Genetic Parameters for Productive and Reproductive Traits for Milk Buffalo in Brazil

Knowing the genetic parameters of productive and reproductive traits in milking buffaloes is essential for planning and implementing of a program genetic selection. In Brazil, this information is still scarce. The objective of this study was to verify the existence of genetic variability in milk yield of buffaloes and their constituents, and reproductive traits for the possibility of application of the selection. A total of 9,318 lactations records from 3,061 cows were used to estimate heritabilities for milk yield (MY), fat percentage (%F), protein percentage (%P), length of lactation (LL), age of first calving (AFC) and calving interval (CI) and the genetic correlations among traits MY, %F and %P. The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year and calving season), number of milking (2 levels), and age of cow at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. Estimated heritability values for MY, % F, % P, LL, AFC and CI were 0.24, 0.34, 0.40, 0.09, 0.16 and 0.05, respectively. The genetic correlation estimates among MY and % F, MY and % P and % F and % P were -0.29, -0.18 and 0.25, respectively. The production of milk and its constituents showed enough genetic variation to respond to a selection program. Negative estimates of genetic correlations between milk production and its components suggest that selection entails a reduction in the other.

Estimates of genetic parameters for total milk yield over multiple ages in Brazilian Murrah buffaloes using different models

The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

Genetic association between milk yield, stayability, and mastitis in Holstein cows under tropical conditions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameters for production traits of dairy Gyr (Bos indicus) x Holstein cattle estimated with a random regression model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multiple-trait genomic evaluation for milk yield and milk quality traits using genomic and phenotypic data in buffalo in Brazil

The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

Accumulated productivity and its genetic association with reproductive traits in females Brahman

Objective. Assessment of genetic parameters for accumulative productivity trait (ACP) and genetic correlations with age at first calving (AFC), between calving interval of first and second parity (BCI1) and longevity (LONG). Materials and methods. 8584 Brahman female records were used with an animal model in multi-trait analysis with restricted maximum likelihood method, implemented using the WOMBAT software. The models considered the fixed effects of contemporary group, parity and weaning weight of first calf covariate, the only random effect was the genetic additive direct. Weaning weight (P240) was included to reduce the effect of selection on the estimation of variance components. Results. The heritability estimates were 0.3 +/- 0.04, 0.11 +/- 0.03, 0.07 +/- 0.03 and 0.24 +/- 0.04 for AFC, BCI1, LONG and ACP respectively. Correlations between ACP and the other features were moderate to high and favorable. Conclusions. ACP can be included in breeding programs for Brahman, and used as selection criteria for its moderate heritability and genetic correlation with reproductive traits.

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Ranking of Nellore animals in cattle championships: genetic parameters and correlations with production traits

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Finishing precocity visual score and genetic associations with growth traits in Angus beef cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Produção de leite, duração da lactação e intervalo de partos em búfalas mestiças Murrah

This study aimed to evaluate the potential for milk production (MP), lactation length (LL) and calving interval (CI), analyze the environmental component affecting these traits, and to estimate the heritability and repeatability for milk production in crossbreds of Murrah buffalo cows in the state of Alagoas, Brazil. Data was composed of 487 observations of MP from 136 lactations recorded between the years of 2000 and 2010. In the analysis of variance for PL, the fixed effects were season (1- October to March, 2 -April to September) and year of the beginning of lactation, calving order and the LL (covariate). For the analysis of LL only the fixed effect of year of the beginning of lactation was included, and finally for the CI analysis, year of the beginning of lactation and calving order. The estimates of covariance were obtained using unicharacteristic analysis by Bayesian inference method, applyingan animal model, through Gibbs sampling. The additive genetic, permanent environment and residual effects were included as random effects in the model. The averages (sd) of MP, LL and CI were 2,218.03 kg (408.18), 282.59 days (39.48) e 422.49 days (91.05), respectively. All the effects included in the models were important (P<0.01). The estimates of heritability and repeatability for PL were 0.29 and 0.69, respectively. The results suggest that there is a moderate genetic variability among individuals for PL, indicating the possibility to obtain gain using selection.

Key participants of the tumor microenvironment of the prostate: An approach of the structural dynamic of cellular elements and extracellular matrix components during epithelial-stromal transition

Cancer is a multistep process that begins with the transformation of normal epithelial cells and continues with tumor growth, stromal invasion and metastasis. The remodeling of the peritumoral environment is decisive for the onset of tumor invasiveness. This event is dependent on epithelial–stromal interactions, degradation of extracellular matrix components and reorganization of fibrillar components. Our research group has studied in a new proposed rodent model the participation of cellular and molecular components in the prostate microenvironment that contributes to cancer progression. Our group adopted the gerbil Meriones unguiculatus as an alternative experimental model for prostate cancer study. This model has presented significant responses to hormonal treatments and to development of spontaneous and induced neoplasias. The data obtained indicate reorganization of type I collagen fibers and reticular fibers, synthesis of new components such as tenascin and proteoglycans, degradation of basement membrane components and elastic fibers and increased expression of metalloproteinases. Fibroblasts that border the region, apparently participate in the stromal reaction. The roles of each of these events, as well as some signaling molecules, participants of neoplastic progression and factors that promote genetic reprogramming during epithelial–stromal transition are also discussed.

Genetic divergence among maize hybrids by morphological descriptors

Two experiments with 25 maize commercial hybrids were carried out in a direct sowing system in Southern Brazil in the harvests of 2009/2010 and 2010/2011. Quantitative descriptors were used with the objective of determining the genetic divergence and the relative contributions of traits among hybrids for extraction of inbred lines. This study was carried out in Oxisol soil using a randomized block design with four replicates. Data were subjected to combined analysis of variance, and based on the multivariate analyses, Tocher and average linkage (UPGMA) cluster analyses, based on generalized distance of Mahalanobis, to quantify divergence in addition to Singh criterion to validate trait with the most contribution. The multivariate methods were consistent with each other, and the weight of 100 grains was the trait that contributed most to the divergence and had similar behavior in grain yield between hybrids in both years. Furthermore, this descriptor representing significant genetic variability for crossings and lines extraction to hybridization between BM 3061, ATL 200 and P 30B39 Y.

The endangered species Brycon orbignyanus: genetic analysis and definition of priority areas for conservation

Currently, biodiversity is threatened by several factors often associated with human population growth and the extension of areas occupied by human activity. In particular, freshwater fish fauna is affected by overfishing, deforestation, water pollution, introduction of exotic species and habitat fragmentation promoted by hydroelectric dams, among other environmental impact factors. Several action plans to preserve ichthyofauna biodiversity have been adopted; however, these plans frequently cover only a small number of species, and decisions are often made without strong scientific support. This study aimed to evaluate the genetic aspects of wild groups of Brycon orbignyanus, an endangered fish species, using microsatellites and D-loop regions to identify the genetic structure of the samples and to establish priority areas for conservation based on the genetic patterns of this species. The results indicated that the samples showed levels of genetic variability compatible with others studies with Neotropical fishes. However, the results obtained in the analysis of molecular variance (AMOVA) for microsatellites (F (ST) = 0.258) and D-loop (F (ST) = 0.234) and the interpopulation fixation index revealed that B. orbignyanus was structured in different subpopulations in the La Plata River basin; the areas with better environmental conditions also showed subgroups with higher rates of genetic variability. Future conservation actions addressing these sites should consider two different management units: the complex formed by the Ivinhema River, Upper Parana, Camargo Port and Ilha Grande groups; and the complex formed by the Verde River and Sucuriu River groups.

Genetic parameters and investigation of genotype x environment interactions in Nellore x Hereford crossbred for resistance to cattle ticks in different regions of Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)