Single-marker and haplotype-based genome-wide association studies for the number of teats in two heavy pig breeds

The number of teats is a reproductive‐related trait of great economic relevance as it affects the mothering ability of the sows and thus the number of properly weaned piglets. Moreover, genetic improvement of this trait is fundamental to parallelly help the selection for increased litter size. We present the results of single‐marker and haplotypes‐based genome‐wide association studies for the number of teats in two large cohorts of heavy pig breeds (Italian Large White and Italian Landrace) including 3990 animals genotyped with the 70K GGP Porcine BeadChip and other 1927 animals genotyped with the Illumina PorcineSNP60 BeadChip. In the Italian Large White population, genome scans identified three genome regions (SSC7, SSC10, and SSC12) that confirmed the involvement of the VRTN gene (as we previously reported) and highlighted additional loci known to affect teat counts, including the FRMD4A and HOXB1 gene regions. A different picture emerged in the Italian Landrace population, with a total of 12 genome regions in eight chromosomes (SSC3, SSC6, SSC8, SSC11, SSC13, SSC14, SSC15, and SSC16) mainly detected via the haplotype‐based genome scan. The most relevant QTL was close to the ARL4C gene on SSC15. Markers in the VRTN gene region were not significant in the Italian Landrace breed. The use of both single‐marker and haplotype‐based genome‐wide association analyses can be helpful to exploit and dissect the genome of the pigs of different populations. Overall, the obtained results supported the polygenic nature of the investigated trait and better elucidated its genetic architecture in Italian heavy pigs.

Single-Step Genome Wide Association Study Identifies QTL Signals for Untrimmed and Trimmed Thigh Weight in Italian Crossbred Pigs for Dry-Cured Ham Production

Simple Summary

Along with the traditional traits, swine breeding programs for Italian dry-cured ham production have recently aimed to include novel phenotypes. The identification of the genomic regions underlying such new traits helps to untangle their genetic architecture and may provide useful information to be integrated in genetic selection. With this aim, we estimated genetic parameters and conducted a single step genome wide association studies (GWAS) on untrimmed and trimmed thigh weight considering two pig crossbred lines approved for Italian Protected Designation of Origin ham production. Quantitative trait loci (QTLs) were characterized based on the variance of 10-SNP sliding windows genomic estimated breeding values. In particular, we identified interesting QTL signals on several chromosomes, notably on chromosome 4, 6, 7 and 15. A high heritability and genetic correlation were observed for the two traits under investigation and although independent studies including other pig populations are required to disentangle the possible effects of specific linkage disequilibrium in our population, our findings suggest that such QTL could be investigated in future pig breeding programs to improve the reliability of genomic estimated breeding values for the dry-cured ham production.

Abstract

Protected Designation of Origin (PDO) dry-cured ham is the most important product in the Italian pig breeding industry, mainly oriented to produce heavy pig carcasses to obtain hams of the right weight and maturity. Recently, along with the traditional traits swine breeding programs have aimed to include novel carcass traits. The identification at the genome level of quantitative trait loci (QTLs) affecting such new traits helps to reveal their genetic determinism and may provide information to be integrated in prediction models in order to improve prediction accuracy as well as to identify candidate genes underlying such traits. This study aimed to estimate genetic parameters and perform a single step genome wide association studies (ssGWAS) on novel carcass traits such as untrimmed (UTW) and trimmed thigh weight (TTW) in two pig crossbred lines approved for the ham production of the Italian PDO. With this purpose, phenotypes were collected from ~1800 animals and 240 pigs were genotyped with Illumina PorcineSNP60 Beadchip. The single-step genomic BLUP procedure was used for the heritability estimation and to implement the ssGWAS. QTL were characterized based on the variance of 10-SNP sliding window genomic estimated breeding values. Moderate heritabilities were detected and QTL signals were identified on chromosome 1, 4, 6, 7, 11 and 15 for both traits. As expected, the genetic correlation among the two traits was very high (~0.99). The QTL regions encompassed a total of 249 unique candidate genes, some of which were already reported in association with growth, carcass or ham weight traits in pigs. Although independent studies are required to further verify our findings and disentangle the possible effects of specific linkage disequilibrium in our population, our results support the potential use of such new QTL information in future breeding programs to improve the reliability of genomic prediction.

