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Polymorphisms in epigenetic and meat quality related genes in fourteen cattle breeds and association with beef quality and carcass traits.

ABSTRACT: Improvement for carcass traits related to beef quality is the key concern in beef production. Recent reports found that epigenetics mediates the interaction of individuals with environment and nutrition. The present study was designed to analyze the genetic effect of single nucleotide polymorphisms (SNPs) in seven epigenetic-related genes (DNMT1, DNMT3a, DNMT3b, DNMT3L, Ago1, Ago2, and HDAC5) and two meat quality candidate genes (CAPN1 and PRKAG3) on fourteen carcass traits related to beef quality in a Snow Dragon beef population, and also to identify SNPs in a total of fourteen cattle populations. Sixteen SNPs were identified and genotyped in 383 individuals sampled from the 14 cattle breeds, which included 147 samples from the Snow Dragon beef population. Data analysis showed significant association of 8 SNPs within 4 genes related to carcass and/or meat quality traits in the beef populations. SNP1 (13154420A>G) in exon 17 of DNMT1 was significantly associated with rib-eye width and lean meat color score (p<0.05). A novel SNP (SNP4, 76198537A>G) of DNMT3a was significantly associated with six beef quality traits. Those individuals with the wild-type genotype AA of DNMT3a showed an increase in carcass weight, chilled carcass weight, flank thicknesses, chuck short rib thickness, chuck short rib score and in chuck flap weight in contrast to the GG genotype. Five out of six SNPs in DNMT3b gene were significantly associated with three beef quality traits. SNP15 (45219258C>T) in CAPN1 was significantly associated with chuck short rib thickness and lean meat color score (p<0.05). The significant effect of SNP15 on lean meat color score individually and in combination with each of other 14 SNPs qualify this SNP to be used as potential marker for improving the trait. In addition, the frequencies of most wild-type alleles were higher than those of the mutant alleles in the native and foreign cattle breeds. Seven SNPs were identified in the epigenetic-related genes. The SNP15 in CAPN1 could be used as a powerful genetic marker in selection programs for beef quality improvement in the Snow Dragon Beef population.

SUBMITTER: Liu X

PROVIDER: S-EPMC4341095 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Studies to identify markers associated with beef tenderness have focused on Warner-Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d'Aquitaine beef cattle breeds.Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle.Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

Project description:BACKGROUND: In a previously reported genome-wide association study based on a high-density bovine SNP genotyping array, 8 SNP were nominally associated (P ? 0.003) with average daily gain (ADG) and 3 of these were also associated (P ? 0.002) with average daily feed intake (ADFI) in a population of crossbred beef cattle. The SNP were clustered in a 570 kb region around 38 Mb on the draft sequence of bovine chromosome 6 (BTA6), an interval containing several positional and functional candidate genes including the bovine LAP3, NCAPG, and LCORL genes. The goal of the present study was to develop and examine additional markers in this region to optimize the ability to distinguish favorable alleles, with potential to identify functional variation. RESULTS: Animals from the original study were genotyped for 47 SNP within or near the gene boundaries of the three candidate genes. Sixteen markers in the NCAPG-LCORL locus displayed significant association with both ADFI and ADG even after stringent correction for multiple testing (P ? 005). These markers were evaluated for their effects on meat and carcass traits. The alleles associated with higher ADFI and ADG were also associated with higher hot carcass weight (HCW) and ribeye area (REA), and lower adjusted fat thickness (AFT). A reduced set of markers was genotyped on a separate, crossbred population including genetic contributions from 14 beef cattle breeds. Two of the markers located within the LCORL gene locus remained significant for ADG (P ? 0.04). CONCLUSIONS: Several markers within the NCAPG-LCORL locus were significantly associated with feed intake and body weight gain phenotypes. These markers were also associated with HCW, REA and AFT suggesting that they are involved with lean growth and reduced fat deposition. Additionally, the two markers significant for ADG in the validation population of animals may be more robust for the prediction of ADG and possibly the correlated trait ADFI, across multiple breeds and populations of cattle.

Project description:Data integration using hierarchical analysis based on the central dogma or common pathway enrichment analysis may not reveal non-obvious relationships among omic data. Here, we applied factor analysis (FA) and Bayesian network (BN) modeling to integrate different omic data and complex traits by latent variables (production, carcass, and meat quality traits). A total of 14 latent variables were identified: five for phenotype, three for miRNA, four for protein, and two for mRNA data. Pearson correlation coefficients showed negative correlations between latent variables miRNA 1 (mirna1) and miRNA 2 (mirna2) (-0.47), ribeye area (REA) and protein 4 (prot4) (-0.33), REA and protein 2 (prot2) (-0.3), carcass and prot4 (-0.31), carcass and prot2 (-0.28), and backfat thickness (BFT) and miRNA 3 (mirna3) (-0.25). Positive correlations were observed among the four protein factors (0.45-0.83): between meat quality and fat content (0.71), fat content and carcass (0.74), fat content and REA (0.76), and REA and carcass (0.99). BN presented arcs from the carcass, meat quality, prot2, and prot4 latent variables to REA; from meat quality, REA, mirna2, and gene expression mRNA1 to fat content; from protein 1 (prot1) and mirna2 to protein 5 (prot5); and from prot5 and carcass to prot2. The relations of protein latent variables suggest new hypotheses about the impact of these proteins on REA. The network also showed relationships among miRNAs and nebulin proteins. REA seems to be the central node in the network, influencing carcass, prot2, prot4, mRNA1, and meat quality, suggesting that REA is a good indicator of meat quality. The connection among miRNA latent variables, BFT, and fat content relates to the influence of miRNAs on lipid metabolism. The relationship between mirna1 and prot5 composed of isoforms of nebulin needs further investigation. The FA identified latent variables, decreasing the dimensionality and complexity of the data. The BN was capable of generating interrelationships among latent variables from different types of data, allowing the integration of omics and complex traits and identifying conditional independencies. Our framework based on FA and BN is capable of generating new hypotheses for molecular research, by integrating different types of data and exploring non-obvious relationships.

Project description:BACKGROUND: Genetic improvement of beef quality will benefit both producers and consumers, and can be achieved by selecting animals that carry desired quantitative trait nucleotides (QTN), which result from intensive searches using genetic markers. This paper presents a genome-wide association approach utilizing single nucleotide polymorphisms (SNP) in the Illumina BovineSNP50 BeadChip to seek genomic regions that potentially harbor genes or QTN underlying variation in carcass quality of beef cattle.This study used 747 genotyped animals, mainly crossbred, with phenotypes on twelve carcass quality traits, including hot carcass weight (HCW), back fat thickness (BF), Longissimus dorsi muscle area or ribeye area (REA), marbling scores (MRB), lean yield grade by Beef Improvement Federation formulae (BIFYLD), steak tenderness by Warner-Bratzler shear force 7-day post-mortem (LM7D) as well as body composition as determined by partial rib (IMPS 103) dissection presented as a percentage of total rib weight including body cavity fat (BDFR), lean (LNR), bone (BNR), intermuscular fat (INFR), subcutaneous fat (SQFR), and total fat (TLFR). RESULTS: At the genome wide level false discovery rate (FDR?<?10%), eight SNP were found significantly associated with HCW. Seven of these SNP were located on Bos taurus autosome (BTA) 6. At a less stringent significance level (P?<?0.001), 520 SNP were found significantly associated with mostly individual traits (473 SNP), and multiple traits (47 SNP). Of these significant SNP, 48 were located on BTA6, and 22 of them were in association with hot carcass weight. There were 53 SNP associated with percentage of rib bone, and 12 of them were on BTA20. The rest of the significant SNP were scattered over other chromosomes. They accounted for 1.90 - 5.89% of the phenotypic variance of the traits. A region of approximately 4 Mbp long on BTA6 was found to be a potential area to harbor candidate genes influencing growth. One marker on BTA25 accounting for 2.67% of the variation in LM7D may be worth further investigation for the improvement of beef tenderness. CONCLUSION: This study provides useful information to further assist the identification of chromosome regions and subsequently genes affecting carcass quality traits in beef cattle. It also revealed many SNP that acted pleiotropically to affect carcass quality. This knowledge is important in selecting subsets of SNP to improve the performance of beef cattle.

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Polymorphisms in epigenetic and meat quality related genes in fourteen cattle breeds and association with beef quality and carcass traits.

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