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The aim of this study was to assess the most important risk factors that influence productive life (PL) and to estimate genetic parameters for PL using a Weibull proportional hazards model in two Spanish dairy goat breeds belonging to different production systems. The dataset consisted of 70,695 and 49,176 lactation records of Florida and Payoya females, respectively, collected over the last two decades. A total of 6,227 (24.21%) Florida and 3,452 (20.42%) Payoya females had censored information. The pedigree included a total of 56,901 animals for Florida and 59,957 for Payoya. The effects included in the model for both breeds were the age at first kidding and the herd-year-season of birth of the doe as time-independent effects; and the age at kidding, the herd-year-season of kidding, the within-herd class of milk production deviation and the combination between the lactation number and the duration of lactation as time-dependent effects. Estimation of genetic parameters was made using a Weibull proportional hazards model using Survival Kit V6.0 software. The results from the Weibull animal models gave estimates of additive genetic variances of 0.99 ± 0.0003 and 0.156 ± 0.021, which corresponds to a heritability of 0.43 ± 0.025 and 0.11 ± 0.021 for Florida and Payoya, respectively. The magnitude of heritability obtained for PL suggests that a substantial response to selection may be expected for longevity, especially in the Florida breed. These results may contribute to the development of a routine genetic evaluation to improve PL in Spanish dairy goat breeds.

This study aimed to assess genetic parameters for ewe productivity in a Tunisian Barbarine sheep line. The traits studied were litter size (LS), birth weight (BW), weight at 90 days (W90), and average daily gain between 10 and 30 days (ADG13). A total of 3804 growth and 2726 lambing records were used. Bivariate linear and threshold animal models were fitted and analyzed using the Gibbs sampling methodology. Heritabilities for LS obtained with univariate threshold, bivariate linear, and threshold models were around 0.15, higher than the estimate obtained by a univariate linear model (0.09 ± 0.03). Direct heritability for growth traits remained consistent across models, except for W90 in the bivariate linear threshold model. Maternal heritability for growth traits was higher than direct heritability, ranging from 0.07 to 0.15, except for BW. The covariances between the direct and maternal effects of growth traits were slightly negative. Repeatability oscillated between 0.16 and 0.62. Direct genetic correlations between LS and the other traits were negative, varying from −0.18 (LS-BW) to −0.83 (LS-W90). Our results suggest that the threshold model may be the most appropriate for LS. A selection index including LS and growth traits may be proposed for routine genetic evaluation in this population.

The aim of this study was to estimate genetic parameters of somatic cell score (SCS) and fat plus protein yield (FPY) using repeatability (RM) and random regression (RRM) models in Florida goats. The data consisted of 340,654 test-day controls of the first three lactations, and the pedigree contained 36,144 animals. Covariance components were estimated with a bivariate RM and RRM using the REML approach. Both models included as fixed effects the combination of herd and control date, litter size, kidding number and lactation length, and as random effects, the additive genetic and permanent environmental effects. A variation in the shape of the genetic parameters along the lactation curve was observed for both traits, and h2 oscillated between 0.272 and 0.279 for SCS and 0.099 and 0.138 for FPY. The genetic correlation between SCS and FPY was negative and medium (−0.304 to −0.477), indicating that a low-SCS EBV is associated with a genetic predisposition to high FPY production. Our results showed that given the magnitude of h2 for SCS and its rg with FPY, the SCS could be used as a selection criterion to increase resistance to mastitis, thus obtaining an improved dairy and cheese aptitude in this breed.

The aim of this study was to compare selection indices for important traits in intensive Spanish goat breeds in four economic scenarios, using the Florida as most representative breed of this production system in Spain. For this analysis, we considered the following traits: milk yield (MY), fat plus protein yields (FPY), casein yield (CY), somatic cell score (SCS), reproductive efficiency (RE), litter size (LS), mammary system (MS), final score (FS), body capacity index (BCI), and length of productive life (LPL). We estimated the genetic parameters and EBVs of most of these traits with REML methodology, while LPL was modeled through survival analysis. Four scenarios were proposed, depending on the overall objective for improvement: (1) milk production, (2) milk production and cheese extract, (3) cheese extract, and (4) milk production, cheese extract and sale of animals. Then, within each scenario, three different types of indices were designed using the different primary and secondary objectives/criteria considered suitable to improve the overall objective. The results indicated that selecting only for primary traits yielded the highest genetic response for all the scenarios. Including secondary traits led to positive correlated responses in those traits, but a decrease in the responses in the primary criteria.

Vitiligo is a depigmentation autoimmune disorder characterized by the progressive loss of melanocytes leading to the appearance of patchy depigmentation of the skin. The presence of vitiligo in horses is greater in those with grey coats. The aim of this study was therefore to perform a genome-wide association study (GWAS) to identify genomic regions and putative candidate loci associated with vitiligo depigmentation and susceptibility in the Pura Raza Español population. For this purpose, we performed a wssGBLUP (weighted single step genomic best linear unbiased prediction) using data from a total of 2359 animals genotyped with Affymetrix Axiom™ Equine 670 K and 1346 with Equine GeneSeek Genomic Profiler™ (GGP) Array V5. A total of 60,136 SNPs (single nucleotide polymorphisms) present on the 32 chromosomes from the consensus dataset after quality control were employed for the analysis. Vitiligo-like depigmentation was phenotyped by visual inspection of the different affected areas (eyes, mouth, nostrils) and was classified into nine categories with three degrees of severity (absent, slight, and severe). We identified one significant genomic region for vitiligo around the eyes, eight significant genomic regions for vitiligo around the mouth, and seven significant genomic regions for vitiligo around the nostrils, which explained the highest percentage of variance. These significant genomic regions contained candidate genes related to melanocytes, skin, immune system, tumour suppression, metastasis, and cutaneous carcinoma. These findings enable us to implement selective breeding strategies to decrease the incidence of vitiligo and to elucidate the genetic architecture underlying vitiligo in horses as well as the molecular mechanisms involved in the disease’s development. However, further studies are needed to better understand this skin disorder in horses.

A total of 1,031,143 records of daily dairy control test of Spanish Florida goats were used for this study. The database was edited, and only the records of the first three lactations were kept. The final database contained 340,654 daily-test somatic cell counts from 27,749 daughters of 941 males and 16,243 goats. The evolution of this count in the last 14 years was analyzed following French and American international associations’ criteria for the risk of mastitis in goats, and confirmed the slight increase in SCS in the last years and the importance of this problem (50% of dairy control tests show a risk of suffering mastitis). For the genetic analysis, the SCS records were log-transformed to normalize this variable. Two strategies were used for the genetic analysis: a univariate animal model for the SCS assuming that SCS does not vary throughout the parities, and a multi-character animal model, where SCS is not considered as the same character in the different parities. The heritabilities (h2) were higher in the multiple traits models, showings an upward trend from the first to the third parity (h2 between 0.245 to 0.365). The genetic correlations of the same trait, as well as between breeding values (GVs) between different parities, were different from unity. The breeding values (EBVs) obtained for both models were subjected to a PCA: the first eigenvector (λ1) explained most of the variations (between 74% to 90%), while the second λ2 accounted for between 9% to 20% of the variance, which shows that the selection will be proportionally favorable but not equivalent in all parities and that there are some variations in the type of response.