Sequence variants associated with resilient responses in growing pigs.

The current work aimed to identify genomic regions and candidate genes associated with resilience in pigs. In previous work, we proposed the body weight deviation from the expected growth curve (ΔBW) and the increase of the positive acute-phase protein haptoglobin (ΔHP) after a vaccine challenge as resilience indicators which may be improved through selective breeding in pigs. Individuals with steady growth rate and minor activation of haptoglobin (high ΔBW and low ΔHP values) were considered resilient. In contrast, pigs with perturbed growth rate and high activation of haptoglobin (low ΔBW and high ΔHP values) were considered susceptible. Both ∆BW and ∆HP were simultaneously considered to select the most resilient (N = 40) and susceptible (N = 40) pigs. A genome-wide association study was carried out for the pigs' response classification to the challenge test using whole-genome sequence data (7,760,720 variants). Eleven associated genomic regions were identified, harbouring relevant candidate genes related to the immune response (such as pro- and anti-inflammatory responses) and growth pathways. These associated genomic regions harboured 41 potential functional mutations (frameshift, splice donor, splice acceptor, start loss and stop loss/gain) in candidate genes. Overall, this study advances our knowledge about the genetic determinism of resilience, highlighting its polygenic nature and strong relationship with immunity and growth.

Impact of the leptin receptor gene on pig performance and quality traits.

The recessive T allele of the missense polymorphism rs709596309 C > T of the leptin receptor gene is associated with intramuscular fat. However, its overall impact on pork production is still partial. In this work, we investigated the all-round effects of the TT genotype on lean growth efficiency and carcass, meat and fat quality using data from an experiment that compared the performance of 48 TT and 48 C- (24 CT and 24 CC) Duroc barrows. The TT pigs were less efficient for lean growth than the C- pigs. Although heavier, their carcasses had less lean content, were shorter and had lighter loins. Apart from increasing marbling and saturated fatty acid content, changes caused by the TT genotype in meat and fat quality are likely not enough to be perceived by consumers. The effect on visual marbling score exceeded that on intramuscular fat content, which suggests a direct influence of the T allele on the pattern of fat distribution in muscle. With current low-protein diets, the T allele is expected to be cost-effective only in niche markets where a very high level of marbling is critical.

A novel QTL region for pH and meat color in Duroc pigs.

One of the most important processes that occur during the transformation of muscle to meat is the pH decline as a consequence of the post-mortem metabolism of muscle tissue. Abnormal pH declines lead to pork defects such as pale, soft, and exudative meat. There is genetic variance for ultimate pH and the role of some genes on this phenotype is well established. After conducting a genome-wide association study on ultimate pH using 526 purebred Duroc pigs, we identified associated regions on Sus scrofa chromosomes (SSC) 3, 8, and 15. Functional candidate genes in these regions included PRKAG3 and PHKG1. The SSC8 region, at 71.6 Mb, was novel and, although no candidate causative gene could be identified, it may have regulatory effects. Subsequent analysis on 828 pigs from the same population confirmed the impact of the three associated regions on pH and meat color. We detected no interaction between the three regions. Further investigations are necessary to unravel the functional significance of the novel genomic region at SSC8. These variants could be used as markers in marker-assisted selection for improving meat quality.

The leptin receptor gene affects piglet behavior and growth.

Piglets with low birth weight present low vitality after farrowing, often leading to impaired weight gain during lactation. A recessive missense variant (C > T) for increased appetite and fatness in the porcine leptin receptor gene (rs709596309) causes a negative maternal effect on the weight of piglets at weaning. However, it is not known whether this variant already exerts an effect on the birth weight and vitality of newborn piglets and on their growing capacity during lactation. An experiment was conducted using 668 purebred Duroc piglets (131 CC, 311 CT, and 226 TT) from 74 multiparous sows (9 CC, 43 CT, and 22 TT) and 14 boars (1 CC, 10 CT, and 3 TT). All piglets were individually weighed at birth and tested for vitality, which was assessed on a scale from 1 (low vitality) to 3 (high vitality) based on behavioral observations, including the status of the piglet immediately before the test. Only non-adopted piglets were considered for piglet performance at weaning. Inferences on the effect of the genotype on birth and weaning traits were done on a Bayesian setting based on 2-trait bivariate models including the effects of the piglet and the litter, as well as the genotype of the sow and the piglet, the sex of the piglet, and the parity number. Vitality and the status of the piglet before the test were analyzed using a liability threshold (probit) model. As compared to other genotypes, TT newborn piglets were 28 g heavier, were more vital (the probability of being scored as highly vital was 6.5% higher) and were more often found suckling before the test (the probability of being suckling at test was 6.5% higher). As a result, they grew more during lactation (153 g) and were heavier at weaning (169 g) than littermates of the two other genotypes, thus partly compensating for the limited maternal capacity of TT sows. Our findings provide evidence that appetite-influencing genes, such as the leptin receptor gene, have developmental implications from very early life stages.

Leptin is a hormone that regulates food intake and energy balance. There is a recessive missense variant in the porcine leptin receptor gene that increases appetite and fatness and causes a negative maternal impact on the weight of piglets at weaning. An experiment was conducted to elucidate whether the genotype of the piglet for this variant has a direct effect on the birth weight and the vitality of newborn piglets and on their growing capacity during lactation. We have determined that piglets that are homozygous for the recessive allele of this variant are heavier and more vital at birth than littermates of the other 2 genotypes. As a result, they grow faster during lactation and are heavier at weaning, thus partly compensating for the limited maternal capacity of the recessive homozygous sows.

Using residual regressions to quantify and map signal leakage in genomic prediction.

BACKGROUND: Most genomic prediction applications in animal breeding use genotypes with tens of thousands of single nucleotide polymorphisms (SNPs). However, modern sequencing technologies and imputation algorithms can generate ultra-high-density genotypes (including millions of SNPs) at an affordable cost. Empirical studies have not produced clear evidence that using ultra-high-density genotypes can significantly improve prediction accuracy. However, (whole-genome) prediction accuracy is not very informative about the ability of a model to capture the genetic signals from specific genomic regions. To address this problem, we propose a simple methodology that detects chromosome regions for which a specific model (e.g., single-step genomic best linear unbiased prediction (ssGBLUP)) may fail to fully capture the genetic signal present in such segments-a phenomenon that we refer to as signal leakage. We propose to detect regions with evidence of signal leakage by testing the association of residuals from a pedigree or a genomic model with SNP genotypes. We discuss how this approach can be used to map regions with signals that are poorly captured by a model and to identify strategies to fix those problems (e.g., using a different prior or increasing marker density). Finally, we explored the proposed approach to scan for signal leakage of different models (pedigree-based, ssGBLUP, and various Bayesian models) applied to growth-related phenotypes (average daily gain and backfat thickness) in pigs. RESULTS: We report widespread evidence of signal leakage for pedigree-based models. Including a percentage of animals with SNP data in ssGBLUP reduced the extent of signal leakage. However, local peaks of missed signals remained in some regions, even when all animals were genotyped. Using variable selection priors solves leakage points that are caused by excessive shrinkage of marker effects. Nevertheless, these models still miss signals in some regions due to low linkage disequilibrium between the SNPs on the array used and causal variants. Thus, we discuss how such problems could be addressed by adding sequence SNPs from those regions to the prediction model. CONCLUSIONS: Residual single-marker regression analysis is a simple approach that can be used to detect regional genomic signals that are poorly captured by a model and to indicate ways to fix such problems.

Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs.

BACKGROUND: Whole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip data. The objective of this study was to investigate the impact of using preselected variants from WGS for single-step genomic predictions in maternal and terminal pig lines with up to 1.8k sequenced and 104k sequence imputed animals per line. METHODS: Two maternal and four terminal lines were investigated for eight and seven traits, respectively. The number of sequenced animals ranged from 1365 to 1491 for the maternal lines and 381 to 1865 for the terminal lines. Imputation to sequence occurred within each line for 66k to 76k animals for the maternal lines and 29k to 104k animals for the terminal lines. Two preselected SNP sets were generated based on a genome-wide association study (GWAS). Top40k included the SNPs with the lowest p-value in each of the 40k genomic windows, and ChipPlusSign included significant variants integrated into the porcine SNP chip used for routine genotyping. We compared the performance of single-step genomic predictions between using preselected SNP sets assuming equal or different variances and the standard porcine SNP chip. RESULTS: In the maternal lines, ChipPlusSign and Top40k showed an average increase in accuracy of 0.6 and 4.9%, respectively, compared to the regular porcine SNP chip. The greatest increase was obtained with Top40k, particularly for fertility traits, for which the initial accuracy based on the standard SNP chip was low. However, in the terminal lines, Top40k resulted in an average loss of accuracy of 1%. ChipPlusSign provided a positive, although small, gain in accuracy (0.9%). Assigning different variances for the SNPs slightly improved accuracies when using variances obtained from BayesR. However, increases were inconsistent across the lines and traits. CONCLUSIONS: The benefit of using sequence data depends on the line, the size of the genotyped population, and how the WGS variants are preselected. When WGS data are available on hundreds of thousands of animals, using sequence data presents an advantage but this remains limited in pigs.

A genome-wide association study for loin depth and muscle pH in pigs from intensely selected purebred lines.

BACKGROUND: Genome-wide association studies (GWAS) aim at identifying genomic regions involved in phenotype expression, but identifying causative variants is difficult. Pig Combined Annotation Dependent Depletion (pCADD) scores provide a measure of the predicted consequences of genetic variants. Incorporating pCADD into the GWAS pipeline may help their identification. Our objective was to identify genomic regions associated with loin depth and muscle pH, and identify regions of interest for fine-mapping and further experimental work. Genotypes for ~ 40,000 single nucleotide morphisms (SNPs) were used to perform GWAS for these two traits, using de-regressed breeding values (dEBV) for 329,964 pigs from four commercial lines. Imputed sequence data was used to identify SNPs in strong ([Formula: see text] 0.80) linkage disequilibrium with lead GWAS SNPs with the highest pCADD scores. RESULTS: Fifteen distinct regions were associated with loin depth and one with loin pH at genome-wide significance. Regions on chromosomes 1, 2, 5, 7, and 16, explained between 0.06 and 3.55% of the additive genetic variance and were strongly associated with loin depth. Only a small part of the additive genetic variance in muscle pH was attributed to SNPs. The results of our pCADD analysis suggests that high-scoring pCADD variants are enriched for missense mutations. Two close but distinct regions on SSC1 were associated with loin depth, and pCADD identified the previously identified missense variant within the MC4R gene for one of the lines. For loin pH, pCADD identified a synonymous variant in the RNF25 gene (SSC15) as the most likely candidate for the muscle pH association. The missense mutation in the PRKAG3 gene known to affect glycogen content was not prioritised by pCADD for loin pH. CONCLUSIONS: For loin depth, we identified several strong candidate regions for further statistical fine-mapping that are supported in the literature, and two novel regions. For loin muscle pH, we identified one previously identified associated region. We found mixed evidence for the utility of pCADD as an extension of heuristic fine-mapping. The next step is to perform more sophisticated fine-mapping and expression quantitative trait loci (eQTL) analysis, and then interrogate candidate variants in vitro by perturbation-CRISPR assays.

Multi-line ssGBLUP evaluation using preselected markers from whole-genome sequence data in pigs.

Genomic evaluations in pigs could benefit from using multi-line data along with whole-genome sequencing (WGS) if the data are large enough to represent the variability across populations. The objective of this study was to investigate strategies to combine large-scale data from different terminal pig lines in a multi-line genomic evaluation (MLE) through single-step GBLUP (ssGBLUP) models while including variants preselected from whole-genome sequence (WGS) data. We investigated single-line and multi-line evaluations for five traits recorded in three terminal lines. The number of sequenced animals in each line ranged from 731 to 1,865, with 60k to 104k imputed to WGS. Unknown parent groups (UPG) and metafounders (MF) were explored to account for genetic differences among the lines and improve the compatibility between pedigree and genomic relationships in the MLE. Sequence variants were preselected based on multi-line genome-wide association studies (GWAS) or linkage disequilibrium (LD) pruning. These preselected variant sets were used for ssGBLUP predictions without and with weights from BayesR, and the performances were compared to that of a commercial porcine single-nucleotide polymorphisms (SNP) chip. Using UPG and MF in MLE showed small to no gain in prediction accuracy (up to 0.02), depending on the lines and traits, compared to the single-line genomic evaluation (SLE). Likewise, adding selected variants from the GWAS to the commercial SNP chip resulted in a maximum increase of 0.02 in the prediction accuracy, only for average daily feed intake in the most numerous lines. In addition, no benefits were observed when using preselected sequence variants in multi-line genomic predictions. Weights from BayesR did not help improve the performance of ssGBLUP. This study revealed limited benefits of using preselected whole-genome sequence variants for multi-line genomic predictions, even when tens of thousands of animals had imputed sequence data. Correctly accounting for line differences with UPG or MF in MLE is essential to obtain predictions similar to SLE; however, the only observed benefit of an MLE is to have comparable predictions across lines. Further investigation into the amount of data and novel methods to preselect whole-genome causative variants in combined populations would be of significant interest.

Identification of breed-specific genomic variants in Colombian Creole pig breeds by whole-genome sequencing.

Dissecting genetic variation of local breeds is important for the success of conservation. In this research, we investigated the genomic variation of Colombian Creole (CR) pigs, with a focus on the breed-specific variants in the exonic region of 34 genes with reported effects on adaptive and economic traits. Seven individuals of each of the three CR breeds (CM, Casco de Mula; SP, San Pedreño; and ZU, Zungo) were whole-genome sequenced along with 7 Iberian (IB) pigs and 7 pigs of each of the four most used cosmopolitan (CP) breeds (Duroc, Landrace × Large White, and Pietrain). Molecular variability in CR (6,451,218 variants; from 3,919,242, in SP, to 4,648,069, in CM) was comparable to that in CP, but higher than in IB. For the investigated genes, SP pigs displayed less exonic variants (178) than ZU (254), CM (263), IB (200), and the individual CP genetic types (201 to 335). Sequence variation in these genes confirmed the resemblance of CR to IB and indicates that CR pigs, particularly ZU and CM, are not exempt from selective introgression of other breeds. A total of 50 exonic variants were identified as being potentially specific to CR, including a high-impact deletion in the intron between exons 15 and 16 of the leptin receptor gene, which was only found in CM and ZU. The identification of breed-specific variants in genes related to adaptive and economical traits can bolster the understanding of the role of gene-environment interactions on local adaptation and points the way for effective breeding and conservation of CR pigs.

Genomic prediction with whole-genome sequence data in intensely selected pig lines.

BACKGROUND: Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage. METHODS: We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests. RESULTS: The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected. CONCLUSIONS: Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis.

Identification of a missense variant in the porcine AGPAT gene family associated with intramuscular fat content through whole-genome sequencing.

The 1-acylglycerol-3-phosphate O-acyltransferases (AGPATs) are enzymes that catalyze the conversion of lysophosphatidic acid to phosphatidic acid, which is a precursor of triacylglycerol, the main fat reservoir in mammals. We used whole-genome sequencing of 205 pigs to identify 6639 genetic variants in the porcine AGPAT gene family. Of these, 166 common variants in the AGPAT5 gene had significant associations with fat content and composition traits. We preselected a missense single nucleotide polymorphism in exon 6 of AGPAT5 (rs196952262, A>G) for validation of its associations in 1034 pigs from the same Duroc line. The A allele showed a positive additive effect for intramuscular fat content (+1.12% ± 0.21, p < 0.001, for gluteus medius and +0.89% ± 0.33, p < 0.01, for longissimus). We also observed significant associations with fatty acid composition that were, at least in part, independent of the increased intramuscular fat. The A allele resulted in more monounsaturated fatty acids (+0.34% ± 0.15, p < 0.05, for longissimus) and a greater monounsaturated/polyunsaturated fatty acids ratio (+0.11 ± 0.04, p < 0.01, for gluteus medius and +0.13 ± 0.05, p < 0.05, for longissimus). The effect of the AGPAT5 variant on intramuscular fat was more noticeable in fatter pigs, and AGPAT5 interacts with other genes that affect overall fatness such as LEPR. AGPAT5 was the most expressed gene of the AGPAT family in pig skeletal muscle. This variant can be used as a marker in assisted selection for modulating pig fat deposition and fatty acid content.

