Single- and joint-population analyses of two experimental pig crosses to confirm quantitative trait loci on Sus scrofa chromosome 6 and leptin receptor effects on fatness and growth traits

The primary goal of this study was to detect and confirm QTL on SSC6 for growth and fatness traits in 2 experimental F(2) intercrosses: Iberian x Landrace (IB x LR) and Iberian x Meishan (IB x MS), which were used in this study for the first time in a QTL analysis related to productive traits. For this purpose, single- and joint-population analyses with single and bivariate trait models of both populations were performed. The presence of the SSC6 QTL for backfat thickness previously identified in the IB x LR cross was detected in this population with additional molecular information, but also was confirmed in the IB x MS cross. In addition, a QTL affecting BW was detected in both crosses in a similar position to the QTL detected for backfat thickness. This is the first study in which a QTL affecting BW is detected on SSC6 in the IB x LR cross, as well as in the IB x MS resource population. Furthermore, we analyzed a previously described nonsynonymous leptin receptor (LEPR) SNP located in exon 14 (c.2002C > T) for causality with respect to this QTL within both F(2) populations. Our results supported the previously reported association between LEPR alleles and backfat thickness in the IB x LR cross, and this association was also confirmed within the IB x MS cross. An association not reported before between LEPR alleles and BW was identified in both populations.     

Evaluation of approaches to detect quantitative trait loci for growth, carcass, and meat quality on swine chromosomes 2, 6, 13, and 18. I. Univariate outbred F2 and sib-pair analyses

Results from univariate outbred F2 interval mapping and sib-pair analyses of 12 growth and 28 carcass traits to identify QTL on SSC 2, 6, 13, and 18 were compared. Phenotypic and genetic data were recorded on a three-generation resource population including 832 F2 pigs from a cross between three Berkshire sires and 18 Duroc dams. Thirty markers with an average spacing of approximately 16 cM were genotyped across the four chromosomes. The outbred F2 mixed model included the effects of sex, birth month, and year, one-QTL additive, dominance and imprinting coefficients calculated every 1 cM using interval mapping, and a random family effect. The general sib-pair model used to describe the phenotypic differences between sib-pairs included the same systematic and random effects and a one-QTL additive coefficient calculated every 1 cM. The outbred F2 analysis found significant evidence of QTL on SSC 2 associated with 105-d weight, backfat thicknesses, LM area, fat percent, shear force, juiciness, marbling, and tenderness. In addition, QTL were identified on SSC 6 relating to 42-d weight and LM area, and on SSC 18 for fat and moisture percents. In most instances, the outbred F2 approach offered greater power to detect QTL; however, the sib-pair analysis offered greater power in several instances. The trait-specific superiority could be due to the relative advantage of each model within a trait data set. The two approaches provided complementary evidence for QTL segregating between the Berkshire and Duroc breeds used in the study that may be used to aid marker-assisted introgression and selection and candidate gene studies to improve swine growth and meat quality characteristics.     

Quantitative trait loci mapping in an F2 Duroc x Pietrain resource population: I. Growth traits

Pigs from the F(2) generation of a Duroc x Pietrain resource population were evaluated to discover QTL affecting growth and composition traits. Body weight and ultrasound estimates of 10th-rib backfat, last-rib backfat, and LM area were serially measured throughout development. Estimates of fat-free total lean, total body fat, empty body protein, empty body lipid, and ADG from 10 to 22 wk of age were calculated, and random regression analyses were performed to estimate individual animal phenotypes representing intercept and linear rates of increase in these serial traits. A total of 510 F(2) animals were genotyped for 124 micro-satellite markers evenly spaced across the genome. Data were analyzed with line cross, least squares regression, interval mapping methods using sex and litter as fixed effects. Significance thresholds of the F-statistic for single QTL with additive, dominance, or imprinted effects were determined at the chromosome- and genome-wise levels by permutation tests. A total of 43 QTL for 22 of the 29 measured traits were found to be significant at the 5% chromosome-wise level. Of these 43 QTL, 20 were significant at the 1% chromosome-wise significance threshold, 14 of these 20 were also significant at the 5% genome-wise significance threshold, and 10 of these 14 were also significant at the 1% genome-wise significance threshold. A total of 22 QTL for the animal random regression terms were found to be significant at the 5% chromosome-wise level. Of these 22 QTL, 6 were significant at the 1% chromosome-wise significance threshold, 4 of these 6 were also significant at the 5% genome-wise significance threshold, and 3 of these 4 were also significant at the 1% genome-wise significance threshold. Putative QTL were discovered for 10th-rib and last-rib backfat on SSC 6, body composition traits on SSC 9, backfat and lipid composition traits on SSC 11, 10th-rib backfat and total body fat tissue on SSC 12, and linear regression of last-rib backfat and total body fat tissue on SSC 8. These results will facilitate fine-mapping efforts to identify genes controlling growth and body composition of pigs that can be incorporated into marker-assisted selection programs to accelerate genetic improvement in pig populations.     

Quantitative trait loci analysis for growth and carcass traits in a Meishan x Duroc F2 resource population

We constructed a pig F2 resource population by crossing a Meishan sow and a Duroc boar to locate economically important trait loci. The F2 generation was composed of 865 animals (450 males and 415 females) from four F1 males and 24 F1 females and was genotyped for 180 informative microsatellite markers spanning 2,263.6 cM of the whole pig genome. Results of the genome scan showed evidence for significant quantitative trait loci (<1% genomewise error rate) affecting weight at 30 d and average daily gain on Sus scrofa chromosome (SSC) 6, carcass yield on SSC 7, backfat thickness on SSC 7 and SSC X, vertebra number on SSC 1 and SSC 7, loin muscle area on SSC 1 and SSC 7, moisture on SSC 13, intramuscular fat content on SSC 7, and testicular weight on SSC 3 and SSC X. Moreover, 5% genomewise significant QTL were found for birth weight on SSC 7, average daily gain on SSC 4, carcass length on SSC 6, SSC 7, and SSC X and lightness (L value) on SSC 3. We identified 38 QTL for 28 traits at the 5% genomewise level. Of the 38 QTL, 24 QTL for 17 traits were significant at the 1% genomewise level. Analysis of marker genotypes supported the breed of origin results and provided further evidence that a suggestive QTL for circumference of cannon bone also was segregating within the Meishan parent. We identified genomic regions related with growth and meat quality traits. Fine mapping will be required for their application in introgression programs and gene cloning.     

Quantitative trait locus mapping in an F2 Duroc x Pietrain resource population: II. Carcass and meat quality traits

Pigs from the F(2) generation of a Duroc x Pietrain resource population were evaluated to discover QTL affecting carcass composition and meat quality traits. Carcass composition phenotypes included primal cut weights, skeletal characteristics, backfat thickness, and LM area. Meat quality data included LM pH, temperature, objective and subjective color information, marbling and firmness scores, and drip loss. Additionally, chops were analyzed for moisture, protein, and fat composition as well as cook yield and Warner-Bratzler shear force measurements. Palatability of chops was determined by a trained sensory panel. A total of 510 F(2) animals were genotyped for 124 microsatellite markers evenly spaced across the genome. Data were analyzed with line cross, least squares regression interval, mapping methods using sex and litter as fixed effects and carcass weight or slaughter age as covariates. Significance thresholds of the F-statistic for single QTL with additive, dominance, or imprinted effects were determined on chromosome- and genome-wise levels by permutation tests. A total of 94 QTL for 35 of the 38 traits analyzed were found to be significant at the 5% chromosome-wise level. Of these 94 QTL, 44 were significant at the 1% chromosome-wise, 28 of these 44 were also significant at the 5% genome-wise, and 14 of these 28 were also significant at the 1% genome-wise significance thresholds. Putative QTL were discovered for 45-min pH and pH decline from 45 min to 24 h on SSC 3, marbling score and carcass backfat on SSC 6, carcass length and number of ribs on SSC 7, marbling score on SSC 12, and color measurements and tenderness score on SSC 15. These results will facilitate fine mapping efforts to identify genes controlling carcass composition and meat quality traits that can be incorporated into marker-assisted selection programs to accelerate genetic improvement in pig populations.     

Two quantitative trait loci on Sus scrofa chromosomes 1 and 7 affecting the number of vertebrae

The objective of the research was to identify QTL affecting the number of vertebrae in swine, one of the major determining factors of growth and body composition. Previously, we reported a QTL for the number of vertebrae located on SSC1qter (terminal band of the q arm of SSC 1) in an F2 family produced by crossing a G?ttingen miniature male with two Meishan females. Eight other swine families were subsequently produced by crosses between different breeds of European, Asian, and miniature pigs. In these families, the QTL on SSC1qter for the number of vertebrae was detected. Unlike the Asian alleles, all European alleles in this study had the effect of increasing the number of vertebrae by 0.44 to 0.69 and acted additively without dominance. The G?ttingen miniature sire, for which we previously reported a smaller additive effect, seemed to be heterozygous at the QTL. In the present study, another QTL was found for the number of vertebrae on SSC7. This QTL was not fixed in the European pigs used as parents in our experimental families, and some of the European alleles increased the number of vertebrae. A half-sib analysis confirmed that this QTL was segregating in a commercial Large White population. Analysis in an F2 family in which the parental pigs were fixed for alternative alleles revealed that the effects of the QTL on SSC1 and on SSC7 were additive and similar in size. The two QTL acted independently without epistatic effects and explained an increase of more than two vertebrae.     

Genetic relationships of body composition, serum leptin, and age at puberty in gilts

Leptin produced by adipocytes acts through leptin receptors in the hypothalamus to control appetite and food intake and thus communicates information about degree of fatness. It is thought that a degree of body fat is required for initiation of puberty and maintenance of reproductive function in mammals. The objective of this study was to determine whether polymorphisms in the leptin (LEP), leptin receptor (LEPR), paired box 5 (PAX5), aldo-keto reductase (AKR), and pro-opiomelanocortin (POMC) genes were associated with age, leptin concentration, backfat as an indicator of body condition, or BW at puberty in 3 lines of gilts and to characterize genetic relationships among these traits. The first 2 lines, born in 2001, were formed by crossing maternal White Cross (Yorkshire x Maternal Landrace) gilts to Duroc (n = 210) or (lean) Landrace (n = 207) boars. The remaining line (n = 507), born in 2002, was formed by crossing progeny of the Duroc- and Landrace-sired lines. At first estrus, age, BW (BWP), and backfat (BFP) at puberty were recorded and blood was collected for leptin assays. Nine SNP were detected in candidate genes/regions: 1 in LEP, 3 in LEPR, 1 in PAX5, 2 in AKR, and 2 in POMC. Animals were genotyped for each of the SNP; genotypes were validated using GenoProb. The association model included fixed effects of farrowing group, covariates of SNP genotypic probabilities (from GenoProb), and random additive polygenic effects to account for genetic similarities between animals not explained by SNP. Variance components for polygenic effects and error were estimated using MTDFREML. Leptin concentrations were logarithmically transformed for data analysis. All 4 traits were moderately to highly heritable (0.38 to 0.48). Age and leptin at puberty had a significant (P < 0.01) genetic correlation at -0.63 +/- 0.097, and the genetic correlation between BWP and age at puberty was 0.65 +/- 0.083 (P < 0.01). Significant additive associations (a; P < 0.05) were detected at PAX5 for age at puberty (a = 3.2 d) and for BFP (a = 0.61 mm). One SNP in LEPR was associated with leptin concentration (a = 0.31 log units; P < 0.05). The associations from PAX5 correspond to a QTL peak for age at puberty detected on SSC1. Although not necessarily the causative mutation, this result implies that a QTL that can decrease age at puberty without increasing BFP and BWP at puberty may exist in this region in commercial pigs.     

