Genomic inbreeding coefficients using imputation genotypes: assessing the effect of ancestral genotyping in Holstein-Friesian dairy cows.

The objective of this study was to assess the effect of using or not the genotypes of the parents of a cow for imputing single nucleotide polymorphisms (SNP), on the estimation of genomic inbreeding coefficients of cows. Imputation (i.e., genotyped plus imputed) genotypes from 68,127 Italian Holstein dairy cows registered in the Italian National Association of Holstein, Brown and Jersey Breeders (ANAFIBJ) were analyzed. Cows were genotyped with the HD Illumina Infinium BovineHD BeadChip and GeneSeek Genomic Profiler HD-150K, and the MD GeneSeek Genomic Profiler 3, GeneSeek Genomic Profiler 4, GeneSeek MD and the Labogena MD. To assess differences among estimators genomic inbreeding coefficients were estimated with 4 PLINK v1.9 estimators (F, Fhat1, 2, 3), 2 genomic relationship matrix (grm) based estimators (Fgrm and Fgrm2; with the latter including also pedigree information) and one estimator of runs of homozygosity (ROH; FROH). Assuming that the correct genomic inbreeding coefficients should be those estimated from genotyped SNP, a comparison of the genomic inbreeding coefficients estimated either with the genotyped SNP or the SNP after imputation was made. Information on the presence or absence of genotypic information from sire, dam and maternal grandsire during the imputation was investigated. Genomic inbreeding coefficients estimated with genotyped SNP or SNP after imputation were consistent for F, Fhat3, Fgrm2 and FROH, when at least one of the parents was genotyped. Biased (mainly higher) genomic inbreeding coefficients of imputation SNP were observed in cows that were genotyped with MD SNP panels whose SNP were poorly represented in the selected imputation SNP data set and also did not have their parents genotyped compared with what expected based on actual genotype data. For cows genotyped with MD the estimators Fhat1, Fhat2 and Fgrm provided higher genomic inbreeding coefficients of imputation SNP even with both parents and the maternal grandsire genotyped. Overall, FROH was the most robust estimator, followed by F and Fhat3. Our findings suggest that SNP selection, parental genotyping and estimator should be considered for designing imputation strategies in dairy cattle for estimating genomic inbreeding with imputation SNP. For computing genomic inbreeding coefficients, it is recommendable to have at least one parent genotyped and use an ROH based estimator.

Genetic evaluation of gestation length in Italian Holstein breed.

Gestation length (GL) can potentially affect health and performance of both the dam and the newborn calf, and it is controlled by two genetic components, direct and maternal. This means that both the calf (direct effect) and the cow (maternal effect) genotypes contribute to determine GL and its variability. The aims of the present study were to estimate direct and maternal variance components of GL, develop a routine genetic evaluation of GL in Italian Holstein and evaluate potential (un)favourable associations with traits for which selection is undertaken in this population. A multiple-trait repeatability linear animal model was employed for the estimation of variance components considering GL in first and later parities as different traits. The posterior mean (PM) of heritability of the direct effect was 0.43 for first parity and 0.35 for later parities. The PM of heritability of the maternal effect was lower, being 0.08 for primiparae and 0.06 for pluriparae. The posterior standard deviation (PSD) of the heritability estimates was small, ranging from 0.001 to 0.005. The relationship of direct and maternal effects with important traits such as milk yield and fertility indicated that selecting for extreme GL, longer or shorter, may have negative consequences on several traits, suggesting that GL has an intermediate optimum in dairy cattle. In conclusion, this study reveals that selecting an intermediate GL in the Italian Holstein population is advisable. Although scarcely variable compared to other conventional traits for which Italian Holstein is selected, GL is heritable and a deeper knowledge can be useful for decision-making at the farm level.

The role of inbreeding depression on productive performance in the Italian Holstein breed.

