Background: A growing demand for improved physical skills and mental attitude in modern sport horses has led to strong selection for performance in many warmblood studbooks. The aim of this study was to detect genomic regions with low diversity, and therefore potentially under selection, in Swedish Warmblood horses (SWB) by analysing high-density SNP data. To investigate if such signatures could be the result of selection for equestrian sport performance, we compared our SWB SNP data with those from Exmoor ponies, a horse breed not selected for sport performance traits.Results: The genomic scan for homozygous regions identified long runs of homozygosity (ROH) shared by more than 85% of the genotyped SWB individuals. Such ROH were located on ECA4, ECA6, ECA7, ECA10 and ECA17. Long ROH were instead distributed evenly across the genome of Exmoor ponies in 77% of the chromosomes. Two population differentiation tests (F_STand XP-EHH) revealed signatures of selection on ECA1, ECA4, and ECA6 in SWB horses.Conclusions: Genes related to behaviour, physical abilities and fertility, appear to be targets of selection in the SWB breed. This study provides a genome-wide map of selection signatures in SWB horses, and ground for further functional studies to unravel the biological mechanisms behind complex traits in horses.

The aim of this research is to propose equations to estimate body weight (BW) from body measures (BMs) in the Cornigliese sheep, an endangered breed reared in Italy for meat purpose. BW and BMs were submitted to correlation and multiple regression analyses. Two datasets were used: (i) 303 animals (178 females, 125 males, BW 4.00–117.80 kg), on which BW, height at withers (HW), chest circumference (ChC) and body length (BL) were measured; (ii) 156 animals (109 females, 47 males, BW 5.15–117.80 kg) out of 303 on which croup height (HCr), chest width (ChW), chest depth (ChD) and croup width (CrW) were also considered. On each dataset, two regression models were applied, one containing all variables (models 1 and 3, respectively, for datasets 1 and 2) and the other one comprising groups of variables, selected by means of the stepwise procedure (models 2 and 4, respectively, for datasets 1 and 2). BW resulted correlated with all BMs (from 0.852 for ChW to 0.950 for ChC; p < .001). Models 1 and 3 fitted the data better than models 2 and 4, both for all animals and for females and males separately. We concluded that BW could be predicted from BMs also in Cornigliese sheep breed. The best fits were obtained when the highest number of measures was included in the model (models 1 and 3). Nevertheless, models 2 and 4 could be used more easily in extensive sheep breeding than models 1 and 3, since they require less parameters.

Horses are nowadays mainly used for sport and leisure activities, and several local breeds, traditionally used in agriculture, have been exposed to a dramatic loss in population size and genetic diversity. The loss of genetic diversity negatively impacts individual fitness and reduces the potential long-term survivability of a breed. Recent advances in molecular biology and bioinformatics have allowed researchers to explore biodiversity one step further. This study aimed to evaluate the loss of genetic variability and identify genomic regions under selection pressure in the Bardigiano breed based on GGP Equine70k SNP data. The effective population size based on Linkage Disequilibrium (N_e) was equal to 39 horses, and it showed a decline over time. The average inbreeding based on runs of homozygosity (ROH) was equal to 0.17 (SD = 0.03). The majority of the ROH were relatively short (91% were ≤2 Mbp long), highlighting the occurrence of older inbreeding, rather than a more recent occurrence. A total of eight ROH islands, shared among more than 70% of the Bardigiano horses, were found. Four of them mapped to known quantitative trait loci related to morphological traits (e.g., body size and coat color) and disease susceptibility. This study provided the first genome-wide scan of genetic diversity and selection signatures in an Italian native horse breed.

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.

Background: Copy Number Variation (CNV) is a common form of genetic variation underlying animal evolution and phenotypic diversity across a wide range of species. In the mammalian genome, high frequency of CNV differentiation between breeds may be candidates for population-specific selection. However, CNV differentiation, selection and its population genetics have been poorly explored in horses. Results: We investigated the patterns, population variation and gene annotation of CNV using the Axiom® Equine Genotyping Array (670,796 SNPs) from a large cohort of individuals (N = 1755) belonging to eight European horse breeds, varying from draught horses to several warmblood populations. After quality control, 152,640 SNP CNVs (individual markers), 18,800 segment CNVs (consecutive SNP CNVs of same gain/loss state or both) and 939 CNV regions (CNVRs; overlapping segment CNVs by at least 1 bp) compared to the average signal of the reference (Belgian draught horse) were identified. Our analyses showed that Equus caballus chromosome 12 (ECA12) was the most enriched in segment CNV gains and losses (~ 3% average proportion of the genome covered), but the highest number of segment CNVs were detected on ECA1 and ECA20 (regardless of size). The Friesian horses showed private SNP CNV gains (> 20% of the samples) on ECA1 and Exmoor ponies displayed private SNP CNV losses on ECA25 (> 20% of the samples). The Warmblood cluster showed private SNP CNV gains located in ECA9 and Draught cluster showed private SNP CNV losses located in ECA7. The length of the CNVRs ranged from 1 kb to 21.3 Mb. A total of 10,612 genes were annotated within the CNVRs. The PANTHER annotation of these genes showed significantly under- and overrepresented gene ontology biological terms related to cellular processes and immunity (Bonferroni P-value < 0.05). We identified 80 CNVRs overlapping with known QTL for fertility, coat colour, conformation and temperament. We also report 67 novel CNVRs. Conclusions: This work revealed that CNV patterns, in the genome of some European horse breeds, occurred in specific genomic regions. The results provide support to the hypothesis that high frequency private CNVs residing in genes may potentially be responsible for the diverse phenotypes seen between horse breeds.

The objective of this study was to estimate inbreeding coefficients in Holstein dairy cattle using imputed SNPs data. A data set of 95,540 Italian Holstein dairy cows from the routine genomic evaluations of the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed, with 84,445 imputed SNP. Ten widely used genomic inbreeding estimators were tested, including 4 PLINK v1.9 estimators (F, F_HAT1, F_HAT2, F_HAT3), 3 genomic relationship matrix (GRM)-based methods [VanRaden's first method with observed allele frequencies (F_GRM) or with fixed frequencies at 0.5 (F_GRM05), VanRaden's third method, allelic frequency free and pedigree regressed (F_GRM2)], runs of homozygosity (ROH)-based estimators in a complete (F_ROH) and simplified version (F_ROH2), and proportion of homozygous SNP (F_PH). Pairwise comparisons among them were made, including the comparison with traditional pedigree-based inbreeding coefficients (F_PED). Our results showed variability among the genomic inbreeding estimators. Coefficients of F_GRM and F_HAT3 were >1, meaning that more variability has been lost than the variability that existed in the base population. Regarding the remaining ones, F_GRM05, F_ROH, F_ROH2, and F_PH provided coefficients within the [0,1] space and are considered comparable to F_PED. Not comparable to F_PED, yet with an interpretable value, can be considered the coefficients of F, F_HAT2, and F_GRM2. Estimators based on ROH had the highest correlation with pedigree-based coefficients (0.59-0.66), among all estimators tested. In this study, Spearman correlations were shown to possibly provide a clearer estimation of the strength of the relationship between estimators. We hypothesize that imputation might cause extreme genomic inbreeding values that deserves further investigation.