The extent to which epistasis contributes to adaptation and speciation has been a controversial topic in evolutionary genetics. One experimental approach to study epistasis is based on quantitative trait locus (QTL) mapping using molecular markers. Comparisons can be made among all possible pair-wise combinations of the markers, irrespective of whether an additive QTL is associated with a marker; several software packages have been developed that facilitate this. We review several examples of using this approach to identify epistatic QTLs for traits of evolutionary or ecological interest. While there is variability in the results, the number of epistatic QTL interactions is often greater than or equal to the number of additive QTLs. The magnitude of epistatic effects can be larger than the additive effects. Thus, epistatic interactions seem to be an important part of natural genetic variation. Future studies of epistatic QTLs could lead to descriptions of the genetic networks underlying variation for fitness-related traits.

Aedes (Stegomyia) aegypti (L.) and Aedes (Stegomyia) albopictus (Skuse) are the most important vectors of the dengue and yellow-fever viruses. Both took advantage of trade developments to spread throughout the tropics from their native area: A. aegypti originated from Africa and A. albopictus from South-East Asia. We investigated the relationships between A. aegypti and A. albopictus mosquitoes based on three mitochondrial-DNA genes (cytochrome b, cytochrome oxidase I and NADH dehydrogenase subunit 5). Little genetic variation was observed for A. albopictus, probably owing to the recent spreading of the species via human activities. For A. aegypti, most populations from South America were found to be genetically similar to populations from South-East Asia (Thailand and Vietnam), except for one sample from Boa Vista (northern Amazonia), which was more closely related to samples from Africa (Guinea and Ivory Coast). This suggests that African populations of A. aegypti introduced during the slave trade have persisted in Boa Vista, resisting eradication campaigns.

The degree to which genetic variation in a given trait varies among different populations of the same species and across different environments has seldom been quantified in wild vertebrate species. We investigated the expression of genetic variability and maternal effects in three larval life-history traits of the amphibian Rana temporaria. In a factorial laboratory experiment, five widely separated populations (max. 1600 km) were subjected to two different environmental treatments. Animal model analyses revealed that all traits were heritable (h2≈0·20) in all populations and under most treatment combinations. Although the cross-food treatment genetic correlations were close to unity, heritabilities under a restricted food regime tended to be lower than those under an ad libitum food regime. Likewise, maternal effects (m2≈0·05) were detected in most traits, and they tended to be most pronounced under restricted food conditions. We detected several cross-temperature genetic and maternal effects correlations that were lower than unity, suggesting that genotype–environment interactions and maternal effect–environment interactions are a significant source of phenotypic variation. The results reinforce the perspective that although the expression of genetic and maternal effects may be relatively homogeneous across different populations of the same species, local variation in environmental conditions can lead to significant variation in phenotypic expression of quantitative traits through genotype–environment and maternal effect–environment interactions.

The ancestral karyotype of the house mouse (Mus musculus) consists of 40 acrocentric chromosomes, but numerous races exist within the domesticus subspecies characterized by different metacentric chromosomes formed by the joining at the centromere of two acrocentrics. An exemplary case is present on the island of Madeira where six highly divergent chromosomal races have accumulated different combinations of 20 metacentrics in 500–1000 years. Chromosomal cladistic phylogenies were performed to test the relative performance of Robertsonian (Rb) fusions, Rb fissions and whole-arm reciprocal translocations (WARTs) in resolving relationships between the chromosomal races. The different trees yielded roughly similar topologies, but varied in the number of steps and branch support. The analyses using Rb fusions/fissions as characters resulted in poorly supported trees requiring six to eight homoplasious events. Allowance for WARTs considerably increased nodal support and yielded the most parsimonious trees since homoplasy was reduced to a single event. The WART-based trees required five to nine WARTs and 12 to 16 Rb fusions. These analyses provide support for the role of WARTs in generating the extensive chromosomal diversification observed in house mice. The repeated occurrence of Rb fusions and WARTs highlights the contribution of centromere-related rearrangements to accelerated rates of chromosomal change in the house mouse.

