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1.
The pH values and temperatures at 45 min, and 3, 9, 15, and 24 h postmortem in the LM and semimembranosus muscle (SM) and glycolytic potential in LM were measured in 1,030 F(2) animals from a White Duroc x Erhualian resource population. A whole genome scan was performed with 183 microsatellites covering 19 porcine chromosomes to detect QTL for traits measured. A total of 73 QTL have been identified, including 1% genome-wise significant QTL for 24-h pH in LM and SM on SSC 15, and for glycolytic potential, total glycogen, and residual glycogen on SSC3, 6, and 7. Six 5% genome-wise significant QTL were detected for 9-h pH in SM on SSC3, pH decline from 3/9 h to 24 h in SM on SSC7, glycolytic potential on SSC1, and total glycogen on SSC1 and 6. This study confirmed QTL previously identified for pH except those on SSC1, 11, 12, and X, and found 11 new 5% genome-wise significant QTL for glycogen-related traits. This is the first time to report QTL for pH development during post-slaughter and for glycolytic potential at 5% genome-wise significance level. In addition, the observed different QTL for pH and pH decline at different times show that causal genes for pH postmortem play distinct roles at specific stages, in specific muscles, or both. These results provide a starting point for fine mapping of QTL for the traits measured and improve the understanding of the genetic basis of pH metabolism after slaughter.  相似文献   

2.
The small intestine is a vital organ in animal gastrointestinal system, in which a large variety of nutrients are absorbed. To identify quantitative trait loci (QTL) for the length of porcine small intestine, phenotypic values were measured in 1034 individuals at 240 d from a White Duroc × Chinese Erhualian intercross F2 population. The length of small intestine showed strong correlation with growth traits and carcass length in the F2 population. A whole‐genome scan was performed based on 183 microsatellites covering the pig genome in the F2 population. A total of 10 QTL for this trait were identified on 8 pig chromosomes (SSC), including four 1% genome‐wide significant QTL on SSC2, 4, 7 and 8, one 5% genome‐wide significant QTL on SSC12, and five 5% chromosome‐wide significant QTL on SSC5, 7, 13 and 14. The Erhualian alleles were generally associated with shorter length of the small intestine except the alleles on SSC7 and 13. The QTL on SSC4 overlapped with the previously reported QTL for the length of small intestine. Several significant QTL on SSC2, 8, and 12 were consistent with previous reports. The significant QTL detected on SSC7 was reported for the first time. All QTL identified in this study corresponded to the known region significantly associated with growth traits, supporting the important role of the length of small intestine in pig growth.  相似文献   

3.
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.  相似文献   

4.
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.  相似文献   

5.
Quantitative trait loci for reproductive traits in a three-generation resource population of a cross between low-indexing pigs from a control line and high-indexing pigs from a line selected 10 generations for increased index of ovulation rate and embryonic survival are reported. Phenotypic data were collected in F2 females for birth weight (BWT, n = 428), weaning weight (WWT, n = 405), age at puberty (AP, n = 295), ovulation rate (OR, n = 423), number of fully formed pigs (FF, n = 370), number of pigs born alive (NBA, n = 370), number of mummified pigs (MUM, n = 370), and number of stillborn pigs (NSB, n = 370). Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers. Sixteen putative QTL (P < 0.10) for reproductive traits were identified in previous analyses of these data with single QTL line-cross models. Data were reanalyzed with multiple QTL models, including imprinting effects. Data also were analyzed with half-sib models. Permutation was used to establish genome-wide significance levels ( = 0.01, 0.05, and 0.10). Thirty-one putative QTL for reproductive traits and two QTL for birth weight were identified (P < 0.10). One Mendelian QTL for FF (P < 0.05), one for NBA (P < 0.05), three for NSB (P < 0.05), three for NN (P < 0.05), seven for AP (P < 0.10), five for MUM (P < 0.10), and one for BWT (P < 0.10) were found. Partial imprinting of QTL affecting OR (P < 0.01), BWT (P < 0.05), and MUM (P < 0.05) was detected. There were four paternally expressed QTL for NN (P < 0.10) and one each for AP (P < 0.05) and MUM (P < 0.10). Maternally expressed QTL affecting NSB (P < 0.10), NN (P < 0.10), and MUM (P < 0.10) were detected. No QTL were detected with half-sib analyses. Multiple QTL models with imprinting effects are more appropriate for analyzing F2 data than single Mendelian QTL line-cross models.  相似文献   

6.
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.  相似文献   

7.
A multigeneration crossbred Meishan-White composite resource population was used to identify quantitative trait loci (QTL) for age at first estrus (AP) and the components of litter size: ovulation rate (OR; number of ova released in an estrous period) and uterine capacity (UC). The population was established by reciprocally mating Meishan (ME) and White composite (WC) pigs. Resultant F1 females were mated to either ME or WC boars to produce backcross progeny (BC) of either 3/4 WC 1/4 ME or 1/4 WC 3/4 ME. To produce the next generation (F3), 3/4 WC 1/4 ME animals were mated to 1/4 WC 3/4 ME animals yielding half-blood (1/2 WC 1/2 ME) progeny. A final generation (F4) was produced by inter se mating F3 animals. Measurements for AP and OR were recorded on 101 BC, 389 F3, and 110 F4 gilts, and UC data were from 101 BC and 110 F4 first parity litters. A genomic scan was conducted with markers (n = 157) spaced approximately 20 cM apart. All parental, F1, BC, and F4 animals but only 84 F3 animals were genotyped and included in this study. The QTL analysis fitted a QTL at 1-cM intervals throughout the genome, and QTL effects were tested using approximate genome-wide significance levels. For OR, a significant (E[false positive] < .05) QTL was detected on chromosome 8, suggestive (E[false positive] < 1.0) QTL were detected on chromosomes 3 and 10, and two additional regions were detected that may possess a QTL (E[false positive] < 2.0) on chromosomes 9 and 15. Two regions possessed suggestive evidence for QTL affecting AP on chromosomes 1 and 10, and one suggestive region on chromosome 8 was identified for UC. Further analyses of other populations of swine are necessary to determine the extent of allelic variation at the identified QTL.  相似文献   

8.
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.  相似文献   

9.
A primary genomic screen for quantitative trait loci (QTL) affecting carcass and growth traits was performed by genotyping 238 microsatellite markers on 185 out of 300 total progeny from a Bos indicus x Bos taurus sire mated to Bos taurus cows. The following traits were analyzed for QTL effects: birth weight (BWT), weaning weight (WW), yearling weight (YW), hot carcass weight (HCW), dressing percentage (DP), fat thickness (FT), marbling score (MAR), longissimus muscle area (LMA), rib bone (RibB), rib fat (RibF), and rib muscle (RibM), and the predicted whole carcass traits, retail product yield (RPYD), fat trim yield (FATYD), bone yield (BOYD), retail product weight (RPWT), fat weight (FATWT), and bone weight (BOWT). Data were analyzed by generating an F-statistic profile computed at 1-cM intervals for each chromosome by the regression of phenotype on the conditional probability of receiving the Brahman allele from the sire. There was compelling evidence for a QTL allele of Brahman origin affecting an increase in RibB and a decrease in DP on chromosome 5 (BTA5). Putative QTL at or just below the threshold for genome-wide significance were as follows: an increase in RPYD and component traits on BTA2 and BTA13, an increase in LMA on BTA14, and an increase in BWT on BTA1. Results provided represent a portion of our efforts to identify and characterize QTL affecting carcass and growth traits.  相似文献   

10.
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.  相似文献   

11.
Most QTL detection studies in pigs have been carried out in experimental F(2) populations. However, segregation of a QTL must be confirmed within a purebred population for successful implementation of marker-assisted selection. Previously, QTL for meat quality and carcass traits were detected on SSC 7 in a Duroc purebred population. The objectives of the present study were to carry out a whole-genome QTL analysis (except for SSC 7) for meat production, meat quality, and carcass traits and to confirm the presence of segregating QTL in a Duroc purebred population. One thousand and four Duroc pigs were studied from base to seventh generation; the pigs comprised 1 closed population of a complex multigenerational pedigree such that all individuals were related. The pigs were evaluated for 6 growth traits, 7 body size traits, 8 carcass traits, 2 physiological traits, and 11 meat quality traits, and the number of pigs with phenotypes ranged from 421 to 953. A total of 119 markers were genotyped and then used for QTL analysis. We utilized a pedigree-based, multipoint variance components approach to test for linkage between QTL and the phenotypic values using a maximum likelihood method; the logarithm of odds score and QTL genotypic heritability were estimated. A total of 42 QTL with suggestive linkages and 3 QTL with significant linkages for 26 traits were detected. These included selection traits such as daily BW gain, backfat thickness, loin eye muscle area, and intramuscular fat content as well as correlated traits such as body size and meat quality traits. The present study disclosed QTL affecting growth, body size, and carcass, physiological, and meat quality traits in a Duroc purebred population.  相似文献   

