A genome-wide association study of production traits in a commercial population of Large White pigs: evidence of haplotypes affecting meat quality

Genetic diversity analysis of two commercial breeds of pigs using genomic and pedigree data

Background

Genetic improvement in livestock populations can be achieved without significantly affecting genetic diversity if mating systems and selection decisions take genetic relationships among individuals into consideration. The objective of this study was to examine the genetic diversity of two commercial breeds of pigs. Genotypes from 1168 Landrace (LA) and 1094 Large White (LW) animals from a commercial breeding program in Brazil were obtained using the Illumina PorcineSNP60 Beadchip. Inbreeding estimates based on pedigree (F_x) and genomic information using runs of homozygosity (F_ROH) and the single nucleotide polymorphisms (SNP) by SNP inbreeding coefficient (F_SNP) were obtained. Linkage disequilibrium (LD), correlation of linkage phase (r) and effective population size (N_e) were also estimated.

Results

Estimates of inbreeding obtained with pedigree information were lower than those obtained with genomic data in both breeds. We observed that the extent of LD was slightly larger at shorter distances between SNPs in the LW population than in the LA population, which indicates that the LW population was derived from a smaller N_e. Estimates of N_e based on genomic data were equal to 53 and 40 for the current populations of LA and LW, respectively. The correlation of linkage phase between the two breeds was equal to 0.77 at distances up to 50 kb, which suggests that genome-wide association and selection should be performed within breed. Although selection intensities have been stronger in the LA breed than in the LW breed, levels of genomic and pedigree inbreeding were lower for the LA than for the LW breed.

Conclusions

The use of genomic data to evaluate population diversity in livestock animals can provide new and more precise insights about the effects of intense selection for production traits. Resulting information and knowledge can be used to effectively increase response to selection by appropriately managing the rate of inbreeding, minimizing negative effects of inbreeding depression and therefore maintaining desirable levels of genetic diversity.

Genome Wide Association Studies (GWAS) Identify QTL on SSC2 and SSC17 Affecting Loin Peak Shear Force in Crossbred Commercial Pigs

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.

A genomewide association study of feed efficiency and feeding behaviors at two fattening stages in a White Duroc × Erhualian F population

Feeding efficiency is a multifactorial and economically important trait in pigs. Genetic improvement of feeding efficiency will greatly benefit the pig industry. In the past decades, the hog market weight has increased worldwide. However, whether the genetic architecture of feeding efficiency is same or not at early and late fattening periods is unclear. To map genomic regions for feed efficiency and feeding behavior traits at early (n ≥ 384) and late (n ≥ 334) growth stages in pigs, we performed genomewide association studies for feed to gain ratio (FCR), residual feed intake (RFI), daily feed intake, daily visit times, daily feeding time (DFT), feed intake per second (FIPS), and feed intake per visit during 3 periods (2 stages and overall) in a White Duroc × Erhualian F2 intercross population. Six chromosomal regions showed significant association with these traits, of which 4 loci were reported for the first time. Our results confirmed the QTL of FCR around 34 Mb on SSC7 and RFI around 134 Mb on SSC12. Of note, 2 regions were associated with more than 1 trait. One was around 36 Mb on SSC7, and there were 47 and 67 SNP associated with FCR from 120 to 210 and from 120 to 240 d, respectively. The top SNP is located in a 2.88-Mb linkage disequilibrium (LD) block that harbors 44 genes. We propose the high mobility group AT-hook 1 gene as a plausible candidate gene in this region. The other was evidenced around 53 Mb on SSC12, which had multiple association signals for DFT and FIPS. The top SNP is located in a 211-kb LD block that harbors only 1 annotated gene, WSCD1, which encodes a protein with sulfotransferase activity and involves the glucose metabolism and, therefore, appears to be a plausible candidate gene. Except the region on SSC12 associated with DFT at both stages, the rest of the regions associated with the traits at only 1 stage, so the genetic architectures of the 2 stages are not same.

Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l’Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.

Genome-wide study on intramuscular fat in Italian Large White pig breed using the PorcineSNP60 BeadChip

Genome-wide association study results are presented for intramuscular fat in Italian Large White pig breed. A total of 886 individuals were genotyped with PorcineSNP60 BeadChip. After quality control performed with plink software and in R environment, 49 208 markers remained for the association analysis. The genome-wide association studies was conducted using linear mixed model implemented in GenABEL. We detected seven new SNPs of genes till now not found associated to intramuscular fat (IMF). Three markers map in a wide intergenic region rich of QTL linked to fat traits, one map 388 kb upstream the gene SDK1, one map inside PPP3CA gene, one inside SCPEP1 gene and the last is not mapped in the porcine genome yet. Associations here presented indicate a moderate effect of these genes on IMF. In particular, PPP3CA, that is involved in the oxidative metabolism of skeletal muscle, could be considerated as an interesting candidate gene for IMF content in pigs. However, further studies are needed to clarify the role of these genes on the physiological processes involved in IMF regulation. These results may be useful to control this trait that is important in terms of nutritional, technological and organoleptic characteristics of fresh meat and processed products.

Efficacy of the porcine species in biomedical research

Since domestication, pigs have been used extensively in agriculture and kept as companion animals. More recently they have been used in biomedical research, given they share many physiological and anatomical similarities with humans. Recent technological advances in assisted reproduction, somatic cell cloning, stem cell culture, genome editing, and transgenesis now enable the creation of unique porcine models of human diseases. Here, we highlight the potential applications and advantages of using pigs, particularly minipigs, as indispensable large animal models in fundamental and clinical research, including the development of therapeutics for inherited and chronic disorders, and cancers.

Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in Swine

Pork quality is important both to the meat processing industry and consumers' purchasing attitude. Copy number variation (CNV) is a burgeoning kind of variants that may influence meat quality. In this study, a genome-wide association study (GWAS) was performed between CNVs and meat quality traits in swine. After false discovery rate (FDR) correction, a total of 8 CNVs on 6 chromosomes were identified to be significantly associated with at least one meat quality trait. All of the 8 CNVs were verified by next generation sequencing and six of them were verified by qPCR. Only the haplotype block containing CNV12 is adjacent to significant SNPs associated with meat quality, suggesting the effects of those CNVs were not likely captured by tag SNPs. The DNA dosage and EST expression of CNV12, which overlap with an obesity related gene Netrin-1 (Ntn1), were consistent with Ntn1 RNA expression, suggesting the CNV12 might be involved in the expression regulation of Ntn1 and finally influence meat quality. We concluded that CNVs may contribute to the genetic variations of meat quality beyond SNPs, and several candidate CNVs were worth further exploration.

Recent advances in omic technologies for meat quality management

The knowledge of the molecular organization of living organisms evolved considerably during the last years. The methodologies associated also progressed with the development of the high-throughput sequencing (SNP array, RNAseq, etc.) and of genomic tools allowing the simultaneous analysis of hundreds or thousands of genes, proteins or metabolites. In farm animals, some proteins, mRNAs or metabolites whose abundance has been associated with meat quality traits have been detected in pig, cattle, chicken. They constitute biomarkers for the assessment and prediction of qualities of interest in each species, with potential biomarkers across species. The ongoing development of rapid methods will allow their use for decision-making and management tools in slaughterhouses, to better allocate carcasses or cuts to the appropriate markets. Besides, their application on living animals will help to improve genetic selection and to adapt a breeding system to fulfill expected quality level. The ultimate goal is to propose effective molecular tools for the management of product quality in meat production chains.

Genome-wide association studies (GWAS) identify a QTL close to PRKAG3 affecting meat pH and colour in crossbred commercial pigs

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

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0192-1) contains supplementary material, which is available to authorized users.

Genome-wide association analysis reveals genetic loci and candidate genes for meat quality traits in Chinese Laiwu pigs

Meat quality traits have economically significant impacts on the pig industry, and can be improved using molecular approaches in pig breeding. Since 1994 when the first genome-wide scan for quantitative trait loci (QTLs) in pig was reported, over the past two decades, numerous QTLs have been identified for meat quality traits by family based linkage analyses. However, little is known about the genetic variants for meat quality traits in Chinese purebred or outbred populations. To unveil it, we performed a genome-wide association study for 10 meat quality traits in Chinese purebred Laiwu pigs. In total, 75 significant SNPs (P < 1.01 × 10(-6)) and 33 suggestive SNPs (P < 2.03 × 10(-5)) were identified. On SSC12, a region between 56.22 and 61.49 Mb harbored a cluster of SNPs that were associated with meat color parameters (L*, lightness; a*, redness; b*, yellowness) and moisture content of longissimus muscle (LM) and semimembranosus muscle at the genome-wide significance level. A region on SSC4 also has pleiotropic effects on moisture content and drip loss of LM. In addition, this study revealed at least five novel QTLs and several candidate genes including 4-linked MYH genes (MYH1, MYH2, MYH3, and MYH13), MAL2, LPAR1, and PRKAG3 at four significant loci. Except for the SSC12 QTL, other QTLs are likely tissue-specific. These results provide new insights into the genetic basis of meat quality traits in Chinese Laiwu pigs and some significant SNPs reported here could be incorporated into the selection programs involving this breed.

A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species

Background

With dense genotyping, many choices exist for methods to detect quantitative trait loci (QTL) in livestock populations. However, no across-species study has been conducted on the performance of different methods using real data. We compared three methods that correct for relatedness either implicitly or explicitly: linkage and linkage disequilibrium haplotype-based analysis (LDLA), efficient mixed-model association (EMMA) analysis, and Bayesian whole-genome regression (BayesC). We analyzed one chromosome in each of five datasets (dairy cattle, beef cattle, sheep, horses, and pigs) using real genotypes based on dense single nucleotide polymorphisms and phenotypes. The P values corrected for multiple testing or Bayes factors greater than 150 were considered to be significant. To complete the real data study, we also simulated quantitative trait loci (QTL) for the same datasets based on the real genotypes. Several scenarios were chosen, with different QTL effects and linkage disequilibrium patterns. A pseudo-null statistical distribution was chosen to make the significance thresholds comparable across methods.

Results

For the real data, the three methods generally agreed within 1 or 2 cM for the locations of QTL regions and disagreed when no signals were significant (e.g. in pigs). For certain datasets, LDLA had more significant signals than EMMA or BayesC, but they were concentrated around the same peaks. Therefore, the three methods detected approximately the same number of QTL regions. For the simulated data, LDLA was slightly less powerful and accurate than either EMMA or BayesC but this depended strongly on how thresholds were set in the simulations.

Conclusions

All three methods performed similarly for real and simulated data. No method was clearly superior across all datasets or for any particular dataset. For computational efficiency and ease of interpretation, EMMA is recommended, but using more than one method is suggested.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0087-7) contains supplementary material, which is available to authorized users.

Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake

Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher's exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs.