Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake

Animal board invited review: Heritability of nitrogen use efficiency in fattening pigs: Current state and possible directions

Pork, an important component of human nutrition worldwide, contributes considerably to anthropogenic nitrogen and greenhouse gas emissions. Reducing the environmental impact of pig production is therefore essential. This can be achieved through system-level strategies, such as optimising resource use, improving manure management and recycling leftovers from human food production, and at the individual animal level by maintaining pig health and fine-tuning dietary protein levels to individual requirements. Breeding, coupled with nutritional strategies, offers a lasting solution to improve nitrogen use efficiency (NUE) - the ratio of nitrogen retained in the body to nitrogen ingested. With a heritability as high as 0.54, incorporating NUE into breeding programmes appears promising. Nitrogen use efficiency involves multiple tissues and metabolic processes, and is influenced by the environment and individual animal characteristics, including its genetic background. Heritable genetic variation in NUE may therefore occur in many different processes, including the central nervous regulation of feed intake, the endocrine system, the gastrointestinal tract where digestion and absorption take place, and the composition of the gut microbiome. An animal's postabsorptive protein metabolism might also harbour important genetic variation, especially in the maintenance requirements of tissues and organs. Precise phenotyping, although challenging and costly, is essential for successful breeding. Various measurement techniques, such as imaging techniques and mechanistic models, are being explored for their potential in genetic analysis. Despite the difficulties in phenotyping, some studies have estimated the heritability and genetic correlations of NUE. These studies suggest that direct selection for NUE is more effective than indirect methods through feed efficiency. The complexity of NUE indicates a polygenic trait architecture, which has been confirmed by genome-wide association studies that have been unable to identify significant quantitative trait loci. Building sufficiently large reference populations to train genomic prediction models is an important next step. However, this will require the development of truly high-throughput phenotyping methods. In conclusion, breeding pigs with higher NUE is both feasible and necessary but will require increased efforts in high-throughput phenotyping and improved genome annotation.

Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.

Genetic Parameter Estimation and Genome-Wide Association Analysis of Social Genetic Effects on Average Daily Gain in Purebreds and Crossbreds

Simple Summary

Average daily gain (ADG) is influenced by both an individual’s direct genetic effect (DGE) and by a social genetic effect (SGE) derived from pen mates. Therefore, identifying the DGE and SGE on ADG is essential for a better understanding of pig breeding systems. We conducted this study to elucidate the genetic characteristics and relationships of DGE and SGE on ADG using purebred and crossbred pigs. We found that the DGE and SGE both contributed to ADG in both populations. In addition, the SGE of purebred pigs was highly correlated with the DGE of crossbred pigs. Furthermore, we identified several genomic regions that may be associated with the DGE and SGE on ADG. Our findings will contribute to future genomic evaluation studies of socially affected traits.

Abstract

Average daily gain (ADG) is an important growth trait in the pig industry. The direct genetic effect (DGE) has been studied mainly to assess the association between genetic information and economic traits. The social genetic effect (SGE) has been shown to affect ADG simultaneously with the DGE because of group housing systems. We conducted this study to elucidate the genetic characteristics and relationships of the DGE and SGE of purebred Korean Duroc and crossbred pigs by single-step genomic best linear unbiased prediction and a genome-wide association study. We used the genotype, phenotype, and pedigree data of 1779, 6022, and 7904 animals, respectively. Total heritabilities on ADG were 0.19 ± 0.04 and 0.39 ± 0.08 for purebred and crossbred pigs, respectively. The genetic correlation was the greatest (0.77 ± 0.12) between the SGE of purebred and DGE of crossbred pigs. We found candidate genes located in the quantitative trait loci (QTLs) for the SGE that were associated with behavior and neurodegenerative diseases, and candidate genes in the QTLs for DGE that were related to body mass, size of muscle fiber, and muscle hypertrophy. These results suggest that the genomic selection of purebred animals could be applied for crossbred performance.

Genetic association of polymorphisms in porcine RGS16 with porcine circovirus viral load in naturally infected Yorkshire pigs

Regulator of G protein signaling 16 (RGS16) is known to be associated with porcine circovirus type 2 (PCV2). PCV2 associated disease (PCVAD) is a serious problem in the swine industry. The representative symptoms of PCVAD are high viral titer proliferation and decreased average daily gain. In this study, we identified single nucleotide polymorphisms (SNPs) in the RGS16 region, including the upstream region. Of the 22 identified SNPs, rs332913874, rs326071195, and rs318298586 were genotyped in 142 Yorkshire pigs. These SNPs were significantly associated with the PCV2 viral load. Moreover, the haplotype combination was also related to the PCV2 viral load. The haplotype and diplotype analysis also had a significant difference with the PCV2 viral load. Taken together, our results suggest that RGS16 SNPs considerably affect the PCV2 viral load.

A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Feed efficiency (FE) traits in pigs are of utmost economic importance. Genetic improvement of FE related traits in pigs might significantly reduce production cost and energy consumption. Hence, our study aimed at identifying SNPs and candidate genes associated with FE related traits, including feed conversion ratio (FCR), average daily gain (ADG), average daily feed intake (ADFI), and residual feed intake (RFI). A genome-wide association study (GWAS) was performed for the four FE related traits in 296 Landrace pigs genotyped with PorcineSNP50 BeadChip. Two different single-trait methods, single SNP linear model GWAS (LM-GWAS) and single-step GWAS (ssGWAS), were implemented. Our results showed that the two methods showed high consistency with respect to SNP identification. A total of 32 common significant SNPs associated with the four FE related traits were identified. Bioinformatics analysis revealed eight common QTL regions, of which three QTL regions related to ADFI and RFI traits were overlapped. Gene ontology analysis revealed six common candidate genes (PRELID2, GPER1, PDX1, TEX2, PLCL2, ICAM2) relevant for the four FE related traits. These genes are involved in the processes of fat synthesis and decomposition, lipid transport process, insulin metabolism, among others. Our results provide, new insights into the genetic mechanisms and candidate function genes of FE related traits in pigs. However, further investigations to validate these results are warranted.

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.

Genome-wide association study reveals genetic loci and candidate genes for average daily gain in Duroc pigs

Objective

Average daily gain (ADG) is an important target trait of pig breeding programs. We aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with ADG in the Duroc pig population.

Methods

We performed a genome-wide association study involving 390 Duroc boars and by using the PorcineSNP60K Beadchip and two linear models.

Results

After quality control, we detected 3,5971 SNPs, which included seven SNPs that are significantly associated with the ADG of pigs. We identified six quantitative trait loci (QTL) regions for ADG. These QTLs included four previously reported QTLs on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, and SSC13, as well as two novel QTLs on SSC6 and SSC16. In addition, we selected six candidate genes (general transcription factor 3C polypeptide 5, high mobility group AT-hook 2, nicotinamide phosphoribosyltransferase, oligodendrocyte transcription factor 1, pleckstrin homology and RhoGEF domain containing G4B, and ENSSSCG00000031548) associated with ADG on the basis of their physiological roles and positional information. These candidate genes are involved in skeletal muscle cell differentiation, diet-induced obesity, and nervous system development.

Conclusion

This study contributes to the identification of the casual mutation that underlies QTLs associated with ADG and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in ADG regulation.

Genome-wide association analysis reveals genetic loci and candidate genes for feeding behavior and eating efficiency in Duroc boars

Efficient use of feed resources is a challenge in the pork industry because the largest variability in expenditure is attributed to the cost of fodder. Efficiency of feeding is directly related to feeding behavior. In order to identify genomic regions controlling feeding behavior and eating efficiency traits, 338 Duroc boars were used in this study. The Illumina Porcine SNP60K BeadChip was used for genotyping. Data pertaining to individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV), mean feed intake rate (FR), and feed conversion ratio (FCR) were collected for these pigs. Despite the limited sample size, the genome-wide association study was acceptable to detect candidate regions association with feeding behavior and eating efficiency traits in pigs. We detected three genome-wide (P < 1.40E-06) and 11 suggestive (P < 2.79E-05) single nucleotide polymorphism (SNP)-trait associations. Six SNPs were located in genomic regions where quantitative trait loci (QTLs) have previously been reported for feeding behavior and eating efficiency traits in pigs. Five candidate genes (SERPINA3, MYC, LEF1, PITX2, and MAP3K14) with biochemical and physiological roles that were relevant to feeding behavior and eating efficiency were discovered proximal to significant or suggestive markers. Gene ontology analysis indicated that most of the candidate genes were involved in the development of the hypothalamus (GO:0021854, P < 0.0398). Our results provide new insights into the genetic basis of feeding behavior and eating efficiency in pigs. Furthermore, some significant SNPs identified in this study could be incorporated into artificial selection programs for Duroc-related pigs to select for increased feeding efficiency.

