Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array.
ABSTRACT: Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle.Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle.We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.
Project description:A previous genome-wide association study deduced that one (ARS-BFGL-NGS-39328), two (Hapmap26001-BTC-038813 and Hapmap31284-BTC-039204), two (Hapmap26001-BTC-038813 and BTB-00246150), and one (Hapmap50366-BTA-46960) genome-wide significant single nucleotide polymorphisms (SNPs) associated with milk fatty acids were close to or within the fatty acid synthase (FASN), peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A), ATP-binding cassette, sub-family G, member 2 (ABCG2) and insulin-like growth factor 1 (IGF1) genes. To further confirm the linkage and reveal the genetic effects of these four candidate genes on milk fatty acid composition, genetic polymorphisms were identified and genotype-phenotype associations were performed in a Chinese Holstein cattle population.Nine SNPs were identified in FASN, among which SNP rs41919985 was predicted to result in an amino acid substitution from threonine (ACC) to alanine (GCC), five SNPs (rs136947640, rs134340637, rs41919992, rs41919984 and rs41919986) were synonymous mutations, and the remaining three (rs41919999, rs132865003 and rs133498277) were found in FASN introns. Only one SNP each was identified for PPARGC1A, ABCG2 and IGF1. Association studies revealed that FASN, PPARGC1A, ABCG2 and IGF1 were mainly associated with medium-chain saturated fatty acids and long-chain unsaturated fatty acids, especially FASN for C10:0, C12:0 and C14:0. Strong linkage disequilibrium was observed among ARS-BFGL-NGS-39328 and rs132865003 and rs134340637 in FASN (D´?>?0.9), and among Hapmap26001-BTC-038813 and Hapmap31284-BTC-039204 and rs109579682 in PPARGC1A (D´?>?0.9). Subsequently, haplotype-based analysis revealed significant associations of the haplotypes encompassing eight FASN SNPs (rs41919999, rs132865003, rs134340637, rs41919992, rs133498277, rs41919984, rs41919985 and rs41919986) with C10:0, C12:0, C14:0, C18:1n9c, saturated fatty acids (SFA) and unsaturated fatty acids (UFA) (P?=?0.0204 to P?<?0.0001).Our study confirmed the linkage between the significant SNPs in our previous genome-wide association study and variants in FASN and PPARGC1A. SNPs within FASN, PPARGC1A, ABCG2 and IGF1 showed significant genetic effects on milk fatty acid composition in dairy cattle, indicating their potential functions in milk fatty acids synthesis and metabolism. The findings presented here provide evidence for the selection of dairy cows with healthier milk fatty acid composition by marker-assisted breeding or genomic selection schemes, as well as furthering our understanding of technological processing aspects of cows' milk.
Project description:The beef aging process is essential for compliance with certain major requisites, such as sensory characteristics for cooking and meat processing. Meat quality analysis of Yunling cattle, a new hybrid beef cattle bred by Chinese researchers, during the aging process, represents a major research gap. To explore Yunling beef initially, indicators associated with meat quality during the aging process of Yunling, Simmental, and Wenshan cattle were measured. In addition, some important economic traits were detected in the three breeds, including growth performance and carcass characteristics. The results showed that the growth performance, carcass traits, pH, and water holding capacity of Yunling and Simmental cattle were basically the same and better, respectively, than those of Wenshan cattle. The proportions of individual fatty acids in Yunling beef were healthier than in the other two breeds. Aging time did not affect the fatty acid profiles of the beef (p > 0.05). The contents of certain fatty acids in the three beef types displayed some differences in terms of days of aging (p < 0.05). The tenderness and meat color were better in the Yunling beef as the aging time increased, indicating that Yunling beef aged for 7 days was more suitable for cooking, exhibiting better sensory characteristics. Thus, a 7-day short-term aging process is very effective in improving the quality of Yunling beef. Our study attempted to fill a gap in the Yunling beef quality analysis during aging, providing further evidence for Yunling beef improvement.
Project description:Genomic prediction has been widely utilized to estimate genomic breeding values (GEBVs) in farm animals. In this study, we conducted genomic prediction for 20 economically important traits including growth, carcass and meat quality traits in Chinese Simmental beef cattle. Five approaches (GBLUP, BayesA, BayesB, BayesC? and BayesR) were used to estimate the genomic breeding values. The predictive accuracies ranged from 0.159 (lean meat percentage estimated by BayesC?) to 0.518 (striploin weight estimated by BayesR). Moreover, we found that the average predictive accuracies across 20 traits were 0.361, 0.361, 0.367, 0.367 and 0.378, and the averaged regression coefficients were 0.89, 0.86, 0.89, 0.94 and 0.95 for GBLUP, BayesA, BayesB, BayesC? and BayesR respectively. The genomic prediction accuracies were mostly moderate and high for growth and carcass traits, whereas meat quality traits showed relatively low accuracies. We concluded that Bayesian regression approaches, especially for BayesR and BayesC?, were slightly superior to GBLUP for most traits. Increasing with the sizes of reference population, these two approaches are feasible for future application of genomic selection in Chinese beef cattle.