Multi-breed genome-wide association study reveals novel loci associated with the weight of internal organs

Background

Recently, many genome-wide association studies (GWAS) have been conducted to understand the genetic architecture of economic important traits in farm animals. Pig is widely used as a biomedical animal model for its similarity with humans in terms of organ formation and disease mechanisms. Moreover, understanding the mechanisms that underlie the development of internal organs will impact the productive potential of pigs. Our aim was to uncover new single nucleotide polymorphisms (SNPs) associated with the weight of internal organs and carcass and also potential candidate genes.

Methods

We performed GWAS for the weight of heart, liver, spleen, kidney and carcass on five pig populations (White Duroc × Erhualian F₂ intercross, Sutai population, Laiwu population, Erhualian population and commercial population, for a total of 2650 individuals). Genotype data was produced using the PorcineSNP60 Beadchip array. After quality control, the data was used for association tests under a general linear mixed model. Population stratification was adjusted by including a random polygenic effect based on a matrix of genotypic relationships. A meta-analysis of our GWAS datasets was conducted by summing up the Chi square values across breeds, with the degrees of freedom of the Chi square distribution equal to the effective number of breeds.

Results

Thirty-nine quantitative trait loci (QTL) located on 15 chromosomes were identified by the single-population GWAS at the suggestive level. Among these, nine QTL surpassed the 5 % genome-wide significance threshold, including four for heart weight on SSC (Sus scrofa chromosome) 2, 4, 7 and 10, two for liver weight on SSC7, two for spleen weight on SSC5 and SSC7 and one for carcass weight on SSC11. The QTL on SSC7 showed pleiotropic effects for heart, liver and spleen weights in the F₂ population. In addition, two QTL were detected in several populations, including one on SSC2 for heart weight in the F₂ and Sutai populations and one on SSC7 for liver weight in the F₂ and Laiwu populations. The meta-analysis detected four novel QTL on SSC1, 3, 8 and 16 for carcass weight.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0168-7) contains supplementary material, which is available to authorized users.

A study of vertebra number in pigs confirms the association of vertnin and reveals additional QTL

Background

Formation of the vertebral column is a critical developmental stage in mammals. The strict control of this process has resulted in little variation in number of vertebrae across mammalian species and no variation within most mammalian species. The pig is quite unique as considerable variation exists in number of thoracic vertebrae as well as number of lumbar vertebrae. At least two genes have been identified that affect number of vertebrae in pigs yet considerable genetic variation still exists. Therefore, a genome-wide association (GWA) analysis was conducted to identify additional genomic regions that affect this trait.

Results

A total of 1883 animals were phenotyped for the number of ribs and thoracolumbar vertebrae as well as successfully genotyped with the Illumina Porcine SNP60 BeadChip. After data editing, 41,148 SNP markers were included in the GWA analysis. These animals were also phenotyped for kyphosis. Fifty-three 1 Mb windows each explained at least 1.0 % of the genomic variation for vertebrae counts while 16 regions were significant for kyphosis. Vertnin genotype significantly affected vertebral counts as well. The region with the largest effect for number of lumbar vertebrae and thoracolumbar vertebrae were located over the Hox B gene cluster and the largest association for thoracic vertebrae number was over the Hox A gene cluster. Genetic markers in significant regions accounted for approximately 50 % of the genomic variation. Less genomic variation for kyphosis was described by QTL regions and no region was associated with kyphosis and vertebra counts.

Conclusions

The importance of the Hox gene families in vertebral development was highlighted as significant associations were detected over the A, B and C families. Further evaluation of these regions and characterization of variants within these genes will expand our knowledge on vertebral development using natural genetic variants segregating in commercial swine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0286-9) contains supplementary material, which is available to authorized users.

