Ovine ß-globin gene: A new qPCR for rapid haplotype identification and association with susceptibility to Haemonchus contortus infection.

Two ß-globin allelic haplotypes (A and B) were identified in domestic sheep, wherein animals which are homozygous for ßB allele (BB haplotype) have a deletion of pre-adult ßC-globin and consequently are less tolerant to anemia and hypoxia. Since Haemonchus contortus infection, is associated with severe anemia, studies performed from 1960s to 1990s investigated the association between ß-globin haplotype and resistance against this parasite. However, the findings were controversial, pointing out from increased resistance in animals harboring the ßA allele to inexistence of association. Thus, our study aimed to develop a qPCR for ß-globin haplotype identification, and to evaluate the association between ß-globin haplotype and resistance against H. contortus in a group of sheep submitted to artificial infection with this parasite. A total of 286 lambs of Morada Nova breed were experimentally challenged with 4000 H. contortus L3 and monitored for 112 days from weaning. Significantly improved (p < 0.05) phenotypic profiles (lower fecal egg counts, higher packed cell volume and birthweight) were observed for AA haplotype animals, especially when compared to BB animals, while AB animals were similar to BB. This is the first report of a qPCR assay for ovine ß-globin haplotype identification. In view of significant differences of phenotypic profiles between haplotype groups, the developed qPCR may constitute an important tool for sheep producers to improve genetic selection of parasite resistant animals.

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed.

BACKGROUND: The development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies. RESULTS: The maximum average LD, measured by r2 varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r2 varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r2 reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size. CONCLUSIONS: This study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.

BACKGROUND: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality. RESULTS: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism. CONCLUSIONS: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle.