Many quantitative traits are measured as percentages. As a result, the assumption of a normal distribution for the residual errors of such percentage data is often violated. However, most quantitative trait locus (QTL) mapping procedures assume normality of the residuals. Therefore, proper data transformation is often recommended before statistical analysis is conducted. We propose the probit transformation to convert percentage data into variables with a normal distribution. The advantage of the probit transformation is that it can handle measurement errors with heterogeneous variance and correlation structure in a statistically sound manner. We compared the results of this data transformation with other transformations and found that this method can substantially increase the statistical power of QTL detection. We develop the QTL mapping procedure based on the maximum likelihood methodology implemented via the expectation-maximization algorithm. The efficacy of the new method is demonstrated using Monte Carlo simulation.

Genes involved in major biological functions, such as reproductive or cognitive functions, are choice targets for natural selection. However, the extent to which these genes are affected by selective pressures remains undefined. The apparent clustering of these genes on sex chromosomes makes this genomic region an attractive model system to study the effects of evolutionary forces. In the present study, we analysed the genetic diversity of a X-linked microsatellite in 1410 X-chromosomes from 10 different human populations. Allelic frequency distributions revealed an unexpected discrepancy between the sexes. By evaluating the different scenarios that could have led to this pattern, we show that sex-specific selection on the tightly linked VCX gene could be the most likely cause of such a distortion.

Identification of cis-regulatory motifs has been difficult due to the short and variable length of the sequences that bind transcription factors. Using both sequence and microarray expression data, we present a method for identifying cis-regulatory motifs that uses regression trees to refine results from simple linear regression of expression levels on motif counts. Analysis of expression patterns from two separate datasets for genes showing significant differences in expression between the sexes in Drosophila melanogaster resulted in a model that identified known binding sites upstream of genes that are differentially expressed in the germline. We obtained a strong result for motif TCGATA, part of the larger, characterized binding site of dGATAb protein. We also identified an uncharacterized motif that is positively associated with sex-biased expression and was assembled from smaller motifs grouped by our model. A regression tree model provides a grouping of independent variables into multiple linear models, an advantage over a single multivariate model. In our case, this grouping of motifs suggests binding sites for cooperating factors in sex-specific expression, as well as a way of combining smaller motifs into larger binding sites.

Newly occurring adaptive genes, such as those providing insecticide resistance, display a fitness cost which is poorly understood. In order to detect subtle behavioural changes induced by the presence of resistance genes, we used natural predators and compared their differential predation on susceptible and resistant Culex pipiens mosquitoes, using strains with a similar genetic background. Resistance genes were either coding an overproduced detoxifying esterase (locus Ester), or an insensitive target (locus ace-1). Differential predation was measured between susceptible and resistant individuals, as well as among resistant mosquitoes. A backswimmer, a water measurer, a water boatman and a predaceous diving beetle were used as larval predators, and a pholcid spider as adult predator. Overall, the presence of a resistance gene increased the probability of predation: all resistance genes displayed predation costs relative to susceptible ones, at either the larval or adult stage, or both. Interestingly, predation preferences among the susceptible and the resistance genes were not ranked uniformly. Possible explanations for these results are given, and we suggest that predators, which are designed by natural selection to detect specific behavioural phenotypes, are useful tools to explore non-obvious differences between two classes of individuals, for example when they differ by the presence or absence of one recent gene, such as insecticide resistance genes.

We used simultaneous mapping of interacting quantitative trait locus (QTL) pairs to study various growth traits in a chicken F2 intercross. The method was shown to increase the number of detected QTLs by 30% compared with a traditional method detecting QTLs by their marginal genetic effects. Epistasis was shown to be an important contributor to the genetic variance of growth, with the largest impact on early growth (before 6 weeks of age). There is also evidence for a discrete set of interacting loci involved in early growth, supporting the previous findings of different genetic regulation of early and late growth in chicken. The genotype–phenotype relationship was evaluated for all interacting QTL pairs and 17 of the 21 evaluated QTL pairs could be assigned to one of four clusters in which the pairs in a cluster have very similar genetic effects on growth. The genetic effects of the pairs indicate commonly occurring dominance-by-dominance, heterosis and multiplicative interactions. The results from this study clearly illustrate the increase in power obtained by using this novel method for simultaneous detection of epistatic QTL, and also how visualization of genotype–phenotype relationships for epistatic QTL pairs provides new insights to biological mechanisms underlying complex traits.

This study investigated whether quantitative trait loci (QTL) identified in experimental crosses of chickens provide a short cut to the identification of QTL in commercial populations. A commercial population of broilers was targeted for chromosomal regions in which QTL for traits associated with meat production have previously been detected in extreme crosses. A three-generation design, consisting of 15 grandsires, 608 half-sib hens and over 15000 third-generation offspring, was implemented within the existing breeding scheme of a broiler breeding company. The first two generations were typed for 52 microsatellite markers spanning regions of nine chicken chromosomes and covering a total of 730 cM, approximately one-fifth of the chicken genome. Using half-sib analyses with a multiple QTL model, linkage was studied between these regions and 17 growth and carcass traits. Out of 153 trait×region comparisons, 53 QTL exceeded the threshold for genome-wide significance while an additional 23 QTL were significant at the nominal 1% level. Many of the QTL affect the carcass proportions and feed intake, for which there are few published studies. Given intensive selection for efficient growth in broilers for more than 50 generations it is surprising that many QTL affecting these traits are still segregating. Future fine-mapping efforts could elucidate whether ancestral mutations are still segregating as a result of pleiotropic effects on fitness traits or whether this variation is due to new mutations.