Effect of genomic X-chromosome regions on Nelore bull fertility.

Scrotal circumference (SC) is a commonly used trait related to sexual precocity in bulls. Genome-wide association studies have uncovered a lot of genes related to this trait, however, only those present on autosomes. The inclusion of the second biggest chromosome (BTAX) can improve the knowledge of the genetic architecture of this trait. In this study, we performed a weighted, single-step, genome-wide association study using a 777 k BovineHD BeadChip (IllumHD) to analyze the association between SNPs and SC in Brazilian Nelore cattle. Phenotypes from 79,300 males and 3263 genotypes (2017 from females and 1246 from males)-(39,367 SNPs markers located at ChrX) were used. We identified eight regions on chromosome X that displayed important associations with SC. The results showed that together the genomic windows explained 28.52% of the genetic variance for the examined trait. Genes with potential functions in reproduction and fertility regulation were highlighted as candidates for sexual precocity rates in Nelore cattle (AFF2 and PJA1). Moreover, we found 10 genes that had not previously been identified as being associated with sexual precocity traits in cattle. These findings will further advance our understanding of the genetic architecture, considering mainly the presence of the chromosome X, for indicine cattle reproductive traits, being useful in the context of genomic prediction in beef cattle.

Influence of coat color on genetic parameter estimates in horses.

The aim of this study was to verify the effect of the inclusion of coat color on the genetic parameter estimation for linear measurements in Campolina horses. Two models (1 and 2) were applied. For model 1, coat color effect was not included as variable of the contemporary group formation; in model 2, it was included. Model 2 presented the best fitting with a Deviance Information Criterion (DIC) of -979,459.020 compared with -1,818,458.572 DIC from model 1. The average of heritability estimates ranged from low to high magnitude (0.15 to 0.53) for model 1 and from moderate to high magnitude for model 2 (0.21 to 0.47). The estimated values varied according to the analyses (models 1 and 2). The highest heritability was found for withers height (0.52), croup height (0.53), and back height (0.51). The genetic correlations ranged from values of moderate to high magnitude for models 1 (0.23 to 0.98) and 2 (0.29 to 0.99), respectively. The finding that genetic variance differed among models 1 and 2 may indicate that genotypes react differently to different coat colors, a fact implying the existence of interaction between these traits and the effect under study. The coat color influence might be explained as a pleiotropic effect of the genes that cause this phenotypic variation and also influence morphometric measures. The inclusion of the coat color effect better estimated the additive genetic variance of morphometric traits in horses. As a consequence, the genetic parameters were also more accurately estimated when it is included in the evaluation model.

The effect of mitochondrial DNA polymorphisms on cattle reproduction.

The aim of this study was to identify SNPs located in mitochondrial DNA that are associated with reproductive traits in beef cows. A total of 1999 Nelore females genotyped with the high-density Illumina BovineHD BeadChip (Illumina Inc., San Diego, CA, USA) were used to study the association of mitochondrial DNA variants with reproductive traits using a single-step procedure. In a preliminary analysis, the present results indicate a small participation of the mitogenome in the expression of reproductive traits in beef cattle. However, possible difficulties related to the biological characteristics of mitochondrial DNA and its inheritance, genotyping, and annotation of the phenotypes studied may also explain the results.

Mapping genomic regions for reproductive traits in beef cattle: Inclusion of the X chromosome.

Although the second largest chromosome of the genome, the X chromosome is usually excluded from genome-wide association studies (GWAS). Considering the presence and importance of genes on this chromosome that are involved in reproduction, the aim of this study was to evaluate the effect of its inclusion in GWAS on reproductive traits (scrotal circumference [SC], early pregnancy [P16] and age at first calving [AFC]) in a Nelore herd. Genotype data from 3,263 animals with the above-mentioned phenotypes were used. The results showed an increase in the variances explained by the autosomal markers for all traits when the X chromosome was not included. For SC, there was an increase of more than 10% for the windows on chromosomes 2 and 6. For P16, the effect was increased by almost 20% for windows on chromosome 5. The same pattern was found for AFC, with an increase of more than 10% for the most important windows. The results indicate that the noninclusion of the X chromosome can overestimate the effects of autosomes on SC, P16 and AFC not only because of the additive effect of the X chromosome itself but also because of its epistatic effect on autosomal genes.

Prediction of genomic breeding values for reproductive traits in Nellore heifers.

The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle. A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.

Genotype by environment interaction in Nelore cattle from five Brazilian states.

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection.

Genotype by environment interaction in Nelore cattle from five Brazilian states

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10 percent) during selection.