A genome-wide screen for resilient responses in growing pigs.

BACKGROUND: There is a growing interest to decipher the genetic background of resilience and its possible improvement through selective breeding. The objective of the present study was to provide new insights into the genetic make-up of resilience in growing pigs by identifying genomic regions and candidate genes associated with resilience indicators. Commercial Duroc pigs were challenged with an attenuated Aujeszky vaccine at 12 weeks of age. Two resilience indicators were used: deviation from the expected body weight at 16 weeks of age given the growth curve of non-vaccinated pigs (∆BW) and the increase in acute-phase protein haptoglobin at four days post-vaccination (∆HP). Genome-wide association analyses were carried out on 445 pigs, using genotypes at 41,165 single nucleotide polymorphisms (SNPs) and single-marker and Bayesian multiple-marker regression approaches. RESULTS: Genomic regions on pig chromosomes 2, 8, 9, 11 (∆BW) and 8, 9, 13 (∆HP) were found to be associated with the resilience indicators and explained high proportions of their genetic variance. The genomic regions that were associated explained 27 and 5% of the genetic variance of ∆BW and ∆HP, respectively. These genomic regions harbour promising candidate genes that are involved in pathways related to immune response, response to stress, or signal transduction (CD6, PTGDR2, IKZF1, RNASEL and MYD88), and growth (GRB10 and LCORL). CONCLUSIONS: Our study identified novel genomic regions that are associated with two resilience indicators (∆BW and ∆HP) in pigs. These associated genomic regions harbour potential candidate genes involved in immune response and growth pathways, which emphasise the strong relationship between resilience and immune response.

Rare and population-specific functional variation across pig lines.

BACKGROUND: It is expected that functional, mainly missense and loss-of-function (LOF), and regulatory variants are responsible for most phenotypic differences between breeds and genetic lines of livestock species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in commercial livestock populations, in particular regarding population-specific variation and how it can affect applications such as across-breed genomic prediction. METHODS: We re-sequenced the whole genome of 7848 individuals from nine commercial pig lines (average sequencing coverage: 4.1×) and imputed whole-genome genotypes for 440,610 pedigree-related individuals. The called variants were categorized according to predicted functional annotation (from LOF to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of their distribution along the genome, alternative allele frequency, per-site Wright's fixation index (FST), individual load, and association to production traits. RESULTS: Of the 46 million called variants, 28% were private (called in only one line) and 21% were widespread (called in all nine lines). Genomic regions with a low recombination rate were enriched with private variants. Low-prevalence variants (called in one or a few lines only) were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory roles (including LOF and deleterious missense variants). On average, individuals carried fewer private deleterious missense alleles than expected compared to alleles with other predicted consequences. Only a small subset of the low-prevalence variants had intermediate allele frequencies and explained small fractions of phenotypic variance (up to 3.2%) of production traits. The significant low-prevalence variants had higher per-site FST than the non-significant ones. These associated low-prevalence variants were tagged by other more widespread variants in high linkage disequilibrium, including intergenic variants. CONCLUSIONS: Most low-prevalence variants have low minor allele frequencies and only a small subset of low-prevalence variants contributed detectable fractions of phenotypic variance of production traits. Accounting for low-prevalence variants is therefore unlikely to noticeably benefit across-breed analyses, such as the prediction of genomic breeding values in a population using reference populations of a different genetic background.

Transcriptome shifts triggered by vitamin A and SCD genotype interaction in Duroc pigs.

