Phenotypic prediction based on metabolomic data for growing pigs from three main European breeds.

Predicting phenotypes is a statistical and biotechnical challenge, both in medicine (predicting an illness) and animal breeding (predicting the carcass economical value on a young living animal). High-throughput fine phenotyping is possible using metabolomics, which describes the global metabolic status of an individual, and is the closest to the terminal phenotype. The purpose of this work was to quantify the prediction power of metabolomic profiles for commonly used production phenotypes from a single blood sample from growing pigs. Several statistical approaches were investigated and compared on the basis of cross validation: raw data vs. signal preprocessing (wavelet transformation), with a single-feature selection method. The best results in terms of prediction accuracy were obtained when data were preprocessed using wavelet transformations on the Daubechies basis. The phenotypes related to meat quality were not well predicted because the blood sample was taken some time before slaughter, and slaughter is known to have a strong influence on these traits. By contrast, phenotypes of potential economic interest (e.g., lean meat percentage and ADFI) were well predicted (R(2) = 0.7; P < 0.0001) using metabolomic data.

Molecular characterization of the porcine TEAD3 (TEF-5) gene: examination of a promoter mutation as the causal mutation of a quantitative trait loci affecting the androstenone level in boar fat.

A quantitative trait loci (QTL) for accumulation of androstenone in fat has been identified in an Large White × Meishan cross in a region of SSC7-containing TEAD3. In humans, TEAD3 is a transcription activator, known to be able to regulate the transcription of HSD3B. This enzyme is involved in the degradation of androstenone in the liver. In this study, porcine transcripts of TEAD3 were characterized and compared with mammalian transcripts. The complete structure of porcine TEAD3 gene was characterized including two 5' non-coding exons and one exon 5 not used in porcine transcripts. Variations were screened in sequences related to TEAD3: in exons, in flanking sequences of exons and in the promoter region. A SNP characterized at 726 bp at 5' of the first exon was tested on several pig populations without coherent and convincing results concerning its association with androstenone levels. We showed that in the liver of adult boars, the transcripts levels of TEAD3 and HSD3B were correlated. As in humans, it is possible that HSD3B is a target gene of TEAD3 in porcine liver. Nevertheless, no expression variation was observed for TEAD3 or HSD3B in liver between animals with different genotypes at the SNP. We concluded that this SNP was not the causal mutation of this QTL.

Microsatellite mapping of quantitative trait loci affecting female reproductive tract characteristics in Meishan x Large White F(2) pigs.

A QTL analysis of female reproductive data from a 3-generation experimental cross between Meishan and Large White pig breeds is presented. Six F(1) boars and 23 F(1) sows, progeny of 6 Large White boars and 6 Meishan sows, produced 502 F(2) gilts whose reproductive tract was collected after slaughter at 30 d of gestation. Five traits [i.e., the total weight of the reproductive tract, of the empty uterine horns, of the ovaries (WOV), and of the embryos], as well as the length of uterine horns (LUH), were measured and analyzed with and without adjustment for litter size. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross regression and a half-full sib maximum likelihood test. A total of 18 genome-wide significant (P < 0.05) QTL were detected on 9 different chromosomes (i.e., SSC 1, 5, 6, 7, 9, 12, 13, 18, and X). Five genome-wide significant QTL were detected for LUH, 4 for weight of the empty uterine horns and WOV, 2 for total weight of the reproductive tract, and 1 for weight of the embryos. Twenty-two additional suggestive QTL were also detected. The largest effects were obtained for LUH and WOV on SSC13 (9.2 and 7.0% of trait phenotypic variance, respectively). Meishan alleles had both positive (e.g., on SSC7) and negative effects (e.g., on SSC13) on the traits investigated. Moreover, the QTL were generally not fixed in founder breeds, and opposite effects were in some cases obtained in different families. Although reproductive tract characteristics had only a moderate correlation with reproductive performances, most of the major QTL detected in this study were previously reported as affecting female reproduction, generally with reduced significance levels. This study thus shows that focusing on traits with high heritability might help to detect loci involved in low heritability major traits for breeding.

Microsatellite mapping of quantitative trait loci affecting meat quality, stress hormones and production traits in Duroc × Large White F2 pigs.