Fine mapping and single nucleotide polymorphism effects estimation on pig chromosomes 1, 4, 7, 8, 17 and X

Fine mapping of quantitative trait loci (QTL) from previous linkage studies was performed on pig chromosomes 1, 4, 7, 8, 17, and X which were known to harbor QTL. Traits were divided into: growth performance, carcass, internal organs, cut yields, and meat quality. Fifty families were used of a F2 population produced by crossing local Brazilian Piau boars with commercial sows. The linkage map consisted of 237 SNP and 37 microsatellite markers covering 866 centimorgans. QTL were identified by regression interval mapping using GridQTL. Individual marker effects were estimated by Bayesian LASSO regression using R. In total, 32 QTL affecting the evaluated traits were detected along the chromosomes studied. Seven of the QTL were known from previous studies using our F2 population, and 25 novel QTL resulted from the increased marker coverage. Six of the seven QTL that were significant at the 5% genome-wide level had SNPs within their confidence interval whose effects were among the 5% largest effects. The combined use of microsatellites along with SNP markers increased the saturation of the genome map and led to smaller confidence intervals of the QTL. The results showed that the tested models yield similar improvements in QTL mapping accuracy.

Genomic growth curves of an outbred pig population

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

A proximal genomic region of mouse chromosome 10 contains quantitative trait loci affecting fatness

Body weight and fatness are quantitative traits of agricultural and medical importance. In previous genome-wide quantitative trait locus (QTL) analyses, two QTLs for body weight and weight gain at an early postnatal growth period were discovered on mouse chromosome 10 from a gene pool of wild subspecies mice, Mus musculus castaneus. In this study, we developed a congenic strain with an approximately 63-Mb wild-derived genomic region on which the two growth QTLs could be located, by recurrent backcrossing to the common inbred strain C57BL/6J. We compared body weights at 1-10 weeks of age, body weight gains at 1-3, 3-6 and 6-10 weeks, internal organ weights and body lengths between the congenic strain developed and C57BL/6J. Unfortunately, no effects of the two growth QTLs on body weights and weight gains were confirmed. However, at least two new QTLs affecting fatness traits were discovered within the introgressed congenic region. The wild-derived allele at one QTL increased body mass index, whereas at another one it decreased white fat pad weight and adiposity index. Thus, the congenic mouse strain developed here is a useful model animal for understanding the genetic and molecular basis of fat deposition in livestock as well as humans.

Quantitative trait loci analysis of swine meat quality traits

A QTL study was performed in large half-sib families to characterize the genetic background of variation in pork quality traits as well as to examine the possibilities of including QTL in a marker-assisted selection scheme. The quality traits included ultimate pH in LM and the semimembranosus, drip loss, and the Minolta color measurements L*, a*, and b* representing meat lightness, redness, and yellowness, respectively. The families consist of 3,883 progenies of 12 Duroc boars that were evaluated to identify the QTL. The linkage map consists of 462 SNP markers on 18 porcine autosomes. Quantitative trait loci were mapped using a linear mixed model with fixed factors (sire, sex, herd, month, sow age) and random factors (polygenic effect, QTL effects, and litter). Chromosome-wide and genome-wide significance thresholds were determined by Peipho's approach, and 95% Bayes credibility intervals were estimated from a posterior distribution of the QTL position. In total, 31 QTL for the 6 meat quality traits were found to be significant at the 5% chromosome-wide level, among which 11 QTL were significant at the 5% genome-wide level and 5 of these were significant at the 0.1% genome-wide level. Segregation of the identified QTL in different families was also investigated. Most of the identified QTL segregated in 1 or 2 families. For the QTL affecting ultimate pH in LM and semimembranosus and L* and b* value on SSC6, the positions of the QTL and the shapes of the likelihood curves were almost the same. In addition, a strong correlation of the estimated effects of these QTL was found between the 4 traits, indicating that the same genes control these traits. A similar pattern was seen on SSC15 for the QTL affecting ultimate pH in the 2 muscles and drip loss. The results from this study will be helpful for fine mapping and identifying genes affecting meat quality traits, and tightly linked markers may be incorporated into marker-assisted selection programs.

