The use of genomic and gene expression large-scale data for the analyses of sexual evolution
Maria D. Vibranovski (USP)

Although more than a decade has passed since the first eukaryotic genome was sequenced, the molecular basis of genome organization and complexity remains a largely unresolved problem. The relationship of genotype to phenotype has proven particularly challenging. I use gametogenesis in Drosophila as a model system to study the evolution and phenotypic expression of genomic features. Gametogenesis is a fascinating biological process; it varies temporally throughout development, and has profound evolutionary impact in that it provides the raw material for the next generation - the gamete. To date, gametogenesis research has primarily focused on single gene studies of fertility. In contrast, I apply a genomic perspective to the overall process of gametogenesis to understand the role sexual selection plays in genome evolution. In my research on genome evolution in Drosophila melanogaster, I have combined bioinformatics and statistics with experimental genomic and molecular genetic methods to obtain large-scale gene expression data on gametogenesis, or spermatogenic- stage-specific transcriptome (SpermPress). The results help to solve two classical problems that have puzzled biologists for decades: evidence for Meiotic Sex Chromosome inactivation and for Post-meiotic transcription. In this talk, I present the results obtained through the application of advanced Bayesian statistics to Gene Chip microarray data. I also introduce another puzzle yet to be solved in the evolutionary biology field related to the role of sperm haploid selection in the evolution of new genes.% The discussion of alternative analyses and models on spermatogenic transcriptome and gene age is pressing and represents part of my current research agenda.