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C S Haley

Publications and source records attributed to C S Haley.

At least 19 recordsLinked to original sources
PubMed1998

Multiple marker mapping of quantitative trait loci in a cross between outbred wild boar and large white pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three generation pig experiment is presented. The population of 199 F2 animals was derived from a cross between wild boar and Large White pigs. Animals were typed for 240 markers spanning 23 Morgans of 18 autosomes and the X chromosome. A series of analyses are presented within a least squares framework. First, these identify chromosomes containing loci controlling trait variation and subsequently attempt to map QTLs to locations within chromosomes. This population gives evidence for a large QTL affecting back fat and another for abdominal fat segregating on chromosome 4. The best locations for these QTLs are within 4 cM of each other and, hence, this is likely to be a single QTL affecting both traits. The allele inherited from the wild boar causes an increase in fat deposition. A QTL for intestinal length was also located in the same region on chromosome 4 and could be the same QTL with pleiotropic effects. Significant effects, owing to multiple QTLs, for intestinal length were identified on chromosomes 3 and 5. A single QTL affecting growth rate to 30 kg was located on chromosome 13 such that the Large White allele increased early growth rate, another QTL on chromosome 10 affected growth rate from 30 to 70 kg and another on chromosome 4 affected growth rate to 70 kg.

Animals↗
PubMed1998

Mapping quantitative trait loci for carcass and meat quality traits in a wild boar x Large White intercross.

An intercross between wild boar and a domestic Large White pig population was used to map quantitative trait loci (QTL) for body proportions, weight of internal organs, carcass composition, and meat quality. The results concerning growth traits and fat deposition traits have been reported elsewhere. In the present study, all 200 F2 animals, their parents, and their grandparents were genotyped for 236 markers. The marker genotypes were used to calculate the additive and dominance coefficients at fixed positions in the genome of each F2 animal, and the trait values were regressed onto these coefficients in intervals of 1 cM. In addition, the effect of proportion of wild boar alleles was tested for each chromosome. Significant QTL effects were found for percentage lean meat and percentage lean meat plus bone in various cuts, proportion of bone in relation to lean meat in ham, muscle area, and carcass length. The significant QTL were located on chromosomes 2, 3, 4, and 8. Each QTL explained 9 to 16% of the residual variance of the traits. Gene action for most QTL was largely additive. For meat quality traits, there were no QTL that reached the significance threshold. However, the average proportion of wild boar alleles across the genome had highly significant effects on reflectance and drip loss. The results show that there are several chromosome regions with a considerable effect on carcass traits in pigs.

Animals↗
PubMed1996

Confidence intervals in QTL mapping by bootstrapping.

The determination of empirical confidence intervals for the location of quantitative trait loci (QTLs) was investigated using simulation. Empirical confidence intervals were calculated using a bootstrap resampling method for a backcross population derived from inbred lines. Sample sizes were either 200 or 500 individuals, and the QTL explained 1, 5, or 10% of the phenotypic variance. The method worked well in that the proportion of empirical confidence intervals that contained the simulated QTL was close to expectation. In general, the confidence intervals were slightly conservatively biased. Correlations between the test statistic and the width of the confidence interval were strongly negative, so that the stronger the evidence for a QTL segregating, the smaller the empirical confidence interval for its location. The size of the average confidence interval depended heavily on the population size and the effect of the QTL. Marker spacing had only a small effect on the average empirical confidence interval. The LOD drop-off method to calculate empirical support intervals gave confidence intervals that generally were too small, in particular if confidence intervals were calculated only for samples above a certain significance threshold. The bootstrap method is easy to implement and is useful in the analysis of experimental data.

Animals↗
PubMed1996

Marker-assisted introgression in backcross breeding programs.

The efficiency of marker-assisted introgression in backcross populations derived from inbred lines was investigated by simulation. Background genotypes were simulated assuming that a genetic model of many genes of small effects in coupling phase explains the observed breed difference and variance in backcross populations. Markers were efficient in introgression backcross programs for simultaneously introgressing an allele and selecting for the desired genomic background. Using a marker spacing of 10-20 cM gave an advantage of one to two backcross generations selection relative to random or phenotypic selection. When the position of the gene to be introgressed is uncertain, for example because its position was estimated from a trait gene mapping experiment, a chromosome segment should be introgressed that is likely to include the allele of interest. Even for relatively precisely mapped quantitative trait loci, flanking markers or marker haplotypes should cover approximately 10-20 cM around the estimated position of the gene, to ensure that the allele frequency does not decline in later backcross generations.

Alleles↗
PubMed1995

The PiGMaP consortium linkage map of the pig (Sus scrofa).

A linkage map of the porcine genome has been developed by segregation analysis of 239 genetic markers. Eighty-one of these markers correspond to known genes. Linkage groups have been assigned to all 18 autosomes plus the X Chromosome (Chr). As 69 of the markers on the linkage map have also been mapped physically (by others), there is significant integration of linkage and physical map data. Six informative markers failed to show linkage to these maps. As in other species, the genetic map of the heterogametic sex (male) was significantly shorter (approximately 16.5 Morgans) than the genetic map of the homogametic sex (female) (approximately 21.5 Morgans). The sex-averaged genetic map of the pig was estimated to be approximately 18 Morgans in length. Mapping information for 61 Type I loci (genes) enhances the contribution of the pig gene map to comparative gene mapping. Because the linkage map incorporates both highly polymorphic Type II loci, predominantly microsatellites, and Type I loci, it will be useful both for large experiments to map quantitative trait loci and for the subsequent isolation of trait genes following a comparative and candidate gene approach.

Animals↗
PubMed1995

Livestock QTLs--bringing home the bacon?

Markers have been used for some time to study the genetic control of economically important traits in livestock. The early work was based on single loci and detected some significant effects, but results were often inconsistent across studies. Now that complete microsatellite-based maps of the major species are becoming available, more complete and rigorous scans of the genome are possible. The first of these have detected some surprisingly large effects, both within breeds and in breed crosses. As research workers digest these results and their implications for livestock breeding programmes and ponder further research, commercial breeding companies have already started applying the first fruits of marker research to breed a better animal.

Alleles↗
PubMed1995

Using marker-maps in marker-assisted selection.

A method of using information on the location of markers to improve the efficiency of marker-assisted selection (MAS) in a population produced by a cross between two inbred lines is developed. The method is closer to mapping QTL than the selection index approaches to MAS described by previous authors. We use computer simulations to compare our method with phenotypic selection and two selection index approaches, simulations being performed on three genetic maps. The simulations show that whilst MAS can be considerably more efficient than phenotypic selection differences between the three MAS methods are slight. Which of the MAS methods is best depends on a number of factors: in particular the genetic map, the time scale under consideration ant the population size are of importance.

Chromosome Mapping↗
PubMed1995

The effect of the Booroola (FecB) gene on peripheral FSH concentrations and ovulation rates during oestrus, seasonal anoestrus and on FSH concentrations following ovariectomy in Scottish Blackface ewes.

The aim of this study was to investigate the role of FSH in the control of ovulation rate by the Booroola gene. Three Booroola genotypes (FecBFecB, FecBFec+ and Fec+Fec+) of the F2 population, from a cross between Booroola Merino and Scottish Blackface, and two Booroola genotypes (FecBFec+ and Fec+Fec+; 25% Booroola Merino and 75% Scottish Blackface), from the backcross of FecBFec+ sires to Scottish Blackface ewes, were compared. During seasonal anoestrus significant differences (P < 0.05) in hCG-stimulated ovulation rates were obtained between FecBFecB and Fec+Fec+ ewes from the F2 population, and FecBFec+ ewes were intermediate. No significant difference in hCG-stimulated ovulation rate was observed in the backcross population between FecBFec+ ewes and Fec+Fec+ ewes. There were no significant differences between genotypes in mean serum FSH concentrations during seasonal anoestrus in either backcross of F2 population. During the breeding season, two separate experiments confirmed the expected ovulation rate differences between genotypes (FecBFecB > FecBFec+ > Fec+Fec+). In both experiments, mean peripheral FSH concentrations in the F2 population were similar in FecBFec+ and Fec+Fec+ ewes, but were significantly higher (P < 0.05) in FecBFecB ewes. In the backcross population, mean peripheral FSH concentrations during the oestrous cycle were not significantly different between FecBFec+ and Fec+Fec+ ewes, despite significant differences in ovulation rate. Ovariectomy during the breeding season resulted in significantly higher (P < 0.001) mean peripheral FSH concentrations in all three genotypes. After ovariectomy, mean FSH concentrations between FecBFec+ and Fec+Fec+ ewes, form both backcross and F2 populations, were not significantly different.(ABSTRACT TRUNCATED AT 250 WORDS)

Anestrus↗
PubMed1994

Genetic mapping of quantitative trait loci for growth and fatness in pigs.

The European wild boar was crossed with the domesticated Large White pig to genetically dissect phenotypic differences between these populations for growth and fat deposition. The most important effects were clustered on chromosome 4, with a single region accounting for a large part of the breed difference in growth rate, fatness, and length of the small intestine. The study is an advance in genome analyses and documents the usefulness of crosses between divergent outbred populations for the detection and characterization of quantitative trait loci. The genetic mapping of a major locus for fat deposition in the pig could have implications for understanding human obesity.

Adipose Tissue↗
PubMed1994

Comparisons between peripheral progesterone concentrations in cyclic and pregnant Landrace x large White and Meishan gilts.

Progesterone concentrations were determined in blood samples collected twice daily (at 0900 and 1700 hours) from the day of oestrus (Day 0) until Days 15-24 in ten Landrace x Large White gilts (four cyclic and six pregnant gilts) and eight Meishan gilts (four cyclic and four pregnant gilts). Progesterone concentrations during the early luteal phase tended to be higher in pregnant Meishan gilts than in pregnant Landrace x Large White gilts. Furthermore, when differences in ovulation rate and peak progesterone concentrations were accounted for, maximum progesterone concentrations occurred earlier in Meishan gilts than in Landrace x Large White gilts (P < 0.01); this difference was particularly marked when pregnant animals of the two breeds were compared. In non-mated animals, analyses of the timing and magnitude of progesterone concentrations observed towards the end of the oestrous cycle revealed that the decrease in progesterone concentrations occurred earlier (P < 0.05) in Meishan gilts. Such breed differences in the peripheral progesterone profile may be associated with reduced prenatal mortality, a characteristic of Meishan females.

Animals↗
PubMed1994

Mapping quantitative trait loci in crosses between outbred lines using least squares.

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F1 (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored.

Alleles↗
PubMed1994

RFLP and linkage analysis of the porcine casein loci--CASAS1, CASAS2, CASB and CASK.

Restriction fragment length polymorphisms (RFLPs) were revealed at the porcine casein loci with the following combinations of restriction endonucleases and porcine cDNA clones: alpha s1-casein (TaqI); alpha s2-casein (BamHI); and beta-casein (SacI). These RFLPs were shown to be under simple monogenic control by segregation analysis of two- and three-generation families. The CASAS1, CASAS2 and CASB casein loci were also shown to be linked with no recombinant haplotypes observed amongst 77 meioses in Large White and Meishan F1 and F2 crosses. No recombinants were observed in a further 106 meioses that were informative for linkage between CASAS1 and CASAS2.

Alleles↗
PubMed1994

Relationships between components of litter size in unilaterally ovariectomized and intact rabbit does.

A study was performed to evaluate the use of unilateral ovariectomy for the measurement of uterine capacity in rabbits through a comparison of the relationships between ovulation rate, number of implanted embryos, and litter size in unilaterally ovariectomized (ULO) and intact does. Data from 211 ULO and 323 intact does were analyzed. The animals were derived from a synthetic line previously selected on litter size. Laparoscopy was performed on all does during their second gestation 12 d after mating and the number of corpora lutea and implantation sites were recorded. Intact and ULO does had the same ovulation rate, confirming the presence of compensatory ovarian hypertrophy in the remaining ovary of the ULO does. The number of implantation sites in the ULO group (11.3) approached the number found in the control group (12.6). Embryonic survival (until implantation) was lower (P < .01) in ULO does (.77) than in intact does (.88), but fetal survival (after implantation) was the same in both groups. The ULO females produced litters 77% of the size of those of the normal control females. Pre- and postimplantation survivals were not related in intact does but seemed to be related in ULO does through an effect on the number of implantation sites. The coefficient of the regression of number of implantation sites on ovulation rate was positive in control does (.62 +/- .06) and was also positive in ULO does (.31 +/- .07), showing that a higher ovulation rate would have resulted in a higher number of embryos being implanted in both groups.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1993

The genetic basis of response in mouse lines divergently selected for body weight or fat content. II. The contribution of genes with a large effect.

Gene action underlying selection responses has been studied using crossbreeding. Maximum likelihood based segregation analysis has been presented for analysing backcross data for the presence of genes with a large effect. Two sets of divergently selected lines (P-lines for body weight and F-lines for fat content) were reciprocally crossed and the F1s were crossed to the high and low lines to produce all possible backcrosses. Earlier analysis had shown that the difference in body weight at 10 weeks (n = 595) between the high and low P-lines was largely (75-80%) explained by autosomal, additive genes with the remainder explained by additive genes on the X chromosome. Maximum likelihood segregation analysis suggested the presence of a major effect on the X chromosome, but as there was only one round of recombination between the X chromosomes in the forming of the backcrosses, linked genes on the X chromosome could have acted together to give the appearance of a single major gene. The difference in fat content between the F-lines (n = 578) could be explained by autosomal genes of largely additive effect. Segregation analysis suggested the presence of a major gene with complete dominance, but this was attributed to a relationship between the mean and the variance: transformation of the data resulted in only polygenic additive genes being of importance. This study concluded that maximum likelihood based analysis and crosses between selected lines provide a powerful means for studying the gene action underlying responses to selection.

Adipose Tissue↗
PubMed1993

Reproductive performance in relation to uterine and embryonic traits during early gestation in Meishan, large white and crossbred sows.

Previous studies have shown that females of the Chinese Meishan breed and of their F1 cross with European Large White pigs are very prolific, producing about four more piglets per litter than control Large White females. The main cause of this prolificacy is enhanced prenatal survival for a given ovulation rate in Meishan and F1 females and this is controlled by genes of the mother, not those of the conceptus. The objectives of this study were to determine whether genotypic differences in embryo survival were apparent in the period immediately after attachment and to compare embryonic and uterine development at this time. Sows in their third parity (20 Large White, 14 Meishan, 25 Large White x Meishan F1 and 25 Meishan x Large White F1) were killed 20-22 days after mating and their reproductive tracts recovered for further study. There were significant differences between the purebred sows, and crossbred sows were approximately intermediate for the number of corpora lutea (20.7 +/- 0.9, 27.8 +/- 1.1, 22.4 +/- 0.8 and 23.3 +/- 0.8 for the four genotypes, respectively), the number of embryos (15.2 +/- 0.9, 23.4 +/- 1.1, 17.2 +/- 0.8 and 18.8 +/- 0.8, respectively) and the proportionate embryo survival (0.74 +/- 0.04, 0.84 +/- 0.04, 0.78 +/- 0.03 and 0.82 +/- 0.03, respectively). There was a negative association within genotype between embryo survival and the number of corpora lutea. Adjusting for the genotypic difference in the number of corpora lutea increased the genotypic differences in embryo survival.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1993

Genetic basis of prolificacy in Meishan pigs.

Research in France and in the UK confirms the prolificacy of the Chinese Meishan breed to be about three to four piglets greater than that of control Large White females. Crossbreeding studies clearly indicate that this breed difference is due to genes acting in the dam and not in the litter itself. There is high heterosis for litter size in F1 Meishan x Large White crossbred females, such that their litter size is similar to or greater than that of purebred Meishan females. There is some discrepancy between studies about whether the Meishan female has a higher ovulation rate than does the Large White breed and this can be attributed in large part to the different basis upon which breed comparisons have been made. Nevertheless, there may be real genetic differences between Meishan pigs exported to different countries. In young gilts at comparable numbers of oestrous cycles after puberty, the ovulation rate is similar in Meishan and Large White gilts, but in older gilts, and particularly in multiparous sows, Meishan pigs have a higher ovulation rate in British studies. Once comparisons of prenatal survival between breeds have been adjusted for any breed difference in ovulation rate, the main cause of prolificacy in Meishan pigs can be seen to be an enhanced level of prenatal survival. Crossbreeding studies show that this is controlled by the maternal genotype and not that of the embryos. The advantage in prenatal survival to the Meishan pig is clearly present in the post-attachment period (after day 20 of gestation), but may also be present earlier in gestation. Results from a study presented here suggest that Meishan sows have a higher uterine capacity than do Large White sows and this allows them to maintain their higher number of attached embryos through gestation. F1 Meishan x Large White crossbred females achieve their high litter size via a different route than do purebred Meishan females. These animals have a lower ovulation rate and fewer attached embryos than do purebred Meishan sows, but a very low level of fetal loss allows them to produce litters of similar size. The low level of fetal loss in F1 females appears to be due to the higher uterine capacity of F1 females compared with purebred Meishan sows.

Animals↗
PubMed1992

Methods of segregation analysis for animal breeding data: a comparison of power.

Maximum likelihood segregation analysis provides potentially the most powerful method for the detection of segregating major genes. Segregation analysis requires the comparison of the likelihood of the data under the combined model (allowing both polygenic and major gene genetic variation) with the likelihood of the data under the polygenic model (allowing only polygenic genetic variation). In this study three approximations to the combined model likelihood were compared using simulated data, both with and without a segregating major gene, containing observations on paternal half-sibs. The use of Hermite integration to replace the integration in the combined model likelihood provided the most powerful test for a major gene. Two approximations, based on extensions of linear-mixed-model theory and estimating transmitting abilities for sires, were also considered. These approximations were less powerful than the use of Hermite integration, although the approximation estimating a transmitting ability for each major genotype for the sires was an improvement over the approximation estimating a single transmitting ability. For each approximation the frequency of detection of a major gene depended on the proportion of the genetic variance explained by the simulated major gene and whether the major gene caused the distribution to be skewed.

Alleles↗