Project description:Acyl-CoA synthetase family member 3 <i>(ACSF3)</i> carries out the first step of mitochondrial fatty acid synthesis II, which is the linkage of malonate and, to a lesser extent, methylmalonate onto CoA. Malonyl-coenzyme A (malonyl-CoA) is a central metabolite in mammalian fatty acid biochemistry that is generated and utilized in the cytoplasm. In this research, we verified the relationship between expression of the <i>ACSF3</i> and the production of triglycerides (TGs) at the cellular level by silencing and over-expressing <i>ACSF3</i>. Subsequently, through Sanger sequencing, five polymorphisms were found in the functional domain of the bovine <i>ACSF3</i>, and the relationship between <i>ACSF3</i> polymorphism and the economic traits and fatty acid composition of Chinese Simmental cattle was analyzed by a means of variance analysis and multiple comparison. The results illustrated that the expression of <i>ACSF3</i> promoted triglyceride synthesis in bovine mammary epithelial cells and bovine fetal fibroblast cells. Further association analysis also indicated that individuals with the AG genotype (g.14211090 G > A) of <i>ACSF3</i> were significantly associated with the fatty acid composition of intramuscular fat (higher content of linoleic acid, α-linolenic acid, and arachidonic acid), and that CTCAG haplotype individuals were significantly related to the fatty acid composition of intramuscular fat (higher linoleic acid content). Individuals with the AA genotypes of g.14211055 A > G and g.14211090 G > A were substantially associated with a larger eye muscle area in the Chinese Simmental cattle population. <i>ACSF3</i> played a pivotal role in the regulation of cellular triacylglycerol and long-chain polyunsaturated fatty acid levels, and polymorphism could serve as a useful molecular marker for future marker-assisted selection in the breeding of intramuscular fat deposition traits in beef cattle.
Project description:Chinese Simmental beef cattle are the most economically important cattle breed in China. Estimated breeding values for growth, carcass, and meat quality traits are commonly used as selection criteria in animal breeding. The objective of this study was to evaluate the accuracy of alternative statistical methods for the estimation of genomic breeding values. Analyses of the accuracy of genomic best linear unbiased prediction (GBLUP), BayesB, and elastic net (EN) were performed with an Illumina BovineHD BeadChip on 1,217 animals by applying 5-fold cross-validation. Overall, the accuracies ranged from 0.17 to 0.296 for ten traits, and the heritability estimates ranged from 0.36 to 0.63. The EN (alpha = 0.001) model provided the most accurate prediction, which was also slightly higher (0.2-2%) than that of GBLUP for most traits, such as average daily weight gain (ADG) and carcass weight (CW). BayesB was less accurate for each trait than were EN (alpha = 0.001) and GBLUP. These findings indicate the importance of using an appropriate variable selection method for the genomic selection of traits and suggest the influence of the genetic architecture of the traits we analyzed.
Project description:Genomic selection has been widely used for complex quantitative trait in farm animals. Estimations of breeding values for slaughter traits are most important to beef cattle industry, and it is worthwhile to investigate prediction accuracies of genomic selection for these traits. In this study, we assessed genomic predictive abilities for average daily gain weight (ADG), live weight (LW), carcass weight (CW), dressing percentage (DP), lean meat percentage (LMP) and retail meat weight (RMW) using Illumina Bovine 770K SNP Beadchip in Chinese Simmental cattle. To evaluate the abilities of prediction, marker effects were estimated using genomic BLUP (GBLUP) and three parallel Bayesian models, including multiple chains parallel BayesA, BayesB and BayesC? (PBayesA, PBayesB and PBayesC?). Training set and validation set were divided by random allocation, and the predictive accuracies were evaluated using 5-fold cross validations. We found the accuracies of genomic predictions ranged from 0.195±0.084 (GBLUP for LMP) to 0.424±0.147 (PBayesB for CW). The average accuracies across traits were 0.327±0.085 (GBLUP), 0.335±0.063 (PBayesA), 0.347±0.093 (PBayesB) and 0.334±0.077 (PBayesC?), respectively. Notably, parallel Bayesian models were more accurate than GBLUP across six traits. Our study suggested that genomic selections with multiple chains parallel Bayesian models are feasible for slaughter traits in Chinese Simmental cattle. The estimations of direct genomic breeding values using parallel Bayesian methods can offer important insights into improving prediction accuracy at young ages and may also help to identify superior candidates in breeding programs.
