Evolutionary changes can be the result of different forces, while adaptive changes can only be explained by the action of natural selection. The comparative analysis of nucleotide sequences in different gene regions is a powerful tool to infer the locus-specific action of natural selection through the footprint that it leaves on linked variation. We are using both a gene-specific and a genome-wide approach to detect adaptive changes. In the gene-specific approach (or candidate gene approach), our work focuses in genes whose function might have been shaped by adaptive evolution. In Drosophila, we are studying genes that encode proteins involved in the olfactory response to chemical stimuli, while in Arabidopsis we are studying genes that encode enzymes of the phenylpropanoid pathway. The availability of the D. melanogaster genome sequence allows a genomics approach to detect the action of natural selection by studying variation in random genomic regions of this species (or of closely related species). We use D. simulans because, as compared to D. melanogaster, it has a higher effective population size and it lacks chromosomal polymorphism.
The large volume of available DNA sequences requires new and powerful computational tools for their analysis. Indeed, the comparative analysis of genes and genomes can provide useful information on their origin and on the mechanisms involved in their evolution. With this goal we are developing bioinformatic tools for the analysis of DNA sequence variation in genes and genomes. We are currently developing algorithms and software for: 1) the analysis of SNPs (Single Nucleotide Polymorphisms); 2) the extensive analysis of nucleotide variation at small DNA coding and noncoding regions (level and pattern of variation, linkage disequilibria, recombination, codon bias, etc.); 3) the analysis of the pattern of variation in whole genomes or chromosomes; 4) displaying the pattern of polymorphism (linkage disequilibria, nucleotide diversity, etc.) along large DNA regions of the genome. We are also developing statistical tests based on the coalescence theory for inferring the action of different demographic processes on DNA sequence variation.
Selected Publications