Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia.
Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia.
PLoS Genet. 2023 Mar 27;19(3):e1010683. doi: 10.1371/journal.pgen.1010683. eCollection 2023 Mar.
Prokaryotic evolution is influenced by the exchange of genetic information between species through a process referred to as recombination. The rate of recombination is a useful measure for the adaptive capacity of a prokaryotic population. We introduce Rhometa (https://github.com/sid-krish/Rhometa), a new software package to determine recombination rates from shotgun sequencing reads of metagenomes. It extends the composite likelihood approach for population recombination rate estimation and enables the analysis of modern short-read datasets. We evaluated Rhometa over a broad range of sequencing depths and complexities, using simulated and real experimental short-read data aligned to external reference genomes. Rhometa offers a comprehensive solution for determining population recombination rates from contemporary metagenomic read datasets. Rhometa extends the capabilities of conventional sequence-based composite likelihood population recombination rate estimators to include modern aligned metagenomic read datasets with diverse sequencing depths, thereby enabling the effective application of these techniques and their high accuracy rates to the field of metagenomics. Using simulated datasets, we show that our method performs well, with its accuracy improving with increasing numbers of genomes. Rhometa was validated on a real S. pneumoniae transformation experiment, where we show that it obtains plausible estimates of the rate of recombination. Finally, the program was also run on ocean surface water metagenomic datasets, through which we demonstrate that the program works on uncultured metagenomic datasets.
原核生物的进化受到通过称为重组的过程在物种之间交换遗传信息的影响。重组率是衡量原核生物种群适应能力的有用指标。我们引入了 Rhometa（https://github.com/sid-krish/Rhometa），这是一个新的软件包，用于从宏基因组的鸟枪法测序读数中确定重组率。它扩展了用于群体重组率估计的组合似然方法，并能够分析现代短读数据集。我们使用模拟和真实实验的短读数据对齐到外部参考基因组，在广泛的测序深度和复杂性范围内评估了 Rhometa。Rhometa 为从当代宏基因组读数据集确定群体重组率提供了全面的解决方案。Rhometa 将基于序列的常规组合似然群体重组率估计器的功能扩展到包括具有不同测序深度的现代对齐宏基因组读数据集，从而能够有效地将这些技术及其高准确率应用于宏基因组学领域。使用模拟数据集，我们表明我们的方法表现良好，其准确性随着基因组数量的增加而提高。Rhometa 在真实的肺炎球菌转化实验中得到了验证，我们表明它获得了合理的重组率估计值。最后，该程序还在海洋表面水宏基因组数据集上运行，通过该程序证明了它可以在未培养的宏基因组数据集中运行。