Genome-wide association analysis and functional annotation of positional candidate genes for feed conversion efficiency and growth rate in pigs

Feed conversion efficiency is a measure of how well an animal converts feed into live weight and it is typically expressed as feed conversion ratio (FCR). FCR and related traits like growth rate (e.g. days to 110 kg—D110) are of high interest for animal breeders, farmers and society due to implications on animal performance, feeding costs and environmental sustainability. The objective of this study was to identify genomic regions associated with FCR and D110 in pigs. A total of 952 terminal line boars, showing an individual variation in FCR, were genotyped using 60K SNP-Chips. Markers were tested for associations with estimated breeding values (EBV) for FCR and D110. For FCR, the largest number of associated SNPs was located on chromosomes 4 (30 SNPs), 1 (25 SNPs), X (15 SNPs) and 6 (12 SNPs). The most prominent genomic regions for D110 were identified on chromosomes 15 (10 SNPs), 1 and 4 (both 9 SNPs). The most significantly associated SNPs for FCR and D110 mapped 129.8 Kb from METTL11B (chromosome 4) and 32Kb from MBD5 (chromosome 15), respectively. A list of positional genes, closest to significantly associated SNPs, was used to identify enriched pathways and biological functions related to the QTL for both traits. A number of candidate genes were significantly overrepresented in pathways of immune cell trafficking, lymphoid tissue structure, organ morphology, endocrine system function, lipid metabolism, and energy production. After resequencing the coding region of selected positional and functional candidate genes, six SNPs were genotyped in a subset of boars. SNPs in PRKDC, SELL, NR2E1 and AKRIC3 showed significant associations with EBVs for FCR/D110. The study revealed a number of chromosomal regions and candidate genes affecting FCR/D110 and pointed to corresponding biological pathways related to lipid metabolism, olfactory reception, and also immunological status.

Genomewide association analysis of sow lactation performance traits in lines of Yorkshire pigs divergently selected for residual feed intake during grow-finish phase

Lactation is an economically and biologically important phase in the life cycle of sows. Short generation intervals in nucleus herds and low heritability of traits associated with lactation along with challenges associated with collecting accurate lactation performance phenotypes emphasize the importance of using genomic tools to examine the underlying genetics of these traits. We report the first genomewide association study (GWAS) on traits associated with lactation and efficiency in 2 lines of Yorkshire pigs that were divergently selected for residual feed intake during grow-finish phase. A total of 862 farrowing records from 2 parities were analyzed using a Bayesian whole genome variable selection model (Bayes B) to locate 1-Mb regions that were most strongly associated with each trait. The GWAS was conducted separately for parity 1 and 2 records. Marker-based heritabilities ranged from 0.03 to 0.39 for parity 1 traits and from 0.06 to 0.40 for parity 2 traits. For all traits studied, around 90% of genetic variance came from a large number of genomic regions with small effects, whereas genomic regions with large effects were found to be different for the same trait measured in parity 1 and 2. The highest percentage of genetic variance explained by a 1-Mb window for each trait ranged from 0.4% for feed intake during lactation to 4.2% for back fat measured at farrowing in parity 1 sows and from 0.2% for lactation feed intake to 5.4% for protein mass loss during lactation in parity 2 sows. A total of thirteen 1-Mb nonoverlapping windows were found to explain more than 1.5% of genetic variance for either a single trait or across multiple traits. These 1-Mb windows were on chromosomes 2, 3, 6, 7, 8, 11, 14, 15, 17, and 18. The major positional candidate genes within 1 Mb upstream and downstream of these windows were , (SSC2), (SSC6) (SSC7), (SSC8), (SSC11), (SSC14), (SSC17). Further validation studies on larger populations are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with sow lactation performance.

Exploring the genetics of feed efficiency and feeding behaviour traits in a pig line highly selected for performance characteristics

The consideration of feed efficiency traits is highly relevant in animal breeding due to economic and ecologic impacts of the efficient usage and utilization of feed resources. In pigs, corresponding observations are recorded using automatic feeding stations and serve as one of the main criteria in most pig selection programmes. Simultaneously, feeding stations also generate feeding behaviour data which represent a nearly unused resource and provide a valuable proxy measure of health status, animal welfare, and management practices. In the current study, an integrated approach was applied to a feed efficiency tested and genome-wide genotyped terminal sire line population. Therefore, genetic analyses were performed combining a single-marker based approach and a Bayesian multi-marker algorithm. Major quantitative trait loci (QTL) for feeding behaviour traits comprising daily occupation time, daily feeder visit, and daily feeding rate were identified on chromosomes 1, 4, 6, 7, 8, and 14. Feed efficiency was represented by feed conversion ratio and daily feed intake revealing prominent genomic regions on chromosomes 1, 6, 9, and 11. The positional and functional candidate genes identified are involved in transport processes like AQP4, SLC22A23, and SLC6A14 as well as energy sensing, generation, and utilization as exemplified by PPP3CA, IQGAP3, ECI2, and DnaJC15. These molecular features provide the first step towards the dissection of the genetic connection between distinct feeding behaviour patterns, feed efficiency and performance, health, and welfare traits driving the implementation of these traits in breeding programmes and pig husbandry.

Genomewide association of piglet responses to infection with one of two porcine reproductive and respiratory syndrome virus isolates

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease in the swine industry. Identification of host genetic factors that enable selection for improved performance during PRRS virus (PRRSV) infection would reduce the impact of this disease on animal welfare and production efficiency. We conducted genomewide association study (GWAS) analyses of data from 13 trials of approximately 200 commercial crossbred nursery-age piglets that were experimentally infected with 1 of 2 type 2 isolates of PRRSV (NVSL 97-7985 [NVSL] and KS2006-72109 [KS06]). Phenotypes analyzed were viral load (VL) in blood during the first 21 d after infection (dpi) and weight gain (WG) from 0 to 42 dpi. We accounted for the previously identified QTL in the region on SSC4 in our models to increase power to identify additional regions. Many regions identified by single-SNP analyses were not identified using Bayes-B, but both analyses identified the same regions on SSC3 and SSC5 to be associated with VL in the KS06 trials and on SSC6 in the NVSL trials ( < 5 × 10); for WG, regions on SSC5 and SSC17 were associated in the NVSL trials ( < 3 × 10). No regions were identified with either method for WG in the KS06 trials. Except for the region on SSC4, which was associated with VL for both isolates (but only with WG for NVSL), identified regions did not overlap between the 2 PRRSV isolate data sets, despite high estimates of the genetic correlation between isolates for traits based on these data. We also identified genomic regions whose associations with VL or WG interacted with either PRRSV isolate or with genotype at the SSC4 QTL. Gene ontology (GO) annotation terms for genes located near moderately associated SNP ( < 0.003) were enriched for multiple immunologically (VL) and metabolism- (WG) related GO terms. The biological relevance of these regions suggests that, although it may increase the number of false positives, the use of single-SNP analyses and a relaxed threshold also increased the identification of true positives. In conclusion, although only the SSC4 QTL was associated with response to both PRRSV isolates, genes near associated SNP were enriched for the same GO terms across PRRSV isolates, suggesting that host responses to these 2 isolates are affected by the actions of many genes that function together in similar biological processes.

Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: II. Genomewide association

Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring genes influencing those traits. The current study aimed at identifying genomic regions associated with variation in feed efficiency and several production traits in a Duroc terminal sire population, including ADFI, ADG, feed conversion ratio, residual feed intake (RFI), real-time ultrasound back fat thickness (BF), ultrasound muscle depth, intramuscular fat content (IMF), birth weight (BW at birth), and weaning weight (BW at weaning). Single trait association analyses were performed using Bayes B models with 35,140 SNP on 18 autosomes after quality control. Significance of nonoverlapping 1-Mb length windows (n = 2,380) were tested across 3 QTL inference methods: posterior distribution of windows variances from Monte Carlo Markov Chain, naive Bayes factor, and nonparametric bootstrapping. Genes within the informative QTL regions for the traits were annotated. A region ranging from166 to 140 Mb (4-Mb length) on SSC 1, approximately 8 Mb upstream of the MC4R gene, was significantly associated with ADFI, ADG, and BF, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting BW at weaning was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2 (or SDR16C5), MOS, RPS20, LYN, and PENK. No QTL were identified for RFI, IMF, and BW at birth. In conclusion, we have identified several genomic regions associated with traits affecting nutrient utilization that could be considered for future genomic prediction to improve feed utilization.

A Whole Genome Association Study on Meat Quality Traits Using High Density SNP Chips in a Cross between Korean Native Pig and Landrace

A whole genome association (WGA) study was performed to detect significant polymorphisms for meat quality traits in an F₂ cross population (N = 478) that were generated with Korean native pig sires and Landrace dams in National Livestock Research Institute, Songwhan, Korea. The animals were genotyped using Illumina porcine 60k SNP beadchips, in which a set of 46,865 SNPs were available for the WGA analyses on ten carcass quality traits; live weight, crude protein, crude lipids, crude ash, water holding capacity, drip loss, shear force, CIE L, CIE a and CIE b. Phenotypes were regressed on additive and dominance effects for each SNP using a simple linear regression model, after adjusting for sex, sire and slaughter stage as fixed effects. With the significant SNPs for each trait (p<0.001), a stepwise regression procedure was applied to determine the best set of SNPs with the additive and/or dominance effects. A total of 106 SNPs, or quantitative trait loci (QTL) were detected, and about 32 to 66% of the total phenotypic variation was explained by the significant SNPs for each trait. The QTL were identified in most porcine chromosomes (SSCs), in which majority of the QTL were detected in SSCs 1, 2, 12, 13, 14 and 16. Several QTL clusters were identified on SSCs 12, 16 and 17, and a cluster of QTL influencing crude protein, crude lipid, drip loss, shear force, CIE a and CIE b were located between 20 and 29 Mb of SSC12. A pleiotropic QTL for drip loss, CIE L and CIE b was also detected on SSC16. These QTL need to be validated in commercial pig populations for genetic improvement in meat quality via marker-assisted selection.

Novel insight into the genomic architecture of feed and nitrogen efficiency measured by residual energy intake and nitrogen excretion in growing pigs

BACKGROUND

Improvement of feed efficiency in pigs is of great economical and environmental interest and contributes to use limited resources efficiently to feed the world population. Genome scans for feed efficiency traits are of importance to reveal the underlying biological causes and increase the rate of genetic gain. The aim of this study was to determine the genomic architecture of feed efficiency measured by residual energy intake (REI), in association with production, feed conversion ratio (FCR) and nitrogen excretion traits through the identification of quantitative trait loci (QTL) at different stages of growth using a three generation full-sib design population which originated from a cross between Pietrain and a commercial dam line.

RESULTS

Six novel QTL for REI were detected explaining 2.7-6.1% of the phenotypic variance in REI. At growth from 60-90 kg body weight (BW), a QTL with a significant dominance effect was identified for REI on SSC14, at a similar location to the QTL for feed intake and nitrogen excretion traits. At growth from 90-120 kg BW, three QTL for REI were detected on SSC2, SSC4 and SSC7 with significant additive, imprinting and additive effects, respectively. These QTL (except for the imprinted QTL) were positionally overlapping with QTL for FCR and nitrogen excretion traits. During final growth (120-140 kg BW), a further QTL for REI was identified on SSC8 with significant additive effect, which overlapped with QTL for nitrogen excretion. During entire analysed growth (60-140 kg BW), a novel additive QTL for REI on SSC4 was observed, with no overlapping with QTL for any other traits considered.

CONCLUSIONS

The occurrence of only one overlapping QTL of REI with feed intake suggests that only a small proportion of the variance in REI was explained by change in feed intake, whereas four overlapping QTL of REI with those of nitrogen excretion traits suggests that mostly underlying factors of feed utilisation such as metabolism and protein turnover were the reason for change in REI. Different QTL for REI were identified at different growth stages, indicating that different genes are responsible for efficiency in feed utilisation at different stages of growth.

Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping

This study was aimed at identifying genomic regions controlling feeding behavior in Danish Duroc boars and its potential implications for eating behavior in humans. Data regarding individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV) and mean feed intake rate (FR) were available for 1130 boars. All boars were genotyped using the Illumina Porcine SNP60 BeadChip. The association analyses were performed using the GenABEL package in the R program. Sixteen SNPs were found to have moderate genome-wide significance (p<5E-05) and 76 SNPs had suggestive (p<5E-04) association with feeding behavior traits. MSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD. Thirty-six SNPs were located in genome regions where QTLs have previously been reported for behavior and/or feed intake traits in pigs. The regions: 64–65 Mb on SSC 1, 124–130 Mb on SSC 8, 63–68 Mb on SSC 11, 32–39 Mb and 59–60 Mb on SSC 12 harbored several signifcant SNPs. Synapse genes (GABRR2, PPP1R9B, SYT1, GABRR1, CADPS2, DLGAP2 and GOPC), dephosphorylation genes (PPM1E, DAPP1, PTPN18, PTPRZ1, PTPN4, MTMR4 and RNGTT) and positive regulation of peptide secretion genes (GHRH, NNAT and TCF7L2) were highly significantly associated with feeding behavior traits. This is the first GWAS to identify genetic variants and biological mechanisms for eating behavior in pigs and these results are important for genetic improvement of pig feed efficiency. We have also conducted pig-human comparative gene mapping to reveal key genomic regions and/or genes on the human genome that may influence eating behavior in human beings and consequently affect the development of obesity and metabolic syndrome. This is the first translational genomics study of its kind to report potential candidate genes for eating behavior in humans.

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain-Large White backcross

Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Piétrain (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW × PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P < 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P < 0.01 at the CW level) were mapped to chromosomes SSC6 - probably due to the halothane alleles - and SSC7, respectively. Three putative QTL for feed intake traits were detected (P < 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P < 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.

Mapeamento de QTL nos cromossomos 1, 2, 3, 12, 14, 15 e X em suínos: características de carcaça e qualidade de carne

A realização do presente estudo teve como objetivo mapear Quantitative Trait Loci (QTL) de carcaça e qualidade de carne em uma população F2 de suínos desenvolvida pelo cruzamento de dois reprodutores da raça brasileira Piau com 18 fêmeas comerciais (Landrace x Large White x Pietrain). O mapa de ligação para essa população foi construído após a genotipagem de 684 animais para 35 marcadores microssatélites. Os dados foram analisados pelo mapeamento por intervalo usando-se sexo, lote e genótipo halotano como efeitos fixos e peso de carcaça ao abate, peso da carcaça direita e idade ao abate como covariáveis. Um total de 18 QTLs foi encontrado; os QTLs para maior espessura de toucinho na região da copa, na linha dorsolombar, e a perda por cozimento foram significativos em nível de 5% genômico. A característica espessura de toucinho foi essencialmente associada aos alelos da raça Piau, conhecido como porco tipo banha. As informações dos QTLs significativos encontrados servem para futuros estudos de mapeamento fino para identificação de genes a serem usados em conjunto com os métodos tradicionais de seleção, para melhorar a eficiência dos programas de melhoramento, assim como prover informação acerca da fisiologia envolvida no desenvolvimento das características quantitativas dos suínos.

Changes in gene expression in a porcine preadipocyte cell line during differentiation

Adipocyte differentiation plays an important role in the formation of fat tissues in pigs and affects meat quality and productivity. Clarification of the nature of the pig genes that participate in adipocyte differentiation will provide a clue to the regulation of fat content and thickness in pig carcases by dietary control; it will also help to find target genes for exploring potentially useful polymorphisms for molecular breeding aimed at fat traits. We constructed a DNA oligomer microarray based on pig transcripts, and we used the array to investigate time-dependent changes in gene expression in the PSPA porcine preadipocyte cell line during differentiation into adipocytes. We selected genes with markedly altered expression (at least fivefold difference in comparison with expression in undifferentiated cells) and classified them into five groups according to gene expression pattern. In the early stage after stimulation of adipocyte differentiation, we observed up-regulation of many genes encoding proteins involved in regulating cell proliferation and transcription. Among the probes corresponding to transcripts that showed marked changes in expression, 27 were located within previously reported QTL regions for traits related to adipose tissues. These results will be valuable resources for finding the genes responsible for fat-related traits that have been identified in previous studies using various pig resource families.

