Genomic prediction for tick resistance in Braford and Hereford cattle1

Abstract

One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for -means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breed-specific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance.

Tag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methods

“…It should be mentioned that the Hereford and Braford population studied here is evaluated and selected as a single breed-type with common breeding objectives and variance components by the Delta G Connection Breeding Program [24]. Moreover, as demonstrated by Biegelmeyer et al [25], correlation of marker phase between these two breeds was estimated at 0.92 for SNPs less than 50 kb apart, which further supports the assumption that the initial detection analyses based on the 50 K SNP panel was suitable [18]. Therefore, we carried out a joint analysis that accounted for breed differences and heterosis to calculate DEBV.…”

“…In total, 10,673 tick counts were available for analyses. Variance components and breeding values were generated from log-transformed tick counts [3, 18] with the BLUPf90 family of programs [19] and estimated breeding values were used for GWAS analyses.…”

“…This model considered fixed effects for contemporary groups, regression coefficients with the linear additive effect for the zebu breed proportion, zebu–HH dominance effect, zebu–HH additive by additive epistatic effect [22], and linear and quadratic coefficients for animal age. Breed composition coefficients were derived from pedigree data [18]. Subsequently, deregressed estimated breeding values (DEBV) for tick resistance were calculated according to Garrick et al [23], in order to remove parent average values and account for heterogeneous variance.…”

“…In addition, a prior distribution for the residual variance was also considered as X −2 ( v , S ), but with v  = 10 and scale S  = 0.0572. Prior expected values of these Chi square distributions for the dispersion parameters that were equal to 0.0182 and 0.0715, respectively for the genetic and residual variances, were based on estimates previously obtained for tick counts in these BO and HH populations [18]. …”

A educação científica CTS no contexto do ensino integrado

“…Na América Latina, o Movimento CTS teve um desenvolvimento particular. Considera-se que o pensamento latino-americano em ciência, tecnologia e sociedade (PLACTS) tenha sido o marco das discussões CTS na região (LINSINGEN, 2007;ROSO;AULER, 2016). Foi um movimento de intelectuais, engenheiros argentinos na sua maioria, que nas décadas de 60 e 70 do século passado, discutiam o papel da ciência e da tecnologia nas relações de dependência da região, assim como em alternativas para o desenvolvimento autônomo das nações latinas -reflexões que continuam a repercutir no cenário regional e nacional contemporâneo (DAGNINO; BRANDÃO;NOVAES, 2004).…”