Inference of Bacterial Microevolution Using Multilocus Sequence Data
We describe a model-based method for using multilocus sequence data to infer the clonal relationships of bacteria and the chromosomal position of homologous recombination events that disrupt a clonal pattern of inheritance. The key assumption of our model is that recombination events introduce a constant rate of substitutions to a contiguous region of sequence. The method is applicable both to multilocus sequence typing (MLST) data from a few loci and to alignments of multiple bacterial genomes. It can be used to decide whether a subset of isolates share common ancestry, to estimate the age of the common ancestor, and hence to address a variety of epidemiological and ecological questions that hinge on the pattern of bacterial spread. It should also be useful in associating particular genetic events with the changes in phenotype that they cause. We show that the model outperforms existing methods of subdividing recombinogenic bacteria using MLST data and provide examples from Salmonella and Bacillus. The software used in this article, ClonalFrame, is available from http://bacteria.stats.ox.ac.uk/.
2. http://www.genetics.org/content/186/4/1435.full
Inference of Homologous Recombination in Bacteria Using Whole-Genome Sequences
Bacteria and archaea reproduce clonally, but sporadically import DNA into their chromosomes from other organisms. In many of these events, the imported DNA replaces an homologous segment in the recipient genome. Here we present a new method to reconstruct the history of recombination events that affected a given sample of bacterial genomes. We introduce a mathematical model that represents both the donor and the recipient of each DNA import as an ancestor of the genomes in the sample. The model represents a simplification of the previously described coalescent with gene conversion. We implement a Monte Carlo Markov chain algorithm to perform inference under this model from sequence data alignments and show that inference is feasible for whole-genome alignments through parallelization. Using simulated data, we demonstrate accurate and reliable identification of individual recombination events and global recombination rate parameters. We applied our approach to an alignment of 13 whole genomes from the Bacillus cereus group. We find, as expected from laboratory experiments, that the recombination rate is higher between closely related organisms and also that the genome contains several broad regions of elevated levels of recombination. Application of the method to the genomic data sets that are becoming available should reveal the evolutionary history and private lives of populations of bacteria and archaea. The methods described in this article have been implemented in a computer software package, ClonalOrigin, which is freely available fromhttp://code.google.com/p/clonalorigin/.
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