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C S Haley

Publications and source records attributed to C S Haley.

At least 55 records · Page 3Linked to original sources
PubMed1999

Detecting QTLs for uni- and bipolar disorder using a variance component method.

The objective of this study was to use a robust variance component method to analyse unipolar and bipolar disorder in a large Scottish extended family (n = 168) in which linkage between markers and disease has been previously reported on the short arm of chromosome 4. Data consisted of diagnosed clinical uni- or bipolar disorder on 143 individuals, with microsatellite marker information on 109 of these individuals. The incidence of unipolar and bipolar disorder in the family was 17/143, and 11/143, respectively. Eleven linked markers on chromosome 4, spanning a region of approximately 26 cM, were used in the analysis. The statistical analysis was performed in two steps. First, pairwise identify-by-descent (IBD) coefficients for all individuals in the pedigree were calculated at 1 cM intervals, using all marker data simultaneously, with a Monte Carlo Markov Chain algorithm. Second, the variance in the trait of interest was partitioned using residual maximum likelihood (REML). Three components of variance were estimated: (i) a genetic component associated with the average relationship between individuals using the numerator relationship matrix, (ii) a genetic component associated with a chromosome location using the estimated IBD coefficients, and (iii) a residual component. The test statistic (LOD score) was calculated from the maximum likelihood of the full model, fitting all three variance components, and the maximum likelihood value from the reduced model, fitting a polygenic and residual component. The largest LOD scores (maximum LOD = 5.9), were found in a region spanning about 10 cM, when the trait was defined as the occurrence of either uni- or bipolar disorder. The putative QTL explained about 25% of the total variation in the trait.

Bipolar Disorder↗
PubMed1999

Genetic determination of cardiac mass in normotensive rats: results from an F344xWKY cross.

Genetic determinants affect adult cardiac mass and the predisposition to develop cardiac hypertrophy. The aim of this study was to identify quantitative trait loci (QTL) that control heart and left ventricular (LV) weight by use of normotensive inbred rat strains that differ in their adult cardiac mass phenotype. We studied 126 male F2 rats derived from a cross of normotensive Wistar-Kyoto and Fischer 344 rats. At 12 weeks of age, total heart weight and LV weight were measured. Genomic DNA from these animals was screened by use of polymorphic microsatellite markers across the whole genome (excluding the sex chromosomes). In this cross, the genetic contribution to total heart weight variation was 56%, and the genetic contribution for LV weight was 55%. Using the Mapmaker/QTL computer package, we identified a significant QTL on chromosome 3 with a log10 likelihood (LOD) score of 4.8, which accounted for 16.5% of the total variance of LV weight. This QTL was centered close to the marker D3Rat29. The QTL was also found to be significantly linked with total heart weight (LOD=4.4). These data provide the first demonstration of a QTL on chromosome 3 that plays a role in determining the difference in LV mass between normotensive Fischer 344 and Wistar- Kyoto inbred rat strains. The prostaglandin synthase 1 gene is located within the QTL.

Animals↗
PubMed1998

Genetic variation within the Hereford breed of cattle.

Genetic differentiation among Hereford populations from Britain, Ireland, Sweden, Canada and New Zealand together with six other beef breeds was assessed using blood type polymorphisms. Changes in the genetic structure of the British Hereford population over time were also examined. Loci surveyed were seven red cell antigen systems (A, B, C, F, L, S, Z), and two serum protein loci (transferrin and albumin). Within group variation was measured by the average expected heterozygosity, and between group relationships by genetic distance. There was significant genetic differentiation among Hereford populations from different countries. Differences between Hereford groups, however, were not as large as differences between breeds. There were also significance differences among British herds. The proportion of Canadian genes in the British 'hybrid' population was estimated to have increased from 0.42 (+/- 0.34) in the 1970s to 0.98 (+/- 0.11) in the 1990s. Canadian Hereford groups were found to be less heterozygous than other groups, and replacement of the British population with Canadian animals may lead to loss of variation. Breeding strategies that preserve original native genes in British Hereford populations should be considered by commercial breeders, in order to prevent the long-term loss of genetic variation within the breed.

Alleles↗
PubMed1998

Genetic relationships among European cattle breeds.