An F2 cross between Duroc and Large White pigs was carried out in order to detect quantitative trait loci (QTL) for 11 meat quality traits (L*, a* and b* Minolta coordinates and water-holding capacity (WHC) of two ham muscles, ultimate pH of two ham and one loin muscles), 13 production traits (birth weight, average daily gain during post-weaning and fattening periods, carcass fat depths at three locations, estimated lean meat content, carcass length and weights of five carcass cuts) and three stress hormone-level traits (cortisol, adrenaline and noradrenaline). Animals from the three generations of the experimental design (including 456 F2 pigs) were genotyped for 91 microsatellite markers covering all the autosomes. A total of 56 QTL were detected: 49 reached the chromosome-wide level (suggestive QTL with a maximal probability of 0.05) and seven were significant at the genome-wide level (with a probability varying from 6 × 10(-4) to 3 × 10(-3)). Twenty suggestive QTL were identified for ultimate pH, colour measurements and WHC on chromosome (SSC) 5, 6, 7, 8, 9, 11, 13, 14, 15 and 17. For production traits, 33 QTL were detected on all autosomes except SSC6, 8 and 9. Seven of these QTL, located on SSC2, 3, 10, 13, 16 and 17, exceeded the genome-wide significance threshold. Finally, three QTL were identified for levels of stress hormones: a QTL for cortisol level on SSC7 in the cortisol-binding globulin gene region, a QTL for adrenaline level on SSC10 and a QTL for noradrenaline level on SSC13. Among all the detected QTL, seven are described for the first time: a QTL for ultimate pH measurement on SSC5, two QTL affecting birth weight on SSC2 and 10, two QTL for growth rate on SSC15 (during fattening) and 17 (during post-weaning) and two QTL affecting the adrenaline and noradrenaline levels. For each QTL, only one to five of the six F1 sires were found to be heterozygous. It means that all QTL are segregating in at least one of the founder populations used in this study. These results suggest that both meat quality and production traits can be improved in purebred Duroc and Large White pigs through marker-assisted selection. It is of particular interest for meat quality traits, which are difficult to include in classical selection programmes.

Detection of quantitative trait loci for teat number and female reproductive traits in Meishan × Large White F2 pigs.

A quantitative trait locus (QTL) analysis of female reproductive data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six F1 boars and 23 F1 sows, progeny of six LW boars and six MS sows, produced 573 F2 females and 530 F2 males. Six traits, i.e. teat number (TN), age at puberty (AP), ovulation rate (OR), weight at mating (WTM), number of viable embryos (NVE) and embryo survival (ES) at 30 days of gestation were analysed. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross (LC) regression and a half-full sib (HFS) maximum likelihood test. Genome-wide (GW) highly significant (P < 0.001) QTL were detected for WTM on SSC 7 and for AP on SSC 13. They explained, respectively, 14.5% and 8.9% of the trait phenotypic variance. Other GW significant (P < 0.05) QTL were detected for TN on SSC 3, 7, 8, 16 and 17, for OR on SSC 4 and 5, and for ES on SSC 9. Two additional chromosome-wide significant (P < 0.05) QTL were detected for TN, three for WTM, four for AP, three for OR, three for NVE and two for ES. With the exception of the two above-mentioned loci, the QTL explained from 1.2% to 4.6% of trait phenotypic variance. QTL alleles were in most cases not fixed in the grand-parental populations and Meishan alleles were not systematically associated with higher reproductive performance.

Effects of quantitative trait loci on chromosomes 1, 2, 4, and 7 on growth, carcass, and meat quality traits in backcross Meishan x Large White pigs.

The aim of this work was to estimate whether genetic dissection of QTL on chromosomes 1, 2, 4, and 7, detected in an F2 Meishan x Large White population, can be achieved with a recombinant back-cross progeny test approach. For this purpose, a first generation of backcross (BC1) was produced by using frozen semen of F1 Large White x Meishan boars with Large White females. Four BC1 boars were selected because of their heterozygosity for at least 1 of the 4 regions. The BC1 boars were crossed with Large White sows, and the resulting BC2 offspring were measured for several growth and body composition traits. Contrary to the F2 animals, BC2 animals were also measured for meat quality traits in adductor, gluteus superficialis (GS), longissimus dorsi, and biceps femoris (BF) muscles. Each BC1 boar was tested for a total of 39 traits and for the 4 regions with statistical interval mapping analyses. The QTL effects obtained in BC1 families showed some differences compared with those described in F1 families. However, we confirmed QTL effects for growth in the SW1301-SW2512 markers interval on chromosome 1 and also for body composition in the SW1828-SW2512 markers interval on chromosome 1, in the SW2443-SWR783 markers interval on chromosome 2, and in the SW1369-SW632 markers interval on chromosome 7. In addition, we detected new QTL for growth traits on chromosome 2 and for meat quality traits on chromosomes 1 and 2. Growth of animals from weaning to the end of the test was influenced by the IGF2 gene region on chromosome 2. Concerning meat quality, ultimate pH of adductor, longissimus dorsi, and BF were affected by the interval delimited by UMNP3000 and SW2512 markers on chromosome 1, and a* of GS, L* of BF, and water-holding capacity of GS were affected by QTL located between marker loci SW2443 and SWR783 on chromosome 2. Recombinant progeny testing appeared to be a suitable strategy for the genetic dissection of the QTL investigated.