Inbreeding depression has become an urgent issue in cosmopolitan breeds where the massive genetic progress achieved in the latest generations is counterbalanced by a dramatic loss of genetic diversity causing increased health issues. Thus, the aim of this study was to estimate inbreeding depression on productive traits in Holstein dairy cattle. More precisely, we aimed to i) determine the level of inbreeding in 27,735 Italian Holstein dairy cows using pedigree and genotype data, ii) quantify the effect of inbreeding on 305-d in milk yield (MY; kg), fat yield (FY; kg), and protein yield (PY; kg) based on different statistical approaches, iii) determine if recent inbreeding has a more harmful impact than ancestral ones, and iv) quantify chromosomal homozygosity effect on productive traits. Quality control was performed on the autosomal chromosomes resulting in a final dataset of 84,443 single nucleotide polymorphisms. Four statistical models were used to evaluate the presence of inbreeding depression, which included linear regression analysis and division of FPED and FROH into percentile classes. Moreover, FROH was partitioned into i) length classes to assess the role of recent and ancestral inbreeding and ii) chromosome-specific contributions (FROH-CHR). Results evidenced that inbreeding negatively impacted the productive performance of Italian Holstein Friesian cows. However, differences between the estimated FPED and FROH coefficients resulted in different estimates of inbreeding depression. For instance, a 1% increase in FPED and FROH was associated with a decrease in MY of about 44 and 61 kg (P < 0.01). Further, when considering the extreme inbreeding percentile classes moving from the 5th lowest to the 95th highest, there was a reduction of -263 kg and -561 kg per lactation for FPED and FROH. Increased inbreeding, estimated by FPED and FROH, had also a negative effect on PY and FY, either fit as a regressor or percentile classes. When evaluating the impact of inbreeding based on runs of homozygosity (ROH) length classes, longer ROH (over 8 Mb) had a negative effect in all traits, indicating that recent inbreeding might be more harmful than the ancestral one. Finally, results within chromosome homozygosity highlighted specific chromosomes with a more deleterious effect on productive traits.

Inbreeding depression is a reduction in performance or health due to the mating of closely related individuals. The overall aim of this study was to investigate the level of inbreeding in the Italian Holstein dairy cow breed and quantify its negative effect on productive performances. The level of inbreeding was estimated by pedigree (FPED) and genomic data by looking at stretches of homozygosity (FROH). Both methods revealed a reduction in milk yield, fat yield, and protein yield when inbreeding increased. Moreover, the study demonstrated that FROH was able to capture more inbreeding depression compared to FPED. In addition, the more recent inbreeding had a stronger negative impact on productive performances compared to ancestral ones. Then, since the amount of runs of homozygosity can vary across the chromosomes of an individual, the effect of each chromosomal homozygosity region on productive traits was also evaluated. The chromosome-level results might be included in breeding programs to limit the accumulation of homozygosity in particular regions that appear to have a more detrimental effect on productive traits. Overall, this study highlights the importance of avoiding inbreeding in animal breeding programs to keep productive animals in the long term.

Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations.

Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application.

Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows.

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, Fhat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1st method, but with observed allele frequencies (Fgrm) and VanRaden's 3rd method that is allelic free and pedigree dependent (Fgrm2)], and (iii) a runs of homozygosity (roh) - based estimator (Froh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.

Estimation of milkability breeding values and variance components for Italian Holstein.

The importance of milkability as a trait is growing because of the need to efficiently use labor and machinery; therefore, it is crucial to update the statistical model for the trait to improve the accuracy of the estimated breeding values, and thus provide a more accurate tool for decision-making at the farm level. In the Italian Holstein Friesian cattle population, milkability is recorded twice a year by the milk recording system as a binary trait (slow, coded as 2, or not slow, coded as 1). Data consisted of 7,862,371 records from 2,945,249 cows collected between 2004 and 2021. A single-trait threshold animal model with repeated measures was used, with parity, days in milk class, calving season, and regression of production (fat + protein grams) within days in milk class as fixed effects and herd-year-season of recording, permanent environment, and animal as random effects. The results for heritability and repeatability were 0.275 and 0.5, estimated with the Gibbs sampler THRGIBBS1F90. Genomic validation, carried out using genotyped proven bulls born before 2009 as the training set, gave a result of 0.386 for reliability. The genetic correlations of this trait confirmed that both extremes of the estimated breeding value must be treated cautiously, because correlations with important traits such as mastitis resistance, body condition score, and teat length are unfavorable.

New insights into the raw milk microbiota diversity from animals with a different genetic predisposition for feed efficiency and resilience to mastitis.