12.
A genome scan to detect QTL influencing growth and carcass-related traits was conducted in a Charolais x Holstein crossbred cattle population. Phenotypic measurements related to growth and carcass traits were made on the 235 second-generation crossbred males of this herd (F2 and reciprocal backcrosses), which were born in 4 consecutive annual cohorts. Traits measured in vivo were related to birth dimensions, growth rates, and ultrasound measurements of fat and muscle depth. The animals were slaughtered near a target BW of 550 kg, and a wide range of postmortem traits were measured: visual assessment of carcass conformation and carcass fatness, estimated subcutaneous fat percentage, weights of kidney knob and channel fat, and weights of carcass components after commercial and full-tissue dissections. The whole population, including grandparents, parents, and the crossbred bulls, was genotyped initially for 139 genome-wide microsatellite markers. Twenty-six additional markers were subsequently analyzed to increase marker density on some of the chromosomes where QTL had been initially identified. The linear regression analyses based on the 165 markers revealed a total of 51 significant QTL at the suggestive level, 21 of which were highly significant (F-value >or=9; based on the genome-wide thresholds obtained in the initial scan). A large proportion of the highly significant associations were found on chromosomes 5 and 6. The most highly significant QTL was localized between markers DIK1054 and DIK082 on chromosome 6 and explained about 20% of the phenotypic variance for the total bone proportion estimated after the commercial dissection. In the adjacent marker interval on this chromosome, 2 other highly significant QTL were found that explain about 30% of the phenotypic variance for birth dimension traits (BW and body length at birth). On chromosome 5, the most significant association influenced the lean:bone ratio at the forerib joint and was flanked by markers DIK4782 and BR2936. Other highly significant associations were detected on chromosomes 10 (estimated subcutaneous fat percentage), 11 (total saleable meat proportion), 16 (prehousing growth rate), and 22 (bone proportion at the leg joint). These results provide a useful starting point for the identification of the genes associated with traits of direct interest to the beef industry, using fine mapping or positional candidate gene approaches.  相似文献   

13.
Muscle histochemical characteristics are decisive determinants of meat quality. The relative percentage and diameters of the different muscular fiber types influence crucial aspects of meat such as color, tenderness, and ultimate pH. Despite its relevance, however, the information on muscle fiber genetic architecture is scant, because histochemical muscle characterization is a laborious task. Here we report a complete QTL scan of muscle fiber traits in 160 animals from a F(2) cross between Iberian and Landrace pigs using 139 markers. We identified 20 genome regions distributed along 15 porcine chromosomes (SSC1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, and X) with direct and(or) epistatic effects. Epistasis was frequent and some interactions were highly significant. Chromosomes 10 and 11 seemed to behave as hubs; they harbored 2 individual QTL, but also 6 epistatic regions. Numerous individual QTL effects had cryptic alleles, with opposite effects to phenotypic pure breed differences. Many of the QTL identified here coincided with previous reports for these traits in the literature, and there was overlapping with potential candidate genes and previously reported meat quality QTL.  相似文献   

14.
To evaluate the influence of enterotoxigenic Escherichia coli (ETEC) F4 receptors on production traits in pigs, ETEC F4ab, F4ac, and F4ad adhesion phenotypes and 27 traits related to growth, carcass, meat quality, and length of the small intestine in a White Duroc x Erhualian intercross population were measured. Performance data revealed that pigs with the F4ab or F4ac receptor (adhesive phenotypes) had greater (P < 0.01) ADG during the fattening period (from 46 to 240 d) and carcass weight and length at 240 d than pigs lacking the receptors (nonadhesive phenotype). Conversely, animals having the F4ad receptor had less (P < 0.01) ADG during the fattening period and carcass weight than those lacking the receptor. In total, 8 adhesion patterns (A to H) for the 3 F4 strains were observed in this experimental population. Pigs with both F4ab and F4ac receptors (phenotype B) had greater (P < 0.01) ADG, carcass weight, and length at 240 d compared with pigs without the F4 receptors. No difference was found (P > 0.05) in traits related to meat quality, fatness, and length of the small intestine between pigs with or without the receptors. On the basis of the antagonistic relationship between susceptibility to F4ab/ac and production traits, we speculate that the prevalence of the ETEC F4ab/ac adhesive phenotype in pig populations is attributable to balanced natural and artificial selection.  相似文献   

15.
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.  相似文献   

16.
A search for genomic regions affecting birth characters and accretion of weight and backfat was conducted in a Meishan-White Composite reciprocal backcross resource population. Birth traits analyzed (n = 750) were vigor score, number of nipples, and birth weight. Subsequent measures on gilts and barrows (n = 706) analyzed were weaning weight, 8-wk weight, ADG from 8 to 18 wk of age, ADG from 18 to 26 wk of age, 26-wk weight, and backfat over the first rib, last rib, and last lumbar vertebrae at 14 and 26 (n = 599) wk of age. Feed intake and growth of 92 individually penned barrows were also analyzed. A genomic scan was conducted with microsatellite markers spaced at approximately 20-cM intervals, a least squares regression interval analysis was implemented, and significance values were converted to genomewide levels. No associations were detected for traits measured at birth except for number of nipples, where one significant and two suggestive regions were identified on chromosomes (SSC) 10, 1, and 3, respectively. Early growth was affected by a region on SSC 1 as evidenced by associations with weights collected at weaning and 8 wk of age and ADG from 8 to 18 wk of age. Other regions detected for early growth rate were on SSC 2, 12, and X. Chromosomal regions on SSC 6 and 7 affected ADG from 18 to 26 wk of age. All measures of backfat were affected by regions on SSC 1 and X, whereas SSC 7 consistently affected backfat measures recorded at 26 wk of age. Suggestive evidence for QTL affecting backfat at 14 wk of age was also detected on SSC 2, 6, 8, and 9. These results have improved our knowledge about the genetics of growth rate and fat accretion at the molecular level in swine.  相似文献   

17.
A directed search for QTL affecting carcass traits was carried out in the region of growth differentiation factor 8 (GDF8, also known as myostatin) on ovine chromosome 2 in seven Texel-sired half-sib families totaling 927 progeny. Weights were recorded at birth, weaning, ultrasound scanning, and slaughter. Ultrasonic measures of LM cross-sectional dimensions and s.c. fat above the LM were made, with the same measurements made on the LM after slaughter. Following slaughter, linear measurements of carcass length and width were made on all carcasses, and legs and loins from 540 lambs were dissected. Genotyping was carried out using eight microsatellite markers from FCB128 to RM356 on OAR 2 and analyzed using Haley-Knott regression. There was no evidence for QTL for growth rates or linear carcass traits. There was some evidence for QTL affecting LM dimensions segregating in some sire families, although it was not consistent between ultrasound and carcass measures of the same traits. There was strong and consistent evidence for a QTL affecting muscle and fat traits in the leg that mapped between markers BM81124 and BULGE20 for the four sires that were heterozygous in this region, but not for the three sires that were homozygous. The size of the effect varied across the four sires, ranging from 0.5 to 0.9 of an adjusted SD for weight-adjusted leg muscle traits, and ranging from 0.6 to 1.2 of an adjusted SD for weight-adjusted leg fat traits. The clearest effect shown was for multivariate analysis combining all leg muscle and fat traits analyzed across sires, where the -log(10) probability was 14. Animals carrying the favorable haplotype had 3.3% more muscle and 9.9% less fat in the leg relative to animals carrying other haplotypes. There was evidence for a second peak in the region of marker TEXAN2 for one sire group. It seems that a QTL affecting muscle and fat traits exists within the New Zealand Texel population, and it maps to the region of GDF8 on OAR2.  相似文献   

18.
Leg weakness in pigs is a serious problem in the pig industry. We performed a whole genome quantitative trait locus (QTL) analysis to find QTLs affecting leg weakness traits in the Landrace population. Half-sib progeny ( n  = 522) with five sires were measured for leg weakness traits. Whole genome QTL mapping was performed using a half-sib regression-based method using 190 microsatellite markers. No experiment-wide significant QTLs affecting leg weakness traits were detected. However, at the 5% chromosome-wide level, QTLs affecting leg weakness traits were detected on chromosomes 1, 3, 10 and 11 with QTL effects ranging from 0.07 to 0.11 of the phenotypic variance. At the 1% chromosome-wide level, QTLs affecting rear feet score and total leg score were detected on chromosomes 2 and 3 with QTL effects of 0.11 and 0.13 of the phenotypic variance, respectively. On chromosome 3 and 10, some QTLs found in this study were located at nearby positions. The present study is one of the first reports of QTLs affecting fitness related traits such as leg weakness traits, that segregate within the Landrace population. The study also provides useful information for studying QTLs in purebred populations.  相似文献   

19.
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.  相似文献   

20.
There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole‐genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half‐sib families, and in some cases full‐sib families; unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate‐sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.  相似文献   

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