Biek Roman, Pybus Oliver G, Lloyd-Smith James O, Didelot Xavier
Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UK; Fogarty International Center, National Institutes of Health, Bethesda MD, USA.
Department of Zoology, University of Oxford, Oxford, UK.
Trends Ecol Evol. 2015 Jun;30(6):306-13. doi: 10.1016/j.tree.2015.03.009. Epub 2015 Apr 14.
Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of 'measurably evolving populations' and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. We argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale, and we highlight important analytical challenges to be overcome to infer pathogen population dynamics from genomic data.
当前的测序技术为研究微生物群体创造了前所未有的机会。对于位点突变率相对较低的病原体,如DNA病毒和细菌,全基因组测序可以揭示在不同时间采集的群体样本之间新的遗传变异的积累。“可测量进化群体”的概念及相关分析方法为快速进化的RNA病毒提供了有力的见解,但它们在其他病原体中的应用仍处于起步阶段。我们认为,一旦在全基因组范围内评估进化,以前关于进化缓慢和快速的病原体之间的区别就会变得模糊,并且我们强调了从基因组数据推断病原体群体动态时需要克服的重要分析挑战。