Biomedical subjects

Colin D Meiklejohn

Publications and source records attributed to Colin D Meiklejohn.

7 recordsLinked to original sources

PubMed2005

Evolution of proteins and gene expression levels are coupled in Drosophila and are independently associated with mRNA abundance, protein length, and number of protein-protein interactions.

Organismic evolution requires that variation at distinct hierarchical levels and attributes be coherently integrated, often in the face of disparate environmental and genetic pressures. A central part of the evolutionary analysis of biological systems remains to decipher the causal connections between organism-wide (or genome-wide) attributes (e.g., mRNA abundance, protein length, codon bias, recombination rate, genomic position, mutation rate, etc) as well as their role-together with mutation, selection, and genetic drift-in shaping patterns of evolutionary variation in any of the attributes themselves. Here we combine genome-wide evolutionary analysis of protein and gene expression data to highlight fundamental relationships among genomic attributes and their associations with the evolution of both protein sequences and gene expression levels. Our results show that protein divergence is positively coupled with both gene expression polymorphism and divergence. We show moreover that although the number of protein-protein interactions in Drosophila is negatively associated with protein divergence as well as gene expression polymorphism and divergence, protein-protein interactions cannot account for the observed coupling between regulatory and structural evolution. Furthermore, we show that proteins with higher rates of amino acid substitutions tend to have larger sizes and tend to be expressed at lower mRNA abundances, whereas genes with higher levels of gene expression divergence and polymorphism tend to have shorter sizes and tend to be expressed at higher mRNA abundances. Finally, we show that protein length is negatively associated with both number of protein-protein interactions and mRNA abundance and that interacting proteins in Drosophila show similar amounts of divergence. We suggest that protein sequences and gene expression are subjected to similar evolutionary dynamics, possibly because of similarity in the fitness effect (i.e., strength of stabilizing selection) of disruptions in a gene's protein sequence or its mRNA expression. We conclude that, as more and better data accumulate, understanding the causal connections among biological traits and how they are integrated over time to constrain or promote structural and regulatory evolution may finally become possible.

Animals↗

PubMed2005

A Bayesian method for analysing spotted microarray data.

In the decade since their invention, spotted microarrays have been undergoing technical advances that have increased the utility, scope and precision of their ability to measure gene expression. At the same time, more researchers are taking advantage of the fundamentally quantitative nature of these tools with refined experimental designs and sophisticated statistical analyses. These new approaches utilise the power of microarrays to estimate differences in gene expression levels, rather than just categorising genes as up- or down-regulated, and allow the comparison of expression data across multiple samples. In this review, some of the technical aspects of spotted microarrays that can affect statistical inference are highlighted, and a discussion is provided of how several methods for estimating gene expression level across multiple samples deal with these challenges. The focus is on a Bayesian analysis method, BAGEL, which is easy to implement and produces easily interpreted results.

Algorithms↗

PubMed2005

Rates of divergence in gene expression profiles of primates, mice, and flies: stabilizing selection and variability among functional categories.

The extent to which natural selection shapes phenotypic variation has long been a matter of debate among those studying organic evolution. We studied the patterns of gene expression polymorphism and divergence in several datasets that ranged from comparisons between two very closely related laboratory strains of mice to comparisons across a considerably longer time scale, such as between humans and chimpanzees, two species of mice, and two species of Drosophila. The results were analyzed and interpreted in view of neutral models of phenotypic evolution. Our analyses used a number of metrics to show that most mRNA levels are evolutionary stable, changing little across the range of taxonomic distances compared. This implies that, overall, widespread stabilizing selection on transcription levels has prevented greater evolutionary changes in mRNA levels. Nevertheless, the range of rates of divergence is large with highly significant differences in the rate and patterns of transcription divergence across functional classes defined on the basis of the gene ontology annotation (primates and mice datasets) or on the basis of the pattern of sex-biased gene expression (Drosophila). Moreover, rates of divergence of sex-biased genes in the contrast between Drosophila species show a distinct pattern from that observed in the contrast between populations of D. melanogaster. Hence, we discuss the time scale of the changes observed and its consequences for the relationship between variation in gene expression within and between species. Finally, we argue that differences in mRNA levels of the magnitudes observed herein could be explained by a remarkably small number of generations of directional selection.

Animals↗

PubMed2004

Regulatory evolution across the protein interaction network.

Protein-protein interactions may impose constraints on both structural and regulatory evolution. Here we show that protein-protein interactions are negatively associated with evolutionary variation in gene expression. Moreover, interacting proteins have similar levels of variation in expression, and their expression levels are positively correlated across strains. Our results suggest that interacting proteins undergo similar evolutionary dynamics, and that their expression levels are evolutionarily coupled. These patterns hold for organisms as diverse as budding yeast and fruit flies.

Animals↗

PubMed2004

Identification of a locus under complex positive selection in Drosophila simulans by haplotype mapping and composite-likelihood estimation.

The recent action of positive selection is expected to influence patterns of intraspecific DNA sequence variation in chromosomal regions linked to the selected locus. These effects include decreased polymorphism, increased linkage disequilibrium, and an increased frequency of derived variants. These effects are all expected to dissipate with distance from the selected locus due to recombination. Therefore, in regions of high recombination, it should be possible to localize a target of selection to a relatively small interval. Previously described patterns of intraspecific variation in three tandemly arranged, testes-expressed genes (janusA, janusB, and ocnus) in Drosophila simulans included all three of these features. Here we expand the original sample and also survey nucleotide polymorphism at three neighboring loci. On the basis of recombination events between derived and ancestral alleles, we localize the target of selection to a 1.5-kb region surrounding janusB. A composite-likelihood-ratio test based on the spatial distribution and frequency of derived polymorphic variants corroborates this result and provides an estimate of the strength of selection. However, the data are difficult to reconcile with the simplest model of positive selection, whereas a new composite-likelihood method suggests that the data are better described by a model in which the selected allele has not yet gone to fixation.

Animals↗

PubMed2003

Rapid evolution of male-biased gene expression in Drosophila.

A number of genes associated with sexual traits and reproduction evolve at the sequence level faster than the majority of genes coding for non-sex-related traits. Whole genome analyses allow this observation to be extended beyond the limited set of genes that have been studied thus far. We use cDNA microarrays to demonstrate that this pattern holds in Drosophila for the phenotype of gene expression as well, but in one sex only. Genes that are male-biased in their expression show more variation in relative expression levels between conspecific populations and two closely related species than do female-biased genes or genes with sexually monomorphic expression patterns. Additionally, elevated ratios of interspecific expression divergence to intraspecific expression variation among male-biased genes suggest that differences in rates of evolution may be due in part to natural selection. This finding has implications for our understanding of the importance of sexual dimorphism for speciation and rates of phenotypic evolution.

Animals↗

PubMed2003

Sex-dependent gene expression and evolution of the Drosophila transcriptome.

Comparison of the gene-expression profiles between adults of Drosophila melanogaster and Drosophila simulans has uncovered the evolution of genes that exhibit sex-dependent regulation. Approximately half the genes showed differences in expression between the species, and among these, approximately 83% involved a gain, loss, increase, decrease, or reversal of sex-biased expression. Most of the interspecific differences in messenger RNA abundance affect male-biased genes. Genes that differ in expression between the species showed functional clustering only if they were sex-biased. Our results suggest that sex-dependent selection may drive changes in expression of many of the most rapidly evolving genes in the Drosophila transcriptome.

Animals↗