Characterization of quantitative trait loci for growth and meat quality in a cross between commercial breeds of swine

A three-generation resource family was created by crossing two Berkshire grandsires with nine Yorkshire granddams to identify QTL affecting growth, body composition, and meat quality. A total of 512 F2 offspring were evaluated for 11 traits related to growth and body composition and 28 traits related to meat quality. All animals were initially genotyped for 125 markers across the genome. The objectives of this advanced phase of the project were to further identify and characterize QTL after genotyping for another 33 markers in special regions of interest, and to develop and apply methods for detecting QTL with parent-of-origin effects. New marker linkage maps were derived and used in QTL analysis based on line-cross least squares regression-interval mapping. A decision tree for identifying QTL with parent-of-origin effects was developed based on tests against the Mendelian mode of expression. Empirical significance thresholds were derived at chromosomewise and genomewise levels using specialized permutation strategies to create data under the null hypothesis appropriate for each test. Significance thresholds derived by the permutation tests were validated based on simulation of a pedigree and data structure similar to the Berkshire-Yorkshire population. The addition of 33 markers resulted in the discovery of 29 new QTL at the 5% chromosomewise level using the Mendelian model of analysis. Thirteen of the original QTL were no longer significant at the 5% chromosomewise level. A total of 33 QTL with parent-of-origin effects were identified, including QTL with paternal expression for backfat and loin muscle area on chromosome 2, near IGF2, and QTL with maternal expression for drip loss and reflectance on chromosome 9. Tests for imprinting against Mendelian expression identified much fewer QTL with parent-of-origin effects than tests based on significance of paternal and maternal alleles, which have been used in other studies. The detected QTL and their identified mode of expression will allow further research in these QTL regions and their utilization in marker-assisted improvement of meat quality.     

The effect of adipocyte and heart fatty acid-binding protein genes on intramuscular fat and backfat content in Meishan crossbred pigs

Effects of genetic variation in porcine adipocyte and heart fatty acid-binding protein genes, A-FABP and H-FABP, respectively, on intramuscular fat (IMF) content and backfat thickness (BFT) were examined in F2 crossbreds of Meishan and Western pigs. The involvement of each FABP gene in IMF accretion was studied to confirm previous results for Duroc pigs. The F2 crossbred pigs were genotyped for various markers including microsatellite sequences situated within both FABP genes. Linkage analysis assigned the A-FABP and H-FABP genes to marker intervals S0001-S0217 (20 cM) on SSC4 and Sw316-S0003 (16.6 cM) on SSC6, respectively, refining previous chromosomal assignments. Next, the role of both chromosome regions/genes on genetic variation in IMF content and BFT was studied by 1) screening SSC4 and SSC6 for QTL affecting both traits by performing a line-cross analysis and 2) estimation of the effect of individual A-FABP and H-FABP alleles on both traits. In the first analysis, suggestive and chromosome-wise significant evidence for a QTL affecting IMF was detected on SSC6. The H-FABP gene is a candidate gene for this effect because it resides within the large region containing this putative QTL. The second analysis showed a considerable but nonsignificant effect of H-FABP microsatellite alleles on IMF content. Suggestive evidence for a QTL affecting BFT was found on SSC6, but H-FABP was excluded as a candidate gene. In conclusion, present and previous results support involvement of H-FABP gene polymorphisms in IMF accretion independently from BFT in pigs. Therefore, implementation of these polymorphisms in marker-assisted selection to control IMF content independently from BFT may be considered. In contrast to previous findings for Duroc pigs, no evidence was found for an effect of the A-FABP gene on IMF or BFT in this population.     

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.     

Identification of quantitative trait loci affecting corpora lutea and number of teats in a Meishan x Duroc F2 resource population

Understanding of the genetic control of female reproductive performance in pigs would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing 3 to 5 more viable piglets per litter than Western breeds. This difference in prolificacy is attributed to the Meishan's superior prenatal survival. Our study utilized a 3-generation resource population, in which the founder grandparental animals were purebred Meishan and Duroc pigs, in a genome scan for QTL. Grandparent, F1, and F2 animals were genotyped for 180 microsatellite markers. Reproductive traits, including number of corpora lutea (number of animals = 234), number of fetuses per animal (n = 226), number of teats (n = 801), and total number born (n = 288), were recorded for F2 females. Genome-wide significance level thresholds of 1, 5, and 10% were calculated using a permutation approach. We identified 9 QTL for 3 traits at a 10% genome-wise significance level. Parametric interval mapping analysis indicated evidence of a 1% genome-wise significant QTL for corpora lutea on SSC 3. Nonparametric interval mapping for number of teats found 4 significant QTL on chromosomes SSC3 (P < 0.01), SSC7 (P < 0.01), SSC8 (P < 0.01), and SSC12 (P < 0.05). Partial imprinting of a QTL affecting teat number (P < 0.10) was detected on SSC8. Using the likelihood-ratio test for a categorical trait, 2 QTL for pin nipples were detected on SSC2 and SSC16 (P < 0.01). Fine mapping of the QTL regions will be required for their application to introgression programs and gene cloning.     

Genome-wide association study of swine farrowing traits. Part II: Bayesian analysis of marker data

Reproductive efficiency has a great impact on the economic success of pork (sus scrofa) production. Number born alive (NBA) and average piglet birth weight (ABW) contribute greatly to reproductive efficiency. To better understand the underlying genetics of birth traits, a genome-wide association study (GWAS) was undertaken. Samples of DNA were collected and tested using the Illumina PorcineSNP60 BeadChip from 1,152 first parity gilts. Traits included total number born (TNB), NBA, number born dead (NBD), number stillborn (NSB), number of mummies (MUM), total litter birth weight (LBW), and ABW. A total of 41,151 SNP were tested using a Bayesian approach. Beginning with the first 5 SNP on SSC1 and ending with the last 5 SNP on the SSCX, SNP were assigned to groups of 5 consecutive SNP by chromosome-position order and analyzed again using a Bayesian approach. From that analysis, 5-SNP groups were selected having no overlap with another 5-SNP groups and no overlap across chromosomes. These selected 5-SNP non-overlapping groups were defined as QTL. Of the available 8,814 QTL, 124 were found to be statistically significant (P < 0.01). Multiple testing was considered using the probability of false positives. Eleven QTL were found for TNB, 3 on SSC1, 3 on SSC4, 1 on SSC13, 1 on SSC14, 2 on SSC15, and 1 on SSC17. Statistical testing for NBA identified 14 QTL, 4 on SSC1, 1 on SSC4, 1 on SSC6, 1 on SSC10, 1on SSC13, 3 on SSC15, and 3 on SSC17. A single NBD QTL was found on SSC11. No QTL were identified for NSB or MUM. Thirty-three QTL were found for LBW, 3 on SSC1, 1 on SSC2, 1 on SSC3, 5 on SSC4, 2 on SSC5, 5 on SSC6, 3 on SSC7, 2 on SSC9, 1 on SSC10, 2 on SSC14, 6 on SSC15, and 2 on SSC17. A total of 65 QTL were found for ABW, 9 on SSC1, 3 on SSC2, 9 on SSC5, 5 on SSC6, 1 on SSC7, 2 on SSC8, 2 on SSC9, 3 on SSC10, 1 on SSC11, 3 on SSC12, 2 on SSC13, 8 on SSC14, 8 on SSC15, 1 on SSC17, and 8 on SSC18. Several candidate genes have been identified that overlap QTL locations among TNB, NBA, NBD, and ABW. These QTL when combined with information on genes found in the same regions should provide useful information that could be used for marker assisted selection, marker assisted management, or genomic selection applications in commercial pig populations.     

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.     

Quantitative trait loci mapping for meat quality and muscle fiber traits in a Japanese wild boar x Large White intercross

Three generations of a swine family produced by crossing a Japanese wild boar and three Large White female pigs were used to map QTL for various production traits. Here we report the results of QTL analyses for skeletal muscle fiber composition and meat quality traits based on phenotypic data of 353 F(2) animals and genotypic data of 225 markers covering almost the entire pig genome for all of the F(2) animals as well as their F(1) parents and F(0) grandparents. The results of a genome scan using least squares regression interval mapping provided evidence that QTL (<1% genome-wise error rate) affected the proportion of the number of type IIA muscle fibers on SSC2, the number of type IIB on SSC14, the relative area (RA) of type I on SSCX, the RA of type IIA on SSC6, the RA of type IIB on SSC6 and SSC14, the Minolta a* values of loin on SSC4 and SSC6, the Minolta b* value of loin on SSC15, and the hematin content of the LM on SSC6. Quantitative trait loci (<5% genome-wise error rate) were found for the number of type I on SSC1, SSC14, and SSCX, for the number of type IIA on SSC14, for the number of type IIB on SSC2, for the RA of type IIA on SSC2, for the Minolta b* value of loin on SSC3, for the pH of loin on SSC15, and for the i.m. fat content on SSC15. Twenty-four QTL were detected for 11 traits at the 5% genome-wise level. Some traits were associated with each other, so the 24 QTL were located on 11 genomic regions. In five QTL located on SSC2, SSC6, and SSC14, each wild boar allele had the effect of increasing types I and IIA muscle fibers and decreasing type IIB muscle fibers. These effects are expected to improve meat quality.     

