Principal components for morphometric traits in Campolina horses.

Principal component analysis (PCA) was applied to evaluate the genetic variability and relationship between 15 morphometric traits in 91,483 Campolina horses, as well as to propose an index based on an aggregate genotype that promotes a particular selection objective. PCA was applied to the genetic (co)variance matrix among variables. After calculation of the principal components, the breeding values were estimated to obtain an index related to the component that explained most of the variation. The first principal component (PC1) accounted for 97.8% of the total additive genetic variance of the traits. PC1 contrasted animals in terms of body size (wither, back and croup heights, body length, and thoracic girth). PC1 traits showed higher heritabilities and positive and high genetic correlations. An index was obtained (HPC1) with the combination of the breeding values of different traits from PC1 which permitted the use of this index as an aggregate genotype to identify the best animals for selection. The second principal component (PC2) was much smaller and grouped traits related to head and neck morphometry, among others. These traits are commonly used for breed qualification, a fact explaining the small variation in this component. An evaluation of the effect of HPC1 on withers height in two-trait analysis was also made which provided positive genetic correlations of moderate to high magnitude (0.73-0.86), indicating that selection for this trait (important in Campolina horses) is accounted for in the index. The use of HCP1 could be considered as an important alternative to selection since it does not consider a single trait but rather a set of variables that capture body proportions.

Variability analyses of the maternal lineage of horses and donkeys.

Equid breeds originating from the Iberian Peninsula and North Africa are believed to have genetically contributed to the formation of breeds and ecotypes from Brazil. The country has numerous breeds and ecotypes of horses and donkeys but there are no extensive studies on maternal genetic diversity and their origins. This study reports the results of the first genetic analysis of all horse and donkey breeds/ecotypes from Brazil based on sequences of the mitochondrial DNA control region (D-loop) whose main objective was to characterize the genetic variation in these animals. These analyses will contribute to the understanding of the current population structure and diversity of breeds/ecotypes of horses and donkeys raised in the Brazil. We analyzed 310 D-loop sequences representing 41 breeds/ecotypes of Equus caballus and Equus asinus, including 14 native horse breeds/ecotypes, 3 native donkey breeds/ecotypes and 24 cosmopolite horse breeds. The results revealed that the breeds are well structured genetically and that they comprise different groups. A total of 80 and 14 haplotypes were identified for horses and donkeys, respectively. Most of the horse mtDNA haplotypes were shared by many breeds, whereas donkey mtDNA haplotypes seemed to be more group-especif. Some groups presented a low intrabreed distance and/or a low haplotype/nucleotide diversity such as Lavradeiro, Crioulo, Piquira and Percheron horses and Brazilian donkey. Thus, specific actions must be designed for each population. The different levels of genetic diversity provided important information for conservation resource management of adapted groups as well as for mating orientation of breed associations. Some autochthonous ecotypes require attention because of their low genetic variability.

Genomic analysis of stayability in Nellore cattle.

Stayability, which can be defined as the probability of a cow calving at a certain age when given the opportunity, is an important reproductive trait in beef cattle because it is directly related to herd profitability. The objective of this study was to estimate genetic parameters and to identify possible genomic regions associated with the phenotypic expression of stayability in Nellore cows. The variance components were estimated by Bayesian inference using a threshold animal model that included the systematic effects of contemporary group and sexual precocity and the random effects of animal and residual. The SNP effects were estimated by the single-step genomic BLUP method using information of 2,838 animals (2,020 females and 930 sires) genotyped with the Illumina High-Density BeadChip Array (San Diego, CA, USA). The variance explained by windows formed by 200 consecutive SNPs was used to identify genomic regions of largest effect on the expression of stayability. The heritability was 0.11 ± 0.01 when A matrix (pedigree) was used and 0.14 ± 0.01 when H matrix (relationship matrix that combines pedigree information and SNP data) was used. A total of 147 candidate genes for stayability were identified on chromosomes 1, 2, 5, 6, 9 and 20 and on the X chromosome. New candidate regions for stayability were detected, most of them related to reproductive, immunological and central nervous system functions.