Genetical research最新文献

Drosophila pseudoobscura has been intensively studied by evolutionary biologists for over 70 years. The recent publication of the genome sequence not only permits studies of comparative genomics with other dipterans but also opens the door to identifying genes associated with adaptive traits or speciation or testing for the signature of natural selection across the genome. Information on regional rates of recombination, localization of inversion breakpoints distinguishing it from its sibling species D. persimilis, and known polymorphic markers may be useful in such studies. Here, we present a molecular linkage map of four of the five major chromosome arms of D. pseudoobscura. In doing so, we order and orient several sequence contig groups, localize the inversion breakpoints on chromosome 2 to intervals of 200 kilobases, and identify one error in the published sequence assembly. Our results show that regional recombination rates in D. pseudoobscura are much higher than in D. melanogaster and significantly higher even than in D. persimilis. Furthermore, we detect a non-significant positive correlation between recombination rate and published DNA sequence variation. Finally, the online Appendix presents 200 primer sequence pairs for molecular markers that can be used for mapping of quantitative trait loci, of which 125 are known to be polymorphic within or between species.

To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.

The comparison of the genetic differentiation of quantitative traits (QST) and molecular markers (FST) can inform on the strength and spatial heterogeneity of selection in natural populations, provided that markers behave neutrally. However, selection may influence the behaviour of markers in selfing species with strong linkage disequilibria among loci, therefore invalidating this test of detection of selection. We address this issue by monitoring the genetic differentiation of five microsatellite loci (FST) and nine quantitative traits (QST) in experimental metapopulations of the predominantly selfing species Arabidopsis thaliana, that evolved during eight generations. Metapopulations differed with respect to population size and selection heterogeneity. In large populations, the genetic differentiation of neutral microsatellites was much larger under heterogeneous selection than under uniform selection. Using simulations, we show that this influence of selection heterogeneity on FST can be attributable to initial linkage disequilibria among loci, creating stronger genetic differentiation of QTL than expected under a simple additive model with no initial linkage. We found no significant differences between FST and QST regardless of selection heterogeneity, despite a demonstrated effect of selection on QST values. Additional data are required to validate the role of mating system and linkage disequilibria in the joint evolution of neutral and selected genetic differentiation, but our results suggest that FST/QST comparisons can be conservative tests to detect selection in selfing species.

In drosophilid flies, male recombination and neo-sex chromosome formation are rare. Following the genotyping of full-sib families with 20 microsatellite markers and subsequent cytological work, we found evidence of both male recombination and neo-sex chromosome formation in Scaptodrosophila hibisci. As far as we are aware, this is the first report of male recombination and neo-sex chromosome formation co-occurring in a drosophilid fly. Two autosomal loci, Sh29c and Sh90, showed aberrant segregation of male parental alleles. We describe how an autosomal fission followed by fusion of one of the autosomal fragments to the Y chromosome to create a Y1Y2X1X2/X1X1X2X2 sex determination system provides the most parsimonious explanation of the patterns we observe. Male recombination was observed in three families, including autosomal linkage groups and the Y1/X2 linkage group. In addition to the X1 linkage group, two autosomal linkage groups were identified.

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 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.

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.

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.

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.

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 (h(2) approximately 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 (m(2) approximately 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.