Genetic parameters of meat quality, carcass composition, and growth traits in commercial swine

Transgenerational epigenetic heritability for growth, body composition, and reproductive traits in Landrace pigs

Epigenetics is an important source of variation in complex traits that is not due to changes in DNA sequences, and is dependent on the environment the individuals are exposed to. Therefore, we aimed to estimate transgenerational epigenetic heritability, percentage of resetting epigenetic marks, genetic parameters, and predicting breeding values using genetic and epigenetic models for growth, body composition, and reproductive traits in Landrace pigs using routinely recorded datasets. Birth and weaning weight, backfat thickness, total number of piglets born, and number of piglets born alive (BW, WW, BF, TNB, and NBA, respectively) were investigated. Models including epigenetic effects had a similar or better fit than solely genetic models. Including genomic information in epigenetic models resulted in large changes in the variance component estimates. Transgenerational epigenetic heritability estimates ranged between 0.042 (NBA) to 0.336 (BF). The reset coefficient estimates for epigenetic marks were between 80% and 90%. Heritability estimates for the direct additive and maternal genetic effects ranged between 0.040 (BW) to 0.502 (BF) and 0.034 (BF) to 0.134 (BW), respectively. Repeatability of the reproductive traits ranged between 0.098 (NBA) to 0.148 (TNB). Prediction accuracies, bias, and dispersion of breeding values ranged between 0.199 (BW) to 0.443 (BF), -0.080 (WW) to 0.034 (NBA), and -0.134 (WW) to 0.131 (TNB), respectively, with no substantial differences between genetic and epigenetic models. Transgenerational epigenetic heritability estimates are moderate for growth and body composition and low for reproductive traits in North American Landrace pigs. Fitting epigenetic effects in genetic models did not impact the prediction of breeding values.

Multiple-trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait

Traits such as meat quality and composition are becoming valuable in modern pork production; however, they are difficult to include in genetic evaluations because of the high phenotyping costs. Combining genomic information with multiple-trait indirect selection with cheaper indicator traits is an alternative for continued cost-effective genetic improvement. Additionally, gut microbiome information is becoming more affordable to measure using targeted rRNA sequencing, and its applications in animal breeding are becoming relevant. In this paper, we investigated the usefulness of microbial information as a correlated trait in selecting meat quality in swine. This study incorporated phenotypic data encompassing marbling, colour, tenderness, loin muscle and backfat depth, along with the characterization of gut (rectal) microbiota through 16S rRNA sequencing at three distinct time points of the animal's growth curve. Genetic progress estimation and cross-validation were employed to evaluate the utility of utilizing host genomic and gut microbiota information for selecting expensive-to-record traits in crossbred individuals. Initial steps involved variance components estimation using multiple-trait models on a training dataset, where the top 25 associated operational taxonomic units (OTU) for each meat quality trait and time point were included. The second step compared the predictive ability of multiple-trait models incorporating different numbers of OTU with single-trait models in a validation set. Results demonstrated the advantage of including genomic information for some traits, while in some instances, gut microbial information proved advantageous, namely, for marbling and pH. The study suggests further investigation into the shared genetic architecture between microbial features and traits, considering microbial data's compositional and high-dimensional nature. This research proposes a straightforward method to enhance swine breeding programs for improving costly-to-record traits like meat quality by incorporating gut microbiome information.

Genetic parameters for calf feeding traits derived from automated milk feeding machines and number of bovine respiratory disease treatments in North American Holstein calves

Precision livestock farming technologies, such as automatic milk feeding machines, have increased the availability of on-farm data collected from dairy operations. We analyzed feeding records from automatic milk feeding machines to evaluate the genetic background of milk feeding traits and bovine respiratory disease (BRD) in North American Holstein calves. Data from 10,076 preweaning female Holstein calves were collected daily over a period of 6 yr (3 yr included per-visit data), and daily milk consumption (DMC), per-visit milk consumption (PVMC), daily sum of drinking duration (DSDD), drinking duration per-visit, daily number of rewarded visits (DNRV), and total number of visits per day were recorded over a 60-d preweaning period. Additional traits were derived from these variables, including total consumption and duration variance (TCV and TDV), feeding interval, drinking speed (DS), and preweaning stayability. A single BRD-related trait was evaluated, which was the number of times a calf was treated for BRD (NTT). The NTT was determined by counting the number of BRD incidences before 60 d of age. All traits were analyzed using single-step genomic BLUP mixed-model equations and fitting either repeatability or random regression models in the BLUPF90+ suite of programs. A total of 10,076 calves with phenotypic records and genotypic information for 57,019 SNP after the quality control were included in the analyses. Feeding traits had low heritability estimates based on repeatability models (0.006 ± 0.0009 to 0.08 ± 0.004). However, total variance traits using an animal model had greater heritabilities of 0.21 ± 0.023 and 0.23 ± 0.024, for TCV and TDV, respectively. The heritability estimates increased with the repeatability model when using only the first 32 d preweaning (e.g., PVMC = 0.040 ± 0.003, DMC = 0.090 ± 0.009, DSDD = 0.100 ± 0.005, DS = 0.150 ± 0.007, DNRV = 0.020 ± 0.002). When fitting random regression models (RRM) using the full dataset (60-d period), greater heritability estimates were obtained (e.g., PVMC = 0.070 [range: 0.020, 0.110], DMC = 0.460 [range: 0.050, 0.680], DSDD = 0.180 [range: 0.010, 0.340], DS = 0.19 [range: 0.070, 0.430], DNRV = 0.120 [range: 0.030, 0.450]) for the majority of the traits, suggesting that RRM capture more genetic variability than the repeatability model with better fit being found for RRM. Moderate negative genetic correlations of -0.59 between DMC and NTT were observed, suggesting that automatic milk feeding machines records have the potential to be used for genetically improving disease resilience in Holstein calves. The results from this study provide key insights of the genetic background of early in-life traits in dairy cattle, which can be used for selecting animals with improved health outcomes and performance.

Do carcass traits influence consumer perception of pork eating quality?

The objective of this study was to assess carcass traits' influence on pork eating quality as evaluated by consumers. A total of 1360 pork chops were used, with 824 from the sirloin end and 536 from the butt end of the loin (Longissimuss thoracis et lumborum), to produce 340 packages, each containing four pork chops. Untrained participants received one package of either sirloin or butt chops, being two pork chops from barrows and two from gilts. Participants answered a survey rating the tenderness, juiciness, flavour, and overall acceptability of each chop on an 8-point scale. Correlation analysis was conducted between carcass traits and pork eating quality attributes. For the descriptive analysis, classes (low, medium, and high) for carcass traits, Warner-Bratzler shear force (WBSF) and cooking loss were created based on our consumer responses dataset for palatability attributes. No significant correlations (P > 0.05) were observed between carcass traits and pork eating quality traits. Tenderness and overall acceptability were negatively correlated (P < 0.05) with cooking loss and WBSF. Loin intramuscular fat (IMF) content showed a weak negative correlation (P < 0.05) with WBSF and cooking loss. Consumers rated chops from the high and medium/high backfat thickness and loin IMF classes slightly higher for tenderness and juiciness, respectively. Additionally, chops from the low and/or medium WBSF and cooking loss classes received slightly higher scores for tenderness and juiciness than pork chops in the high classes. In conclusion, the study indicated that carcass traits had minimal impact on overall acceptability of pork by consumers.

Investigation on muscle fiber types and meat quality and estimation of their heritability and correlation coefficients with each other in four pig populations

The aim of this study was to investigate the muscle fiber types and meat quality in four populations and estimate the heritability and correlation coefficients of those traits in Shanxia long black pig (SX). In this study, a total of 318 pigs were recorded for 16 traits of the muscle fiber types and meat quality in four populations, including 256 individuals from the new breed SX. The population had a significant effect on all recorded traits, and the meat quality of the Lulai black pig was better than the remaining populations. The heritability (h2 ) of meat quality traits was from 0.06 (pH at 24 h) to 0.47 (shearing force), and the muscle fiber types belonged to the traits with low to medium heritability. The density of total fiber had the highest h2 (0.40), while the percentage of type IIA had the lowest h2 (0.04). Most traits are phenotypically correlated with each other, but only a small proportion of traits are genetically correlated with each other. None fiber type genetically correlated with meat quality significantly, because the genetic correlation coefficients had large standard errors. These results provided some insights into genetic improvements for the meat quality in pig breeds and also indicated that the parameters of muscle fiber characteristics can explain parts of the variation in meat quality.

Genomic architecture of carcass and pork traits and their association with immune capacity

Carcass and pork traits have traditionally been considered of prime importance in pig breeding programmes. However, the changing conditions in modern farming, coupled with antimicrobial resistance issues, are raising the importance of health and robustness-related traits. Here, we explore the genetic architecture of carcass and pork traits and their relationship with immunity phenotypes in a commercial Duroc pig population. A total of nine traits related to fatness, lean content and meat pH were measured at slaughter (∼190 d of age) in 378 pigs previously phenotyped (∼70 d of age) for 36 immunity-related traits, including plasma concentrations of immunoglobulins, acute-phase proteins, leukocytes subpopulations and phagocytosis. Our study showed medium to high heritabilities and strong genetic correlations between fatness, lean content and meat pH at 24 h postmortem. Genetic correlations were found between carcass and pork traits and white blood cells. pH showed strong positive genetic correlations with leukocytes and eosinophils, and strong negative genetic correlations with haemoglobin, haematocrit and cytotoxic T cell proportion. In addition, genome-wide association studies (GWASs) pointed out four significantly associated genomic regions for lean meat percentages in different muscles, ham fat, backfat thickness, and semimembranosus pH at 24 h. The functional annotation of genes located in these regions reported a total of 14 candidate genes, with BGN, DPP10, LEPR, LEPROT, PDE4B and SLC6A8 being the strongest candidates. After performing an expression GWAS for the expression of these genes in muscle, two signals were detected in cis for the BGN and SLC6A8 genes. Our results indicate a genetic relationship between carcass fatness, lean content and meat pH with a variety of immunity-related traits that should be considered to improve immunocompetence without impairing production traits.

Screening of lncRNA profiles during intramuscular adipogenic differentiation in longissimus dorsi and semitendinosus muscles in pigs

Intramuscular fat content is an important factor that determines meat quality in pigs. In recent years, epigenetic regulation has increasingly studied the physiological model of intramuscular fat. Although long noncoding RNAs (lncRNAs) play essential roles in various biological processes, their role in intramuscular fat deposition in pigs remains largely unknown. In this study, intramuscular preadipocytes in the longissimus dorsi and semitendinosus of Large White pigs were isolated and induced into adipogenic differentiation in vitro. High-throughput RNA-seq was carried out to estimate the expression of lncRNAs at 0, 2 and 8 days post-differentiation. At this stage, 2135 lncRNAs were identified. KEGG analysis showed that the differentially expressed lncRNAs were common in pathways involved with adipogenesis and lipid metabolism. lnc_000368 was found to gradually increase during the adipogenic process. Reverse-transcription quantitative polymerase chain reaction and a western blot revealed that the knockdown of lnc_000368 significantly repressed the expression of adipogenic genes and lipolytic genes. As a result, lipid accumulation in porcine intramuscular adipocytes was impaired by the silencing of lnc_000368. Overall, our study identified a genome-wide lncRNA profile related to porcine intramuscular fat deposition, and the results suggest that lnc_000368 is a potential target gene that might be targeted in pig breeding in the future.

Comparison on genomic prediction using pedigree BLUP and single step GBLUP through the Hanwoo full-sib family

OBJECTIVE

When evaluating individuals with the same parent and no phenotype by pedigree best linear unbiased prediction (BLUP), it is difficult to explain carcass grade difference and select individuals because they have the same value in pedigree BLUP (PBLUP). However, single step GBLUP (ssGBLUP), which can estimate the breeding value suitable for the individual by adding genotype, is more accurate than the existing method.

METHODS

The breeding value and accuracy were estimated with pedigree BLUP and ssGBLUP using pedigree and genotype of 408 Hanwoo cattle from 16 families with the same parent among siblings produced by fertilized egg transplantation. A total of 14,225 Hanwoo cattle with pedigree, genotype and phenotype were used as the reference population. PBLUP obtained estimated breeding value (EBV) using the pedigree of the test and reference populations, and ssGBLUP obtained genomic EBV (GEBV) after constructing and H-matrix by integrating the pedigree and genotype of the test and reference populations.

RESULTS

For all traits, the accuracy of GEBV using ssGBLUP is 0.18 to 0.20 higher than the accuracy of EBV obtained with PBLUP. Comparison of EBV and GEBV of individuals without phenotype, since the value of EBV is estimated based on expected values of alleles passed down from common ancestors. It does not take Mendelian sampling into consideration, so the EBV of all individuals within the same family is estimated to be the same value. However, GEBV makes estimating true kinship coefficient based on different genotypes of individuals possible, so GEBV that corresponds to each individual is estimated rather than a uniform GEBV for each individual.

CONCLUSION

Since Hanwoo cows bred through embryo transfer have a high possibility of having the same parent, if ssGBLUP after adding genotype is used, estimating true kinship coefficient corresponding to each individual becomes possible, allowing for more accurate estimation of breeding value.

Genetic dissection of 26 meat cut, meat quality and carcass traits in four pig populations

BACKGROUND

Currently, meat cut traits are integrated in pig breeding objectives to gain extra profit. However, little is known about the heritability of meat cut proportions (MCP) and their correlations with other traits. The aims of this study were to assess the heritability and genetic correlation of MCP with carcass and meat quality traits using single nucleotide polymorphism chips and conduct a genome-wide association study (GWAS) to identify candidate genes for MCP.

RESULTS

Seventeen MCP, 12 carcass, and seven meat quality traits were measured in 2012 pigs from four populations (Landrace; Yorkshire; Landrace and Yorkshire hybrid pigs; Duroc, and Landrace and Yorkshire hybrid pigs). Estimates of the heritability for MCP ranged from 0.10 to 0.55, with most estimates being moderate to high and highly consistent across populations. In the combined population, the heritability estimates for the proportions of scapula bone, loin, back fat, leg bones, and boneless picnic shoulder were 0.44 ± 0.04, 0.36 ± 0.04, 0.44 ± 0.04, 0.38 ± 0.04, and 0.39 ± 0.04, respectively. Proportion of middle cuts was genetically significantly positively correlated with intramuscular fat content and backfat depth. Proportion of ribs was genetically positively correlated with carcass oblique length and straight length (0.35 ± 0.08 to 0.45 ± 0.07) and negatively correlated with backfat depth (- 0.26 ± 0.10 to - 0.45 ± 0.10). However, weak or nonsignificant genetic correlations were observed between most MCP, indicating their independence. Twenty-eight quantitative trait loci (QTL) for MCP were detected by GWAS, and 24 new candidate genes related to MCP were identified, which are involved with growth, height, and skeletal development. Most importantly, we found that the development of the bones in different parts of the body may be regulated by different genes, among which HMGA1 may be the strongest candidate gene affecting forelimb bone development. Moreover, as previously shown, VRTN is a causal gene affecting vertebra number, and BMP2 may be the strongest candidate gene affecting hindlimb bone development.

CONCLUSIONS

Our results indicate that breeding programs for MCP have the potential to enhance carcass composition by increasing the proportion of expensive cuts and decreasing the proportion of inexpensive cuts. Since MCP are post-slaughter traits, the QTL and candidate genes related to these traits can be used for marker-assisted and genomic selection.

Identifying Genetic Architecture of Carcass and Meat Quality Traits in a Ningxiang Indigenous Pig Population

Ningxiang pig is a breed renowned for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 min and 24 h) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30~0.80) for carcass traits and from low to high (0.11~0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the GRM4 gene emerged as a pleiotropic gene that correlated with carcass length and backfat thickness. The ADGRF1, FKBP5, and PRIM2 genes were associated with carcass length, while the NIPBL gene was linked to backfat thickness. These genes hold the potential for use in selective breeding programs targeting carcass traits in Ningxiang pigs.

Genetic architecture for skeletal muscle glycolytic potential in Chinese Erhualian pigs revealed by a genome-wide association study using 1.4M SNP array

Introduction: Muscle glycolytic potential (GP) is a key factor affecting multiple meat quality traits. It is calculated based on the contents of residual glycogen and glucose (RG), glucose-6-phosphate (G6P), and lactate (LAT) contents in muscle. However, the genetic mechanism of glycolytic metabolism in skeletal muscle of pigs remains poorly understood. With a history of more than 400 years and some unique characteristics, the Erhualian pig is called the “giant panda” (very precious) in the world’s pig species by Chinese animal husbandry.

Methods: Here, we performed a genome-wide association study (GWAS) using 1.4M single nucleotide polymorphisms (SNPs) chips for longissimus RG, G6P, LAT, and GP levels in 301 purebred Erhualian pigs.

Results: We found that the average GP value of Erhualian was unusually low (68.09 μmol/g), but the variation was large (10.4–112.7 μmol/g). The SNP-based heritability estimates for the four traits ranged from 0.16–0.32. In total, our GWAS revealed 31 quantitative trait loci (QTLs), including eight for RG, nine for G6P, nine for LAT, five for GP. Of these loci, eight were genome-wide significant (p &lt; 3.8 × 10−7), and six loci were common to two or three traits. Multiple promising candidate genes such as FTO, MINPP1, RIPOR2, SCL8A3, LIFR and SRGAP1 were identified. The genotype combinations of the five GP-associated SNPs also showed significant effect on other meat quality traits.

Discussion: These results not only provide insights into the genetic architecture of GP related traits in Erhualian, but also are useful for pig breeding programs involving this breed.

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.

Combining genome-wide association study based on low-coverage whole genome sequencing and transcriptome analysis to reveal the key candidate genes affecting meat color in pigs

Meat color is an attractive trait that influences consumers' purchase decisions at the point of sale. To decipher the genetic basis of meat color traits, we performed a genome-wide association study based on low-coverage whole-genome sequencing. In total, 669 (Pietrain × Duroc) × (Landrace × Yorkshire) pigs were genotyped using low-coverage whole-genome sequencing. Single nucleotide polymorphism (SNP) calling and genotype imputation were performed using the BaseVar + STITCH channel. Six individuals with an average depth of 12.05× whole-genome resequencing were randomly selected to assess the accuracy of imputation. Heritability evaluation and genome-wide association study for meat color traits were conducted. Functional enrichment analysis of the candidate genes from genome-wide association study and integration analysis with our previous transcriptome data were conducted. The imputation accuracy parameters, allele frequency R² , concordance rate, and dosage R² were 0.959, 0.952, and 0.933, respectively. The heritability values of a*_45 min , b*_45 min , L*_45 min , C*, and H⁰ were 0.19, 0.11, 0.06, 0.16, and 0.26, respectively. In total, 3884 significant SNPs and 15 QTL, corresponding to 382 genes, were associated with meat color traits. Functional enrichment analysis revealed that 10 genes were the potential candidates for regulating meat color. Moreover, integration analysis revealed that DMRT2, EFNA5, FGF10, and COL11A2 were the most promising candidates affecting meat color. In summary, this study provides new insights into the molecular basis of meat color traits, and provides a new theoretical basis for the molecular breeding of meat color traits in pigs.

Heritability estimates and predictive ability for pig meat quality traits using identity-by-state and identity-by-descent relationships in an F2 population

Genomic relationships can be computed with dense genome-wide genotypes through different methods, either based on identity-by-state (IBS) or identity-by-descent (IBD). The latter has been shown to increase the accuracy of both estimated relationships and predicted breeding values. However, it is not clear whether an IBD approach would achieve greater heritability ( h 2 ) and predictive ability ( r ̂ y , y ̂ ) than its IBS counterpart for data with low-depth pedigrees. Here, we compare both approaches in terms of the estimated of h 2 and r ̂ y , y ̂ , using data on meat quality and carcass traits recorded in experimental crossbred pigs, with a pedigree constrained to only three generations. Three animal models were fitted which differed on the relationship matrix: an IBS model ( G IBS ), an IBD (defined within the known pedigree) model ( G IBD ), and a pedigree model ( A 22 ). In 9 of 20 traits, the range of increase for the estimates of σ u 2 and h 2 was 1.2-2.9 times greater with G IBS and G IBD models than with A 22 . Whereas for all traits, both parameters were similar between genomic models. The r ̂ y , y ̂ of the genomic models was higher compared to A 22 . A scarce increment in r ̂ y , y ̂ was found with G IBS when compared to G IBD , most likely due to the former recovering sizeable relationships among founder F₀ animals.

