The effect of recombination in Aeromonas

Although several approaches have been attempted, the estimation of recombination frequencies in natural populations ofbacteria remains challenging. Previous studies have demonstrated awide variety of situations among bacterial species, ranging from theclonal diversification of Salmonella or Escherichia coli, which aremainly due to mutation, to the frequent recombination found inNeisseria gonorrhoeae or Helicobacter pylori. Most of the populationstudies done with bacterial species suggest that recombination occursin nature but that it is infrequent compared to mutation. Consequently,bacterial populations consist largely of independent clonal lineages.Our research suggests little or null influence of recombination in thegenetic structure of "Aeromonas hydrophila Species Complex", despite the presence of some strains with recombinant gene fragments.

The effect of recombination in Aeromonas

Although several approaches have been attempted, the estimation of recombination frequencies in natural populations ofbacteria remains challenging. Previous studies have demonstrated awide variety of situations among bacterial species, ranging from theclonal diversification of Salmonella or Escherichia coli, which aremainly due to mutation, to the frequent recombination found inNeisseria gonorrhoeae or Helicobacter pylori. Most of the populationstudies done with bacterial species suggest that recombination occursin nature but that it is infrequent compared to mutation. Consequently,bacterial populations consist largely of independent clonal lineages.Our research suggests little or null influence of recombination in thegenetic structure of "Aeromonas hydrophila Species Complex", despite the presence of some strains with recombinant gene fragments.

Gene flow and gene flux shape evolutionary patterns of variation in Drosophila subobscura

Gene flow (defined as allele exchange between populations) and gene flux (defined as allele exchange during meiosis in heterokaryotypic females) are important factors decreasing genetic differentiation between populations and inversions. Many chromosomal inversions are under strong selection and their role in recombination reduction enhances the maintenance of their genetic distinctness. Here we analyze levels and patterns of nucleotide diversity, selection and demographic history, using 37 individuals of Drosophila subobscura from Mount Parnes (Greece) and Barcelona (Spain). Our sampling focused on two frequent O-chromosome arrangements that differ by two overlapping inversions (OST and O3+4), which are differentially adapted to the environment as observed by their opposing latitudinal clines in inversion frequencies. The six analyzed genes (Pif1A, Abi, Sqd, Yrt, Atpa and Fmr1) were selected for their location across the O-chromosome and their implication in thermal adaptation. Despite the extensive gene flux detected outside the inverted region, significant genetic differentiation between both arrangements was found inside it. However, high levels of gene flow were detected for all six genes when comparing the same arrangement among populations. These results suggest that the adaptive value of inversions is maintained, regardless of the lack of genetic differentiation within arrangements from different populations, and thus favors the Local Adaptation hypothesis over the Coadapted Genome hypothesis as the basis of the selection acting on inversions in these populations.

Multilocus sequence analysis reveals the genetic diversity of European fruit tree phytoplasmas and supports the existence of inter-species recombination

The genetic diversity of three temperate fruit tree phytoplasmas ‘Candidatus Phytoplasma prunorum’, ‘Ca. P. mali’ and ‘Ca. P. pyri’ has been established by multilocus sequence analysis. Among the four genetic loci used, the genes imp and aceF distinguished 30 and 24 genotypes, respectively, and showed the highest variability. Percentage of substitution for imp ranged from 50 to 68% according to species. Percentage of substitution varied between 9 and 12% for aceF, whereas it was between 5 and 6% for pnp and secY. In the case of ‘Ca P. prunorum’ the three most prevalent aceF genotypes were detected in both plants and insect vectors, confirming that the prevalent isolates are propagated by insects. The four isolates known to be hypo-virulent had the same aceF sequence, indicating a possible monophyletic origin. Haplotype network reconstructed by eBURST revealed that among the 34 haplotypes of ‘Ca. P. prunorum’, the four hypo-virulent isolates also grouped together in the same clade. Genotyping of some Spanish and Azerbaijanese ‘Ca. P. pyri’ isolates showed that they shared some alleles with ‘Ca. P. prunorum’, supporting for the first time to our knowledge, the existence of inter-species recombination between these two species.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, andmany others, offer tremendous promise for the personalized treatment of cancer. Thesetechnologies measure the amount of specific proteins, RNA, DNA or other moleculartargets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumorspecimens are heterogeneous; an individual specimen typically contains unknownamounts of multiple tissues types. Thus, the measured molecular concentrations resultfrom an unknown mixture of tissue types, and must be normalized to account for thecomposition of the mixture.For example, a breast tumor biopsy may contain normal, dysplastic and cancerousepithelial cells, as well as stromal components (fatty and connective tissue) and bloodand lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic andcancerous epithelial cells. The remaining tissue components serve to “contaminate”the signal of interest. The proportion of each of the tissue components changes asa function of patient characteristics (e.g., age), and varies spatially across the tumorregion. Because each of the tissue components produces a different molecular signature,and the amount of each tissue type is specimen dependent, we must estimate the tissuecomposition of the specimen, and adjust the molecular signal for this composition.Using the idea of a chemical mass balance, we consider the total measured concentrationsto be a weighted sum of the individual tissue signatures, where weightsare determined by the relative amounts of the different tissue types. We develop acompositional source apportionment model to estimate the relative amounts of tissuecomponents in a tumor specimen. We then use these estimates to infer the tissuespecificconcentrations of key molecular targets for sub-typing individual tumors. Weanticipate these specific measurements will greatly improve our ability to discriminatebetween different classes of tumors, and allow more precise matching of each patient tothe appropriate treatment