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.

Population genetic structure and demography analysis in palinurus elephas populations from atlantic and mediterranean waters

Report for the scientific sojourn at the University of Reading, United Kingdom, from January until May 2008. The main objectives have been firstly to infer population structure and parameters in demographic models using a total of 13 microsatellite loci for genotyping approximately 30 individuals per population in 10 Palinurus elephas populations both from Mediterranean and Atlantic waters. Secondly, developing statistical methods to identify discrepant loci, possibly under selection and implement those methods using the R software environment. It is important to consider that the calculation of the probability distribution of the demographic and mutational parameters for a full genetic data set is numerically difficult for complex demographic history (Stephens 2003). The Approximate Bayesian Computation (ABC), based on summary statistics to infer posterior distributions of variable parameters without explicit likelihood calculations, can surmount this difficulty. This would allow to gather information on different demographic prior values (i.e. effective population sizes, migration rate, microsatellite mutation rate, mutational processes) and assay the sensitivity of inferences to demographic priors by assuming different priors.