No abstract

A theoretical analysis of the effects of inversions on recombination and gene flux between arrangements caused by gene conversion and crossing over was carried out. Two different mathematical models of recombination were used: the Poisson model (without interference) and the Counting model (with interference). The main results are as follows. (1) Recombination and gene flux are highly site-dependent both inside and outside the inverted regions. (2) Crossing over overwhelms gene conversion as a cause of gene flux in large inversions, while conversion becomes relatively significant in short inversions and in regions around the breakpoints. (3) Under the Counting model the recombination rate between two markers depends strongly on the position of the markers along the inverted segment. Two equally spaced markers in the central part of the inverted segment have less recombination than if they are in a more extreme position. (4) Inversions affect recombination rates in the uninverted regions of the chromosome. Recombination increases in the distal segment and decreases in the proximal segment. These results provide an explanation for a number of observations reported in the literature. Because inversions are ubiquitous in the evolutionary history of many Drosophila species, the effects of inversions on recombination are expected to influence DNA variation patterns.

Recombination is a main factor determining nucleotide variability in different regions of the genome. Chromosomal inversions, which are ubiquitous in the genus Drosophila, are known to reduce and redistribute recombination, and thus their specific effect on nucleotide variation may be of major importance as an explanatory factor for levels of DNA variation. Here, we use the coalescent approach to study this effect. First, we develop analytical expressions to predict nucleotide variability in old inversion polymorphisms that have reached mutation-drift-flux equilibrium. The effects on nucleotide variability of a new arrangement appearing in the population and reaching a stable polymorphism are then studied by computer simulation. We show that inversions modulate nucleotide variability in a complex way. The establishment of an inversion polymorphism involves a partial selective sweep that eliminates part of the variability in the population. This is followed by a slow convergence to the equilibrium values. During this convergence, regions close to the breakpoints exhibit much lower variability than central regions. However, at equilibrium, regions close to the breakpoints have higher levels of variability and differentiation between arrangements than regions in the middle of the inverted segment. The implications of these findings for overall variability levels during the evolution of Drosophila species are discussed.

The levels and patterns of variation at a neutral locus are analyzed in a haploid asexual population undergoing accumulation of deleterious mutations due to Muller's ratchet. We find that the movement of Muller's ratchet can be associated with a considerable reduction in genetic diversity below classical neutral expectation. The extent to which variability is reduced is a function of the deleterious mutation rate, the fitness effects of the mutations, and the population size. Approximate analytical expressions for the expected genetic diversity are compared with simulation results under two different models of deleterious mutations: a model where all deleterious mutations have equal effects and a model where there are two classes of deleterious mutations. We also find that Muller's ratchet can produce a considerable distortion in the neutral frequency spectrum toward an excess of rare variants.

DNA sequence variation studies report the transfer of small segments of DNA among different sequences caused by gene conversion events. Here, we provide an algorithm to detect gene conversion tracts and a statistical model to estimate the number and the length distribution of conversion tracts for population DNA sequence data. Two length distributions are defined in the model: (1) that of the observed tract lengths and (2) that of the true tract lengths. If the latter follows a geometric distribution, the relationship between both distributions depends on two basic parameters: ψ, which measures the probability of detecting a converted site, and φ the parameter of the geometric distribution, from which the average true tract length, 1 / (1 – φ), can be estimated. Expressions are provided for estimating φ by the method of the moments and that of the maximum likelihood. The robustness of the model is examined by computer simulation. The present methods have been applied to the published rp49 sequences of Drosophila subobscura. Maximum likelihood estimate of φ for this data set is 0.9918, which represents an average conversion tract length of 122 bp. Only a small percentage of extant conversion events is detected.