Evolution of the obscura group Drosophila species.: III. phylogenetic relationships in the subobscura cluster based on homologies of chromosome A

The Drosophila subobscura cluster comprises D. subobscura, D. madeirensis and D. guanche, species closely related to some interspecific crosses are possible. This paper clarifies definitively the homologies of the segments of the sex chromosome A (= X) among these species and thus permits a phylogenetic seriation of them. This seriation is identical to the one suggested by the study of chromosome O and concordant with similar data for the remaining three rod autosomes (J, U and E), which, however, do not provide qualitative evidence on this subject.info:eu-repo/semantics/publishedVersio

How and Why Chromosome Inversions Evolve

Chromosome inversions are a major engine of genome evolution. New genomic and ecological data are beginning to reveal the evolutionary forces that drive the evolution of inversions

Arm-specific dynamics of chromosome evolution in malaria mosquitoes

<p>Abstract</p> <p>Background</p> <p>The malaria mosquito species of subgenus <it>Cellia </it>have rich inversion polymorphisms that correlate with environmental variables. Polymorphic inversions tend to cluster on the chromosomal arms 2R and 2L but not on X, 3R and 3L in <it>Anopheles gambiae </it>and homologous arms in other species. However, it is unknown whether polymorphic inversions on homologous chromosomal arms of distantly related species from subgenus <it>Cellia </it>nonrandomly share similar sets of genes. It is also unclear if the evolutionary breakage of inversion-poor chromosomal arms is under constraints.</p> <p>Results</p> <p>To gain a better understanding of the arm-specific differences in the rates of genome rearrangements, we compared gene orders and established syntenic relationships among <it>Anopheles gambiae, Anopheles funestus</it>, and <it>Anopheles stephensi</it>. We provided evidence that polymorphic inversions on the 2R arms in these three species nonrandomly captured similar sets of genes. This nonrandom distribution of genes was not only a result of preservation of ancestral gene order but also an outcome of extensive reshuffling of gene orders that created new combinations of homologous genes within independently originated polymorphic inversions. The statistical analysis of distribution of conserved gene orders demonstrated that the autosomal arms differ in their tolerance to generating evolutionary breakpoints. The fastest evolving 2R autosomal arm was enriched with gene blocks conserved between only a pair of species. In contrast, all identified syntenic blocks were preserved on the slowly evolving 3R arm of <it>An. gambiae </it>and on the homologous arms of <it>An. funestus </it>and <it>An. stephensi</it>.</p> <p>Conclusions</p> <p>Our results suggest that natural selection favors specific gene combinations within polymorphic inversions when distant species are exposed to similar environmental pressures. This knowledge could be useful for the discovery of genes responsible for an association of inversion polymorphisms with phenotypic variations in multiple species. Our data support the chromosomal arm specificity in rates of gene order disruption during mosquito evolution. We conclude that the distribution of breakpoint regions is evolutionary conserved on slowly evolving arms and tends to be lineage-specific on rapidly evolving arms.</p

On the power and the systematic biases of the detection of chromosomal inversions by paired-end genome sequencing

One of the most used techniques to study structural variation at a genome level is paired-end mapping (PEM). PEM has the advantage of being able to detect balanced events, such as inversions and translocations. However, inversions are still quite difficult to predict reliably, especially from high-throughput sequencing data. We simulated realistic PEM experiments with different combinations of read and library fragment lengths, including sequencing errors and meaningful base-qualities, to quantify and track down the origin of false positives and negatives along sequencing, mapping, and downstream analysis. We show that PEM is very appropriate to detect a wide range of inversions, even with low coverage data. However, % of inversions located between segmental duplications are expected to go undetected by the most common sequencing strategies. In general, longer DNA libraries improve the detectability of inversions far better than increments of the coverage depth or the read length. Finally, we review the performance of three algorithms to detect inversions -SVDetect, GRIAL, and VariationHunter-, identify common pitfalls, and reveal important differences in their breakpoint precisions. These results stress the importance of the sequencing strategy for the detection of structural variants, especially inversions, and offer guidelines for the design of future genome sequencing projects

The adaptive significance of chromosomal inversion polymorphisms in Drosophila melanogaster

Chromosomal inversions, structural mutations that reverse a segment of a chromosome, cause suppression of recombination in the heterozygous state. Several studies have shown that inversion polymorphisms can form clines or fluctuate predictably in frequency over seasonal time spans. These observations prompted the hypothesis that chromosomal rearrangements might be subject to spatially and/or temporally varying selection. Here, we review what has been learned about the adaptive significance of inversion polymorphisms in the vinegar fly Drosophila melanogaster, the species in which they were first discovered by Sturtevant in 1917. A large body of work provides compelling evidence that several inversions in this system are adaptive; however, the precise selective mechanisms that maintain them polymorphic in natural populations remain poorly understood. Recent advances in population genomics, modelling and functional genetics promise to greatly improve our understanding of this long‐standing and fundamental problem in the near future

Prediction and estimation of effective population size

Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics, and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci, and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating Ne for future research