Dataset Information

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

ABSTRACT: 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.Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches.The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.

SUBMITTER: Mudadu MA

PROVIDER: S-EPMC4791965 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Mudadu Maurício A MA Porto-Neto Laercio R LR Mokry Fabiana B FB Tizioto Polyana C PC Oliveira Priscila S N PS Tullio Rymer R RR Nassu Renata T RT Niciura Simone C M SC Tholon Patrícia P Alencar Maurício M MM Higa Roberto H RH Rosa Antônio N AN Feijó Gélson L D GL Ferraz André L J AL Silva Luiz O C LO Medeiros Sérgio R SR Lanna Dante P DP Nascimento Michele L ML Chaves Amália S AS Souza Andrea R D L AR Packer Irineu U IU Torres Roberto A A RA Siqueira Fabiane F Mourão Gerson B GB Coutinho Luiz L LL Reverter Antonio A Regitano Luciana C A LC

BMC genomics 20160315

<h4>Background</h4>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 Informa ...[more]

PMID: 26979536

Similar Datasets

Project description:The Montana Tropical® Composite is a recently developed beef cattle population that is rapidly expanding in Brazil and other tropical countries. This is mainly due to its improved meat quality and adaptation to tropical climate conditions compared to Zebu and Taurine cattle breeds, respectively. This study aimed to investigate the genetic architecture of ultrasound-based carcass and meat quality traits in Montana Tropical® Composite beef cattle. Therefore, we estimated variance components and genetic parameters and performed genome-wide association studies using the weighted single-step Genomic Best Linear Unbiased Prediction (GBLUP) approach. A pedigree dataset containing 28,480 animals was used, in which 1,436 were genotyped using a moderate-density Single Nucleotide Polymorphism panel (30K; 30,105 SNPs). A total of 9,358, 5,768, 7,996, and 1,972 phenotypic records for the traits Longissimus muscle area (LMA), backfat thickness (BFT), rump fat thickness (RFT), and for marbling score (MARB), respectively, were used for the analyses. Moderate to high heritability estimates were obtained and ranged from 0.16 ± 0.03 (RFT) to 0.33 ± 0.05 (MARB). A high genetic correlation was observed between BFT and RFT (0.97 ± 0.02), suggesting that a similar set of genes affects both traits. The most relevant genomic regions associated with LMA, BFT, RFT, and MARB were found on BTA10 (5.4-5.8 Mb), BTA27 (25.2-25.5 Mb), BTA18 (60.6-61.0 Mb), and BTA21 (14.8-15.4 Mb). Two overlapping genomic regions were identified for RFT and MARB (BTA13:47.9-48.1 Mb) and for BFT and RFT (BTA13:61.5-62.3 Mb). Candidate genes identified in this study, including PLAG1, LYN, WWOX, and PLAGL2, were previously reported to be associated with growth, stature, skeletal muscle growth, fat thickness, and fatty acid composition. Our results indicate that ultrasound-based carcass and meat quality traits in the Montana Tropical® Composite beef cattle are heritable, and therefore, can be improved through selective breeding. In addition, various novel and already known genomic regions related to these traits were identified, which contribute to a better understanding of the underlying genetic background of LMA, BFT, RFT, and MARB in the Montana Tropical Composite population.

Project description: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.

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.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets