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Population Genetics, Molecular Evolution and Genome Evolution
We apply a multidisciplinary approach-combining empirical work, large-scale genomic analyses, and the development of computational and theoretical tools-to investigate 1) weak selection, 2) the evolution of gene (intron-exon) structures in eukaryotes, 3) the evolution of recombination and mutation rates across genomes and among species, 4) the evolutionary consequences of changes in population size between closely related species, 5) the role of Darwinian selection in gene expression divergence and 6) the genetic basis of speciation between closely related Drosophila species.
Likely, many mutations important to evolution have much smaller selection coefficients than it is practicable to demonstrate in the laboratory. Population genetics and molecular evolution analyses-the study of nucleotide variability within and between species, respectively-are powerful tools that allow us to detect the action of selection on naturally-occurring mutations, even if the fitness effects of these mutations are extremely weak.
We study the evolution of factors that influence the efficacy of selection in eukaryotes, focusing on two major factors: recombination and population size. To measure possible changes in the effectiveness of selection, we study weakly selected mutations such as synonymous mutations (changes in the coding sequence that do not alter protein sequence) and small insertion/deletions (indels). We investigate causes and consequences of changes in populations size and recombination rates between closely related species.
We also apply molecular evolution and population genetics techniques to study recent Drosophila speciation events and gain insight into the relative influence of selection in phenotypic differentiation and reproductive isolation.
The same population genetics techniques that are commonly applied to nucleotide changes and indels can be also applied to genomic and gene features, allowing us to investigate the forces involved in the evolution of exon-intron structures, gene duplication, genome organization and genome size. This genomics-meets-population genetics approach (i.e. population genomics) can be implemented with computer simulations mimicking the evolutionary process (in silico evolution), a computationally-intensive technique that provides new and valuable insights into the expected outcome of complex evolutionary processes. |
