (57.5-58.2 Mb), where the ANKH gene is mapped. This gene has been associated with lactose, alpha-lactalbumin and BHB. Results of this study confirmed the usefulness of genomic information to provide more accurate variance components and breeding values, and important insights about the genomic determination of BHB milk content., (© 2021 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.)