期刊
PHYTOPATHOLOGY
卷 107, 期 9, 页码 1000-1010出版社
AMER PHYTOPATHOLOGICAL SOC
DOI: 10.1094/PHYTO-12-16-0425-RVW
关键词
-
资金
- U.S. Department of Agriculture (USDA) Agricultural Research Service Grant [5358-22000-039-00D]
- USDA National Institute of Food and Agriculture Grant [2011-6800430154]
- USDA-ARS Floriculture Nursery Initiative
- Oregon Department of Agriculture/Oregon Association of Nurseries (ODA-OAN) research programs
- USDA NIFA [2012-67012-19844]
- NIFA [578421, 2012-67012-19844] Funding Source: Federal RePORTER
Population genetic analysis is a powerful tool to understand how pathogens emerge and adapt. However, determining the genetic structure of populations requires complex knowledge on a range of subtle skills that are often not explicitly stated in book chapters or review articles on population genetics. What is a good sampling strategy? How many isolates should I sample? How do I include positive and negative controls in my molecular assays? What marker system should I use? This review will attempt to address many of these practical questions that are often not readily answered from reading books or reviews on the topic, but emerge from discussions with colleagues and from practical experience. A further complication for microbial or pathogen populations is the frequent observation of clonality or partial clonality. Clonality invariably makes analyses of population data difficult because many assumptions underlying the theory from which analysis methods were derived are often violated. This review provides practical guidance on how to navigate through the complex web of data analyses of pathogens that may violate typical population genetics assumptions. We also provide resources and examples for analysis in the R programming environment.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据