Dataset Information

Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.

ABSTRACT: The use of relatively low numbers of sires in cattle breeding programs, particularly on those for carcass and weight traits in Nellore beef cattle (Bos indicus) in Brazil, has always raised concerns about inbreeding, which affects conservation of genetic resources and sustainability of this breed. Here, we investigated the distribution of autozygosity levels based on runs of homozygosity (ROH) in a sample of 1,278 Nellore cows, genotyped for over 777,000 SNPs. We found ROH segments larger than 10 Mb in over 70% of the samples, representing signatures most likely related to the recent massive use of few sires. However, the average genome coverage by ROH (>1 Mb) was lower than previously reported for other cattle breeds (4.58%). In spite of 99.98% of the SNPs being included within a ROH in at least one individual, only 19.37% of the markers were encompassed by common ROH, suggesting that the ongoing selection for weight, carcass and reproductive traits in this population is too recent to have produced selection signatures in the form of ROH. Three short-range highly prevalent ROH autosomal hotspots (occurring in over 50% of the samples) were observed, indicating candidate regions most likely under selection since before the foundation of Brazilian Nellore cattle. The putative signatures of selection on chromosomes 4, 7, and 12 may be involved in resistance to infectious diseases and fertility, and should be subject of future investigation.

SUBMITTER: Zavarez LB

PROVIDER: S-EPMC4310349 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.

Zavarez Ludmilla B LB Utsunomiya Yuri T YT Carmo Adriana S AS Neves Haroldo H R HH Carvalheiro Roberto R Ferenčaković Maja M Pérez O'Brien Ana M AM Curik Ino I Cole John B JB Van Tassell Curtis P CP da Silva Marcos V G B MV Sonstegard Tad S TS Sölkner Johann J Garcia José F JF

Frontiers in genetics 20150129

The use of relatively low numbers of sires in cattle breeding programs, particularly on those for carcass and weight traits in Nellore beef cattle (Bos indicus) in Brazil, has always raised concerns about inbreeding, which affects conservation of genetic resources and sustainability of this breed. Here, we investigated the distribution of autozygosity levels based on runs of homozygosity (ROH) in a sample of 1,278 Nellore cows, genotyped for over 777,000 SNPs. We found ROH segments larger than 1 ...[more]

PMID: 25688258

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Project description:BACKGROUND: Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. METHODS: Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. RESULTS: Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships. CONCLUSIONS: Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information.

Project description:Proteins are the major constituents of muscle and are key molecules regulating the metabolic changes during conversion of muscle to meat. Brazil is one of the largest exporters of beef and most Brazilian cattle are composed by zebu (Nellore) genotype. Bos indicus beef is generally leaner and tougher than Bos taurus such as Angus. The aim of this study was to compare the muscle proteomic and phosphoproteomic profile of Angus and Nellore. Seven animals of each breed previously subjected the same growth management were confined for 84 days. Proteins were extracted from Longissimus lumborum samples collected immediately after slaughter and separated by two-dimensional electrophoresis. Pro-Q Diamond stain was used in phosphoproteomics. Proteins identification was performed using matrix assisted laser desorption/ionization time-of-flight mass spectrometry. Tropomyosin alpha-1 chain, troponin-T, myosin light chain-1 fragment, cytoplasmic malate dehydrogenase, alpha-enolase and 78 kDa glucose-regulated protein were more abundant in Nellore, while myosin light chain 3, prohibitin, mitochondrial stress-70 protein and heat shock 70 kDa protein 6 were more abundant in Angus (P<0.05). Nellore had higher phosphorylation of myosin regulatory light chain-2, alpha actin-1, triosephosphate isomerase and 14-3-3 protein epsilon. However, Angus had greater phosphorylation of phosphoglucomutase-1 and troponin-T (P<0.05). Therefore, proteins involved in contraction and muscle organization, myofilaments expressed in fast or slow-twitch fibers and heat shock proteins localized in mitochondria or sarcoplasmic reticulum and involved in cell flux of calcium and apoptosis might be associated with differences in beef quality between Angus and Nellore. Furthermore, prohibitin appears to be a potential biomarker of intramuscular fat in cattle. Additionally, differences in phosphorylation of myofilaments and glycolytic enzymes could be involved with differences in muscle contraction force, susceptibility to calpain, apoptosis and postmortem glycolysis, which might also be related to differences in beef quality among Angus and Nellore.

Project description:This study evaluated 53 primiparous cows (36.8±1.23 months old and 484±40.9 kg of body weight) performance tested (GrowSafe® System) from 22±5 to 190±13 days of lactation in order to obtain daily dry matter intake (DMI). The animals received a high-forage diet (forage-to-concentrate ratio of 90:10). Milk production of the cows was evaluated three times by mechanical milking and the energy-corrected milk yield (ECMY) was calculated. Energy status (through the indicators glucose, cholesterol, triglycerides, and ?-hydroxybutyrate), protein status (indicators albumin, urea, and creatinine), mineral status (indicators calcium, phosphorus, and magnesium), and hormonal status (indicators insulin and cortisol) were estimated four times throughout lactation. The residual feed intake (RFI) of cows was calculated considering DMI, average daily gain (ADG) and mid-test metabolic weight (BW0.75) obtained in early lactation (from 22±5 to 102±7 days), and the animals were classified as negative (most efficient) or positive RFI (least efficient). The RFI model explained 53% of the variation in DMI. The mean DMI, ADG, ECMY, and calf weight as a percentage of cow weight were 12.47±2.70 kg DM/day, 0.632±0.323 kg/day, 10.47±3.23 kg/day, and 36.6±5.39%, respectively. Negative RFI cows consumed 11.5% less DM than positive RFI cows, with performance and metabolic profile being similar to those of positive RFI cows, except for a lower milk protein content and higher blood cholesterol concentration. In conclusion, negative (most efficient) and positive RFI (least efficient) Nellore cows, fed an ad libitum high-forage diet, produced similar amounts of milk, fat and lactose and had similar subcutaneous fat thickness, weight, calf weight as a percentage of cow weight, and blood metabolite concentrations (except for cholesterol). Therefore, there are economic benefits to utilizing RFI in a cow herd since cattle had decreased DMI with similar overall performance, making them more profitable due to lower input costs.

Dataset Information

Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.

Publications

Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.

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