Haplotypes of the porcine peroxisome proliferator-activated receptor delta gene are associated with backfat thickness

BACKGROUND

Peroxisome proliferator-activated receptor delta belongs to the nuclear receptor superfamily of ligand-inducible transcription factors. It is a key regulator of lipid metabolism. The peroxisome proliferator-activated receptor delta gene (PPARD) has been assigned to a region on porcine chromosome 7, which harbours a quantitative trait locus for backfat. Thus, PPARD is considered a functional and positional candidate gene for backfat thickness. The purpose of this study was to test this candidate gene hypothesis in a cross of breeds that were highly divergent in lipid deposition characteristics.

RESULTS

Screening for genetic variation in porcine PPARD revealed only silent mutations. Nevertheless, significant associations between PPARD haplotypes and backfat thickness were observed in the F2 generation of the Mangalitsa x Piétrain cross as well as a commercial German Landrace population. Haplotype 5 is associated with increased backfat in F2 Mangalitsa x Piétrain pigs, whereas haplotype 4 is associated with lower backfat thickness in the German Landrace population. Haplotype 4 and 5 carry the same alleles at all but one SNP. Interestingly, the opposite effects of PPARD haplotypes 4 and 5 on backfat thickness are reflected by opposite effects of these two haplotypes on PPAR-delta mRNA levels. Haplotype 4 significantly increases PPAR-delta mRNA levels, whereas haplotype 5 decreases mRNA levels of PPAR-delta.

CONCLUSION

This study provides evidence for an association between PPARD and backfat thickness. The association is substantiated by mRNA quantification. Further studies are required to clarify, whether the observed associations are caused by PPARD or are the result of linkage disequilibrium with a causal variant in a neighbouring gene.

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.

Combined line-cross and half-sib QTL analysis in Duroc-Pietrain population

A Duroc-Pietrain resource population was built to detect quantitative trait loci (QTL) that affect growth, carcass composition, and pork quality. The data were analyzed by applying three least-squares Mendelian models: a line-cross (LC) model, a half-sib (HS) model, and a combined LC and HS model (CB), which enabled the detection of QTL that had fixed, equal, and different allele frequencies for alternate breed alleles, respectively. Permutation tests were performed to determine 5% chromosome-wide and 5% genome-wide threshold values. A total of 40 (137) QTL were detected at the 5% genome-wide (chromosome-wide) level for the 35 traits analyzed. Of the 137 QTL detected, 62 were classified as the LC type (LC-QTL), 47 as the HS type (HS-QTL), and 28 as the CB type (CB-QTL). The results indicate that implementation of a series of model-based framework is not only beneficial to detect QTL, but also provides us with a new and more robust interpretation from which further methodology could be developed.

Single nucleotide polymorphisms in several porcine cathepsin genes are associated with growth, carcass, and production traits in Italian Large White pigs

To identify DNA markers associated with performance, carcass, and meat production traits including muscle postmortem cathepsin activity, several porcine genes encoding for lysosomal proteinases (cathepsin B, CTSB; cathepsin D, CTSD; cathepsin F, CTSF; cathepsin H, CTSH; cathepsin L, CTSL; and cathepsin Z, CTSZ) and for a cathepsin inhibitor (cystatin B) were investigated. Single nucleotide polymorphisms were identified in CTSD, CTSH, CTSL, and CTSZ genes with a combination of in silico expressed sequence tag database mining and single-strand conformation polymorphism analysis. Sequencing and PCR-RFLP protocols were used to validate the identified polymorphisms. Allele frequencies at these loci were investigated in Italian Large White, Landrace, Duroc, Piétrain, Belgian Landrace, Hampshire, and Meishan breeds. Genotyping CTSD and CTSH markers made it possible to genetically map these genes to SSC 2 and 7, respectively. Markers in CTSD, CTSH, CTSL, and CTSZ genes, together with mutations we previously reported in cystatin B, CTSB, and CTSF genes, were genotyped in an Italian Large White sib-tested population (272 or 482 animals). For these animals, meat quality traits (cathepsin B activity, pH measured at 2 h postmortem, pH measured at 24 h postmortem, glycogen, lactate, and glycolytic potential of semimembranosus muscle) and EBV for ADG, lean cuts (LC), backfat thickness (BFT), ham weight (HW), and feed:gain ratio (FGR) were determined. Analyzed markers did not show any association with muscle cathepsin B activity. Thus, it could be possible that different genes, other than these investigated candidates, affect this trait, which is correlated with the excessive softness defect of dry-cured hams. The results of association analysis confirmed the effects we already reported in another study for CTSF on ADG (P = 0.008), LC (P = 0.001), and BFT (P = 0.02). Moreover, CTSD was associated with ADG, LC (P < 0.0001), BFT, HW, and FGR (P < 0.001); CTSH was associated with FGR (P = 0.026); and CTSZ was associated with ADG (P = 0.006), LC (P = 0.01), HW (P = 0.024), and FGR (P = 0.029). The biochemical and physiological functions of the lysosomal proteinases, together with the results obtained in our investigation, suggest that the cathepsin gene family might play important roles affecting economic traits in pigs.