Genome-Wide Association Studies for Flesh Color and Intramuscular Fat in (Duroc × Landrace × Large White) Crossbred Commercial Pigs

The intuitive impression of pork is extremely important in terms of whether consumers are enthusiastic about purchasing it. Flesh color and intramuscular fat (IMF) are indispensable indicators in meat quality assessment. In this study, we determined the flesh color and intramuscular fat at 45 min and 12 h after slaughter (45 mFC, 45 mIMF, 12 hFC, and 12 hIMF) of 1518 commercial Duroc × Landrace × Large White (DLY) pigs. We performed a single nucleotide polymorphism (SNP) genome-wide association study (GWAS) analysis with 28,066 SNPs. This experiment found that the correlation between 45 mFC and 12 hFC was 0.343. The correlation between 45 mIMF and 12 hIMF was 0.238. The heritability of the traits 45 mFC, 12 hFC, 45 mIMF, and 12 hIMF was 0.112, 0.217, 0.139, and 0.178, respectively, and we identified seven SNPs for flesh color and three SNPs for IMF. Finally, several candidate genes regulating these four traits were identified. Three candidate genes related to flesh color were provided: SNCAIP and PRR16 on SSC2, ST3GAL4 on SSC5, and GALR1 on SSC1. A total of three candidate genes related to intramuscular fat were found, including ABLIM3 on SSC2, DPH5 on SSC4, and DOCK10 on SSC15. Furthermore, GO and KEGG analysis revealed that these genes are involved in the regulation of apoptosis and are implicated in functions such as pigmentation and skeletal muscle metabolism. This study applied GWAS to analyze the scoring results of flesh color and IMF in different time periods, and it further revealed the genetic structure of flesh color and IMF traits, which may provide important genetic loci for the subsequent improvement of pig meat quality traits.

miR-381-3p Inhibits Intramuscular Fat Deposition through Targeting FABP3 by ceRNA Regulatory Network

Intramuscular fat (IMF) deposition is an important determinant of pork quality and a complex process facilitated by non-coding ceRNAs. In this study, 52 Berkshire × Anqing Sixwhite crossbred pigs were slaughtered to measure eight carcass and pork quality traits. Whole-transcriptome sequencing analysis was performed using longissimus dorsi samples of six low- and high-IMF samples; 34 ceRNA networks, based on 881, 394, 158 differentially expressed (DE) lncRNAs, miRNAs, and mRNAs, were constructed. Following weighted gene co-expression network analysis between the low and high IMF, only one ceRNA, lncRNA4789/miR-381-3p/FABP3, that showed similar DE trend in longissimus dorsi tissue was retained. Dual-luciferase reporter assays further indicated that FABP3 was a direct, functional target of miR-381-3p, where miR-381-3p overexpression inhibited the mRNA and protein expression of FABP3. In addition, overexpressed lncRNA4789 attenuated the effect of miR-381-3p on FABP3 by sponging miR-381-3p. Cell function verification experiment demonstrated that miR-381-3p suppressed IMF deposition by inhibiting preadipocyte cell differentiation and lipid droplet deposition via the suppression of FABP3 expression in the peroxisome proliferator-activated receptor signalling pathway, whereas lncRNA4789 rescued FABP3 expression by sponging miR-381-3p. Our study may aid in identifying novel molecular markers for its optimization in IMF which is of importance in breeding for improving pork quality.

The Genetic Architecture of Meat Quality Traits in a Crossbred Commercial Pig Population

Meat quality is of importance in consumer acceptance and purchasing tendency of pork. However, the genetic architecture of pork meat quality traits remains elusive. Herein, we conducted genome-wide association studies to detect single nucleotide polymorphisms (SNPs) and genes affecting meat pH and meat color (L*, lightness; a*, redness; b*, yellowness) in 1518 three-way crossbred pigs. All individuals were genotyped using the GeneSeek Porcine 50K BeadChip. In sum, 30 SNPs and 20 genes are found to be associated with eight meat quality traits. Notably, we detect one significant quantitative trait locus (QTL) on SSC15 with a 143 kb interval for meat pH (pH_12h), together with the most promising candidate TNS1. Interestingly, two newly identified SNPs located in the TTLL4 gene demonstrate the highest phenotypic variance of pH_12h in this QTL, at 2.67%. The identified SNPs are useful for the genetic improvement of meat quality traits in pigs by assigning higher weights to associated SNPs in genomic selection.

Performance, Carcass Traits, Pork Quality and Expression of Genes Related to Intramuscular Fat Metabolism of Two Diverse Genetic Lines of Pigs

We aimed to evaluate the performance, carcass and pork quality traits, as well as the mRNA expression of genes related to intramuscular fat deposition in female pigs from different genetic lines. A total of eighteen female pigs (Large White × Landrace × Duroc × Pietrain) × (Large White × Landrace) (Hybrid) averaging 88.96 ± 3.44 kg in body weight and twelve female pigs (Duroc) × (Large White × Landrace) (Duroc) averaging 85.63 ± 1.55 kg in body weight were assigned to a completely randomized design experimental trial that lasted 45 days. Pigs from both genetic lines received the same diet, which was initially adjusted for their nutritional requirements from 0 to 17 days of age and subsequently adjusted for nutritional requirements from 17 to 45 days of age. The performance of pigs did not differ among groups (p > 0.05). Duroc pigs showed a lower backfat thickness (p < 0.03) and greater intramuscular fat content (p < 0.1). A greater mRNA expression of the peroxisome proliferator-activated receptor gamma gene (PPARγ, p = 0.008) and fatty acid protein translocase/cluster differentiation (FAT/CD36, p = 0.002) was observed in the Longissimus dorsi muscle of Duroc pigs. Similarly, a greater expression of PPARγ (p = 0.009) and FAT/CD36 (p = 0.02) was observed in the Soleus muscle of Duroc pigs. Overall, we observed that despite the lack of differences in performance between the genetic groups, Duroc pigs had greater intramuscular fat content than hybrid pigs. The increased intramuscular fat content was associated with an increase in the mRNA expression of key transcriptional factors and genes encoding enzymes involved in adipogenesis and lipogenesis in glycolytic and oxidative skeletal muscle tissues.

Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine

Background

Meat quality and composition traits have become valuable in modern pork production; however, genetic improvement has been slow due to high phenotyping costs. Combining genomic information with multi-trait indirect selection based on cheaper indicator traits is an alternative for continued cost-effective genetic improvement.

Methods

Data from an ongoing breeding program were used in this study. Phenotypic and genomic information was collected on three-way crossbred and purebred Duroc animals belonging to 28 half-sib families. We applied different methods to assess the value of using purebred and crossbred information (both genomic and phenotypic) to predict expensive-to-record traits measured on crossbred individuals. Estimation of multi-trait variance components set the basis for comparing the different scenarios, together with a fourfold cross-validation approach to validate the phenotyping schemes under four genotyping strategies.

Results

The benefit of including genomic information for multi-trait prediction depended on the breeding goal trait, the indicator traits included, and the source of genomic information. While some traits benefitted significantly from genotyping crossbreds (e.g., loin intramuscular fat content, backfat depth, and belly weight), multi-trait prediction was advantageous for some traits even in the absence of genomic information (e.g., loin muscle weight, subjective color, and subjective firmness).

Conclusions

Our results show the value of using different sources of phenotypic and genomic information. For most of the traits studied, including crossbred genomic information was more beneficial than performing multi-trait prediction. Thus, we recommend including crossbred individuals in the reference population when these are phenotyped for the breeding objective.

Genome-Wide Association Study and FST Analysis Reveal Four Quantitative Trait Loci and Six Candidate Genes for Meat Color in Pigs

Meat color is the primary criterion by which consumers evaluate meat quality. However, there are a few candidate genes and molecular markers of meat color that were reported for pig molecular breeding. The purpose of the present study is to identify the candidate genes affecting meat color and provide the theoretical basis for meat color molecular breeding. A total of 306 Suhuai pigs were slaughtered, and meat color was evaluated at 45 min and 24 h after slaughter by CIELAB color space. All individuals were genotyped using GeneSeek GGP-Porcine 80K SNP BeadChip. The genomic estimated breeding values (GEBVs), heritability, and genetic correlation of meat color were calculated by DMU software. The genome-wide association studies (GWASs) and the fixation index (F_ST) tests were performed to identify SNPs related to meat color, and the candidate genes within 1 Mb upstream and downstream of significant SNPs were screened by functional enrichment analysis. The heritability of L* 45 min, L* 24 h, a* 45 min, a* 24 h, b* 45 min, and b* 24 h was 0.20, 0.16, 0.30, 0.13, 0.29, and 0.22, respectively. The genetic correlation between a* (a* 45 min and a* 24 h) and L* (L* 45 min and L* 24 h) is strong, whereas the genetic correlation between b* 45 min and b* 24 h is weak. Forty-nine significant SNPs associated with meat color were identified through GWAS and F_ST tests. Among these SNPs, 34 SNPs were associated with L* 45 min within a 5-Mb region on Sus scrofa chromosome 11 (SSC11); 22 SNPs were associated with a* 45 min within a 14.72-Mb region on SSC16; six SNPs were associated with b* 45 min within a 4.22-Mb region on SSC13; 11 SNPs were associated with b* 24 h within a 2.12-Mb region on SSC3. These regions did not overlap with meat color–associated QTLs reported previously. Moreover, six candidate genes (HOMER1, PIK3CG, PIK3CA, VCAN, FABP3, and FKBP1B), functionally related to muscle development, phosphatidylinositol phosphorylation, and lipid binding, were detected around these significant SNPs. Taken together, our results provide a set of potential molecular markers for the genetic improvement of meat color in pigs.

Phenotypic and genetic correlations of pork myoglobin content with meat colour and other traits in an eight breed-crossed heterogeneous population

