Allele- and parent-of-origin-specific effects on expression of the KCNJ11 gene: A candidate for meat tenderness in cattle.

In contrast to the Mendelian inheritance model, parental alleles can contribute unequally to gene expression, which may result in phenotypic variance among individuals and bias in the predicted additive effect of molecular markers associated with production traits. Given the need to understand the effects of allelic variation and parent-of-origin effects on the expression of genes with a commercial interest in cattle, we analyzed the expression of KCNJ11 (potassium inwardly rectifying channel, subfamily J, member 11), which was previously described as a functional candidate gene for meat tenderness. Allele-specific and parent-of-origin-dependent expression of this gene were assessed in bovine muscle using the rs379610823 single nucleotide polymorphism as a reference. Biallelic expression was observed; however, the T allele was expressed at significantly higher levels than the C allele. Furthermore, increased expression of KCNJ11 was found in animals harboring the maternal T allele. This study is the first to describe the differential allelic expression of bovine KCNJ11. Our findings are important for understanding the mechanisms that underlie the pattern of KCNJ11 expression and its potential impact on the phenotypic variation of meat tenderness in Nelore beef cattle. This reinforces the need for further investigation of allelic- and parent-of-origin expression deviation in genetic markers eligible for the selection of target traits.

Single nucleotide polymorphisms in candidate genes associated with gastrointestinal nematode infection in goats.

Cytokines are small cell-signaling proteins that play an important role in the immune system, participating in intracellular communication. Four candidate genes of the cytokine family (IL2, IL4, IL13, and IFNG) were selected to identify Single Nucleotide Polymorphisms (SNPs) that might be associated with resistance to gastrointestinal endoparasites in goats. A population of 229 goats, F2 offspring from an F1 intercross was produced by crossing pure Saanen goats, considered as susceptible to gastrointestinal endoparasites, with pure Anglo-Nubian goats, considered resistant. Blood was collected for DNA extraction and fecal samples were also collected for parasite egg count. Polymorphisms were prospected by sequencing animals with extreme phenotype for fecal egg count (FEC) distribution. The association between SNPs and phenotype was determined by using the Fisher exact test with correction for multiple tests. Three of the 10 SNPs were identified as significant (P ≤ 0.03). They were found in intron 1 of IL2 (ENSBTA00000020883), intron 3 of IL13 (ENSBTA00000015953) and exon 3 of IFNG (ENSBTA00000012529), suggesting an association between them and gastrointestinal endoparasite resistance. Further studies will help describe the effects of these markers accurately before implementing them in marker assisted selection. This study is the pioneer in describing such associations in goats.

A genome-wide scan for selection signatures in Nellore cattle.

Brazilian Nellore cattle (Bos indicus) have been selected for growth traits for over more than four decades. In recent years, reproductive and meat quality traits have become more important because of increasing consumption, exports and consumer demand. The identification of genome regions altered by artificial selection can potentially permit a better understanding of the biology of specific phenotypes that are useful for the development of tools designed to increase selection efficiency. Therefore, the aims of this study were to detect evidence of recent selection signatures in Nellore cattle using extended haplotype homozygosity methodology and BovineHD marker genotypes (>777,000 single nucleotide polymorphisms) as well as to identify corresponding genes underlying these signals. Thirty-one significant regions (P < 0.0001) of possible recent selection signatures were detected, and 19 of these overlapped quantitative trait loci related to reproductive traits, growth, feed efficiency, meat quality, fatty acid profiles and immunity. In addition, 545 genes were identified in regions harboring selection signatures. Within this group, 58 genes were associated with growth, muscle and adipose tissue metabolism, reproductive traits or the immune system. Using relative extended haplotype homozygosity to analyze high-density single nucleotide polymorphism marker data allowed for the identification of regions potentially under artificial selection pressure in the Nellore genome, which might be used to better understand autozygosity and the effects of selection on the Nellore genome.

Genome scan for meat quality traits in Nelore beef cattle.

Meat quality traits are economically important because they affect consumers' acceptance, which, in turn, influences the demand for beef. However, selection to improve meat quality is limited by the small numbers of animals on which meat tenderness can be evaluated due to the cost of performing shear force analysis and the resultant damage to the carcass. Genome wide-association studies for Warner-Bratzler shear force measured at different times of meat aging, backfat thickness, ribeye muscle area, scanning parameters [lightness, redness (a*), and yellowness] to ascertain color characteristics of meat and fat, water-holding capacity, cooking loss (CL), and muscle pH were conducted using genotype data from the Illumina BovineHD BeadChip array to identify quantitative trait loci (QTL) in all phenotyped Nelore cattle. Phenotype count for these animals ranged from 430 to 536 across traits. Meat quality traits in Nelore are controlled by numerous QTL of small effect, except for a small number of large-effect QTL identified for a*fat, CL, and pH. Genomic regions harboring these QTL and the pathways in which the genes from these regions act appear to differ from those identified in taurine cattle for meat quality traits. These results will guide future QTL mapping studies and the development of models for the prediction of genetic merit to implement genomic selection for meat quality in Nelore cattle.