Validation of a paternally imprinted QTL affecting pH24h distinct from PRKAG3 on SSC15

We previously performed a genome scan in a White Duroc × Erhualian F(2) population and identified a QTL on SSC15 with strong effect on pH24h in M. Longissimus dorsi and M. Semimembranous muscle tissue. At that time, the mode of inheritance of this QTL was not clarified, and it was also unclear whether the observed QTL effect was completely or partially caused by mutations in the PRKAG3 gene, which is the only major gene on SSC15 so far known to influence pH24h. In this study, effects of the PRKAG3 gene on meat quality traits were estimated by association analyses. Two substitutions in PRKAG3, p.Ile199Val (p.I199V) and p.Thr30Asn (p.T30N), were found to be segregating in the F(2) population and to significantly affect pH24h and total glycogen in meat, respectively. However, we excluded PRKAG3 as a causative gene for the detected QTL based on the following reasons: (i) the gene was located outside of the QTL confidence interval; (ii) when the PRKAG3 substitution was included as a fixed effect in the QTL model, the F-ratio for the QTL increased rather than decreased; (iii) favourable alleles for pH24h at the QTL and at the PRKAG3 p.I199V locus originated from Erhualian and White Duroc founders, respectively; (iv) more importantly, this QTL showed exclusive maternal expression, differing from the Mendelian expression of PRKAG3. In conclusion, this study is the first to report a maternally-expressed QTL for pH24h on SSC15, which is distinct from PRKAG3.

Quantitative trait loci for meat quality traits in pigs considering imprinting and epistatic effects

The aim of the research was to gain a better understanding of the genomic regulation of meat quality by investigating individual and epistatic QTL in a three-generation full-sib population (Pietrain x crossbred dam line). In total, 386 animals were genotyped for 96 markers. Analysed traits included pH, reflectance value, conductivity, and meat colour. Thirteen significant individual QTL were identified. The most significant QTL were detected on SSC1 and SSC9 for pH, on SSC4 for meat colour, and on SSC8 for conductivity, accounting for 3.4% to 4.7% of the phenotypic variance. Nine significant epistatic QTL pairs were detected accounting for between 5.7% and 10.9% of the phenotypic variance. Epistatic QTL pairs showing the largest effects were for reflectance value between two locations of SSC4, and for pH between SSC10 and SSC13, explaining 9.5% and 10.9% of the phenotypic variance, respectively. This study indicates that meat quality traits are influenced by numerous QTL as well as a complex network of interactions.

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.

Epistatic analysis of carcass characteristics in pigs reveals genomic interactions between quantitative trait loci attributable to additive and dominance genetic effects

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F(2) animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC10, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the melanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance x dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive x dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits.

Mapping quantitative trait loci for feed consumption and feeding behaviors in a White Duroc x Chinese Erhualian resource population

To identify QTL for feed consumption and feeding behavior traits in pigs, ADFI, feed conversion ratio (FCR), number of visits to the feeder per day (NVD), and average feeding rate (AFR) were recorded in 577 F(2) animals from a White Duroc x Chinese Erhualian resource population during the fattening period of 120 to 240 d. A whole genome scan was performed with 183 microsatellites covering the pig genome across the entire resource population. A total of 8 QTL were identified on 5 pig chromosomes, including 3 genome-wide significant QTL for FCR on SSC2, 7, and 9, 1 significant QTL for ADFI on SSC3, and 1 for NVD on SSC7. These QTL were identified for the first time, except for the QTL for FCR on SSC2. Four of the 5 significant QTL were adjacent to the known QTL for growth, carcass, and fat deposition traits, supporting the existence of gene(s) with pleiotropic effects on these traits. White Duroc alleles were generally associated with greater phenotypic values, except for those on SSC7 and 9. Comparison of QTL for feed consumption and feeding behaviors indicated that distinct chromosomes had effects on the 2 types of traits. Characterization of causative gene(s) underlying the identified QTL would shed new light on the genetic basis of feed consumption and feeding behaviors in pigs.

yellow0, a marker for low body weight in Drosophila melanogaster

Marker-assisted selection (MAS) is an important modern breeding technique, but it has been found that the effect of the markers for quantitative trait loci (QTL) is inconsistent, leading in some cases to MAS failure and raising doubts about its effectiveness. Here the model organism Drosophila melanogaster was employed to study whether an effective marker could be found and applied to MAS. We crossed the stock carrying the y (0) marker (a recessive mutation allele of the yellow gene on the X chromosome) with three other stocks carrying corresponding wild-type markers in an F2 design, and found that the y (0) marker was in significant association with low body weight (P<0.001). This association was consistent across different backgrounds and the marker effects in female and male were approximately 0.95 sigma (P) (phenotypic standard deviation) and 0.68 sigma (P), respectively. We next introgressed a fragment via the y (0) marker into a wild stock background over 20 generations of marker-assisted introgression (MAI), and constructed the introgression stock y (0)(OR)20 in which body weight decreased by 13% and 7%, in female and male, respectively, compared to the wild stock (P<0.0001). This indicated that there must be a single QTL for low body weight that is tightly linked to the y (0) marker. We then shortened the introgressed fragment to less than 1.5 cM by a deeper MAI using the y (0) marker and the white marker. This narrower fragment also resulted in a similar decrease in body weight to that induced by y (0)(OR)20, indicating that the QTL for low body weight is located within this less-than-1.5 cM interval. Molecular characteristics of the y (0) marker by PCR amplification and Southern blotting revealed that yellow gene was deficient in the y (0) stock, leading to disappearance of melanin from the cuticle and probably influencing the developmental process. The above results confirmed the existence of effective QTL markers applicable to MAS breeding schemes, and their potential application in breeding new stocks.

An integrated RH map of porcine chromosome 10

BACKGROUND

Whole genome radiation hybrid (WG-RH) maps serve as "scaffolds" to significantly improve the orientation of small bacterial artificial chromosome (BAC) contigs, order genes within the contigs and assist assembly of a sequence-ready map for virtually any species. Here, we report the construction of a porcine: human comparative map for pig (Sus scrofa) chromosome 10 (SSC10) using the IMNpRH2(12,000-rad) porcine WG-RH panel, integrated with the IMpRH(7000-rad) WG-RH, genetic and BAC fingerprinted contig (FPC) maps.

RESULTS

Map vectors from the IMNpRH2(12,000-rad) and IMpRH(7,000-rad) panels were merged to construct parallel framework (FW) maps, within which FW markers common to both panels have an identical order. This strategy reduced map discrepancies between the two panels and significantly improved map accuracy. A total of 216 markers, including 50 microsatellites (MSs), 97 genes and ESTs, and 69 BAC end sequences (BESs), were ordered within two linkage groups at two point (2 pt) LOD score of 8. One linkage group covers SSC10p with accumulated map distances of 738.2 cR(7,000) and 1814.5 cR(12,000), respectively. The second group covers SSC10q at map distances of 1336.9 cR(7,000) and 3353.6 cR(12,000), yielding an overall average map resolution of 16.4 kb/cR(12,000) or 393.5 kb per marker on SSC10. This represents an approximately 2.5-fold increase in map resolution over the IMpRH(7,000-rad) panel. Based on 127 porcine markers that have homologous sequences in the human genome, a detailed comparative map between SSC10 and human (Homo sapiens) chromosome (HSA) 1, 9 and 10 was built.

CONCLUSION

This initial comparative RH map of SSC10 refines the syntenic regions between SSC10 and HSA1, 9 and 10. It integrates the IMNpRH2(12,000-rad) and IMpRH(7,000-rad), genetic and BAC FPC maps and provides a scaffold to close potential gaps between contigs prior to genome sequencing and assembly. This map is also useful in fine mapping of QTLs on SSC10.

Genomic scan for quantitative trait loci of chemical and physical body composition and deposition on pig chromosome X including the pseudoautosomal region of males

A QTL analysis of pig chromosome X (SSCX) was carried out using an approach that accurately takes into account the specific features of sex chromosomes i.e. their heterogeneity, the presence of a pseudoautosomal region and the dosage compensation phenomenon. A three-generation full-sib population of 386 animals was created by crossing Pietrain sires with a crossbred dam line. Phenotypic data on 72 traits were recorded for at least 292 and up to 315 F2 animals including chemical body composition measured on live animals at five target weights ranging from 30 to 140 kg, daily gain and feed intake measured throughout growth, and carcass characteristics obtained at slaughter weight (140 kg). Several significant and suggestive QTL were detected on pig chromosome X: (1) in the pseudoautosomal region of SSCX, a QTL for entire loin weight, which showed paternal imprinting, (2) closely linked to marker SW2456, a suggestive QTL for feed intake at which Pietrain alleles were found to be associated with higher feed intake, which is unexpected for a breed known for its low feed intake capacity, (3) at the telomeric end of the q arm of SSCX, QTL for jowl weight and lipid accretion and (4) suggestive QTL for chemical body composition at 30 kg. These results indicate that SSCX is important for physical and chemical body composition and accretion as well as feed intake regulation.

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only.