Quantitative trait loci for production traits in pigs: a combined analysis of two Meishan x Large White populations

Combined analysis of data from two or more resource populations can improve the power and accuracy of QTL mapping and allow some cross-validation of results. In this study, we performed a genome-wide scan using combined data from two F(2) populations derived from a cross between Large White and Chinese Meishan pigs. A total of 739 pigs were included in the analysis. In total 187 markers were genotyped in the two populations, including 115 markers genotyped in both populations, and these markers covered 2282 cM of the pig genome with an average of 13.58 cM between markers. Seven traits (teat number, birth weight, weaning weight, test-end weight, fat depth at shoulder, fat depth at mid back and fat depth at loin) were analysed for both individual populations and the combined population. There were 9 (2, 10), 1 (4, 4) and 14 (5, 18) QTL that achieved 1% genome-wide, 5% genome-wide and suggestive significance levels respectively in population 1 (population 2, combined population). Additive effects of QTL detected in the two populations at all significance levels were largely consistent suggesting that the QTL represent real genetic effects, but this was not the case for dominance or imprinting effects. There were also a number of significant interactions between detected QTL effects and population.

Investigation of candidate genes for glycolytic potential of porcine skeletal muscle: Association with meat quality and production traits in Italian Large White pigs

The objective of this study was to investigate the association of DNA markers in candidate genes for glycolytic potential on meat quality parameters (pH(1), pH(u), glycogen and lactate content and glycolytic potential of semimembranosus muscle) and estimated breeding values (EBVs) for average daily gain, lean cuts, back fat thickness, ham weight, and feed:gain ratio in 272 Italian Large White pigs. Three mutations in the PRKAG3 gene (T30N, G52S and I199V) were investigated as well as single nucleotide polymorphisms in two other skeletal muscle genes (PGAM2 and PKM2) involved in the glycolytic pathway. Association analysis with the PRKAG3 markers showed significant results (P<0.05) only for pH(1) (I199V, with significant additive effect) and lactate content (T30N), confirming, at least in part, the effects of this gene on meat quality traits. Significant association (P<0.05) was also observed for PGAM2 and ham weight EBV with significant additive and dominance effects. PKM2 was associated with average daily gain, lean cuts (P<0.001), back fat thickness and feed:gain ratio (P<0.05), with significant additive and/or dominance effects on these traits. PKM2 encodes for a key enzyme of the muscle glycolytic pathway and maps on porcine chromosome 7 where other studies have reported important QTL for the same traits. These data might suggest an important function of this gene in the mechanisms that produce the observed effects. The results will be important to evaluate the inclusion of some of these DNA polymorphisms in marker assisted selection programs.

