Informational, ecological and system approaches for complete genome analysis

In the study of the genetic modifications leading populations to adapt to their environment, it is important to distinguish changes resulting in an increase in biological fiteness from those slightly deleterious. Besides that the concept of neutral changes is defined since the ? Origin of species? by Charles Darwin, its relevance to the overall changes defining evolutionary process was considered to be very low, if existent. But, in the late sixties, with the advances of molecular experiments and the first comparative studies in this field, neutral changes were proven to be almost sufficient to explain the amount of changes per generation observed at molecular level. Based on this observation, the first neutral models of molecular evolution were implemented and are, up today, the best statistical alternative to test for any effect of natural selection on biological sequences. In ecology the implementation of neutral models able to explain accurately the distribution and abundances of species in their ecosystems arrived later, and became popular only recently. In both fields molecular evolution and ecology, neutral models are powerful predictors based on a simple process and are great null models against to test more complicated hypotheses considering the effect of natural selection. This thesis analyzes three different biological approximations on complete genomes. Each of which states an explicit neutral model and its respective deviations. The statement of this common denominator along the three principal chapters of this thesis gives explanatory value to the results exposed. Without it, the conclusions are irrelevant. These approximations are: Informational content: This is the most simple analysis that can be done taking genomes as a container of biological information. Under this perspective, the set of nucleotides A, C, G and T are considered the fundamental and independent units of the genomes. Our first objective will be to measure the content of information of the genomes, this along a broad array of species representative of almost all the diversity of life. Ecological: the study of diversity and abundance of families of genetic elements (mostly transposable elements) in eukaryotic genomes has been already studied in a population genetic context, however, these works were hardly able to consider more than a few genetic families in a single genome. Here, taking advantage from statistical tools implemented by ecologists, we will define the neutral components explaining the distribution and abundances of all great families of genetic elements in a large and complete set of eukaryotic genomes. We will see how all eukaryotic chromosomes fit to neutral models. Systemic: this is the last approximation under which we analyzed the genomes. This level of analysis involves group of genes with similar functional characteristics, concretely we will focus in proteins acting together to accomplish a biochemical pathway or a biological function. Close to this level of analysis, several studies tried to discriminate functional enrichments among group of genes under positive selection. However, at genomic level, this kind of analysis was unable to bring significant results. Here, our objective consisted in implementing a new methodology able to distinguish the effect of natural selection directly on different functional categories. In the last chapter of this thesis we will briefly overview different tools derived from our research and that we believe, are of great interest for scientific community. These tools will be described in three sections: 1) Ecolopy where we will present a package able to fit genomic data in different neutral ecological model, 2) ETE-Evol, a plugin for a well known and efficient program for manipulating phylogenetic trees, containing a set of utilities and wrappers to broadly used softwares for the measure of the effect of natural selection on protein-coding genes, and 3) Phylemon2.0, a web server proposing a broad array of tools framed into the phylogenetic, phylogenomics and evolutionary hypothesis testing fields.