Genomic structure and marker-derived gene networks for growth and meat quality traits of brazilian nelore beef cattle.

Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.

A single nucleotide polymorphism in NEUROD1 is associated with production traits in nelore beef cattle.

Feed efficiency and carcass characteristics are late-measured traits. The detection of molecular markers associated with them can help breeding programs to select animals early in life, and to predict breeding values with high accuracy. The objective of this study was to identify polymorphisms in the functional and positional candidate gene NEUROD1 (neurogenic differentiation 1), and investigate their associations with production traits in reference families of Nelore cattle. A total of 585 steers were used, from 34 sires chosen to represent the variability of this breed. By sequencing 14 animals with extreme residual feed intake (RFI) values, seven single nucleotide polymorphisms (SNPs) in NEUROD1 were identified. The investigation of marker effects on the target traits RFI, backfat thickness (BFT), ribeye area (REA), average body weight (ABW), and metabolic body weight (MBW) was performed with a mixed model using the restricted maximum likelihood method. SNP1062, which changes cytosine for guanine, had no significant association with RFI or REA. However, we found an additive effect on ABW (P ≤ 0.05) and MBW (P ≤ 0.05), with an estimated allele substitution effect of -1.59 and -0.93 kg0.75, respectively. A dominant effect of this SNP for BFT was also found (P ≤ 0.010). Our results are the first that identify NEUROD1 as a candidate that affects BFT, ABW, and MBW. Once confirmed, the inclusion of this SNP in dense panels may improve the accuracy of genomic selection for these traits in Nelore beef cattle as this SNP is not currently represented on SNP chips.