Evolutionary Coherence among Orthologs of the Order Rhizobiales.

The order Rhizobiales of the a -proteobacteria is one of the taxa with more complete genomes available. It allows designing comparative and evolutionary studies at high level taxonomic categories. Moreover, the order Rhizobiales groups species with very distinct and contrasting life-styles. There are pathogens of animals and plants, autotrophic species and symbionts of plants. The differences in life-styles probably owe to adaptations and require particular sets of genes, and could explain the variability in genome structure among these species. Nonetheless, if the order Rhizobiales is a natural clade, it must conserve a common core of genes across all the species. Therefore, the core of rhizobial orthologs would produce coherent phylogenies that might reveal the speciation process. The next questions will be addressed in this project:

  • What is the set of orthologs common to the species of the order Rhizobiales
  • Do they are coherent with the species divergence?
  • If question 2 is negative, what is the fraction of incongruent orthologs? Why do they are incongruent?
  • Do the orthologs have conserved the same function?
  • Does it possible to identify the genes responsible for specific adaptations?

We will take R. etli CFN42 as reference specie for this study, and all the orthologs detected in the order Rhizobiales for phylogenetic reconstruction. At first, we will determine the evolutionary histories for the entire set of orthologs. By different test of congruency and distance, it will be tested the coherence among all topologies of the trees generated. Since we started with a working definition of orthology (the best bi-directional hits criterion), our approach aims to contrast it with the species divergence. It is expected to find a diversity of evolutive histories according to the selective regimes and life-style of the specie.


M. C. Santiago Castillo, design, performs experiments and data analysis.
Dr. Víctor González, experimental design and data analysis.

Evolutionary Genomics Program