Conditioning factors of linearized wood's function lactation curve shape parameters, milk yield, fat and protein content in murciano-granadina primiparous does

Research Areas: Agriculture ; Veterinary Sciences ; ZoologyA total of 137,927 controls of 22,932 Murciano-Granadina first lactation goats (measured between 1996–2016) were evaluated to determine the influence of the number of kids, season, year and farm on total milk yield, daily milk yield, lactation length, total production of fat and protein and percentages of fat and protein. All factors analyzed had a significant effect on the variables studied, except for the influence of the number of kids on the percentages of fat and protein, where the variation was very small. Goats with two offspring produced nearly 15% more milk, fat and protein per lactation compared to goats with simple kids. Kiddings occurring in summer–autumn resulted in average milk, fat and protein yields nearly 14, 19 and 23% higher when compared to winter–spring kiddings. Lactation curves were evaluated to determine the effects of the number of kids and season, using the linearized version of the model of Wood in random regression analyses. Peak Yield increased by about 0.3 kg per additional offspring at kidding, but persistence was higher in goats with single offspring. The kidding season significantly influenced the lactation curve shape. Hence summer-kidding goats were more productive, and peak occurred earlier, while a higher persistence was observed in goats kidding during autumn.info:eu-repo/semantics/publishedVersio

Characterisation of biological growth curves of different varieties of an endangered native hen breed kept under free range conditions

The aim of this study is to model the growth samples of four varieties (White, Black, Partridge, Franciscan) of Spanish Utrerana hen breed, which is endangered, by using Brody, Von Bertalanffy, Verhulst, Logistic and Gompertz models. For this purpose, a total of 16,235 weight data observations from 2004 animals reared in free range system were collected. Logistic was the best suited model for predicting the biological growth curve of White variety in both sexes, while Von Bertalanffy was the best fitting model for the rest of individuals of the breed, based on the 5 goodness-of-fit and flexibility criteria: Pseudo-R2 , mean squared error, Akaike information criterion, Bayesian information criterion and the biological coherence of the estimated parameters. Black variety was the heaviest, with values of 2605.96 and 2032.61 g (for males and females, respectively) for a parameter, while White variety presented the lowest maturity weight (a ¼ 2442.99 and 1874.24 g, for males and females, respectively). Conclusively, this growth characterisation is essential for the conservation of the Utrerana hen, to search for new market niches and a greater profitability to this differentiated product.info:eu-repo/semantics/publishedVersio

Determination of breeding criteria for gait proficiency in leisure riding and racing dromedary camels: a stepwise multivariate analysis of factors predicting overall biomechanical performance

To date, the biomechanical dynamics in camelids have not been addressed, although it might be a factor that can affect selection and breeding in this species. Therefore, the aim of this article is to conduct curve fitting and discriminant canonical analysis to identify the mathematical function that best captures the dynamics of camel locomotion and to study the impact of kinematic, morphometric, physiological, and phaneroptic variables on gait performance in leisure riding and racing activities in dromedaries, respectively. The cubic function emerged as the most suitable mathematical model to represent the locomotive behavior of camels. Various factors were found to play a pivotal role in the athletic performance of leisure riding and racing dromedary camels. Concretely, angular measurements at the distal fore and rear extremity areas, pelvis inclination, relative volume of the hump, impact forces of the front limbs, post-neutering effects, and the kinematic behavior of the scapula, shoulder, carpus, hip, and foot are the factors that greatly impact gait performance in leisure riding and racing camels. The biomechanical performance at these specific body regions has a profound impact on weight absorption and minimization of mechanic impact during camel locomotion, static/dynamic balance, force distribution, energy of propulsion, movement direction and amplitude, and storage of elastic strain in leisure riding and racing dromedaries. In contrast, other animal- and environment-dependent factors do not exert significant influence on camel gait performance, which can be attributed to species-specific, inherited adaptations developed in response to desert conditions, including the pacing gait, broad foot pads, and energy-efficient movements. The outcomes of our functional data analysis can provide valuable insights for making informed breeding decisions aimed at enhancing animal functional performance in camel riding and racing activities. Furthermore, these findings can open avenues for exploring alternative applications, such as camel-assisted therapy

Study of meat and carcass quality-related traits in Turkey populations through discriminant canonical analysis

The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discussing carcass and meat characteristics in the turkey species was performed. Meat and carcass attributes of nine different turkey populations were collected and grouped in terms of the following clusters: carcass dressing traits, muscle fiber properties, pH, color-related traits, water-retaining characteristics, texture-related traits, and meat chemical composition. The Bayesian ANOVA analysis reported that the majority of variables statistically differed (p < 0.05), and the multicollinearity analysis revealed the absence of redundancy problems among variables (VIF < 5). The DCA reported that cold carcass weight, slaughter weight, sex-male, carcass/piece weight, and the protein and fat composition of meat were the traits explaining variability among different turkey genotypes (Wilks’ lambda: 0.488, 0.590, 0.905, 0.906, 0.937, and 0.944, respectively). The combination of traits in the first three dimensions explained 94.93% variability among groups. Mahalanobis distances cladogram-grouped populations following a cluster pattern and suggest its applicability as indicative of a turkey genotype’s traceability

Can donkey behavior and cognition be used to trace back, explain, or forecast moon cycle and weather events?

Donkeys have been reported to be highly sensitive to environmental changes. Their 8900-8400-year-old evolution process made them interact with diverse environmental situations that were very distant from their harsh origins. These changing situations not only affect donkeys' short-term behavior but may also determine their long-term cognitive skills from birth. Thus, animal behavior becomes a useful tool to obtain past, present or predict information from the environmental situation of a particular area. We performed an operant conditioning test on 300 donkeys to assess their response type, mood, response intensity, and learning capabilities, while we simultaneously registered 14 categorical environmental factors. We quantified the effect power of such environmental factors on donkey behavior and cognition. We used principal component analysis (CATPCA) to reduce the number of factors affecting each behavioral variable and built categorical regression (CATREG) equations to model for the effects of potential factor combinations. Effect power ranged from 7.9% for the birth season on learning (p < 0.05) to 38.8% for birth moon phase on mood (p < 0.001). CATPCA suggests the percentage of variance explained by a four-dimension-model (comprising the dimensions of response type, mood, response intensity and learning capabilities), is 75.9%. CATREG suggests environmental predictors explain 28.8% of the variability of response type, 37.0% of mood, and 37.5% of response intensity, and learning capabilities

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R 2 ) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R 2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R 2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p &gt; 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry

Diversidade genética do cavalo Pantaneiro e relações com outras raças de eqüinos

The objective of this work was to evaluate the genetic diversity of Brazilian Pantaneiro horse by microsatellite markers, investigate the effect of genetic bottlenecks and estimate genetic differentiation among four horse breeds. Genetic variation was estimated through allele frequencies and mean breed heterozygosity. Nei´s genetic distances among the breeds Pantaneiro, Thoroughbred, Arabian, Spanish Pure Breed (Andalusian), and Uruguay Creole were calculated, and it was used to construct an UPGMA dendrogram. Clustering at different K values was calculated to infer population structure and assign individuals to populations. Nei´s distances showed a minimum distance between Pantaneiro horse and Spanish Pure Breed (0.228), and similar distances from Spanish Pure Breed to Thoroughbred and to Arabian (0.355 and 0.332). It was observed a great level of diversity, clear distance from Pantaneiro horse to other breeds, and genetic uniformity within breed. It was verified a certain level of substructure of Pantaneiro horse showing no influences from the other studied breeds.O objetivo deste trabalho foi avaliar a variabilidade genética do cavalo Pantaneiro, por meio de marcadores microssatélites, investigar o efeito genético de "bottlenecks" e estimar a variação genética entre quatro raças de cavalo. A diversidade genética foi estimada por meio da freqüência de alelos e da média de heterozigosidade por raças. A distância genética de Nei foi calculada para as raças Pantaneiro, Puro Sangue Inglês, Árabe, Puro Sangue Espanhol e Crioulo Uruguaio. O agrupamento em diferentes valores de K foi calculado para inferir a estrutura da população e determinar indivíduos às populações. A distância de Nei mostrou distância mínima entre o cavalo Pantaneiro e o Puro Sangue Espanhol (0,228), e entre o Puro Sangue Espanhol e o Puro Sangue Inglês e o Árabe (0,355 e 0,332, respectivamente). Foi observada grande diversidade genética dentro da raça Pantaneiro, evidente distância desta raça em relação às demais raças estudadas, e uniformidade genética dentro da raça. Verificou-se certo nível de subestruturação no cavalo Pantaneiro, sem demonstrar influência das outras raças estudadas

Genomic patterns of homozygosity and inbreeding depression in Murciano-Granadina goats

Inbreeding depression can adversely affect traits related to fitness, reproduction and productive performance. Although current research suggests that inbreeding levels are generally low in most goat breeds, the impact of inbreeding depression on phenotypes of economic interest has only been investigated in a few studies based on genealogical data. We genotyped 1040 goats with the Goat SNP50 BeadChip. This information was used to estimate different molecular inbreeding coefficients and characterise runs of homozygosity and homozygosity patterns. We detected 38 genomic regions with increased homozygosity as well as 8 ROH hotspots mapping to chromosomes 1, 2, 4, 6, 14, 16 and 17. Eight hundred seventeen goats with available records for dairy traits were analysed to evaluate the potential consequences of inbreeding depression on milk phenotypes. Four regions on chromosomes 8 and 25 were significantly associated with inbreeding depression for the natural logarithm of the somatic cell count. Notably, these regions contain several genes related with immunity, such as SYK, IL27, CCL19 and CCL21. Moreover, one region on chromosome 2 was significantly associated with inbreeding depression for milk yield. Although genomic inbreeding levels are low in Murciano-Granadina goats, significant evidence of inbreeding depression for the logarithm of the somatic cell count, a phenotype closely associated with udder health and milk yield, have been detected in this population. Minimising inbreeding would be expected to augment economic gain by increasing milk yield and reducing the incidence of mastitis, which is one of the main causes of dairy goat culling

A genome-wide analysis of copy number variation in Murciano-Granadina goats

Altres ajuts: CERCA Programme/Generalitat de CatalunyaBackground: In this work, our aim was to generate a map of the copy number variations (CNV) segregating in a population of Murciano-Granadina goats, the most important dairy breed in Spain, and to ascertain the main biological functions of the genes that map to copy number variable regions. Results: Using a dataset that comprised 1036 Murciano-Granadina goats genotyped with the Goat SNP50 BeadChip, we were able to detect 4617 and 7750 autosomal CNV with the PennCNV and QuantiSNP software, respectively. By applying the EnsembleCNV algorithm, these CNV were assembled into 1461 CNV regions (CNVR), of which 486 (33.3% of the total CNVR count) were consistently called by PennCNV and QuantiSNP and used in subsequent analyses. In this set of 486 CNVR, we identified 78 gain, 353 loss and 55 gain/loss events. The total length of all the CNVR (95.69 Mb) represented 3.9% of the goat autosomal genome (2466.19 Mb), whereas their size ranged from 2.0 kb to 11.1 Mb, with an average size of 196.89 kb. Functional annotation of the genes that overlapped with the CNVR revealed an enrichment of pathways related with olfactory transduction (fold-enrichment = 2.33, q-value = 1.61 × 10-10), ABC transporters (fold-enrichment = 5.27, q-value = 4.27 × 10-04) and bile secretion (fold-enrichment = 3.90, q-value = 5.70 × 10-03). Conclusions: A previous study reported that the average number of CNVR per goat breed was ~ 20 (978 CNVR/50 breeds), which is much smaller than the number we found here (486 CNVR). We attribute this difference to the fact that the previous study included multiple caprine breeds that were represented by small to moderate numbers of individuals. Given the low frequencies of CNV (in our study, the average frequency of CNV is 1.44%), such a design would probably underestimate the levels of the diversity of CNV at the within-breed level. We also observed that functions related with sensory perception, metabolism and embryo development are overrepresented in the set of genes that overlapped with CNV, and that these loci often belong to large multigene families with tens, hundreds or thousands of paralogous members, a feature that could favor the occurrence of duplications or deletions by non-allelic homologous recombination

Expression patterns and genetic variation of the ovine skeletal muscle transcriptome of sheep from five Spanish meat breeds

The goal of the current study is to analyse the gene expression profile of the ovine skeletal muscle as well as to characterize the genetic variation of transcripts expressed in such tissue. This aim has been achieved by sequencing the longissimus dorsi transcriptomes of 50 sheep distributed in five pools representing the Canaria de Pelo, Roja Mallorquina, Gallega, Xisqueta and Ripollesa Spanish autochthonous breeds. Approximately, 363 million reads per pool have been produced and 71.9-82.9% have been successfully mapped to the ovine genome in a paired-end mode (2 X 75 bp). The 200 most expressed muscle transcripts (-1% of the total transcript count) account for 51% (Canaria de Pelo) to 67% (Gallega) of the total ovine skeletal muscle mRNA expression. These highly expressed genes play key roles in pathways related with striated muscle contraction, gluconeogenesis, glycolysis, citric acid cycle and respiratory electron transport. RNA-Sequencing of muscle transcripts has also revealed that -72% of the SNPs detected with this approach are shared by at least two pools, and 10% of them segregate in the five pools under analysis. Most of the substitutions detected by RNA-Seq are synonymous or missense and only a minority are predicted to have consequences on protein function