Genome-scale rates of evolutionary change in bacteria.
Genome-scale rates of evolutionary change in bacteria.
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DOI：
10.1099/mgen.0.000094
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发表时间：
2016-11
影响因子：
3.9
通讯作者：
Holmes EC
中科院分区：
文献类型：
--
作者：
Duchêne S;Holt KE;Weill FX;Le Hello S;Hawkey J;Edwards DJ;Fourment M;Holmes EC
估计细菌基因组进化的速率对于理解主要的进化和生态过程至关重要，例如疾病的出现，长期宿主-病原体关联和短期传播模式。细菌基因组数据集的激增为估计这些速率并揭示塑造细菌进化动力学的因素提供了新的机会。对于许多生物体来说，进化速率的估计值与数据采样的时间尺度成反比。然而，由于难以估计全基因组进化速率，这种关系在细菌中仍未探索，这受到数据中时间结构的程度和重组的流行程度的影响。我们收集了来自16种细菌病原体的36个全基因组序列数据集，以系统地估计和比较它们的进化速率，并评估在没有重组的情况下时间结构的程度。大多数（28/36）的数据集具有足够的类时钟结构，以稳健地估计进化速率。然而，在一些物种中，即使使用几个世纪以来采样的“古代DNA”数据也无法进行可靠的估计，这表明它们进化得非常缓慢，或者它们在谱系之间显示出广泛的速率变化。稳健估计的进化速率跨越了几个数量级，从大约10−5到10−8个核苷酸替换/地点年-1。这种变化与采样时间呈负相关，这种关系最好用指数衰减曲线来描述。为了避免潜在的估计偏差，这种时间依赖性时，应考虑推断细菌的进化时间尺度。
Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host–pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with ‘ancient DNA’ data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria.