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Inferring bacterial recombination rates from large-scale sequencing datasets.

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PubMed ID: 30664775

Imagen Publicación

Lin M, Kussell E

Nat Methods. Jan 2019. doi: 10.1038/s41592-018-0293-7

COMMENT

Objectives

present a robust, computationally efficient method ( https://github.com/kussell-lab/mcorr ) for inferring the parameters of homologous recombination in bacteria

Main results

we determine recombination rates and diversity levels of the shared gene pool that has contributed to a given sample. We validated the recombination parameters using data from laboratory experiments. We determined the recombination parameters for a wide range of bacterial species, and inferred the distribution of shared gene pools for global Helicobacter pylori isolates. Using metagenomics data of the infant gut microbiome, we measured the recombination parameters of multidrug-resistant Escherichia coli ST131

Conclusions

Correlation profile analysis infers the basic parameters of bacterial recombination using any type of available sequence data, from whole genomes to metagenomes, which opens a range of new possibilities for ecological, evolutionary, and population genetic inference. In applications to ancient DNA samples, this tool reveals evolutionary processes in bacterial populations of past eras.

Contributor

Marina Manrique