The main environmental factor that affects the regulation of reproductive seasonality is photoperiod through its effects on melatonin secretion. The melatonin receptor MTRN1A appears to be involved in regulating the reproductive seasonality and milk production in the period. The aim of this study was to identify polymorphisms in the MTRN1A gene and their possible associations with milk, fat and protein productions, fat and protein percentages, age at first calving, and first calving interval in buffaloes. Three genotypes (CC, CT, and TT) were identified by PCR-RFLP, and there was a significant association with protein percentage (P < 0.0001). Further studies are necessary to better understand the influence of melatonin gene and their receptors in the productive functions of buffaloes.

Objetivando estudiar la conformación corporal de ovinos de pelo criollos (Camura), se tomó una muestra aleatoria de 311 hembras mayores a 2 años de edad, vacías, pertenecientes a 8 fincas ubicadas en la sub-región Sabanas y Golfo de Morrosquillo en el departamento de Sucre, durante los meses de enero-marzo de 2011. Las características fanerópticas y morfológicas fueron la base del estudio, evaluándose variables cualitativas como: color de la capa, pigmentación de mucosas, pezuñas y ubre, al igual que inclinación de la grupa, perfil cefálico, dirección y tamaño de las orejas, profundidad de la ubre y tamaño del cuello, las cuales se registraron en fichas de campo. Los controles de cada una de las variables cualitativas se realizaron mediante observación directa e imágenes fotográficas, para la descripción de color de capa. Para evaluar las variables cualitativas se utilizó estadística descriptiva basada en tablas de distribución de frecuencias. En los ovinos de pelo criollos (Camura), predominó el color café, con mucosas nasales de tonalidades negras y oscurecidas, pezuñas marrón claro, ubre poco profunda sin pigmentación, grupa inclinada, cuello largo, perfil cefálico recto, orejas horizontales y de tamaño que varía entre pequeño y mediano. Peso corporal de 30,2  5,5 Kg. En conclusión las hembra ovino criollo - Camura colombiana, muestran una morfología corporal acorde a la producción cárnica, conjuntamente con aquellos que permiten una locomoción adecuada bajo sistemas extensivos, manteniendo una buena adaptación a las condiciones ambientales a las cuales está expuesta.

The diacylglycerol-O-transferase 1 gene is a positional and functional candidate for milk composition traits. The objective of this study was to evaluate the segregation of the variable number of tandem repeat polymorphisms in the regulatory region of diacylglycerol-O-transferase 1 gene in a water buffalo herd, and to assess the association of this mutation with milk production traits. For this purpose, 196 Murrah buffalo cows were genotyped by PCR. The association of the marker with total milk, fat, and protein yields at 305 d of lactation, milk fat and protein percentage, and somatic cell scores were evaluated by single-trait analyses using a generalized mixed model. Two segregating alleles were identified in the population. The allele with 2 repeats affected fat percentage favorably. The present results suggest that this polymorphism is an interesting marker to include in the genetic evaluation of buffaloes.

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal.

ABSTRACT. The objective of this study was to compare the multi-trait model using pedigree information and a model using genomic information in addition to pedigree information. We used data from 5896 lactations of 2021 buffalo cows, of which 384 were genotyped using the Illumina Infinium ® bovine HD BeadChip, considering seven traits related to milk yield (MY305), fat (FY305), protein (PY305), and lactose (LY305), percentages of fat (%F) and protein (%P), and somatic cell score (SCS). We carried out two analyses, one using phenotype and pedigree information (matrix A) and the other using the relationship matrix based on pedigree and genomics information (a single step, matrix H). The (co)variance components were estimated using multiple-trait analysis by the Bayesian inference method. The model included the fixed effects of contemporary groups (herd-year and calving season), and the age of cow at calving as (co)variables (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The estimates of heritability using matrix A were 0.25, 0.22, 0.26, (2015) 0.25, 0.37, 0.42, and 0.17, while using matrix H the heritability values were 0. 25, 0.24, 0.26, 0.26, 0.38, 0.47, and 0.18 for MY305, FY305, PY305, LY305, %F, %P, and SCS, respectively. The estimates of breeding values in the two analyses were similar for the traits studied, but the accuracies were greater when using matrix H (higher than 8% in the traits studied). Therefore, the use of genomic information in the analyses improved the accuracy.