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Phytopathology
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License: implied-oa
Data sources: UnpayWall
Phytopathology
Article . 1997 . Peer-reviewed
Data sources: Crossref
Phytopathology
Article . 2012
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The Population Genetics of Fungi: Tools and Techniques

Authors: B A, McDonald;

The Population Genetics of Fungi: Tools and Techniques

Abstract

Over the last 10 years plant pathologists have begun to realize that more knowledge about the genetic structure of populations of plant pathogens is needed to implement effective control strategies (48). Research on the genetic structure of fungal populations has mushroomed, and review papers that summarize these studies are numerous (7,27,33,34,38). Although the number of fungal studies has increased greatly, the most comprehensive work has focused on a small number of plant-pathogenic fungi. The majority of these fungi can be recognized easily by their fruiting bodies or disease symptoms on aboveground plant parts. It has proven more difficult to assess the genetic structure of fungal populations that exist mainly belowground, because the distribution of individuals cannot be visualized directly and appropriate sampling procedures are less obvious and more cumbersome. Nevertheless, substantial progress has been made in interpreting the population genetic structure of some soilborne fungi (1,17). The purpose of this paper is to provide an overview of the tools and techniques of fungal population genetics. I will try to emphasize approaches that may be applied to studies of soilborne fungi. Instead of providing detailed methods, I will cite recent references where appropriate. There are many opinions regarding which techniques and tools are best suited to studies of fungal populations. I will give a personal and biased viewpoint, which I believe will be most useful to those who are just entering the field.

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    292
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
292
Top 1%
Top 1%
Top 10%
hybrid