Project description:Detecting genes associated with milk fat composition could provide valuable insights into the complex genetic networks of genes underling variation in fatty acids synthesis and point towards opportunities for changing milk fat composition via selective breeding. In this study, we conducted a genome-wide association study (GWAS) for 22 milk fatty acids in 784 Chinese Holstein cows with the PLINK software. Genotypes were obtained with the Illumina BovineSNP50 Bead chip and a total of 40,604 informative, high-quality single nucleotide polymorphisms (SNPs) were used. Totally, 83 genome-wide significant SNPs and 314 suggestive significant SNPs associated with 18 milk fatty acid traits were detected. Chromosome regions that affect milk fatty acid traits were mainly observed on BTA1, 2, 5, 6, 7, 9, 13, 14, 18, 19, 20, 21, 23, 26 and 27. Of these, 146 SNPs were associated with more than one milk fatty acid trait; most of studied fatty acid traits were significant associated with multiple SNPs, especially C18:0 (105 SNPs), C18 index (93 SNPs), and C14 index (84 SNPs); Several SNPs are close to or within the DGAT1, SCD1 and FASN genes which are well-known to affect milk composition traits of dairy cattle. Combined with the previously reported QTL regions and the biological functions of the genes, 20 novel promising candidates for C10:0, C12:0, C14:0, C14:1, C14 index, C18:0, C18:1n9c, C18 index, SFA, UFA and SFA/UFA were found, which composed of HTR1B, CPM, PRKG1, MINPP1, LIPJ, LIPK, EHHADH, MOGAT1, ECHS1, STAT1, SORBS1, NFKB2, AGPAT3, CHUK, OSBPL8, PRLR, IGF1R, ACSL3, GHR and OXCT1. Our findings provide a groundwork for unraveling the key genes and causal mutations affecting milk fatty acid traits in dairy cattle.
Project description:The intramuscular fat (IMF) content of different beef cattle breeds varies greatly, which plays an important role in taste and nutritional value. However, the molecular mechanism of fat metabolism and deposition in beef cattle is still not very clear. In this study, the meat quality traits of Angus cattle and Chinese Simmental cattle were compared, the transcriptome of the longissimus dorsi muscle (LD) between Angus cattle and Chinese Simmental cattle was then analyzed to identify key genes related to fat metabolism and adipogenesis by high-throughput RNA-seq technology. In the current study conducted a comprehensive analysis on the transcriptome of the longissimus dorsi muscle (LD) of Angus and Simmental cattle, and identified differentially expressed genes related to lipid metabolism，which may have a great impact on on the formation of IMF. Overall design: RNAseq profiles of Angus and Chinese Simmental longissimus dorsi (LD)
Project description:Background:Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinning these traits and promote the improvement of fatty acid profiles. In this study, we performed a genome-wide association study (GWAS) on fatty acid composition using high-density single nucleotide polymorphism (SNP) arrays in Chinese Wagyu cattle. Results:In total, we detected 15 and 8 significant genome-wide SNPs for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, respectively. Also, we identified nine candidate genes based on 100 kb regions around associated SNPs. Four SNPs significantly associated with C14:1 cis-9 were embedded with stearoyl-CoA desaturase (SCD), while three SNPs in total were identified for C22:6 n-3 within Phospholipid scramblase family member 5 (PLSCR5), Cytoplasmic linker associated protein 1 (CLASP1), and Chymosin (CYM). Notably, we found the top candidate SNP within SCD can explain ~ 7.37% of phenotypic variance for C14:1 cis-9. Moreover, we detected several blocks with high LD in the 100 kb region around SCD. In addition, we found three significant SNPs within a 100 kb region showing pleiotropic effects related to multiple FA groups (PUFA, n-6, and PUFA/SFA), which contains BAI1 associated protein 2 like 2 (BAIAP2L2), MAF bZIP transcription factor F (MAFF), and transmembrane protein 184B (TMEM184B). Conclusions:Our study identified several significant SNPs and candidate genes for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, and these findings will further assist the design of breeding programs for meat quality in cattle.
Project description:Elongation of very long chain fatty acids (ELOVL)5 is one of seven mammalian fatty acid condensing enzymes involved in microsomal fatty acid elongation. To determine the in vivo substrates and function of ELOVL5, we generated Elovl5(-/-) mice. Studies using liver microsomal protein from wild-type and knockout mice demonstrated that the elongation of gamma-linolenic (C18:3, n-6) to dihomo-gamma-linolenic (C20:3, n-6) and stearidonic (C18:4, n-3) to omega3-arachidonic acid (C20:4, n-3) required ELOVL5 activity. Tissues of Elovl5(-/-) mice accumulated the C18 substrates of ELOVL5 and the levels of the downstream products, arachidonic acid (C20:4, n-6) and docosahexaenoic acid (DHA, C22:6, n-3), were decreased. A consequence of decreased cellular arachidonic acid and DHA concentrations was the activation of sterol regulatory element-binding protein (SREBP)-1c and its target genes involved in fatty acid and triglyceride synthesis, which culminated in the development of hepatic steatosis in Elovl5(-/-) mice. The molecular and metabolic changes in fatty acid metabolism in Elovl5(-/-) mice were reversed by dietary supplementation with arachidonic acid and DHA. These studies demonstrate that reduced ELOVL5 activity leads to hepatic steatosis, and endogenously synthesized PUFAs are key regulators of SREBP-1c activation and fatty acid synthesis in livers of mice.