The main objective of this study was to assess the microbiota diversity in milk samples collected from Holstein cows with different estimated breeding values for predicted feed efficiency, milk coagulation, resilience to mastitis, and consequently, to study its effects on milk quality. One hundred and twenty milk samples were collected in two seasons (summer and winter) from different commercial dairy farms in the Nord-east of Italy. For each trait, 20 animals divided into two groups of the high (10 cows) and the low (10 cows) were selected to study the microbiota profile using 16S rRNA metabarcoding sequencing. The alpha and beta diversity analysis revealed significant differences between the high and the low groups for feed efficiency and resilience to mastitis, while no significant difference was detected for milk coagulation. Moreover, remarkable differences among the taxa were detected between the two seasons, where the winter was more diverse than summer when applied the Chao1 index. Lastly, the linear discriminant analysis (LDA) effect size (LEfSe) indicated Aerococcus, Corynebacterium, Facklamia, and Psychrobacter taxa with more abundance in the high group of feed efficiency, whereas, in resilience to mastitis, only two genera of Mycoplana and Rhodococcus were more abundant in the low group. In addition, LEfSe analysis between the seasons showed significant differences in the abundance of Bacteroides, Lactobacillus, Corynebacterium, Escherichia, Citrobacter, Pantoea, Pseudomonas, and Stenotrophomonas. These findings indicate that the different genetic predisposition for feed efficiency and resilience to mastitis could affect the raw milk microbiota and, consequently, its quality. Moreover, we found more abundance of mastitis-associated bacteria in the milk of dairy cows with a higher feed efficiency index.

Identification of SNPs Associated with Somatic Cell Score in Candidate Genes in Italian Holstein Friesian Bulls.

Mastitis is an infectious disease affecting the mammary gland, leading to inflammatory reactions and to heavy economic losses due to milk production decrease. One possible way to tackle the antimicrobial resistance issue stemming from antimicrobial therapy is to select animals with a genetic resistance to this disease. Therefore, aim of this study was to analyze the genetic variability of the SNPs found in candidate genes related to mastitis resistance in Holstein Friesian bulls. Target regions were amplified, sequenced by Next-Generation Sequencing technology on the Illumina® MiSeq, and then analyzed to find correlation with mastitis related phenotypes in 95 Italian Holstein bulls chosen with the aid of a selective genotyping approach. On a total of 557 detected mutations, 61 showed different genotype distribution in the tails of the deregressed EBVs for SCS and 15 were identified as significantly associated with the phenotype using two different approaches. The significant SNPs were identified in intergenic or intronic regions of six genes, known to be key components in the immune system (namely CXCR1, DCK, NOD2, MBL2, MBL1 and M-SAA3.2). These SNPs could be considered as candidates for a future genetic selection for mastitis resistance, although further studies are required to assess their presence in other dairy cattle breeds and their possible negative correlation with other traits.

Genetic Diversity in the Italian Holstein Dairy Cattle Based on Pedigree and SNP Data Prior and After Genomic Selection.

Genetic diversity has become an urgent matter not only in small local breeds but also in more specialized ones. While the use of genomic data in livestock breeding programs increased genetic gain, there is increasing evidence that this benefit may be counterbalanced by the potential loss of genetic variability. Thus, in this study, we aimed to investigate the genetic diversity in the Italian Holstein dairy cattle using pedigree and genomic data from cows born between 2002 and 2020. We estimated variation in inbreeding, effective population size, and generation interval and compared those aspects prior to and after the introduction of genomic selection in the breed. The dataset contained 84,443 single-nucleotide polymorphisms (SNPs), and 74,485 cows were analyzed. Pedigree depth based on complete generation equivalent was equal to 10.67. A run of homozygosity (ROH) analysis was adopted to estimate SNP-based inbreeding (FROH). The average pedigree inbreeding was 0.07, while the average FROH was more than double, being equal to 0.17. The pattern of the effective population size based on pedigree and SNP data was similar although different in scale, with a constant decrease within the last five generations. The overall inbreeding rate (ΔF) per year was equal to +0.27% and +0.44% for Fped and FROH throughout the studied period, which corresponded to about +1.35% and +2.2% per generation, respectively. A significant increase in the ΔF was found since the introduction of genomic selection in the breed. This study in the Italian Holstein dairy cattle showed the importance of controlling the loss of genetic diversity to ensure the long-term sustainability of this breed, as well as to guarantee future market demands.

Genetic relationships of alternative somatic cell count traits with milk yield, composition and udder type traits in Italian Jersey cows.

