Variation and covariation in strongyle infection in East African shorthorn zebu calves.

Parasite burden varies widely between individuals within a population, and can covary with multiple aspects of individual phenotype. Here we investigate the sources of variation in faecal strongyle eggs counts, and its association with body weight and a suite of haematological measures, in a cohort of indigenous zebu calves in Western Kenya, using relatedness matrices reconstructed from single nucleotide polymorphism (SNP) genotypes. Strongyle egg count was heritable (h(2) = 23.9%, s.e. = 11.8%) and we also found heritability of white blood cell counts (WBC) (h(2) = 27.6%, s.e. = 10.6%). All the traits investigated showed negative phenotypic covariances with strongyle egg count throughout the first year: high worm counts were associated with low values of WBC, red blood cell count, total serum protein and absolute eosinophil count. Furthermore, calf body weight at 1 week old was a significant predictor of strongyle EPG at 16-51 weeks, with smaller calves having a higher strongyle egg count later in life. Our results indicate a genetic basis to strongyle EPG in this population, and also reveal consistently strong negative associations between strongyle infection and other important aspects of the multivariate phenotype.

Bone mineral density QTL at sexual maturity and end of lay.

1. An F2 cross of a broiler male line and a White Leghorn layer line was used to identify quantitative trait loci (QTL) for bone density at the onset of lay and at the end of the laying period. A total of 686 measures of humeral bone density were available for analysis. 2. There was no evidence for epistasis. 3. Genome-wide significant QTL for bone density at the onset of lay were identified on chromosomes 1 (311 cM) and 8 (2 cM) and on chromosomes 1 (311 cM), 3 (57 cM) and 8 (2 cM) with a covariate for the number of yellow follicles (a proxy for the concentration of circulating oestrogen). 4. Evidence for only 4 chromosome-wide suggestive QTL were detected at the end of lay (72 weeks). 5. Analysis of the combined data confirmed two genome-wide suggestive QTL on chromosome 1 (137 and 266 cM) and on chromosomes 8 (2 cM) and 9 (10 cM) in analyses with or without the covariate. 6. Positive QTL alleles came from the broiler line with the exception of 2 suggestive QTL at the onset of lay on chromosomes 3 and 5 in an analysis with the covariate. 7. In general, QTL acted additively, except that dominant effects were identified for three suggestive QTL at the onset of lay on chromosomes 3 (57 and 187 cM) and 5 (9 cM). 8. The significant QTL in this study were at similar locations to QTL identified in a range of crosses in other publications, suggesting that they are prime candidates for the search for genes and mutations that could be used as selection criteria to improve bone strength and decrease fractures in commercial laying hens.

The quantitative genetic basis of sex ratio variation in Nasonia vitripennis: a QTL study.

Our understanding of how natural selection should shape sex allocation is perhaps more developed than for any other trait. However, this understanding is not matched by our knowledge of the genetic basis of sex allocation. Here, we examine the genetic basis of sex ratio variation in the parasitoid wasp Nasonia vitripennis, a species well known for its response to local mate competition (LMC). We identified a quantitative trait locus (QTL) for sex ratio on chromosome 2 and three weaker QTL on chromosomes 3 and 5. We tested predictions that genes associated with sex ratio should be pleiotropic for other traits by seeing if sex ratio QTL co-occurred with clutch size QTL. We found one clutch size QTL on chromosome 1, and six weaker QTL across chromosomes 2, 3 and 5, with some overlap to regions associated with sex ratio. The results suggest rather limited scope for pleiotropy between these traits.

Overlap of quantitative trait loci for early growth rate, and for body weight and age at onset of sexual maturity in chickens.

Critical age, weight and body composition have been suggested as necessary correlates of sexual maturity. A genome scan to identify quantitative trait loci (QTL) for age and body weight at first egg (AFE and WFE) was conducted on 912 birds from an F(2) broiler-layer cross using 106 microsatellite markers. Without a covariate, QTL for body WFE were detected on chromosomes 2, 4, 8, 27 and Z and a single QTL for AFE was detected on chromosome 2. With AFE as a covariate, additional QTL for body WFE were found on chromosomes 1 and 13, with abdominal fat pad as covariate a QTL for body WFE was found on chromosome 1. With body WFE as covariate, additional QTL for AFE were found on chromosomes 1, 3, 4, 13 and 27. The QTL generally acted additively and there was no evidence for epistasis. Consistent with the original line differences, broiler alleles had positive effects on body WFE and negative effects on AFE, whereas the phenotypic correlation between the two traits was positive. The mapped QTL for body WFE cumulatively accounted for almost half the body weight difference between the chicken lines at puberty. Overlapping QTL for body WFE and body weight to 9 weeks of age indicate that most QTL affecting growth rate also affect body WFE. The co-localisation of QTL for body weight, growth and sexual maturity suggests that body weight and growth rate are closely related to the attainment of sexual maturity and that the genetic determination of growth rate has correlated effects on puberty.

Feed efficiency and body composition are related to cortisol response to adrenocorticotropin hormone and insulin-induced hypoglycemia in rams.

Metabolic rate and energy consumption increase through the activation of the hypothalamic-pituitary-adrenal axis when an animal is exposed to a stressor. Residual feed intake (RFI) as a measure of efficiency has been shown to be related to exogenous adrenocorticotropin hormone (ACTH)-stimulated cortisol concentrations, which is indicative of the relationship between an animal's response to stress and the efficiency with which the energy is used for growth and production. In this study, we tested the hypothesis that sheep with low post-ACTH serum cortisol concentration relative to the other sheep in the flock have lower RFI values and lower cortisol concentrations following insulin-induced hypoglycemia. Adrenocorticotropin hormone (2.0 microg/kg body weight)-stimulated cortisol concentrations were measured in 100 sheep. The extreme responders were selected (n = 12 high cortisol, n = 12 low cortisol), and feed efficiency and body composition parameters were measured. A second ACTH challenge and an insulin challenge were administered. More efficient sheep (more negative RFI value) were found to have lower (P < 0.05) cortisol concentrations following both an ACTH challenge and an insulin challenge. Low-cortisol sheep (low response to ACTH or insulin) were found to have a lower (P < 0.05) proportion of fat tissue in comparison to the high-cortisol animals. These data clearly indicate that an animal's response to exogenous ACTH or insulin-induced hypoglycemia as a stressor is related (P < 0.05) to efficiency of energy use when measured as RFI. These data have important implications in enabling identification of animals that are superior in terms of feed efficiency and for understanding the physiological mechanisms underlying efficiency of energy use.

Rams with poor feed efficiency are highly responsive to an exogenous adrenocorticotropin hormone (ACTH) challenge.

An animal's response to a stressor is to increase metabolic rate, and thus energy consumption through the activation of the hypothalamic-pituitary-adrenal axis. Changes to energy use by an animal are likely to influence the efficiency with which it is utilised. In this study, we tested the hypothesis that less efficient sheep are more responsive to exogenous administration of adrenocorticotropin hormone. This was done by firstly determining the appropriate dose (0.4, 1.6 or 6.4microg/kg LW) and peak serum cortisol response time (45min) to exogenous administration of adrenocorticotropin hormone in a pilot study (n=3 sheep). Following this, adrenocorticotropin hormone (2.0microg/kg LW) stimulated cortisol levels were measured in a larger group of sheep (n=50) of known feed efficiency (feed conversion ratio and residual feed intake values). Less efficient sheep (more positive residual feed intake values) were found to have a greater (P<0.001) increase in cortisol concentration in comparison to more efficient animals. Those sheep which had higher levels of cortisol also had a greater proportion (P<0.001) of fat tissue. These data clearly demonstrated that efficiency of energy use, when measured as residual feed intake, is significantly related to an animal's stress response. These findings have important implications for understanding the physiological mechanisms underpinning efficiency of energy use, and may be useful in successfully identifying animals which are superior in terms of feed efficiency.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Methods for multiple-marker mapping of quantitative trait loci in half-sib populations.

In this paper we consider the detection of individual loci controlling quantitative traits of interest (quantitative trait loci or QTLs) in the large half-sib family structure found in some species. Two simple approaches using multiple markers are proposed, one using least squares and the other maximum likelihood. These methods are intended to provide a relatively fast screening of the entire genome to pinpoint regions of interest for further investigation. They are compared with a more traditional single-marker least-squares approach. The use of multiple markers is shown to increase power and has the advantage of providing an estimate for the location of the QTL. The maximum-likelihood and the least-squares approaches using multiple markers give similar power and estimates for the QTL location, although the likelihood approach also provides estimates of the QTL effect and sire heterozygote frequency. A number of assumptions have been made in order to make the likelihood calculations feasible, however, and computationally it is still more demanding than the least-squares approach. The least-squares approach using multiple markers provides a fast method that can easily be extended to include additional effects.