Bacteria, unlike us, can reproduce on their own. They do however have mechanisms that transfer DNA between organisms, a process more formally known as recombination. The mechanisms by which recombination takes place have been studied extensively in the laboratory but much remains to be understood concerning how, when and where recombination takes place within natural populations of bacteria and how it helps them to adapt to new environments. ClonalOrigin performs a comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.
ClonalOrigin is described in the following paper:
Didelot X, Lawson D, Darling A, Falush D (2010) Inference of homologous recombination in bacteria using whole genome sequences. Genetics 186 (4), 1435-1449 doi:10.1534/genetics.110.120121 http://www.genetics.org/cgi/content/abstract/genetics.110.120121v1
Instructions for how to download and install ClonalOrigin are available at: https://github.com/xavierdidelot/ClonalOrigin/wiki/Install
Instructions for how to use ClonalOrigin once installed are available at: https://github.com/xavierdidelot/ClonalOrigin/wiki/Usage
Estimating strength of bias in the recombination process
We define biased recombination in contrast to free recombination where all individuals in the population are equally likely to recombine. There are many factors contributing to recombination being biased rather than free. Laboratory experiments have shown that the recombination process is homology dependent whereby it tends to happen more often between individuals that are less diverged. Furthermore, the geographical and ecological structures observed in many bacterial populations implies a greater opportunity of recombination for pairs of cells that are closely related. Purifying selection may also effectively prevent recombination between distantly related bacteria. All these effects would clearly be hard to disentangle, and here we group them all under the single concept of biased recombination. The strength of this bias is an important factor to take into account in order to understand recombination in bacteria. In particular, this determines how often recombination happens within the diversity of the population under study rather than from other sources.
We have introduced a model for biased recombination which is based on the ClonalOrigin model. We use approximate Bayesian computation and whole genome data to infer the rate of bias in the recombination process in bacteria. The user guide and Matlab code can be downloaded from: http://www.stats.ox.ac.uk/~ansari/BiasedRecV1.tgz
Full details of the biased recombination model have been published in the following paper: Ansari MA, Didelot X. Inference of the Properties of the Recombination Process from Whole Bacterial Genomes. Genetics. 2014;196: 253–265. doi:10.1534/genetics.113.157172 http://www.genetics.org/content/early/2013/10/21/genetics.113.157172