Biomedical subjects

S A Knott

Publications and source records attributed to S A Knott.

At least 19 recordsLinked to original sources

PubMed2005

Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross.

1. A genome scan was performed to locate genomic regions associated with traits that are known to vary in birds (most commonly broilers) suffering from heart, lung or muscular dysfunction and for weight of the dressed carcass and some internal organs. 2. The F2 population studied was derived from a cross between a broiler and a layer line and consisted of over 460 birds that were genotyped for 101 markers. 3. There was strong support for segregation of quantitative trait loci (QTL) for carcass and organ weights and blood variables. We identified 11 genome-wide significant QTL (most of them for dressed carcass weight) and several genome-wide suggestive QTL. 4. The results point to some genome regions that may be associated with health-related traits and merit further study, with the final aim of identifying linked genetic markers that could be used in commercial breeding programmes to decrease the incidence of muscular and metabolic disorders in broiler populations.

Animals↗

PubMed2004

A genome scan and follow-up study identify a bipolar disorder susceptibility locus on chromosome 1q42.

In this study, we report a genome scan for psychiatric disease susceptibility loci in 13 Scottish families. We follow up one of the linkage peaks on chromosome 1q in a substantially larger sample of 22 families affected by schizophrenia (SCZ) or bipolar affective disorder (BPAD). To minimise the effect of genetic heterogeneity, we collected mainly large extended families (average family size >18). The families collected were Scottish, carried no chromosomal abnormalities and were unrelated to the large family previously reported as segregating a balanced (1:11) translocation with major psychiatric disease. In the genome scan, we found linkage peaks with logarithm of odds (LOD) scores >1.5 on chromosomes 1q (BPAD), 3p (SCZ), 8p (SCZ), 8q (BPAD), 9q (BPAD) and 19q (SCZ). In the follow-up sample, we obtained most evidence for linkage to 1q42 in bipolar families, with a maximum (parametric) LOD of 2.63 at D1S103. Multipoint variance components linkage gave a maximum LOD of 2.77 (overall maximum LOD 2.47 after correction for multiple tests), 12 cM from the previously identified SCZ susceptibility locus DISC1. Interestingly, there was negligible evidence for linkage to 1q42 in the SCZ families. These results, together with results from a number of other recent studies, stress the importance of the 1q42 region in susceptibility to both BPAD and SCZ.

Bipolar Disorder↗

PubMed2003

Extent of linkage disequilibrium in a Sardinian sub-isolate: sampling and methodological considerations.

The extent of linkage disequilibrium (LD) is an important factor when designing experiments for mapping disease or trait loci using LD mapping methods. It depends on the population history and hence is a characteristic of each population. Here, we have assessed the extent of LD in a sub-isolate of the general Sardinian population (775 members of one village) using 22 polymorphic markers on chromosome 19. We found high levels of disequilibrium that extended to 8 cM, when based on D', and 11 cM when based on the significance level of the allelic association. The fact that conclusions based on both methods are similar suggests that the estimates are quite robust. We have also shown, through a simple resampling technique, that small sample sizes can overestimate both the mean value of D' and its variance up to a factor of about 2 and 16, respectively, when the number of diplotypes (the pair of haplotypes that compose the genotype) decreased from 186 to 26. We evaluated the effect on D' of the depth of the pedigree available when using phased founders, and compared the estimates with those obtained when using unphased founders, and also the effect of grouping alleles on the value of D' and the significance level. Owing to the high sampling variance of LD, we recommend the use of at least 200 unrelated individuals when characterizing the extent of LD.

Alleles↗

PubMed2003

Power of linkage disequilibrium mapping to detect a quantitative trait locus (QTL) in selected samples of unrelated individuals.

We considered a strategy to map quantitative trait loci (QTLs) using linkage disequilibrium (LD) when the QTL and marker locus were multiallelic. The strategy involved phenotyping a large number of unrelated individuals and genotyping only selected individuals from the two tails of the trait distribution. Power to detect trait-marker association was assessed as a function of the number of QTL and marker alleles. Two patterns of LD were used to study their influence on power. When the frequency of the QTL allele with the largest effect and that of the marker allele linked in coupling were equal, power was maximum. In this case, increasing the number of QTL alleles reduced the power. The maximum difference in power between the two LD patterns studied was approximately 30%. For low QTL heritabilities (h2QTL<0.1) and single trait studies we recommend selecting around 5% of the upper and lower tails of the trait distribution.

Chromosome Mapping↗

PubMed2003

Estimation of linkage disequilibrium in a sample of the United Kingdom dairy cattle population using unphased genotypes.

The association between genetic marker alleles was estimated for two regions of the bovine genome from a random sample of 50 young dairy bulls born in the United Kingdom between 1988 and 1995. Microsatellite marker genotypes were obtained for six markers on chromosome 2 and seven markers on chromosome 6, spanning 38 and 20 cM, respectively. Two different methods, which do not require family information, were used to estimate population haplotype frequencies. Haplotype frequencies were estimated for pairs of loci using the expectation-maximization algorithm and for all linked loci using a Bayesian approach via a Markov chain-Monte Carlo algorithm. Significant (P = 0.0007) linkage disequilibrium was detected between pairs of loci in syntenic groups (that is, loci in the same linkage group), extending to about 10 cM. No significant linkage disequilibrium was detected between markers in nonsyntenic regions. Given the observed level of linkage disequilibrium, mapping methods based on population-wide association might provide a better resolution than traditional quantitative trait loci mapping methods in the U.K. dairy cattle population and may reduce the required sample sizes of the experiments.

Algorithms↗

PubMed2002

Simple deterministic identity-by-descent coefficients and estimation of QTL allelic effects in full and half sibs.

Accurate and rapid methods for the detection of quantitative trait loci (QTLs) and evaluation of consequent allelic effects are required to implement marker-assisted selection in outbred populations. In this study, we present a simple deterministic method for estimating identity-by-descent (IBD) coefficients in full- and half-sib families that can be used for the detection of QTLs via a variance-component approach. In a simulated dataset, IBD coefficients among sibs estimated by the simple deterministic and Markov chain Monte Carlo (MCMC) methods with three or four alleles at each marker locus exhibited a correlation of greater than 0.99. This high correlation was also found in QTL analyses of data from an outbred pig population. Variance component analysis used both the simple deterministic and MCMC methods to estimate IBD coefficients. Both procedures detected a QTL at the same position and gave similar test statistics and heritabilities. The MCMC method, however, required much longer computation than the simple method. The conversion of estimated QTL genotypic effects into allelic effects for use in marker-assisted selection is also demonstrated.

Animals↗

PubMed2002

On the use of double haploids for detecting QTL in outbred populations.

The power to detect quantitative trait loci (QTL) using the double haploid (DH), full-sib (FS) and hierarchical (HI) designs implemented in outbred fish populations was assessed for interval mapping using deterministic methods. The predictions were tested using simulation. The DH design was most efficient for the range of designs and parameters considered and was most beneficial when the FS design was not very powerful. The difference between the design was largest for a low amount of residual genetic variation. Accounting for an increase of the environmental variance due to the genetic constitution of the double haploid progeny changed the magnitude of the power, but the ranking of the designs remained the same. As large full sib family sizes can be obtained in fish, the practical value of HI designs as a strategy for increasing the power of QTL mapping experiments is limited when compared with the FS design. Overall, the results suggested that the DH design could be a very useful tool for QTL mapping in fish, and of particular importance when the effect of the QTL is low and the residual genetic variation from other chromosomes can be controlled by using multiple markers.

Animals↗

PubMed2002

Approaches to interval mapping of QTL in a multigeneration pedigree: the example of porcine chromosome 4.

Quantitative trait loci (QTLs) have been mapped in many studies of F2 populations derived from crosses between diverse lines. One approach to confirming these effects and improving the mapping resolution is genetic chromosome dissection through a backcrossing programme. Analysis by interval mapping of the data generated is likely to provide additional power and resolution compared with treating data marker by marker. However, interval mapping approaches for such a programme are not well developed, especially where the founder lines were outbred. We explore alternative approaches to analysis using, as an example, data from chromosome 4 in an intercross between wild boar and Large White pigs where QTLs have been previously identified. A least squares interval mapping procedure was used to study growth rate and carcass traits in a subsequent second backcross generation (BC2). This procedure requires the probability of inheriting a wild boar allele for each BC2 animal for locations throughout the chromosome. Two methods for obtaining these probabilities were compared: stochastic or deterministic. The two methods gave similar probabilities for inheriting wild boar alleles and, hence, gave very similar results from the QTL analysis. The deterministic approach has the advantage of being much faster to run but requires specialized software. A QTL for fatness and for growth were confirmed and, in addition, a QTL for piglet growth from weaning at 5 weeks up to 7 weeks of age and another for carcass length were detected.

Alleles↗

PubMed2000

Multitrait least squares for quantitative trait loci detection.

A multiple-trait QTL mapping method using least squares is described. It is presented as an extension of a single-trait method for use with three-generation, outbred pedigrees. The multiple-trait framework allows formal testing of whether the same QTL affects more than one trait (i.e., a pleiotropic QTL) or whether more than one linked QTL are segregating. Several approaches to the testing procedure are presented and their suitability discussed. The performance of the method is investigated by simulation. As previously found, multitrait analyses increase the power to detect a pleiotropic QTL and the precision of its location estimate. With enough information, discrimination between alternative genetic models is possible.

Animals↗

PubMed1999

Testing the correspondence between map positions of quantitative trait loci.

There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.

Animals↗

PubMed1998

On the use of linear regression and maximum likelihood for QTL mapping in half-sib designs.

Methods of identification of quantitative trait loci (QTL) using a half-sib design are generally based on least-squares or maximum likelihood approaches. These methods differ in the genetical model considered and in the information used. Despite these differences, the power of the two methods in a daughter design in very similar. Using an analogy with a one-way analysis of variance, we propose an equation connecting the two test-statistics (F ratio for regression and likelihood ratio test in the case of the maximum likelihood). The robustness of this relationship is tested by simulation for different single QTL models. In general, the correspondence between the two statistics is good under both the null hypothesis and the alternative hypothesis of a single QTL segregating. Practical implications are discussed with particular emphasis on the theoretical distribution of the likelihood ratio test.

Chromosome Mapping↗

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↗

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

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↗

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↗

PubMed1992

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

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↗