Exclusion of the swine leukocyte antigens as candidate region and reduction of the position interval for the Sus scrofa chromosome 7 QTL affecting growth and fatness.

Pig chromosome 7 (SSC 7) has been shown to be rich in QTL affecting performance and quality traits. Most studies mapped the QTL close to the swine leukocyte antigens (SLA), which has a large effect on adaptability and natural selection. Previous comparative mapping studies suggested that the 15-cM region limited by markers LRA1 (mapped at 55 cM) and S0102 (mapped at 70 cM) contains hundreds of genes. To decrease the number of candidate genes, we improved the mapping resolution with a genetic chromosome dissection through a backcross recombinant progeny test program between Meishan (MS) and European (EU; i.e., Large White or Landrace) breeds. Three first-generation backcross--(EU x MS) x EU--and two second-generation backcross--([EU x MS] x EU) x EU--sires carrying a recombination in the QTL mapping interval were progeny-tested (i.e., measured for a total of 44 growth, fatness, carcass and meat quality traits). Progeny family size varied from 29 to 119 pigs. Animals were genotyped for markers covering the region of interest. Progeny-test results allowed the QTL interval to be decreased from 15 to 20 cM down to 10 cM, and even less than 6 cM if we assumed that the EU pigs used in this study share only one QTL allele. Except for a putative QTL affecting some carcass composition traits, the SLA is excluded as a candidate region, suggesting that it might be possible to apply a marker-assisted selection strategy for this QTL, while controlling SLA allele diversity. The strong QTL effects remaining in animals with only 12.5% (issued from first-generation backcross boars) and 6.25% (issued from second-generation back-cross boars) Meishan genetic background shows that epistatic interactions are likely to be limited. Finally, the QTL does not have strong effects on meat quality traits.

Detection of quantitative trait loci for fat androstenone levels in pigs.

A QTL analysis of fat androstenone levels from a three-generation experimental cross between Large White and Meishan pig breeds was carried out. A total of 485 F2 males grouped in 24 full-sib families, their 29 parents and 12 grandparents were typed for 137 markers distributed over the entire porcine genome. The F2 male population was measured for fat androstenone levels at 100, 120, 140, and 160 d of age and at slaughter around 80 kg liveweight. Statistical analyses were performed using two interval mapping methods: a line-cross (LC) regression method, which assumes alternative alleles are fixed in founder lines, and a half- full-sib (HFS) maximum likelihood method, where allele substitution effects were estimated within each half- and full-sib family. Both methods revealed genomewide significant gene effects on chromosomes 3, 7, and 14. The QTL explained, respectively, 7 to 11%, 11 to 15%, and 6 to 8% of phenotypic variance. Three additional significant QTL explaining 4 to 7% of variance were detected on chromosomes 4 and 9 using LC method and on chromosome 6 using HFS method. Suggestive QTL were also obtained on chromosomes 2, 10, 11, 13, and 18. Meishan alleles were associated with higher androstenone levels, except on chromosomes 7, 10, and 13, although 10 and 13 additive effects were near zero. The QTL had essentially additive effects, except on chromosomes 4, 10, and 13. No evidence of linked QTL or imprinting effects on androstenone concentration could be found across the entire porcine genome. The steroid chromosome P450 21-hydroxylase (CYP21) and cytochrome P450 cholesterol side chain cleavage subfamily XIA (CYP11A) loci were investigated as possible candidate genes for the chromosome 7 QTL. No mutation of coding sequence has been found for CYP21. Involvement of a candidate regulatory mutation of CYP11A gene proposed by others can be excluded in our animals.

A new contribution to the integration of human and porcine genome maps: 623 new points of homology.

In this study we examined homologies between 1,735 porcine microsatellites and human sequence. For 1,710 microsatellites we directly used the sequence flanking the repeat available in GenBank. For a set of 305 microsatellites, a BAC library was screened and end-sequencing provided 461 additional sequences. Altogether 2,171 porcine sequences were tentatively aligned with the sequence of the human genome using the fasta program. Human homologies were observed for 652 microsatellite loci and porcine chromosome assignments available for 623 microsatellites provide useful links in the human and pig comparative map. Moreover for 92 STS, a significant sequence similarity was detected using at least two sequences and in all cases corresponding human locations were consistent. The present study allowed the integration of anonymous markers and the porcine linkage map into the framework of the comparative data between human and porcine genomes (http://w3.toulouse.inra.fr/lgc/pig/msat/). Moreover all conserved syntenic segments were defined on human chromosomes.

Genetic linkage mapping of quantitative trait loci for behavioral and neuroendocrine stress response traits in pigs.

A QTL analysis of behavioral and neuroendocrine responses to a "novel environment" stress was conducted in a three-generation experimental cross between Meishan and Large White pig breeds. A total of 186 F2 males and 182 F2 females were studied for their behavioral and neuroendocrine reactivity to a novel environment test at 6 wk of age. Locomotion, vocalization, and defecation rate, as well as exploration time, were measured for 10 min. Blood samples were taken immediately before and after the test to measure plasma levels of ACTH, cortisol, and glucose. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross regression method, where founder lines were assumed to be fixed for different QTL alleles, and a half-/full-sib maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed a highly significant gene effect for poststress cortisol level (P < 0.001) and a significant effect for basal cortisol level (P < 0.05) at the end of the q arm of chromosome 7, explaining, respectively, 20% and 7% of the phenotypic variance. Meishan alleles are associated with higher cortisol levels and are partially dominant (for poststress levels) over Large White alleles. Other significant gene effects on biological measures were detected on chromosomes 1 and 17 (ACTH response to stress), 3, 5, and 8 (glucose levels). The SSC 17 QTL explains 12% of the phenotypic variance of poststress ACTH levels, with a suggestive evidence of imprinting effects. Meishan alleles are associated with lower poststress ACTH levels. Gene effects of low amplitude only were found for behavioral reactivity traits. Considering the effects of stress neuroendocrine systems on energy fluxes and protein deposition, and the importance of stress reactivity for meat quality and animal welfare, these results open new perspectives for pig selection.

Detection of quantitative trait loci for growth and fatness in pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.

A mutation in PRKAG3 associated with excess glycogen content in pig skeletal muscle.

A high proportion of purebred Hampshire pigs carries the dominant RN- mutation, which causes high glycogen content in skeletal muscle. The mutation has beneficial effects on meat content but detrimental effects on processing yield. Here, it is shown that the mutation is a nonconservative substitution (R200Q) in the PRKAG3 gene, which encodes a muscle-specific isoform of the regulatory gamma subunit of adenosine monophosphate-activated protein kinase (AMPK). Loss-of-function mutations in the homologous gene in yeast (SNF4) cause defects in glucose metabolism, including glycogen storage. Further analysis of the PRKAG3 signaling pathway may provide insights into muscle physiology as well as the pathogenesis of noninsulin-dependent diabetes mellitus in humans, a metabolic disorder associated with impaired glycogen synthesis.

Genetic diversity of eleven European pig breeds.

A set of eleven pig breeds originating from six European countries, and including a small sample of wild pigs, was chosen for this study of genetic diversity. Diversity was evaluated on the basis of 18 microsatellite markers typed over a total of 483 DNA samples collected. Average breed heterozygosity varied from 0.35 to 0.60. Genotypic frequencies generally agreed with Hardy-Weinberg expectations, apart from the German Landrace and Schwäbisch-Hällisches breeds, which showed significantly reduced heterozygosity. Breed differentiation was significant as shown by the high among-breed fixation index (overall F(ST)= 0.27), and confirmed by the clustering based on the genetic distances between individuals, which grouped essentially all individuals in 11 clusters corresponding to the 11 breeds. The genetic distances between breeds were first used to construct phylogenetic trees. The trees indicated that a genetic drift model might explain the divergence of the two German breeds, but no reliable phylogeny could be inferred among the remaining breeds. The same distances were also used to measure the global diversity of the set of breeds considered, and to evaluate the marginal loss of diversity attached to each breed. In that respect, the French Basque breed appeared to be the most "unique" in the set considered. This study, which remains to be extended to a larger set of European breeds, indicates that using genetic distances between breeds of farm animals in a classical taxonomic approach may not give clear resolution, but points to their usefulness in a prospective evaluation of diversity.