The aim of this study was to estimate genetic associations between alternative somatic cell count (SCC) traits and milk yield, composition and udder type traits in Italian Jersey cows. Alternative SCC traits were test-day (TD) somatic cell score (SCS) averaged over early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), a binary trait indicating absence or presence of at least one TD SCC >400,000 cells/ml in the lactation (Infection) and the ratio of the number of TD SCC >400,000 cells/ml to total number of TD in the lactation (Severity). Heritabilities of SCC traits, including lactation-mean SCS (SCS_LM), ranged from 0.038 to 0.136. Genetic correlations between SCC traits were moderate to strong, with very few exceptions. Unfavourable genetic associations between milk yield and SCS_SD and Infection indicated that high-producing cows were more susceptible to variation in SCC than low-producing animals. Cows with deep udders, loose attachments, weak ligaments and long teats were more susceptible to an increase of SCC in milk. Overall, results suggest that alternative SCC traits can be exploited to improve cow's resistance to mastitis in Italian Jersey breed.

Missense and nonsense mutations in melanocortin 1 receptor (MC1R) gene of different goat breeds: association with red and black coat colour phenotypes but with unexpected evidences.

BACKGROUND: Agouti and Extension loci control the relative amount of eumelanin and pheomelanin production in melanocytes that, in turn, affects pigmentation of skin and hair. The Extension locus encodes the melanocortin 1 receptor (MC1R) whose permanent activation, caused by functional mutations, results in black coat colour, whereas other inactivating mutations cause red coat colour in different mammals. RESULTS: The whole coding region of the MC1R gene was sequenced in goats of six different breeds showing different coat colours (Girgentana, white cream with usually small red spots in the face; Maltese, white with black cheeks and ears; Derivata di Siria, solid red; Murciano-Granadina, solid black or solid brown; Camosciata delle Alpi, brown with black stripes; Saanen, white; F1 goats and the parental animals). Five single nucleotide polymorphisms (SNPs) were identified: one nonsense mutation (p.Q225X), three missense mutations (p.A81V, p.F250V, and p.C267W), and one silent mutation. The stop codon at position 225 should cause the production of a shorter MC1R protein whose functionality may be altered. These SNPs were investigated in a larger sample of animals belonging to the six breeds. The Girgentana breed was almost fixed for the p.225X allele. However, there was not complete association between the presence of red spots in the face and the presence of this allele in homozygous condition. The same allele was identified in the Derivata di Siria breed. However, its frequency was only 33%, despite the fact that these animals are completely red. The p.267W allele was present in all Murciano-Granadina black goats, whereas it was never identified in the brown ones. Moreover, the same substitution was present in almost all Maltese goats providing evidence of association between this mutation and black coat colour. CONCLUSION: According to the results obtained in the investigated goat breeds, MC1R mutations may determine eumelanic and pheomelanic phenotypes. However, they are probably not the only factors. In particular, the surprising not complete association of the nonsense mutation (p.Q225X) with red coat colour raises a few hypotheses on the determination of pheomelanic phenotypes in goats that should be further investigated.

The hairless (hr) gene is involved in the congenital hypotrichosis of Valle del Belice sheep.

Congenital hypotrichosis in mammalian species consists of partial or complete absence of hair at birth. The hairless gene is often responsible for this disorder in men, mice and rats. Recent experimental data on Valle del Belice sheep reared in Sicily for milk production, support the genetic control of the ovine hypotrichosis as a Mendelian recessive trait. The ovine hairless gene was chosen as the candidate gene involved in this disorder. Blood samples were collected from Valle del Belice sheep with the normal and hypotrichotic phenotypes. Almost the entire hairless gene was successfully amplified using the long PCR technique. Unrelated sheep with differing phenotypes were randomly chosen for sequencing the amplified products. Different mutations related to the hypotrichotic phenotype were found in exon 3. In fact, sequencing revealed an A/T transversion at position 739, a G/A transition at position 823, and a C/T transition at position 1312. From these nucleotide exchanges, three substitutions of the processed mature protein were deduced at the amino acid positions 247 (Thr/Ser), 275 (Ala/Thr), and 438 (Gln/Stop). A PCR-SSCP based test was developed in order to detect the last mutation, which is responsible for the hypotrichotic phenotype.