BACKGROUND: The composition of intramuscular fat depends on genetic and environmental factors, including the diet. In pigs, we identified a haplotype of three SNP mutations in the stearoyl-coA desaturase (SCD) gene promoter associated with higher content of monounsaturated fatty acids in intramuscular fat. The second of these three SNPs (rs80912566, C > T) affected a putative retinol response element in the SCD promoter. The effect of dietary vitamin A restriction over intramuscular fat content is controversial as it depends on the pig genetic line and the duration of the restriction. This study aims to investigate changes in the muscle transcriptome in SCD rs80912566 TT and CC pigs fed with and without a vitamin A supplement during the fattening period. RESULTS: Vitamin A did not affect carcass traits or intramuscular fat content and fatty acid composition, but we observed an interaction between vitamin A and SCD genotype on the desaturation of fatty acids in muscle. As reported before, the SCD-TT pigs had more monounsaturated fat than the SCD-CC animals. The diet lacking the vitamin A supplement enlarged fatty acid compositional differences between SCD genotypes, partly because vitamin A had a bigger effect on fatty acid desaturation in SCD-CC pigs (positive) than in SCD-TT and SCD-TC animals (negative). The interaction between diet and genotype was also evident at the transcriptome level; the highest number of differentially expressed genes were detected between SCD-TT pigs fed with the two diets. The genes modulated by the diet with the vitamin A supplement belonged to metabolic and signalling pathways related to immunity and inflammation, transport through membrane-bounded vesicles, fat metabolism and transport, reflecting the impact of retinol on a wide range of metabolic processes. CONCLUSIONS: Restricting dietary vitamin A during the fattening period did not improve intramuscular fat content despite relevant changes in muscle gene expression, both in coding and non-coding genes. Vitamin A activated general pathways of retinol response in a SCD genotype-dependant manner, which affected the monounsaturated fatty acid content, particularly in SCD-CC pigs.

A Methodology to Quantify Resilience in Growing Pigs.

There is a growing concern about the genetic determinism of resilience and its possible implementation in breeding programs. The objective of our study was to elaborate novel resilience indicators in growing pigs based on the deviation from the expected growth curve and the increment of the acute-phase protein haptoglobin (HP) after applying a common vaccine. A total of 445 pigs were vaccinated with an attenuated Aujeszky vaccine at 12 weeks of age. Deviation from the expected body weight (ΔBW) given the growth curve of unvaccinated pigs at 28 days post-vaccination (DPV) and the increment of HP at 4 DPV (ΔHP) were suggested as resilience indicators. Challenged pigs that maintained their productivity and had a minor activation of HP were deemed resilient, whereas pigs that had low ∆BW values and a high activation of HP were deemed susceptible. Pigs were also classified based on ∆BW and ∆HP relative to the expected BW at 28 DPV and to the basal level of HP, respectively. The concordance was high between both methods, indicating that ΔBW and ΔHP are not sensitive to the animal's expected BW nor the basal level of HP. The heritability estimates were moderate for ∆BW (0.33) and low-to-moderate for ∆HP (0.16). Our study suggests ΔBW and ΔHP as novel resilience indicators in pigs. The suggested indicators capture different aspects of resilience, are easy to measure, and are genetically controlled. Thus, they may be improved through selective breeding. Further analyses are needed to validate our findings.

Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds.

BACKGROUND: Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. METHODS: Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10-6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. RESULTS: We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. CONCLUSIONS: Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

A sequence variant in the diacylglycerol O-acyltransferase 2 gene influences palmitoleic acid content in pig muscle.

The bulk of body fat in mammals is in the form of triacylglycerol. Diacylglycerol O-acyltransferase 2 (DGAT2) catalyses the terminal step in triacylglycerol synthesis. The proximity of DGAT2 with stearoyl-CoA desaturase (SCD) in the endoplasmic reticulum may facilitate provision of de novo SCD-mediated fatty acids as substrate for DGAT2. Here, we first searched for sequence variants in the DGAT2 gene to then validate their effect on fat content and fatty acid composition in muscle, subcutaneous fat and liver of 1129 Duroc pigs. A single nucleotide polymorphism in exon 9 (ss7315407085 G > A) was selected as a tag variant for the 33 sequence variants identified in the DGAT2 region. The DGAT2-G allele increased DGAT2 expression in muscle and had a positive impact on muscular C14 and C16 fatty acids at the expense of C18 fatty acids. Although there was no evidence for an interaction of DGAT2 with functional SCD genotypes, pigs carrying the DGAT2-G allele had proportionally more palmitoleic acid relative to palmitic acid. Our findings indicate that DGAT2 preferentially uptakes shorter rather than longer-chain fatty acids as substrate, especially if they are monounsaturated, and confirm that fatty acid metabolism in pigs is subjected to subtle tissue-specific genetic regulatory mechanisms.

