The genome of bread wheat is hexaploid and contains 1·6×1010 bp of DNA, of which more than 80% is repetitive sequences. Its size and complexity represent a challenge for the isolation of agronomically important genes, for which we frequently know only their position on the genetic map. Recently, new genomic resources and databases from genome projects have simplified the molecular analysis of the wheat genome. The first genes to be isolated from wheat by map-based cloning include three resistance genes against the fungal diseases powdery mildew and leaf rust. In this review, we will describe the approaches and resources that have contributed to this progress, and discuss genomic strategies that will simplify positional cloning in wheat in the near future.

A mutation endowing herbicide resistance is often found to induce a parallel morphological or fitness penalty. To test whether such ‘cost’ of resistance to herbicides is expressed through lower resource acquisition, changes in resource allocation, or both, is of ecological significance. Here, we analysed 12 morphological traits in 900 plants covering three herbicide resistance mutations at genes AUX1, AXR1 and AXR2 in the model species Arabidopsis thaliana. Comparing these 2,4-D herbicide-resistant homozygous (RR) and heterozygous (RS) plants to homozygous susceptible (SS) plants, this analysis estimates the dominance level of the resistance allele on morphology. We also demonstrated that the herbicide resistance cost was primarily expressed as a change in resource acquisition (62·1–94% of the analysed traits). Although AUX1, AXR1 and AXR2 genes act in the same metabolic pathway of auxin response, each resistance factor was found to have its own unique signature in the way the cost was expressed. Furthermore, no link was observed between the absolute fitness penalty and the respective modifications of resource acquisition and/or resource allocation in the resistant plants. These results and their implications for herbicide resistance spread and establishment are discussed.

The typical life cycle of aphids involves several parthenogenetic generations followed by a single sexual one in autumn, i.e. cyclical parthenogenesis. Sexual females are genetically identical to their parthenogenetic mothers and carry two sex chromosomes (XX). Male production involves the elimination of one sex chromosome (to produce X0) that could give rise to genetic conflicts between X-chromosomes. In addition, deleterious recessive mutations could accumulate on sex chromosomes during the parthenogenetic phase and affect males differentially depending on the X-chromosome they inherit. Genetic conflicts and deleterious mutations thus may induce transmission bias that could be exaggerated in males. Here, the transmission of X-chromosomes has been studied in the laboratory in two cyclically parthenogenetic lineages of the bird cherry-oat aphid Rhopalosiphum padi. X-chromosome transmission was followed, using X-linked microsatellite loci, at male production in the two lineages and in their hybrids deriving from reciprocal crosses. Genetic analyses revealed non-Mendelian inheritance of X-chromosomes in both parental and hybrid lineages at different steps of male function. Putative mechanisms and evolutionary consequences of non-Mendelian transmission of X-chromosomes to males are discussed.

Divergence between species in regulatory pathways may contribute to hybrid incompatibilities such as sterility. Consistent with this idea, genes involved in male fertility often evolve faster than most other genes both in amino acid sequence and in expression. Previously, we identified a panel of male-specific genes underexpressed in sterile male hybrids of Drosophila simulans and D. mauritiana relative to pure species, and we showed that this underexpression is associated with infertility. In a preliminary effort to assess the generalities in the patterns of evolution of these genes, I examined patterns of mRNA expression in three of these genes in sterile F1 hybrid males of D. pseudoobscura and D. persimilis. F1 hybrid males bearing D. persimilis X chromosomes underexpressed all these genes relative to the parental species, while hybrids bearing D. pseudoobscura X chromosomes underexpressed two of these three genes. Interestingly, the third gene, CG5762, has undergone extensive amino acid evolution within the D. pseudoobscura species group, possibly driven by positive natural selection. We conclude that some of the same genes exhibit disruptions in expression within each of the two species groups, which could suggest commonalities in the regulatory architecture of sterility in these groups. Alternative explanations are also considered.

We performed a quantitative trait locus (QTL) analysis of eight body weights recorded weekly from 3 weeks to 10 weeks after birth and two weight gains recorded between 3 weeks and 6 weeks, and between 6 weeks and 10 weeks in an intersubspecific backcross population of wild Mus musculus castaneus mice captured in the Philippines and the common inbred strain C57BL/6J (M. musculus domesticus), to elucidate the complex genetic architecture of body weight and growth. Interval mapping identified 17 significant QTLs with main effects on 11 chromosomes. In particular, the main effect of the most potent QTL on proximal chromosome 2 increased linearly with age, whereas other QTLs exerted effects on either the early or late growth period. Surprisingly, although wild mice displayed 60% of the body size of their C57BL/6J counterparts, the wild-derived allele enhanced growth at two QTLs. Interestingly, five of the 17 main-effect QTLs identified had significant epistatic interaction effects. Five new epistatic QTLs with no main effects were identified on different chromosomes or regions. For one pair of epistatic QTLs, mice that were heterozygous for the wild-derived allele at one QTL and homozygous for that allele at another QTL exhibited the most rapid growth in all four possible genotypic combinations. Out of the identified QTLs, several showed significant sex-specific effects.

Quantitative trait loci (QTL) are usually searched for using classical interval mapping methods which assume that the trait of interest follows a normal distribution. However, these methods cannot take into account features of most survival data such as a non-normal distribution and the presence of censored data. We propose two new QTL detection approaches which allow the consideration of censored data. One interval mapping method uses a Weibull model (W), which is popular in parametrical modelling of survival traits, and the other uses a Cox model (C), which avoids making any assumption on the trait distribution. Data were simulated following the structure of a published experiment. Using simulated data, we compare W, C and a classical interval mapping method using a Gaussian model on uncensored data (G) or on all data (G′=censored data analysed as though records were uncensored). An adequate mathematical transformation was used for all parametric methods (G, G′ and W). When data were not censored, the four methods gave similar results. However, when some data were censored, the power of QTL detection and accuracy of QTL location and of estimation of QTL effects for G decreased considerably with censoring, particularly when censoring was at a fixed date. This decrease with censoring was observed also with G′, but it was less severe. Censoring had a negligible effect on results obtained with the W and C methods.

Marker-assisted introgression or backcrossing is a widely used method to improve commercial breeding lines or study the effects of genes in a homogeneous genetic background. In this context, the recovery of the recipient parent genome is a major objective of backcrossing. Selection on markers has been shown to be very useful to accelerate the rate of recovery of the recipient parent genome in backcrossing. In this study we show how much information markers give on the true genetic composition of individuals by deriving the variance and estimating the distribution of the genetic composition of individuals sharing a known genotype at markers. These calculations enable predictions of the number of individuals carrying an ideal genotype at markers that must be produced to fulfil background selection objectives.

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances, corresponding to the maximum likelihood estimator, performs better than estimators based on the posterior expectation. We also show that while the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors, the MCMC-based method has a distinct advantage in the presence of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances.