Selection For Meat Quality Traits Research Articles

Genomic selection for meat quality traits based on VIS/NIR spectral information1

The principle of genomic selection (GS) entails estimating breeding values (BVs) by summing all the SNP polygenic effects. The VIS/NIRS wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all “polygenic effects” associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359 Duroc×Landrace×Yorkshire pigs from Guangxi, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed four breeding strategies applied to different scenarios: I, only spectral and genotypic data exist for the target population; II, only spectral data exist for the target population; III, only spectral and genotypic data but with different prediction processes exist for the target population; and IV, only spectral and phenotypic data exist for the target population. The four scenarios were used to evaluate the GEBV accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies II, III, and IV was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2%, 40.8% and 15.5% respectively on average. Among them, the prediction accuracy of Strategy II for Fat (%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy I was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the four strategies was lower than that of traditional GS methods, with Strategy IV being the lowest as it ’did not require genotyping. Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.

Genomic selection for meat quality traits in Pekin duck

Genomic selection uses genome-wide molecular marker data to predict an animal's genetic value in the breeding program. This study's objective was to present heritability estimates and accuracy of genomic prediction using different methods for meat quality traits in Pekin duck. There were two kinds of ducks in the genomic selection training population: 639 fat-type ducks and 540 lean-type ducks. A single-trait animal model was used to estimate heritability and adjust the phenotype. GBLUP and BayesR methods were performed to estimate the SNP effects. The accuracy of genomic prediction was calculated using 5-fold cross-validation. The accuracy varied from 0.235 to 0.501 with the lowest accuracy estimated for traits associated with abdominal fat weight in the combined population and the most remarkable accuracy observed for abdominal fat percentage traits in the lean-type duck population. Overall, BayesR can achieve the highest prediction accuracy, while the combined population strategy could be used to increase the accuracy of prediction only when the two populations have the same breeding aim for a certain trait.

Genomic selection for meat quality traits in Nelore cattle

The objective of this study was to present heritability estimates and accuracy of genomic prediction using different methods for meat quality traits in Nelore cattle. Approximately 5000 animals with phenotypes and genotypes of 412,000 SNPs, were divided into two groups: (1) training population: animals born from 2008 to 2013 and (2) validation population: animals born in 2014. A single-trait animal model was used to estimate heritability and to adjust the phenotype. The methods of GBLUP, Improved Bayesian Lasso and Bayes Cπ were performed to estimate the SNP effects. Accuracy of genomic prediction was calculated using Pearson's correlations between direct genomic values and adjusted phenotypes, divided by the square root of heritability of each trait (0.03–0.19). The accuracies varied from 0.23 to 0.73, with the lowest accuracies estimated for traits associated with fat content and the greatest accuracies observed for traits of meat color and tenderness. There were small differences in genomic prediction accuracy between methods.

A novel single nucleotide polymorphism of the POU1F1 gene associated with meat quality traits in rabbits

Abstract The purpose of this research was to investigate the effect of the POU1F1 gene on meat quality traits in the Hyla, Champagne, and Tianfu Black rabbit breeds. We detected one single nucleotide polymorphism and the SNP was located at 536 bp in intron 5 of this gene. Chi-square tests showed that the genotypic frequencies in the three rabbit populations were not in Hardy-Weinberg equilibrium. The PIC values indicated that the three populations had intermediate levels of genetic diversity. Rabbits with the CC genotype had a significantly greater pH0h than those with the CT genotype in the biceps femoris muscle. The least squares means for cooking loss in CT and CC rabbits were significantly higher than those for TT rabbits. Rabbits with the CC genotype had a significantly higher intramuscular fat content in the longissimus dorsi and biceps femoris muscles than those with genotype TT and CT. Thus, the results here indicate that this POU1F1 SNP may be of potential use in marker assisted selection for meat quality traits in rabbits.

Back fat thickness and meat tenderness are associated with a 526 T→A mutation in the exon 1 promoter region of the MyF-5 gene in Chinese Bos taurus

Qualitative trait loci (QTL) for growth and meat quality traits in cattle (Bos taurus) have been previously mapped to three chromosome regions, 0 to 30, 55 to 70, and 70 to 80 cM on chromosome 5. We evaluated the allele frequencies and gene-specific single nucleotide polymorphisms (SNPs) of bovine myogenic factor 5 (MyF-5) in the QTL regions and their associations with live weight and meat characteristics in indigenous Chinese cattle breeds. PCR-SSCP methodology showed a T>A mutation at 526 bp. Least square analysis revealed a significant association of this SNP with backfat thickness and meat tenderness (P < 0.05), while no significant association was found with live weight, loin eye height, loin eye area, rib area, or water holding capacity. Allele frequencies of MyF-5-A/B in the five breeds were 0.760/0.239, 0.752/0.247, 0.629/0.370, 0.715/0.284, and 0.750/0.250, for JiaXian red, Luxi, Nanyang, Qinchuan, and XiaNan crossbreed, respectively. The genotype distributions for these alleles in two of the Chinese cattle breeds (Luxi and Qinchuan) were not in Hardy-Weinberg equilibrium (P < 0.05); while those for the other three breeds (JiaXian red, Nanyang, and XiaNan) were in agreement with Hardy-Weinberg equilibrium (P > 0.05). The genotypic frequencies among all five cattle breeds showed moderate diversity (0.25 < polymorphism information content < 0.5). Based on our findings, we suggest that the MyF-5 gene influences back fat thickness and meat tenderness in Chinese Bos taurus. This SNP could be useful for marker-assisted selection for meat quality traits in these cattle.

Association of CAST Gene Polymorphisms with Carcass and Meat Quality Traits in Chinese Commercial Cattle Herds

Calpastatin (CAST), an endogenous inhibitor of the calpains, plays an important role in post-mortem tenderization of meat. The objectives of this study were to investigate single nucleotide polymorphisms (SNPs) in the bovine CAST gene and association with carcass and meat quality traits. A total of 212 cattle from commercial herds were tested in this study including 2 pure introduced breeds, 4 cross populations, and 3 pure Chinese native breeds. Five SNPs were identified at position 2959 (A/G), 2870 (G/A), 3088 (C/T), 3029 (G/A) and 2857 (C/T) in the CAST gene (GenBank Accession No. AF159246). Allele frequencies of SNP2959 and SNP2870 were 0.701 (A) and 0.462 (A), respectively. A general linear model was used to evaluate the associations between the two markers and 7 traits. The results showed that both SNP2959 and SNP2870 were significantly (p<0.01) associated with the Wamer-Bratzler shear force (WBSF), while they had no significant association with the other 6 traits in the whole population. However, in Chinese native pure breeds, only SNP2870 had significant association with WBSF (p<0.05). The simultaneous analysis of two-marker genotype effects indicated animals containing the A/G haplotype (A for SNP2959 and G for SNP2870) tended to have lower shear force than those containing the G/A haplotype, and, especially, animals homozygous for the A/G haplotype had approximately 2 kg lower shear force than those homozygous for the G/A haplotype (p<0.01). These results suggested that both markers may be effective for the marker-assisted selection of meat quality traits in Chinese commercial herds, especially SNP2870 which can be used for Chinese native cattle. I.

Genetic trend estimates of meat quality traits in a male broiler line

The present research was conducted to estimate the genetic trends for meat quality traits in a male broiler line. The traits analyzed were initial pH, pH at 6 h after slaughter, final pH, initial range of falling pH, final range of falling pH, lightness, redness, yellowness, weep loss, drip loss, shrink loss, and shear force. The number of observations varied between 618 and 2125 for each trait. Genetic values were obtained by restricted maximum likelihood, and the numerator relationship matrix had 107,154 animals. The genetic trends were estimated by regression of the broiler average genetic values with respect to unit of time (generations), and the average genetic trend was estimated by regression coefficients. Generally, for the traits analyzed, small genetic trends were obtained, except for drip loss and shear force, which were higher. The small magnitude of the trends found could be a consequence of the absence of selection for meat quality traits in the line analyzed. The estimates of genetic trends obtained were an indication of an improvement in the meat quality traits in the line analyzed, except for drip loss.