Showing papers by "Liqing Zhang published in 2007"
TL;DR: The results show that different mechanisms contribute differently to the evolution of small and large gene families, including unequal crossover and retrotransposition.
Abstract: Background: The rate of gene duplication is an important parameter in the study of evolution, but the influence of gene conversion and technical problems have confounded previous attempts to provide a satisfying estimate. We propose a new strategy to estimate the rate that involves separate quantification of the rates of two different mechanisms of gene duplication and subsequent combination of the two rates, based on their respective contributions to the overall gene duplication rate. Results: Previous estimates of gene duplication rates are based on small gene families. Therefore, to assess the applicability of this to families of all sizes, we looked at both two-copy gene families and the entire genome. We studied unequal crossover and retrotransposition, and found that these mechanisms of gene duplication are largely independent and account for a substantial amount of duplicated genes. Unequal crossover contributed more to duplications in the entire genome than retrotransposition did, but this contribution was significantly less in two-copy gene families, and duplicated genes arising from this mechanism are more likely to be retained. Combining rates of duplication using the two mechanisms, we estimated the overall rates to be from approximately 0.515 to 1.49 × 10 -3 per gene per million years in human, and from approximately 1.23 to 4.23 × 10 -3 in mouse. The rates estimated from two-copy gene families are always lower than those from the entire genome, and so it is not appropriate to use small families to estimate the rate for the entire genome. Conclusion: We present a novel strategy for estimating gene duplication rates. Our results show that different mechanisms contribute differently to the evolution of small and large gene families.
45 citations
TL;DR: It is shown that both chromosomal proximity and expression correlation in TAGs do not differ significantly from their neighboring non-TAG gene pairs, suggesting that tandem duplication is unlikely to be the cause for the higher-than-random expression association between neighboring genes on a chromosome in human and mouse.
Abstract: Tandemly arrayed genes (TAGs) account for about one third of the duplicated genes in eukaryotic genomes, yet there has not been any systematic study of their gene expression patterns Taking advantage of recently published large-scale microarray data sets, we studied the expression divergence of 361 two-member TAGs in human and 212 two-member TAGs in mouse and examined the effect of sequence divergence, gene orientation, and chromosomal proximity on the divergence of TAG expression patterns Our results show that there is a weak negative correlation between sequence divergence of TAG members and their expression similarity There is also a weak negative correlation between chromosomal proximity of TAG members and their expression similarity We did not detect any significant relationship between gene orientation and expression similarity We also found that downstream TAG members do not show significantly narrower expression breadth than upstream members, contrary to what we predict based on TAG expression divergence hypothesis that we propose Finally, we show that both chromosomal proximity and expression correlation in TAGs do not differ significantly from their neighboring non-TAG gene pairs, suggesting that tandem duplication is unlikely to be the cause for the higher-than-random expression association between neighboring genes on a chromosome in human and mouse
6 citations
TL;DR: This work extends the work of Whitlock in examining the critical effective population sizes from the fixation of both deleterious and beneficial mutations under drift and selection to prevent mutation breakdown of the population.
Abstract: This work extends the work of Whitlock in examining the critical effective population sizes from the fixation of both deleterious and beneficial mutations under drift and selection to prevent mutation breakdown of the population. The validity of approximations for the probability of fixation depends on the nature of the assumed distribution for the fitness effect of both types of mutations. Using no approximation for the probability of fixation and assuming a heavy tailed fitness effect distribution, the current model indicates that the coefficients of variation for the fitness effect distributions of both types of mutations and the fitness effect distribution mean for the beneficial mutations are important predictors of the critical effective population size. The current model further predicts that very small populations can be sustained if the fitness effect variances for both types of mutations and the mean for beneficial mutations are large.
2 citations
07 May 2007
TL;DR: A novel way to identify antisense genes is presented and the results obtained through it are shown to show a possible way that may lead to more accurate prediction of antisensing genes.
Abstract: Antisense genes have been shown to have a variety of functions in both prokaryotes and recently in eukaryotes as well. They are hypothesized to be an important part of every genome and have been shown to be evolutionarily conserved as well. Naturally, it is in our interest to develop a software for identifying antisense pairs. While a variety of approaches and software do exist, each approach has its limitations and the software is not meant for large-scale analyses for identifying both cis and trans antisense genes. Here we present a novel way to identify antisense genes and show the results we obtained through it. While in no means a perfect solution, we do manage to show a possible way that may lead to more accurate prediction of antisense genes.