2014
DOI: 10.1016/j.pbi.2013.12.003
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Genomic variability as a driver of plant–pathogen coevolution?

Abstract: Pathogens apply one of the strongest selective pressures in plant populations. Understanding plant–pathogen coevolution has therefore been a major research focus for at least sixty years [1]. Recent comparative genomic studies have revealed that the genes involved in plant defense and pathogen virulence are among the most polymorphic in the respective genomes. Which fraction of this diversity influences the host–pathogen interaction? Do coevolutionary dynamics maintain variation? Here we review recent literatu… Show more

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Cited by 126 publications
(106 citation statements)
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“…Hence, these fungi are ideal models to study the impact of recombination on pathogen evolution. Loci contributing to virulence in pathogens undergo rapid allele frequency changes in response to changes in host populations (Barrett et al 2009;Thrall et al 2012), and fungal pathogenicity is often found to be encoded by a large number of virulence loci distributed throughout the genome (Karasov et al 2014). Recombination enables the emergence of pathogen strains that carry novel combinations of virulence alleles that may increase virulence in specific hosts.…”
mentioning
confidence: 99%
“…Hence, these fungi are ideal models to study the impact of recombination on pathogen evolution. Loci contributing to virulence in pathogens undergo rapid allele frequency changes in response to changes in host populations (Barrett et al 2009;Thrall et al 2012), and fungal pathogenicity is often found to be encoded by a large number of virulence loci distributed throughout the genome (Karasov et al 2014). Recombination enables the emergence of pathogen strains that carry novel combinations of virulence alleles that may increase virulence in specific hosts.…”
mentioning
confidence: 99%
“…Selective sweeps, usually associated with purifying selection, occur when environments select for the same traits/genotypes among populations inhabiting different ecological niches, thereby reducing genetic differentiation in related traits/genotypes among geographic populations (Zhan et al. 2004; Karasov et al., 2014). The hypothesis of a selective sweep occurring in the effector gene was supported by a comparative population genetic analysis of Avr3a and SSR marker loci which showed that genetic differentiation in Avr3a (assessed through the G ST statistic) was significantly lower than genetic differentiation in the SSR marker loci (assessed through the F ST statistic, Zhan et al., 2005).…”
Section: Discussionmentioning
confidence: 99%
“…Examples of complex R loci in crop plants include the resistance genes Rp1 in maize (Smith et al, 2004), Cf-4/9 in tomato (Parniske et al, 1997), M in flax (Anderson et al, 1997), Dm3 in lettuce (Shen et al, 2002) and R1 in potato (Ballvora et al, 2002). Typically, the recognized effectors as well as the recognizing NLRs show increased levels of polymorphisms and are likely under balancing selection to maintain allelic diversity within natural populations (Bergelson et al, 2001;Karasov et al, 2014). These complexities have limited the ability to determine the sequences of complex NLR loci in the past, especially using short-read sequencing data (Cao et al, 2011).…”
Section: Widespread Complexity At An Arabidopsis Tir-nlr Locusmentioning
confidence: 99%
“…By contrast, many NLRs conferring resistance to naturally occurring pathogens recognize single 'cognate' effectors, leading to co-evolutionary arms races on ligandand receptor-binding surfaces (Dodds et al, 2006;Krasileva et al, 2010;Kanzaki et al, 2012;Cesari et al, 2013). Pressure to evade and re-establish immunity is evident from allelic sequence divergence with the signature of positive selection (Bergelson et al, 2001;Karasov et al, 2014). New recognition capability can also result from the complexity of NLR genetic loci, where gene rearrangements, duplications and transposon insertions can result in dozens of NLR receptor variants (McDowell et al, 1998;Baumgarten et al, 2003;Meyers et al, 2003;Leister, 2004).…”
Section: Introductionmentioning
confidence: 99%