Markers with segregation ratio distortion are commonly observed in data sets used for quantitative trait locus (QTL) mapping. In this study, a multipoint method of maximum likelihood (ML) was newly developed to estimate the positions and effects of the segregation distortion loci (SDLs) in two F2 populations of rice (Oryza sativa L.), i.e. Taichung65/Bhadua (TB; japonica–indica cross) and CPSLO17/W207-2 (CW; japonica–japonica). Of the four parents, W207-2 and Bhadua were found to be spikelet semi-sterile and stably inherited through selfing, and spikelet fertility segregated in the two populations. Therefore, recombination frequencies were recalculated after mapping the SDLs by using the multipoint method, and the molecular linkage maps of the two F2 populations were constructed to detect QTLs underlying spikelet fertility. As a result, five SDLs in the TB population were mapped on chromosomes 1, 3, 8 and 9, respectively. Two major QTLs underlying spikelet fertility, namely qSS-6a and qSS-8a, were detected on chromosomes 6 and 8, respectively. In the CW population, a total of 12 SDLs were detected on all 12 chromosomes except 1, 5, 7 and 11. Three QTLs underlying spikelet sterility, namely qSS-2, qSS-6b and qSS-8b on chromosomes 2, 6 and 8, were determined on the whole genome scale. Interestingly, both qSS-6a and qSS-6b, detected in the two F2 populations respectively, were located on a similar position as the S5 gene on chromosome 6; while qSS-8a and qSS-8b were also simultaneously detected on similar positions of the short arm of chromosome 8 in the two populations, which should be a new sterility gene showing the same type of zygotic selection.

We have isolated the clock gene period (per) from the medfly Ceratitis capitata, one of the most economically important insect pest species. The overall pattern of conserved, non-conserved and functional domains that are observed within dipteran and lepidopteran per orthologues is preserved within the coding sequence. Expression analysis from fly heads revealed a daily oscillation in per mRNA in both light[ratio ]dark cycles and in constant darkness. However PER protein levels from head extracts did not show any significant evidence for cycling in either of these two conditions. When the Ceratitis per transgene under the control of the Drosophila per promoter and 3′UTR was introduced into Drosophila per-null mutant hosts, the transformants revealed a low level of rescue of behavioural rhythmicity. Nevertheless, the behaviour of the rhythmic transformants showed some similarities to that of Ceratitis, suggesting that Ceratitis per carries species-specific information that can evidently affect the Drosophila host's downstream rhythmic behaviour.

The effect was investigated of the hypomorphic DNA double-strand break repair, notably synthesis-dependent strand annealing, deficient mutation mus309 on the third chromosome of Drosophila melanogaster on intergenic and intragenic meiotic recombination in the X chromosome. The results showed that the mutation significantly increases the frequency of intergenic crossing over in two of three gene intervals of the X chromosome studied. Interestingly the increase was most prevalent in the tip of the X chromosome where crossovers normally are least frequent per physical map unit length. In particular crossing over interference was also affected, indicating that the effect of the mus309 mutation involves preconditions of crossing over but not the event of crossing over itself. On the other hand, the results also show that most probably the mutation does not have any effect on intragenic recombination, i.e. gene conversion. These results are fully consistent with the present molecular models of meiotic crossing over initiated by double-strand breaks of DNA followed by formation of a single-end-invasion intermediate, or D-loop, which is subsequently processed to generate either crossover or non-crossover products involving formation of a double Holliday junction. In particular the results suggest that the mus309 gene is involved in resolution of the D-loop, thereby affecting the choice between double-strand-break repair (DSBR) and synthesis-dependent strand annealing (SDSA) pathways of meiotic recombination.

Sequence polymorphisms result in phenotypic variation through the pathways of interacting genes and their products. We focused on transcript-level variation in the splicing pathway for sex determination – a model network defining downstream morphological characters that are dimorphic between males and females. Expression of Sex lethal, transformer, transformer2, doublesex, intersex and hermaphrodite was assayed with quantitative RT-PCR in 0- to 1-day-old adult males and females of 36 Drosophila melanogaster inbred lines. Abundant genetic variation in the transcript levels was found for all genes. Sex-specific splices had high concentrations in the appropriate sex. In the other sex, low but detectable concentrations were also observed. Abundances of splices strongly co-varied between sexes among genotypes, with little genetic variation strictly limited to one sex. The level of sexually dimorphic Yolk protein1 expression – an immediate downstream target of the pathway – was modelled as the target phenotype of the upstream sex determination pathway. Substantial genetic variation in this phenotype in males was explained by leaky splicing of female-specific transcripts. If higher transcript levels of the appropriate isoform of sex determination genes are beneficial in a sex, then stronger leakiness of the inappropriate transcript might be deleterious, perhaps contributing to the fitness trade-offs previously observed between the sexes.

Sperm competition is an important fitness component in many animal groups. Drosophila melanogaster males exhibit substantial genetic variation for sperm competitive ability and females show considerable genetic variation for first versus second male sperm use. Currently, the forces responsible for maintaining genetic variation in sperm competition related phenotypes are receiving much attention. While several candidate genes contributing to the variation seen in male competitive ability are known, genes involved in female sperm use remain largely undiscovered. Without knowledge of the underlying genes, it will be difficult to distinguish between different models of sexual selection such as cryptic female choice and sexual conflict. We used quantitative trait locus (QTL) mapping to identify regions of the genome contributing to female propensity to use first or second male sperm, female refractoriness to re-mating, and early-life fertility. The most well supported markers influencing the phenotypes include 33F/34A (P2), 57B (refractoriness) and 23F/24A (fertility). Between 10% and 15% of the phenotypic variance observed in these recombinant inbred lines was explained by these individual QTLs. More detailed investigation of the regions detected in this experiment may lead to the identification of genes responsible for the QTLs identified here.

Cluster analyses of gene expression data are usually conducted based on their associations with the phenotype of a particular disease. Many disease traits have a clearly defined binary phenotype (presence or absence), so that genes can be clustered based on the differences of expression levels between the two contrasting phenotypic groups. For example, cluster analysis based on binary phenotype has been successfully used in tumour research. Some complex diseases have phenotypes that vary in a continuous manner and the method developed for a binary trait is not immediately applicable to a continuous trait. However, understanding the role of gene expression in these complex traits is of fundamental importance. Therefore, it is necessary to develop a new statistical method to cluster expressed genes based on their association with a quantitative trait phenotype. We developed a model-based clustering method to classify genes based on their association with a continuous phenotype. We used a linear model to describe the relationship between gene expression and the phenotypic value. The model effects of the linear model (linear regression coefficients) represent the strength of the association. We assumed that the model effects of each gene follow a mixture of several multivariate Gaussian distributions. Parameter estimation and cluster assignment were accomplished via an Expectation-Maximization (EM) algorithm. The method was verified by analysing two simulated datasets, and further demonstrated using real data generated in a microarray experiment for the study of gene expression associated with Alzheimer's disease.

The fate of lethal alleles in populations is of interest in evolutionary and conservation biology for several reasons. For instance, lethals may contribute substantially to inbreeding depression. The frequency of lethal alleles depends on population size, but it is not clear how it is affected by population structure. By analysing the case of the infinite island model by numerical approaches and analytical approximations it is shown that, like population size, population structure affects the fate of lethal alleles if dominance levels are low. Inbreeding depression caused by such alleles is also affected by the population structure, whereas the mutation load is only weakly affected. Heterosis also depends on population structure, but it always remains low, of the order of the mutation rate or less. These patterns are compared with those caused by mildly deleterious mutations to give a general picture of the effect of population structure on inbreeding depression, heterosis, and the mutation load.

Two growth-selected lines in chickens have been developed from a single founder population by divergent selection for body weight at 56 days of age. After more than 40 generations of selection they show a nine-fold difference in body weight at selection age and large differences in growth rate, appetite, fat deposition and metabolic characteristics. We have generated a large intercross between these lines comprising more than 800 F2 birds. QTL mapping revealed 13 loci affecting growth. The most striking observation was that the allele in the high weight line in all cases was associated with enhanced growth, but each locus explained only a small proportion of the phenotypic variance using a standard QTL model (1·3–3·1%). This result is in sharp contrast to our previous study where we reported that the two-fold difference in adult body size between the red junglefowl and White Leghorn domestic chickens is explained by a small number of QTLs with large additive effects. Furthermore, no QTLs for anorexia or antibody response were detected despite large differences for these traits between the founder lines. The result is an excellent example where a large phenotypic difference between populations occurs in the apparent absence of any single locus with large phenotypic effects. The study underscores the need for powerful experimental designs in genetic studies of multifactorial traits. No QTL at all would have reached genome-wide significance using a less powerful design (e.g. approx. 200 F2 individuals) regardless of the nine-fold phenotypic difference between the founder lines for the selected trait.

The mechanism underlying the maintenance of adaptive genetic variation is a long-standing question in evolutionary genetics. There are two concepts (mutation–selection balance and balancing selection) which are based on the phenotypic differences between alleles. Mutation – selection balance and balancing selection cannot properly explain the process of gene substitution, i.e. the molecular evolution of quantitative trait loci affecting fitness. I assume that such loci have non-essential functions (small effects on fitness), and that they have the potential to evolve into new functions and acquire new adaptations. Here I show that a high amount of neutral polymorphism at these loci can exist in real populations. Consistent with this, I propose a hypothesis for the maintenance of genetic variation in life history traits which can be efficient for the fixation of alleles with very small selective advantage. The hypothesis is based on neutral polymorphism at quantitative trait loci and both neutral and adaptive gene substitutions. The model of neutral – adaptive conversion (NAC) assumes that neutral alleles are not neutral indefinitely, and that in specific and very rare situations phenotypic (relative fitness) differences between them can appear. In this paper I focus on NAC due to phenotypic plasticity of neutral alleles. The important evolutionary consequence of NAC could be the increased adaptive potential of a population. Loci responsible for adaptation should be fast evolving genes with minimally discernible phenotypic effects, and the recent discovery of genes with such characteristics implicates them as suitable candidates for loci involved in adaptation.

A Bayesian model and variable dimensional parameter estimation based on Markov chain Monte Carlo was applied to map quantitative trait loci (QTLs) in a doubled haploid mapping population of rainbow trout. To increase power, the analysis was performed using the multiple-QTL model, which simultaneously accounted for all the environmental and genetic main effects that influence the expression of early development life history traits. By doing so we obtained the posterior estimated effects for the environmental factors as well as the number, positions, and the effects for the QTLs. The analyses revealed QTLs for time at hatching, embryonic length and weight at swim-up stage. The posterior expectation of the number of QTLs in different linkage groups shows that at least four QTLs are needed to explain the observed differences in early development between the clonal lines. The Bayesian method effectively combined all the information available to accurately position these QTLs in the rainbow trout genome.

Mammalian mitochondrial genomes are organized in a conserved and extremely compact manner, encoding molecules that play a vital role in oxidative phosphorylation (OXPHOS) and carry out a number of other important biological functions. A large-scale screening of the normalized mitochondrial gene expression profiles generated from publicly available mammalian serial analysis of gene expression (SAGE) datasets (over 17·7 millions of tags) was performed in this study. Acquired SAGE libraries represent an extensive range of human, mouse, rat, bovine and swine cell and tissue samples (normal and pathological) in a variety of conditions. Using a straightforward in silico algorithm, variations in total mitochondrial gene expression, as well as in the expression of individual genes encoded by mitochondrial genomes are addressed, and common patterns in the species- and tissue-specific mitochondrial gene expression profiles are discussed.

Inbreeding depression threatens the survival of small populations of both captive and wild outbreeding species. In order to fully understand this threat, it is necessary to investigate what role purging plays in reducing inbreeding depression. Ballou (1997) undertook such an investigation on 25 mammalian populations, using an ancestral inbreeding regression model to detect purging. He concluded that there was a small but highly significant trend of purging on neonatal survival across the populations. We tested the performance of the regression model that Ballou used to detect purging on independently simulated data. We found that the model has low statistical power when inbreeding depression is caused by the build-up of mildly deleterious alleles. It is therefore possible that Ballou's study may have underestimated the effects of ancestral inbreeding on the purging of inbreeding depression in captive populations if their inbreeding depression was caused mainly by mildly deleterious mutations. We also developed an alternative regression model to Ballou's, which showed an improvement in the detection of purging of mildly deleterious alleles but performed less well if deleterious alleles were of a large effect.

To study the effects of maternal and endosperm quantitative trait locus (QTL) interaction on endosperm development, we derive a two-stage hierarchical statistical model within the maximum-likelihood context, implemented with an expectation-maximization algorithm. A model incorporating both maternal and offspring marker information can improve the accuracy and precision of genetic mapping. Extensive simulations under different sampling strategies, heritability levels and gene action modes were performed to investigate the statistical properties of the model. The QTL location and parameters are better estimated when two QTLs are located at different intervals than when they are located at the same interval. Also, the additive effect of the offspring QTLs is better estimated than the additive effect of the maternal QTLs. The implications of our model for agricultural and evolutionary genetic research are discussed.

Haplotype inference has become an important part of human genetic data analysis due to its functional and statistical advantages over the single-locus approach in linkage disequilibrium mapping. Different statistical methods have been proposed for detecting haplotype – disease associations using unphased multi-locus genotype data, ranging from the early approach by the simple gene-counting method to the recent work using the generalized linear model. However, these methods are either confined to case – control design or unable to yield unbiased point and interval estimates of haplotype effects. Based on the popular logistic regression model, we present a new approach for haplotype association analysis of human disease traits. Using haplotype-based parameterization, our model infers the effects of specific haplotypes (point estimation) and constructs confidence interval for the risks of haplotypes (interval estimation). Based on the estimated parameters, the model calculates haplotype frequency conditional on the trait value for both discrete and continuous traits. Moreover, our model provides an overall significance level for the association between the disease trait and a group or all of the haplotypes. Featured by the direct maximization in haplotype estimation, our method also facilitates a computer simulation approach for correcting the significance level of individual haplotype to adjust for multiple testing. We show, by applying the model to an empirical data set, that our method based on the well-known logistic regression model is a useful tool for haplotype association analysis of human disease traits.

There is increasing evidence that closely related species contain many polymorphisms that were present in their common ancestral species. Use of a more distant relative as an outgroup increases the ability to detect such ancestral polymorphisms. We describe a method for further improving estimates of the fraction of polymorphisms that are ancestral, and illustrate this with reference to data on Drosophila pseudoobscura and D. miranda. We also derive formulae for the proportion of fixations arising from ancestral polymorphisms and new mutations, respectively. The results should be useful for tests of selection based on the levels of expected and observed ancestral polymorphisms.

The Transforming growth factor-β (TGF-β) family control diverse cellular processes and specify cell-fate/differentiation during embryogenesis in vertebrates and invertebrates. Mutations disrupting TGF-β signalling lead to developmental abnormalities and a range of diseases such as cancer. Nodal is a major TGF-β signal, responsible for gastrulation in embryogenesis. Arkadia (Akd) was discovered by mouse gene-trap mutagenesis and encodes a nuclear E3 ubiquitin ligase. Akd allows the Nodal signal to reach its maximum level and Akd-null mice lack mammalian organiser (MO) and mesendodermal tissues. Although Akd RNA is ubiquitously expressed, Akd-null mice lose a subset of Nodal-dependent functions. The specificity of Akd function is therefore most likely to be regulated post-transcriptionally or by co-factors. Akd possesses differentially spliced 5′ untranslated regions (UTRs) and large 3′ UTR. We have employed bioinformatics and developed a reporter system to address Akd post-transcriptional regulation. Akd RNA may initiate from different promoters and 5′ UTR differential splicing, upstream AUGs (uAUGs) and open-reading frames upstream (uORFs) may regulate protein translation. 5′ and 3′ UTRs can interact to either destabilise or decrease translational efficiency of RNA. The nature of this interaction is cell-type and signal level dependent. These data may represent mechanisms by which translational control of Arkadia is achieved and ultimately how TGF-β/Nodal signalling is regulated during embryogenesis.