Potential gain from optimizing multigeneration selection on an identified quantitative trait locus.

The potential extra response that can be obtained from the optimal use of a known QTL in selection by optimizing weights in an index of breeding value for the QTL and polygenic EBV was investigated for a range of parameters. Optimal strategies were derived for a deterministic model of simultaneous selection on a QTL and polygenic effects using optimal control theory. Responses over 10 generations to the following selection strategies were compared: 1) standard QTL selection, with QTL weights equal to 1, 2) optimal QTL selection, 3) stepwise single-generation optimal QTL selection, and 4) non-QTL selection based on phenotype. Cumulative discounted response with discount rates of 10 or 30% per generation were evaluated and used as objective for optimal selection strategies. Optimal selection balanced the conflict between short- and long-term responses and gave greater cumulative discounted response than standard QTL selection of up to 20%, but less than 5% for most cases. Discount rate had limited impact. For a QTL with an additive effect of one polygenic standard deviation, cumulative discounted response from optimal QTL selection was less than 5% greater than response for non-QTL selection for most cases. Exceptions were traits with low heritability and recessive QTL at low frequency, for which extra response was up to 55% greater. Stepwise optimal selection resulted in less cumulative discounted response than standard QTL selection for QTL with negative dominance. The benefit of optimal over stepwise optimal selection was limited (less than 4%) for most cases, except for overdominant QTL. These results indicate that optimizing selection on an identified QTL can result in greater responses to selection but that extra responses tend to be limited for the situations studied here of single-stage purebred selection on a single QTL for a trait observed on both sexes.     

Joint analysis of two breed cross populations in pigs to improve detection and characterization of quantitative trait loci

The purpose of this study was to develop and implement least squares interval-mapping models for joint analysis of breed cross QTL mapping populations and to evaluate the effect of joint analysis on QTL detected for economic traits in data from two breed crosses in pigs. Data on 26 growth, carcass composition, and meat quality traits from F2 crosses between commercially relevant pig breeds were used: a Berkshire x Yorkshire cross at Iowa State University (ISU) and a Berkshire x Duroc cross at the University of Illinois (UOI). All animals were genotyped for a total of 39 (ISU) and 32 (UOI) markers on chromosomes 2, 6, 13, and 18. Marker linkage maps derived from the individual and joint data were similar with regard to order and relative position, but some differences in absolute distances existed. Maps from the joint data were used in all analyses. The individual and joint data sets were analyzed using several least squares interval-mapping models: line-cross (LC) models with Mendelian and parent-of-origin effects; halfsib models (HS); and combined models (CB) that included LC and HS effects. Lack-of-fit tests between the models were used to characterize QTL for mode of expression and to identify segregation of QTL within parental breeds. A total of 26 (8), 47 (18), and 53 (16) QTL were detected at the 5% chromosome (genome)-wise level in the ISU, UOI, and joint data for the 26 analyzed traits. Of the 53 QTL detected in the joint data, only six were detected in both populations and for many, allele effects differed between the two crosses. Despite the lack of overlap between the two populations, joint analysis resulted in an increase in significance for many QTL, including detection of ten QTL that did not reach significance in either population. Confidence intervals for position also were smaller for several QTL. In contrast, 24 QTL, most of which were detected at chromosome-wise levels in the ISU or UOI population, were not detected in the joint data. Presence of paternally expressed QTL near the IGF2 region of SSC2 was confirmed, with major effects on backfat and loin muscle area, particularly in the UOI population, as well as one or more QTL for carcass composition in the distal arm of Chromosome 6. Results of this study suggest that joint analysis using a range of QTL models increases the power of QTL mapping and QTL characterization, which helps to identify genes for subsequent marker-assisted selection.     