A QTL study of growth and body shape in the inter-species hybrid of Père David's deer (Elaphurus davidianus) and red deer (Cervus elaphus)

An interspecies deer hybrid resource population developed from a cross of Père David's and red deer was used to detect QTL that account for species differences. A genome scan, coupled with composite interval mapping, was conducted to search for QTL controlling body measurements at pre-pubescent age (6 months of age) and puberty (15 months of age) in this interspecies hybrid. Five linkage groups that harbour QTL affecting morphology were identified. A joint-traits analysis was used to search for putative pleiotropic QTL on four of these linkage groups, and three were significantly associated with pleiotropic QTL for nose width and foot length (metacarpal and phalanges), which collectively accounted for 29-58% of the phenotypic difference between the two deer species. This study suggests that a few loci with large pleiotropic effects may be responsible for species-specific differences in growth and structure-related traits.

Detection of Quantitative Trait Loci Associated with Several Internal Organ Traits and Teat Number Trait in a Pig Population

Quantitative trait loci (QTL) were detected for 8 internal organ traits, 3 carcass length traits, and teat number trait in 214 pigs in a resource population that included 180 F(2) individuals. A total of 39 microsatellite markers were examined on SSC4, SSC6, SSC7, SSC8, and SSC13. The genetic traits included heart weight (HW), lung weight (LW), liver and gallbladder weight (LGW), spleen weight (SPW), stomach weight (STW), small intestine weight (SIW), large intestine weight (LIW), kidney weight (KW), carcass length to the first cervical vertebra (CL1), carcass length to the first thoracic vertebra (CL2), rib numbers (RNS), and teat numbers (TNS). Results indicated that, 3 highly significant QTL (P <or= 0.01 at chromosome-wise level) for HW (at 30 cM on SSC6), RNS (at 115 cM on SSC7), TNS (at 110 cM on SSC7), and 6 significant QTL (P <or= 0.05 at chromosome-wise level) for LW (at 119 cM on SSC13), LGW (at 94 cM on SSC6), SPW (at 106 cM on SSC8), SIW (0 cM on SSC4), LIW (170 cM on SSC 4), and TNS (at 95 cM on SSC6) were detected. The phenotypic variances for which these QTL were accounted ranged from 0.04 % to 14.06 %. Most of these QTL had not been previously reported.

Results of a whole-genome quantitative trait locus scan for growth, carcass composition and meat quality in a porcine four-way cross

A whole-genome quantitative trait locus (QTL) scan for 31 phenotypes related to growth, carcass composition and meat quality was conducted using 1187 progeny of a commercial four-way cross. Animals were genotyped for 198 microsatellite markers that spanned the entire porcine genome. QTL analysis was conducted to extract information from paternal and maternal meioses separately using a rank-based nonparametric approach for half-sib designs. Nine QTL exceeded genome-wide significance: one QTL affecting growth (average daily gain on SSC1), two QTL influencing carcass composition (fatness on SSC3 and muscle mass on SSC15) and six QTL influencing meat quality (tenderness on SSC4 and SSC14; colour on SSC5, SSC6 and SSCX; and conductivity on SSC16). All but one of these coincided with previously reported QTL. In addition, we present evidence for 78 suggestive QTL with a combined false discovery rate of 40%.

SNP detection and genetic mapping of porcine genes encoding enzymes in hepatic metabolic pathways and evaluation of linkage with carcass traits

We have previously identified and mapped porcine expressed sequence tags (ESTs) derived from genes that are preferentially expressed in liver. The aim of the present study was to identify single nucleotide polymorphisms (SNPs) in porcine genes encoding enzymes in hepatic metabolic pathways and use the SNPs for mapping. Furthermore, these genes, which are involved in utilization and partitioning of nutrients, were examined for their effects on carcass and meat quality traits by linkage analyses. In total, 100 ESTs were screened for SNPs by single strand conformation polymorphism analyses across a diverse panel of animals with a 36% success rate. Twelve of 36 polymorphic loci segregated in a three-generation Duroc x Berlin Miniature Pig (F2) resource population, the DUMI resource population, and were genetically mapped. Interval mapping of the corresponding chromosomes was performed to verify mapping of the genes within quantitative trait loci (QTL) regions detected in this resource population. QTL with genome-wide significance were detected in the vicinity of GNMT, ESTL147 and HGD. These loci therefore are positional candidate genes.