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.

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.

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.

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, F_hat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1^st method, but with observed allele frequencies (F_grm) and VanRaden's 3^rd method that is allelic free and pedigree dependent (F_grm2)], and (iii) a runs of homozygosity (roh) - based estimator (F_roh). 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

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The national genetic evaluation for milkability in Italian Holstein was revised.

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A stricter data editing and a different approach to the phenotype, from ratio to single observations, were applied.

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A different statistical model was used, changing from a linear to a threshold model.

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Higher genomic reliability was achieved with the revised model.

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The revised model provides more reliable breeding values for decision-making at the farm level.

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.

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 (F_ROH). The average pedigree inbreeding was 0.07, while the average F_ROH 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 F_ped and F_ROH 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.

Genome-wide scan reveals genetic divergence in Italian Holstein cows bred within PDO cheese production chains

Dairy cattle breeds have been exposed to intense artificial selection for milk production traits over the last fifty years. In Italy, where over 80% of milk is processed into cheese, selection has also focused on cheese-making traits. Due to a deep-rooted tradition in cheese-making, currently fifty Italian cheeses are marked with the Protected Designation of Origin (PDO) label as they proved traditional land of origin and procedures for milk transformation. This study aimed to explore from a genetic point of view if the presence of such diverse productive contexts in Italy have shaped in a different manner the genome of animals originally belonging to a same breed. We analyzed high density genotype data from 1000 Italian Holstein cows born between 2014 and 2018. Those animals were either farmed in one of four Italian PDO consortia or used for drinkable milk production only. Runs of Homozygosity, Bayesian Information Criterion and Discriminant Analysis of Principal Components were used to evaluate potential signs of genetic divergence within the breed. We showed that the analyzed Italian Holstein cows have genomic inbreeding level above 5% in all subgroups, reflecting the presence of ongoing artificial selection in the breed. Our study provided a comprehensive representation of the genetic structure of the Italian Holstein breed, highlighting the presence of potential genetic subgroups due to divergent dairy farming systems. This study can be used to further investigate genetic variants underlying adaptation traits in these subgroups, which in turn might be used to design more specialized breeding programs.