Genetic variation in recombination rate in the pig.

BACKGROUND: Meiotic recombination results in the exchange of genetic material between homologous chromosomes. Recombination rate varies between different parts of the genome, between individuals, and is influenced by genetics. In this paper, we assessed the genetic variation in recombination rate along the genome and between individuals in the pig using multilocus iterative peeling on 150,000 individuals across nine genotyped pedigrees. We used these data to estimate the heritability of recombination and perform a genome-wide association study of recombination in the pig. RESULTS: Our results confirmed known features of the recombination landscape of the pig genome, including differences in genetic length of chromosomes and marked sex differences. The recombination landscape was repeatable between lines, but at the same time, there were differences in average autosome-wide recombination rate between lines. The heritability of autosome-wide recombination rate was low but not zero (on average 0.07 for females and 0.05 for males). We found six genomic regions that are associated with recombination rate, among which five harbour known candidate genes involved in recombination: RNF212, SHOC1, SYCP2, MSH4 and HFM1. CONCLUSIONS: Our results on the variation in recombination rate in the pig genome agree with those reported for other vertebrates, with a low but nonzero heritability, and the identification of a major quantitative trait locus for recombination rate that is homologous to that detected in several other species. This work also highlights the utility of using large-scale livestock data to understand biological processes.

Circulating Non-Esterified Fatty Acids as Biomarkers for Fat Content and Composition in Pigs.

Circulating non-esterified fatty acids (NEFA) can reflect the composition of dietary fat or adipose tissues depending on the fasting conditions. Therefore, circulating NEFA may be valuable as biomarkers for meat quality traits, such as intramuscular fat content and fatty acid composition in finishing pigs. Genetic variants that regulate lipid metabolism can also modulate the circulating NEFA. We conducted an experiment with 150 heavy Duroc pigs to evaluate fluctuations in the circulating NEFA composition due to age, fasting duration and two genetic polymorphisms, one in the leptin receptor (LEPR; rs709596309) and one in the stearoyl-CoA desaturase (SCD; rs80912566) gene. Circulating NEFA were more saturated and less monounsaturated than the subcutaneous and intramuscular adipose tissues. Absolute circulating NEFA content was more influenced by fasting duration than age. The SCD polymorphism did not impact NEFA content or composition. The LEPR polymorphism affected the content but not the fatty acid composition. Circulating oleic acid NEFA content after a short fasting was positively correlated with intramuscular fat content and, after a long fasting, with intramuscular oleic acid content. We conclude that circulating NEFA reflect environmental and genetic metabolic changes but are of limited value as biomarkers for intramuscular fat content and fatty acid composition.

Antagonistic maternal and direct effects of the leptin receptor gene on body weight in pigs.

Maternal effects on offspring growth can impact survival and evolution of natural and domesticated populations. Genetic correlation estimates often support a negative relationship between direct and maternal effects. However, the genetic underpinnings whereby this antagonism operates are unclear. In pigs, sow feeding status and body composition condition piglet development and growth. We hypothesized that variants in genes impacting these traits may be causative of maternal influences that could be antagonistic to the direct effects for piglet growth. A recessive missense mutation (C>T) in the porcine leptin receptor (LEPR) gene (rs709596309) has been identified as the possible causal polymorphism for increased feed intake and fatness. Using data from a Duroc line, we show that the TT sows exerted a negative impact on the body weight of their offspring at the end of the growing period of similar extent to the positive direct effect of the TT genotype over each individual. Thus, TT pigs from TT dams were about as heavy as CC and CT (C-) pigs from C-dams, but TT pigs from C-dams were around 5% heavier than C-pigs from TT dams. In contrast, body composition was only influenced by LEPR direct effects. This antagonism is due to a higher propensity of TT pigs for self-maintenance rather than for offspring investment. We show that TT pigs consumed more feed, favored fatty acid uptake over release, and produced lighter piglets at weaning than their C-counterparts. We conclude that LEPR underlies a transgenerational mechanism for energy distribution that allocates resources to the sow or the offspring according to whether selective pressure is exerted before or after weaning.