Genetic relationships among 37 European cattle breeds were investigated using blood group and serum protein polymorphisms. The 18,859 animals included in the study represented a random sample from pedigree populations in the UK. Within-breed variation was estimated by average heterozygosity and number of alleles observed, and breed relationships were evaluated by genetic distance. Standard errors of the heterozygosity, number of alleles and genetic distance were obtained by bootstrapping. The significance of breed differences was tested using an exact test of differentiation. French, Italian and Channel Island breeds were found to have generally higher heterozygosities and a greater number of alleles than breeds from mainland Britain and North Europe. Genetic distances ranged between 0.011 (+/- 0.005) and 0.309 (+/- 0.071). Two major breed groups were identified; a group of French, Italian and Channel Island breeds together with the Simmental and Gelbvieh, and a second group consisting of the mainland British and North European breeds. The exact test of breed differentiation showed all breeds to be significantly different from one another (P < 0.0001). Overall relationships among breeds reflected their geographical origin and common ancestry rather than the agricultural use for which the breeds have been selected.

Alleles↗
PubMed1998

Mapping of quantitative trait loci on porcine chromosome 4.

A F2 population derived from a cross between European Large White and Chinese Meishan pigs was established in order to study the genetic basis of breed differences for growth and fat traits. Chromosome 4 was chosen for initial study as previous work had revealed quantitative trait loci (QTLs) on this chromosome affected growth and fat traits in a Wild Boar x Large White cross. Individuals in the F2 population were typed for nine markers spanning a region of approximately 124 CM. We found evidence for QTLs affecting growth between weaning and the end of test (additive effect: 43.4 g/day) and fat depth measured in the mid-back position (additive effect: 1.82 mm). There was no evidence of interactions between the QTLs and sex, grandparents or F1 sires, suggesting that the detected QTLs were fixed for alternative alleles in the Meishan and Large White breeds. Comparison of locations suggests that these QTLs could be the same as those found in the Wild Boar x Large White cross.

Animals↗
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

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth.

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.

Alleles↗
PubMed1998

A nonparametric bootstrap method for testing close linkage vs. pleiotropy of coincident quantitative trait loci.

A novel method using the nonparametric bootstrap is proposed for testing whether a quantitative trait locus (QTL) at one chromosomal position could explain effects on two separate traits. If the single-QTL hypothesis is accepted, pleiotropy could explain the effect on two traits. If it is rejected, then the effects on two traits are due to linked QTLs. The method can be used in conjunction with several QTL mapping methods as long as they provide a straightforward estimate of the number of QTLs detectable from the data set. A selection step was introduced in the bootstrap procedure to reduce the conservativeness of the test of close linkage vs. pleiotropy, so that the erroneous rejection of the null hypothesis of pleiotropy only happens at a frequency equal to the nominal type I error risk specified by the user. The approach was assessed using computer simulations and proved to be relatively unbiased and robust over the range of genetic situations tested. An example of its application on a real data set from a saline stress experiment performed on a recombinant population of wheat (Triticum aestivum L. ) doubled haploid lines is also provided.

Computer Simulation↗
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↗
PubMed1998

Strategies to utilize marker-quantitative trait loci associations.

Marker-assisted selection holds promise because genetic markers provide completely heritable traits than can be measured at any age in either sex and that are potentially correlated with traits of economic value. Theoretical and simulation studies show that the advantage of using marker-assisted selection can be substantial, particularly when marker information is used, because normal selection is less effective, for example, for sex-limited or carcass traits. Assessment of the available information and its most effective use is difficult, but approaches such as crossvalidation may help in this respect. Marker systems are now becoming available that allow the high density of markers required for close associations between marker loci and trait loci. Emerging technologies could allow large numbers of polymorphic sites to be identified, practically guaranteeing that markers will be available that are in complete association with any trait locus. Identifying which polymorphism out of many that is associated with any trait will remain problematic, but multiple-locus disequilibrium measures may allow performance to be associated with unique marker haplotypes. This type of approach, combined with cheap and high density markers, could allow a move from selection based on a combination of "infinitesimal" effects plus individual loci to effective total genomic selection. In such a unified model, each region of the genome would be given its appropriate weight in a breeding program. However, the collection of good quality trait information will remain central to the use of these technologies for the foreseeable future.

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↗