Measurably evolving pathogens in the genomic era

被引:183
作者
Biek, Roman [1 ,2 ]
Pybus, Oliver G. [3 ]
Lloyd-Smith, James O. [2 ,4 ]
Didelot, Xavier [5 ]
机构
[1] Univ Glasgow, Boyd Orr Ctr Populat & Ecosyst Hlth, Inst Biodivers Anim Hlth & Comparat Med, Coll Med Vet & Life Sci, Glasgow, Lanark, Scotland
[2] NIH, Fogarty Int Ctr, Bethesda, MD 20892 USA
[3] Univ Oxford, Dept Zool, Oxford, England
[4] Univ Calif Los Angeles, Dept Ecol & Evolutionary Biol, Los Angeles, CA 90095 USA
[5] Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, London, England
基金
美国国家卫生研究院; 欧洲研究理事会; 英国生物技术与生命科学研究理事会; 美国国家科学基金会;
关键词
bacteria; DNA virus; epidemiological models; evolutionary rate; infectious disease; phylodynamics; MYCOBACTERIUM-TUBERCULOSIS; POPULATION GENOMICS; TRANSMISSION TREES; EVOLUTIONARY RATES; ESCHERICHIA-COLI; MOLECULAR CLOCKS; GLOBAL SPREAD; RECOMBINATION; INFERENCE; DYNAMICS;
D O I
10.1016/j.tree.2015.03.009
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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.
引用
收藏
页码:306 / 313
页数:8
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