Meat colour is one of the most important meat quality traits affecting consumption desire. Genetic improvement for meat colour traits is not so easy because pigs can be phenotyped only after slaughter. Besides the parameters from the optical instrument, other indexes that reflect the material basis of meat colour should be measured accurately and used in the genomic analysis. Myoglobin (Mb) is the main chemical component determining meat colour. However, to what extent the Mb content contributes to meat colour, and whether it can be used as a trait for pig breeding to improve meat colour, and the correlations of Mb content with complex porcine traits are largely unknown. To address these questions, we measured the muscle Mb content in 624 pigs from the 7th generation of a specially designed eight breed-crossed pig heterogeneous population, evaluated its phenotypic and genetic correlations with longissimus thoracis colour score at 24 h after slaughter. More than that, we also systematically phenotyped more than 100 traits on these animals to evaluate the potential correlations between muscle Mb content and economically important traits. Our results showed that the average muscle Mb content in the 624 pigs was 1.00 mg/g, ranging from 0.51 to 2.17 mg/g. We found that higher Mb content usually correlated with favourable meat colour, higher marbling score, less moisture content, and less drip loss. Genetic correlation analysis between muscle Mb content and 101 traits measured in this study shows that Mb content is also significantly correlated with 31 traits, including marbling, shear force, firmness, and juiciness. To our knowledge, this is one of the largest studies about the correlations of muscle Mb content with as many as 100 various traits in a large-scale genetically diversified population. Our results showed that the Mb content could be a selection parameter for the genetic improvement of meat colour. The selection for higher Mb content will also benefit marbling, shear force, firmness, and overall liking but might not affect the growth, carcass, and fat deposition traits.

Genetic parameters and purebred-crossbred genetic correlations for growth, meat quality, and carcass traits in pigs

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.

Effects of sire line, birth weight and sex on growth performance and carcass traits of crossbred pigs under standardized environmental conditions

A variety of available terminal sire lines makes the choice of terminal sire line complex for the pig producer. Higher birth weights are important for subsequent growth performance and selection for this trait is also necessary in sire lines. The aim was to investigate the effect of sire line, birth weight and gender on growth performance, carcass traits and meat quality. In total 3844 crossbred pigs from Camborough Pig Improvement Company (PIC) dams matched with either a Synthetic (A) or Piétrain (B) sire line were used. Pigs from line A grew faster (p<0.01), showed higher feed intake (p<0.01) and reached a higher final body weight (p≤0.01), but they had a similar efficiency (p=0.179). Leaner carcasses and heavier primal cuts (p<0.001) were observed in pigs from line B. Carcasses from pigs sired by line A had higher meat quality (p<0.001). Males had a higher growth rate (p≤0.05) but had a poorer feed efficiency (p<0.01). Heavier birth weight pigs and females had leaner, higher value carcasses with heavier primal cuts (p<0.001) compared to middle and low birth weight females or males. Sire line by sex interactions was significant for growth (p≤0.05) and carcass traits (p<0.001). Interaction between sire line and birth weight classes were only detected for loin depth (p<0.01). Line A is preferable if the numbers of fatting pigs per fattening place and year should be improved, and line B is an option to increase leanness and carcass primal cuts.

LncRNA IMFlnc1 promotes porcine intramuscular adipocyte adipogenesis by sponging miR-199a-5p to up-regulate CAV-1

Background

Local Chinese local pig breeds have thinner muscle fiber and higher intramuscular-fat (IMF) content. But its regulation mechanism has not been discussed in-depth. Studies indicated that long non coding RNAs (lncRNAs) play important role in muscle and fat development.

Results

The lncRNAs expressional differences in the longissimus dorsi (LD) muscle were identified between Huainan pigs (local Chinese pigs, fat-type, HN) and Large White pigs (lean-type, LW) at 38, 58, and 78 days post conception (dpc). In total, 2131 novel lncRNAs were identified in 18 samples, and 291, 305, and 683 differentially expressed lncRNAs (DELs) were found between these two breeds at three stages, respectively. The mRNAs that co-expressed with these DELs were used for GO and KEGG analysis, and the results showed that muscle development and energy metabolism were more active at 58 dpc in HN, but at 78 dpc in LW pigs. Muscle cell differentiation and myofibril assembly might associated with earlier myogenesis and primary-muscle-fiber assembly in HN, and cell proliferation, insulin, and the MAPK pathway might be contribute to longer proliferation and elevated energy metabolism in LW pigs at 78 dpc. The PI3K/Akt and cAMP pathways were associated with higher IMF deposition in HN. Intramuscular fat deposition-associated long noncoding RNA 1 (IMFlnc1) was selected for functional verification, and results indicated that it regulated the expressional level of caveolin-1 (CAV-1) by acting as competing endogenous RNA (ceRNA) to sponge miR-199a-5p.

Conclusions

Our data contributed to understanding the role of lncRNAs in porcine-muscle development and IMF deposition, and provided valuable information for improving pig-meat quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-020-00324-8.

Microbiability of meat quality and carcass composition traits in swine

The impact of gut microbiome composition was investigated at different stages of production (weaning, Mid‐test and Off‐test) on meat quality and carcass composition traits of 1,123 three‐way crossbred pigs. Data were analysed using linear mixed models which included the fixed effects of dam line, contemporary group and gender as well as the random effects of pen, animal and microbiome information at different stages. The contribution of the microbiome to all traits was prominent although it varied over time, increasing from weaning to Off‐test for most traits. Microbiability estimates of carcass composition traits were greater than that of meat quality traits. Among all of the traits analysed, belly weight (BEL) had a higher microbiability estimate (0.29 ± 0.04). Adding microbiome information did not affect the estimates of genomic heritability of meat quality traits but affected the estimates of carcass composition traits. Fat depth had a greater decrease (10%) in genomic heritability at Off‐test. High microbial correlations were found among different traits, particularly with traits related to fat deposition with a decrease in the genomic correlation up to 20% for loin weight and BEL. This suggested that genomic correlation was partially contributed by genetic similarity of microbiome composition. The results indicated that better understanding of microbial composition could aid the improvement of complex traits, particularly the carcass composition traits in swine by inclusion of microbiome information in the genetic evaluation process.

