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Genetic parameters were estimated for objective and subjective traits assessed after 3 and 29 days aging in meat samples of 1154 commercial beef cattle. Meat attributes [Warner-Bratzler shear force (WBSF), intramuscular fat (IMF), and pH] and sensory traits [flavor intensity (FI), off-flavor (OF), connective tissue (CT), overall tenderness (OT), sustained juiciness (SJ), and overall palatability (OP)] were available. The animal mixed model used included additive genetic and residual effects as random effects, contemporary group as fixed effect and genomic breed composition and slaughter age as covariates. Genetic parameters were estimated using airemlf90 software and single-step genomic BLUP. Heritability estimates for OT (3 and 29 d), OP (3 d) and OF (29 d) were of moderate magnitude ranging from 0.18 ± 0.07 to 0.31 ± 0.07. Heritabilities were negligible or of low magnitude for all other sensory traits with values ranging from 0.03 ± 0.05 to 0.14 ± 0.07. Among objectively measured traits, the estimate of heritability for meat pH was moderate at day 3 (0.20 ± 0.08) and negligible at 29 (0.00 ± 0.05). For IMF and WBSF the heritability estimates were 0.43 ± 0.09 and 0.54 ± 0.09, and 0.22 ± 0.07 and 0.19 ± 0.07 for day 3 and 29, respectively. Genetic correlations between days for each sensory trait tended to be of high and positive magnitude ranging from 0.54 ± 0.60 to 0.99 ± 0.28. Genetic and phenotypic correlations of subjectively assessed traits were consistent in direction and magnitude with WBSF (negative) and IMF (positive) suggesting that genetic selection based on objectively measured traits can be used for meat quality improvement and to increase consumer satisfaction. In addition, selection can be implemented using sensory traits collected after 3 days of aging., Competing Interests: Declaration of Competing Interest All authors declare no conflicts of interest related to this study, and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in purebred (PB) and commercial crossbred (CB) pigs is necessary for a successful breeding program because, although the breeding goal is to improve CB performance, phenotype collection and selection are usually carried out in PB populations housed in biosecure nucleus herds. Thus, the selection is indirect, and the accuracy of selection depends on the genetic correlation between PB and CB performance (rpc). The objectives of this study were to 1) estimate genetic parameters for growth, meat quality, and carcass traits in a PB sire line and related commercial CB pigs and 2) estimate the corresponding genetic correlations between purebred and crossbred performance (rpc). Both objectives were investigated by using pedigree information only (PBLUP) and by combining pedigree and genomic information in a single-step genomic BLUP (ssGBLUP) procedure. Growth rate showed moderate estimates of heritability for both PB and CB based on PBLUP, while estimates were higher in CB based on ssGBLUP. Heritability estimates for meat quality traits were diverse and slightly different based on PB and CB data with both methods. Carcass traits had higher heritability estimates based on PB compared with CB data based on PBLUP and slightly higher estimates for CB data based on ssGBLUP. A wide range of estimates of genetic correlations were obtained among traits within the PB and CB data. In the PB population, estimates of heritabilities and genetic correlations were similar based on PBLUP and ssGBLUP for all traits, while based on the CB data, ssGBLUP resulted in different estimates of genetic parameters with lower SEs. With some exceptions, estimates of rpc were moderate to high. The SE on the rpc estimates was generally large when based on PBLUP due to limited sample size, especially for CBs. In contrast, estimates of rpc based on ssGBLUP were not only more precise but also more consistent among pairs of traits, considering their genetic correlations within the PB and CB data. The wide range of estimates of rpc (less than 0.70 for 7 out of 13 traits) indicates that the use of CB phenotypes recorded on commercial farms, along with genomic information, for selection in the PB population has potential to increase the genetic progress of CB performance., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Of all the meat quality traits, tenderness is considered the most important with regard to eating quality and market value. In this study we have utilised genome wide association studies (GWAS) for peak shear force (PSF) of loin muscle as a measure of tenderness for 1,976 crossbred commercial pigs, genotyped for 42,721 informative SNPs using the Illumina PorcineSNP60 Beadchip. Four 1 Mb genomic regions, three on SSC2 (at 4 Mb, 5 Mb and 109 Mb) and one on SSC17 (at 20 Mb), were detected which collectively explained about 15.30% and 3.07% of the total genetic and phenotypic variance for PSF respectively. Markers ASGA0008566, ASGA0008695, DRGA0003285 and ASGA0075615 in the four regions were strongly associated with the effects. Analysis of the reference genome sequence in the region with the most important SNPs for SSC2_5 identified FRMD8, SLC25A45 and LTBP3 as potential candidate genes for meat tenderness on the basis of functional annotation of these genes. The region SSC2_109 was close to a previously reported candidate gene CAST; however, the very weak LD between DRGA0003285 (the best marker representing region SSC2_109) and CAST indicated the potential for additional genes which are distinct from, or interact with, CAST to affect meat tenderness. Limited information of known genes in regions SSC2_109 and SSC17_20 restricts further analysis. Re-sequencing of these regions for informative animals may help to resolve the molecular architecture and identify new candidate genes and causative mutations affecting this trait. These findings contribute significantly to our knowledge of the genomic regions affecting pork shear force and will potentially lead to new insights into the molecular mechanisms regulating meat tenderness.

Background: Improving meat quality is a high priority for the pork industry to satisfy consumers' preferences. GWAS have become a state-of-the-art approach to genetically improve economically important traits. However, GWAS focused on pork quality are still relatively rare., Results: Six genomic regions were shown to affect loin pH and Minolta colour a* and b* on both loin and ham through GWAS in 1943 crossbred commercial pigs. Five of them, located on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, SSC16 and SSCX, were associated with meat colour. However, the most promising region was detected on SSC15 spanning 133-134 Mb which explained 3.51% - 17.06% of genetic variance for five measurements of pH and colour. Three SNPs (ASGA0070625, MARC0083357 and MARC0039273) in very strong LD were considered most likely to account for the effects in this region. ASGA0070625 is located in intron 2 of ZNF142, and the other two markers are close to PRKAG3, STK36, TTLL7 and CDK5R2. After fitting MARC0083357 (the closest SNP to PRKAG3) as a fixed factor, six SNPs still remained significant for at least one trait. Four of them are intragenic with ARPC2, TMBIM1, NRAMP1 and VIL1, while the remaining two are close to RUFY4 and CDK5R2. The gene network constructed demonstrated strong connections of these genes with two major hubs of PRKAG3 and UBC in the super-pathways of cell-to-cell signaling and interaction, cellular function and maintenance. All these pathways play important roles in maintaining the integral architecture and functionality of muscle cells facing the dramatic changes that occur after exsanguination, which is in agreement with the GWAS results found in this study., Conclusions: There may be other markers and/or genes in this region besides PRKAG3 that have an important effect on pH and colour. The potential markers and their interactions with PRKAG3 require further investigation.

Genetic correlations between performance traits with meat quality and carcass traits were estimated on 6,408 commercial crossbred pigs with performance traits recorded in production systems with 2,100 of them having meat quality and carcass measurements. Significant fixed effects (company, sex and batch), covariates (birth weight, cold carcass weight, and age), random effects (additive, litter and maternal) were fitted in the statistical models. A series of pairwise bivariate analyses were implemented in ASREML to estimate heritability, phenotypic, and genetic correlations between performance traits (n = 9) with meat quality (n = 25) and carcass (n = 19) traits. The animals had a pedigree compromised of 9,439 animals over 15 generations. Performance traits had low-to-moderate heritabilities (±SE), ranged from 0.07±0.13 to 0.45±0.07 for weaning weight, and ultrasound backfat depth, respectively. Genetic correlations between performance and carcass traits were moderate to high. The results indicate that: (a) selection for birth weight may increase drip loss, lightness of longissimus dorsi, and gluteus medius muscles but may reduce fat depth; (b) selection for nursery weight can be valuable for increasing both quantity and quality traits; (c) selection for increased daily gain may increase the carcass weight and most of the primal cuts. These findings suggest that deterioration of pork quality may have occurred over many generations through the selection for less backfat thickness, and feed efficiency, but selection for growth had no adverse effects on pork quality. Low-to-moderate heritabilities for performance traits indicate that they could be improved using traditional selection or genomic selection. The estimated genetic parameters for performance, carcass and meat quality traits may be incorporated into the breeding programs that emphasize product quality in these Canadian swine populations.

Interest in genetic improvement of carcass and tenderness traits of beef cattle using genome-based selection (GS) and marker-assisted management programs is increasing. The success of such a program depends on the presence of linkage disequilibrium between the observed markers and the underlying QTL as well as on the relationship between the discovery, validation, and target populations. For molecular breeding values (MBV) predicted for a target population using SNP markers, reliabilities of these MBV can be obtained from validation analyses conducted in an independent population distinct from the discovery set. The objective of this study was to test MBV predicted for carcass and tenderness traits of beef cattle in a Canadian-based validation population that is largely independent of a United States-based discovery set. The discovery data set comprised of genotypes and phenotypes from >2,900 multibreed beef cattle while the validation population consisted of 802 crossbred feeder heifers and steers. A bivariate animal model that fitted actual phenotype and MBV was used for validation analyses. The reliability of MBV was defined as square of the genetic correlation (R(2) g) that represents the proportion of the additive genetic variance explained by the SNP markers. Several scenarios involving different starting marker panels (384, 3K, 7K, and 50K) and different sets of SNP selected to compute MBV (50, 100, 200, 375, 400, 600, and 800) were investigated. Validation results showed that the most reliable MBV (R(2) g) were 0.34 for HCW, 0.36 for back fat thickness, 0.28 for rib eye area, 0.30 for marbling score, 0.25 for yield grade, and 0.38 for Warner-Bratzler shear force across the different scenarios explored. The results indicate that smaller SNP panels can be developed for use in genetic improvement of beef carcass and tenderness traits to exploit GS benefits.

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.

A number of studies have mapped QTL regulating porcine fatness and growth traits to the region of the major histocompatibility complex (MHC) on porcine chromosome 7 using various experimental crosses. The QTL results from crosses using the Chinese Meishan (MS) (slow growing and fat) are particularly interesting because the MS alleles have been found to be associated with increased growth rate and reduced backfat depth. We investigated these QTL further in a composite population derived previously over eight generations by intercrossing Meishan and the European Large White breeds. Genotype information from 32 markers in a 15cM target region was used in linkage and association analyses. A two-step variance component analysis identified QTL for three growth-related traits, explaining 19 ∼ 24% of the phenotypic variance with a confidence interval of 4 cM in the target region. SNP association analyses found that ss181128966 and ss181128924 within the QTL interval were strongly associated with the growth traits. Only weak signals for an effect on backfat depth were found in the association and linkage analyses, possibly because of past directional selection in the composite population., (© 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.)

Peroxisome proliferator-activated receptor gamma (PPARG) is a key transcription factor that controls adipocyte differentiation and fat deposition in mammals. The primary goal of this study was to investigate PPARG as a candidate gene for meat quality and carcass traits in swine. Part of the PPARG promoter, along with the most 5'-proximal exon of the gene, was amplified by PCR and subsequently screened for polymorphisms by sequencing. A Met59Val substitution was detected in the porcine PPARG gene along with four polymorphisms in the promoter region of the adipose-specific PPARG2. Three of these polymorphisms were chosen for genotyping and tested for association with meat quality, carcass and growth traits, according to the candidate gene approach. More than 1500 animals from different lines and populations were used in the study with records for meat quality and carcass traits. No convincing associations were found between the traits investigated and the PPARG genotypes. It does not appear that variation at the PPARG locus is affecting meat quality, carcass or growth traits in the pig populations studied.