The Pangenome of the Plant-Selected Rhizobium leguminosarum bv viciae Sub-popuations

Rhizobium leguminosarum bv viciae (Rlv) is a bacterium able to establish effective symbioses with four different legume genera: Pisum, Lens, Lathyrus and Vicia. Classic studies using trap plants have previously shown that, given a choice, different plants prefer specific genotypes of rhizobia, which are adapted to the host (1, 2). In previous work we have performed a Pool-Seq analysis bases on pooled DNA samples from Rlv nodule isolates obtained from Pisum sativum, Lens culinaris, Vicia fava and V. sativa plants, used as rhizobial traps. This experiment allowed us to test the host preference hypothesis: different plant hosts select specific sub-populations of rhizobia from the available population present in a given soil. We have observed that plant-selected sub-populations are different at the single nucleotide polymorphism (SNP) level. We have selected individual isolates from each sub-population (9 fava-bean isolates, 14 pea isolates 9 vetch isolates and 9 lentil isolates) and sequenced their genomes at draft level (ca. 30x, 90 contigs). Genomic analyses have been carried out using J-species and CMG-Biotools. All the isolates had similar genome size (7.5 Mb) and number of genes (7,300). The resulting Average Nucleotide Identity (ANIm) tree showed that Rhizobium leguminosarum bv viciae is a highly diverse group. Each plant-selected subpopulation showed a closed pangenome and core genomes of similar size (11,500 and 4,800 genes, respectively). The addition of all four sub-population results in a larger, closed pangenome of 19,040 genes and a core genome of similar size (4,392 genes). Each sub-population contains a characteristic set of genes but no universal, plant-specific genes were found. The core genome obtained from all four sub-populations is probably a representative core genome for Rhizobium leguminosarum, given that the reference genome (Rhizobium leguminosarum bv. viciae strain 3841) contains most of the core genome. We have also analyzed the symbiotic cluster (nod), and different nod cluster genotypes were found in each sub-population. Supported by MINECO (Consolider-Ingenio 2010, MICROGEN Project, CSD2009-00006).

Modeling, simulation and application of bacterial transduction in genetic algorithms

At present, all methods in Evolutionary Computation are bioinspired by the fundamental principles of neo-Darwinism, as well as by a vertical gene transfer. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganisms (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring the possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). Our results showed how PETRI approaches higher fitness values as transduction probability comes close to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ?bacterial colonies?.