Genome-wide association study of resistance/susceptibility to infectious bovine keratoconjunctivitis in Brazilian Hereford cattle.

Genome-wide association studies were conducted to identify the more informative genomic regions and SNPs, as well as to identify candidate genes associated with infectious bovine keratoconjunctivitis (IBK) resistance/susceptibility in Hereford cattle. A Bayes B statistical approach was initially applied in genome-wide association studies by using deregressed estimated breeding values for IBK resistance/susceptibility. To estimate the combined effect of a genomic region that is potentially associated with QTL, 2504 non-overlapping 1-Mb windows that varied in SNP number were defined, with the most informative 24 windows including 427 SNPs and explaining more than 20% of the estimated genetic variance for IBK resistance/susceptibility. These regions were explored with respect to their biological functions through functional analysis to map potential candidate genes. The significant SNPs were mapped on chromosomes 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 20, 23, and 28, and candidate genes were detected as related to the IBK. Most informative SNPs in term of genetic variance were located in proximity of genes related to phenotypic expression of lesions and biological processes associated to the IBK. Knowledge about phenotypic and genomic variation generated in the present study can be used to on design selection strategies to improve the resistance to IBK of Hereford cattle herds.

Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree-based models.

The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single-nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high-density panel (BovineHD - Illumina® bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire's information, and 2.8% (13) were related to the dam's information. We observed 27.2% (236/868) of Mendelian conflicts for sire-progeny genotyped pairs and 14.3% (13/91) for dam-progeny genotyped pairs. We performed 2174 new definitions of half-siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher-quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non-corrected relationship matrix.

Transcriptional profiling during foetal skeletal muscle development of Piau and Yorkshire-Landrace cross-bred pigs.

Skeletal muscle development is a complex process involving the coordinated expression of thousands of genes. The aim of this study was to identify differentially expressed genes in longissimus dorsi (LD) muscle of pigs at 40 and 70 days (d) of gestation (developmental stages encompassing primary and secondary fibre formation) in Yorkshire-Landrace (YL) cross-bred pigs and Piau pigs (a naturalized Brazilian breed), which are two breed types that differ in muscularity. Foetuses were obtained from gilts at each gestational age (n = 3 YL; n = 4 Piau), and transcriptional profiling was performed using the Pigoligoarray microarray containing 20 400 oligonucleotides. A total of 486 oligonucleotides were differentially expressed (fold change (FC) ≥ 1.5; false discovery rate (FDR) ≤ 0.05) between 40 and 70 d gestation in either YL or Piau pigs, and a total of 1300 oligonucleotides were differentially expressed (FC ≥ 1.5; FDR ≤ 0.05) between YL and Piau pigs at either age. Gene ontology annotation and pathway analyses determined functional classifications for differentially expressed genes and revealed breed type-specific developmental expression patterns. Thirteen genes were selected for confirmation by qRT-PCR analyses, and expression patterns for most of these genes were confirmed, providing further insight into the roles of these genes in pig muscle development. This study revealed both developmental and breed type-specific patterns of gene expression in foetal pig skeletal muscle, including genes not previously associated with myogenesis. This information will contribute to future pig genetic improvement efforts.

Analyses of reaction norms reveal new chromosome regions associated with tick resistance in cattle.

Despite single nucleotide polymorphism (SNP) availability and frequent cost reduction has allowed genome-wide association studies even in complex traits as tick resistance, the use of this information source in SNP by environment interaction context is unknown for many economically important traits in cattle. We aimed at identifying putative genomic regions explaining differences in tick resistance in Hereford and Braford cattle under SNP by environment point of view as well as to identify candidate genes derived from outliers/significant markers. The environment was defined as contemporary group means of tick counts, since they seemed to be the most appropriate entities to describe the environmental gradient in beef cattle. A total of 4363 animals having tick counts (n=10 673) originated from 197 sires and 3966 dams were used. Genotypes were acquired on 3591 of these cattle. From top 1% SNPs (410) having the greatest effects in each environment, 75 were consistently relevant in all environments, which indicated SNP by environment interaction. The outliers/significant SNPs were mapped on chromosomes 1, 2, 5, 6, 7, 9, 11, 13, 14, 15, 16, 18, 21, 23, 24, 26 and 28, and potential candidate genes were detected across environments. The presence of SNP by environment interaction for tick resistance indicates that genetic expression of resistance depends upon tick burden. Markers with major portion of genetic variance explained across environments appeared to be close to genes with different direct or indirect functions related to immune system, inflammatory process and mechanisms of tissue destruction/repair, such as energy metabolism and cell differentiation.

Genomewide association study for production and meat quality traits in Canchim beef cattle.

The commercial value of the bovine carcass is determined by a set of traits, such as weight, yield, back fat thickness, and marbling; therefore, the genetic improvement of growth, meat, and carcass quality traits is an important tool to add value to the supply chain. Genomewide association studies (GWAS) enable the identification of loci that control phenotypic expression of quantitative traits (QTL). Therefore, the objective of this work was to perform a GWAS to identify genomic regions and genes associated with growth, carcass traits, and meat quality in Canchim beef cattle. These traits were yearling weight (YW), rib eye area (REA), back fat thickness (BFT), and marbling (MARB). To increase sample size and marker density, genotype imputation was performed, and only markers imputed with greater than 95% accuracy were used. Genomewide association study was performed using a Bayesian approach, by the Bayes B statistical method, incorporating genotypes and phenotypes from 614 animals from both the Canchim breed and the MA genetic group (offspring of Charolais bulls and one-half Canchim + one-half Zebu cows). This investigation identified 1 and 4 genomic regions explaining 0.23 and 7.35% of the genetic variance for REA and YW, respectively. These regions harbor a total of 19 genes, 7 of which were classified for biological functions by functional analysis. Significant associations were not observed for BFT and MARB. The identification of QTL that had been previously described in the literature reinforces associations found in this study.

Genomic prediction for tick resistance in Braford and Hereford cattle.

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.