Estimation of genome-wide haplotype effects in half-sib designs

Genome-wide estimated breeding values can be computed from the simultaneous estimates of the effects of small intervals of DNA throughout the genome on a trait or traits of interest. Small intervals or segments of DNA can be created by the use of thousands of single nucleotide polymorphisms (SNP) available in panels of 10, 25 and 50 thousand SNP. A simulation study was conducted to compare factors that could influence the accuracy of genome-wide selection. Factors studied were the heritability of the trait, dispersion of quantitative trait loci (QTL) across the genome and size of the QTL effects. A 100-cM genome was assumed with 100 equally spaced SNP markers and 10 QTL. A granddaughter design was constructed with 20 sires and 100 sons per sire. Population-wide linkage disequilibrium was assumed to be sufficient after 25 generations of random mating starting with 30 sires and 400 dams. Best linear unbiased prediction was used to simultaneously estimate the effects of 99 SNP intervals, based on determining the SNP haplotype of each son inherited from the sire. Indicator variables were used in the model to indicate haplotype transmission. A genome-wide estimated breeding value was calculated as the sum of the appropriate haplotype interval estimates for each son. Correlations between estimated and true breeding values ranged from 0.60 to 0.79. Situations with unequally sized QTL effects and randomly dispersed QTL gave higher correlations. QTL positions could be estimated to within 2 cM or less.     

Mapping quantitative trait loci for metabolic and cytological fatness traits of connected F2 crosses in pigs

In the present study 3 connected F(2) crosses were used to map QTL for classical fat traits as well as fat-related metabolic and cytological traits in pigs. The founder breeds were Chinese Meishan, European Wild Boar, and Pietrain with to some extent the same founder animals in the different crosses. The different selection history of the breeds for fatness traits as well as the connectedness of the crosses led to a high statistical power. The total number of F(2) animals varied between 694 and 966, depending on the trait. The animals were genotyped for around 250 genetic markers, mostly microsatellites. The statistical model was a multi-allele, multi-QTL model that accounted for imprinting. The model was previously introduced from plant breeding experiments. The traits investigated were backfat depth and fat area as well as relative number of fat cells with different sizes and 2 metabolic traits (i.e., soluble protein content as an indicator for the level of metabolic turnover and NADP-malate dehydrogenase as an indicator for enzyme activity). The results revealed in total 37 significant QTL on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 14, 17, and 18, with often an overlap of confidence intervals of several traits. These confidence intervals were in some cases remarkably small, which is due to the high statistical power of the design. In total, 18 QTL showed significant imprinting effects. The small and overlapping confidence intervals for the classical fatness traits as well as for the cytological and metabolic traits enabled positional and functional candidate gene identification for several mapped QTL.     

A whole-genome scan for quantitative trait loci affecting teat number in pigs

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.     

利用24个微卫星进行猪数量性状座位定位及其遗传效应分析

以 3头英系大白公猪与 7头梅山母猪杂交产生的三代资源家系用来检测猪重要经济性状的数量性状座位(QTL) ,2 0 0 0年下半年随机选留 140头F2代个体 ,进行屠宰测定 ,记录了包括生长、胴体组成等 43个性状 ;从已定位于家猪 3、4和 7号染色体上的遗传标记中选用 2 4个微卫星标记对所有个体进行基因型检测。采用最小二乘回归区间定位法进行QTL检测 ,通过置换实验来确定显著性阈值。在所研究的 32个生长和胴体性状中 ,3条染色体总共 16个QTL达到染色体显著水平 (P <0 0 5 ) ,其中 4个达到染色体极显著性水平 (P <0 0 1) ;同时在 4号和 7号染色体上还检测到了影响器官重性状的 3个QTL ,达到了染色体显著水平 (P <0 0 5 )。在某些QTL座位 ,其有利等位基因来源于具有较低性状平均值的品种。 2QTL模型分析下 ,在 4号染色体上检测到影响板油重的 2个QTL ,并且它们的效应方向相反。