Modeling host-microbiome interactions for the prediction of meat quality and carcass composition traits in swine

BACKGROUND

The objectives of this study were to evaluate genomic and microbial predictions of phenotypes for meat quality and carcass traits in swine, and to evaluate the contribution of host-microbiome interactions to the prediction. Data were collected from Duroc-sired three-way crossbred individuals (n = 1123) that were genotyped with a 60 k SNP chip. Phenotypic information and fecal 16S rRNA microbial sequences at three stages of growth (Wean, Mid-test, and Off-test) were available for all these individuals. We used fourfold cross-validation with animals grouped based on sire relatedness. Five models with three sets of predictors (full, informatively reduced, and randomly reduced) were evaluated. 'Full' included information from all genetic markers and all operational taxonomic units (OTU), while 'informatively reduced' and 'randomly reduced' represented a reduced number of markers and OTU based on significance preselection and random sampling, respectively. The baseline model included the fixed effects of dam line, sex and contemporary group and the random effect of pen. The other four models were constructed by including only genomic information, only microbiome information, both genomic and microbiome information, and microbiome and genomic information and their interaction.

RESULTS

Inclusion of microbiome information increased predictive ability of phenotype for most traits, in particular when microbiome information collected at a later growth stage was used. Inclusion of microbiome information resulted in higher accuracies and lower mean squared errors for fat-related traits (fat depth, belly weight, intramuscular fat and subjective marbling), objective color measures (Minolta a*, Minolta b* and Minolta L*) and carcass daily gain. Informative selection of markers increased predictive ability but decreasing the number of informatively reduced OTU did not improve model performance. The proportion of variation explained by the host-genome-by-microbiome interaction was highest for fat depth (~ 20% at Mid-test and Off-test) and shearing force (~ 20% consistently at Wean, Mid-test and Off-test), although the inclusion of the interaction term did not increase the accuracy of predictions significantly.

CONCLUSIONS

This study provides novel insight on the use of microbiome information for the phenotypic prediction of meat quality and carcass traits in swine. Inclusion of microbiome information in the model improved predictive ability of phenotypes for fat deposition and color traits whereas including a genome-by-microbiome term did not improve prediction accuracy significantly.

Estimation of Genetic Parameters for Pork Quality, Novel Carcass, Primal-Cut and Growth Traits in Duroc Pigs

Simple Summary

There is a growing interest in worldwide swine breeding programs to genetically select for pork quality and primal cuts in addition to the traditional growth and carcass leanness traits. Accurate population genetic parameters are needed to estimate correlated responses to selection and incorporate novel traits in the selection objective. Therefore, we estimated heritabilities and genetic correlations for 39 pork quality, growth and carcass traits in Duroc pigs. In general, moderate and favorable genetic correlations were observed between pork quality (e.g., loin color and marbling scores) and carcass traits. Additionally, moderate to low correlations were found among pork quality, growth and carcass traits. Our findings suggest that pig breeders can successfully incorporate pork quality and novel carcass traits in the selection objectives without undesirable impacts upon growth rate and carcass leanness.

Abstract

More recently, swine breeding programs have aimed to include pork quality and novel carcass (e.g., specific primal cuts such as the Boston butt or belly that are not commonly used in selection indexes) and belly traits together with growth, feed efficiency and carcass leanness in the selection indexes of terminal-sire lines, in order to efficiently produce pork with improved quality at a low cost to consumers. In this context, the success of genetic selection for such traits relies on accurate estimates of heritabilities and genetic correlations between traits. The objective of this study was to estimate genetic parameters for 39 traits in Duroc pigs (three growth, eight conventional carcass (commonly measured production traits; e.g., backfat depth), 10 pork quality and 18 novel carcass traits). Phenotypic measurements were collected on 2583 purebred Duroc gilts, and the variance components were estimated using both univariate and bivariate models and REML procedures. Moderate to high heritability estimates were found for most traits, while genetic correlations tended to be low to moderate overall. Moderate to high genetic correlations were found between growth, primal-cuts and novel carcass traits, while low to moderate correlations were found between pork quality and growth and carcass traits. Some genetic antagonisms were observed, but they are of low to moderate magnitude. This indicates that genetic progress can be achieved for all traits when using an adequate selection index.

The interaction between microbiome and pig efficiency: A review

The existence of genetic control over the abundance of particular taxa and the link of these to energy balance and growth has been documented in model organisms and humans as well as several livestock species. Preliminary evidence of the same mechanisms is currently under investigation in pigs. Future research should expand these results and elicit the extent of genetic control of the gut microbiome population in swine and its relationship with growth efficiency. The quest for a more efficient pig at the interface between the host and its metagenome rests on the central hypothesis that the gut microbiome is an essential component of the variability of growth in all living organisms. Swine do not escape this general rule, and the identification of the significance of the interaction between host and its gut microbiota in the growth process could be a game-changer in the achievement of sustainable and efficient lean meat production. Standard sampling protocols, sequencing techniques, bioinformatic pipelines and methods of analysis will be paramount for the portability of results across experiments and populations. Likewise, characterizing and accounting for temporal and spatial variability will be a necessary step if microbiome is to be utilized routinely as an aid to selection.