Population Genetic Analyses of Botrytis cinerea Isolates From Michigan Vineyards Using a High-Throughput Marker System Approach

Abstract

As sequencing costs continue to decrease, new tools are being developed for assessing pathogen diversity and population structure. Traditional marker types, such as microsatellites, are often more cost effective than single-nucleotide polymorphism (SNP) panels when working with small numbers of individuals, but may not allow for fine scale evaluation of low or moderate structure in populations. Botrytis cinerea is a necrotrophic plant pathogen with high genetic variability that can infect more than 200 plant species worldwide. A panel of 52 amplicons were sequenced for 82 isolates collected from four Michigan vineyards representing 2 years of collection and varying fungicide resistance. A panel of nine microsatellite markers previously described was also tested across 74 isolates from the same population. A microsatellite and SNP marker analysis of B. cinerea populations was performed to assess the genetic diversity and population structure of Michigan vineyards, and the results from both marker types were compared. Both methods were able to detect population structure associated with resistance to the individual fungicides thiabendazole and boscalid, and multiple fungicide resistance (MFR). Microsatellites were also able to differentiate population structure associated with another fungicide, fluopyram, while SNPs were able to additionally differentiate structure based on year. For both methods, AMOVA results were similar, with microsatellite results explaining a smaller portion of the variation compared with the SNP results. The SNP-based markers presented here were able to successfully differentiate population structure similar to microsatellite results. These SNP markers represent new tools to discriminate B. cinerea isolates within closely related populations using multiple targeted sequences.

Phenotype and genotype characterization of Botrytis cinerea isolates from cut roses in Yunnan, China

“…Compared to previous approaches, research on population analysis using WGS data (Atwell et al, 2015(Atwell et al, , 2018Mercier et al, 2021) remains relatively limited. Population structure and evolution are thought to be closely related to the collection site (Campia et al, 2017;Wessels et al, 2013), host (Walker et al, 2015), fungicide sensitivity (Naegele et al, 2021) and the presence or absence of TEs (Delong et al, 2020). In our study, 100 isolates of B. cinerea were collected from 64 different rose varieties, with 52 isolates obtained from individual varieties (Table S1).…”

Genetic and molecular landscapes of the generalist phytopathogen Botrytis cinerea

“…In recent years, researchers have extensively investigated B. cinerea genes through gene deletion or knockout studies, revealing significant impacts on pathogenicity (Bi et al, 2023;Cheung et al, 2020;Veloso & van Kan, 2018). There are diverse transformation protocols to generate defined B. cinerea mutants, ranging from homologous recombination F I G U R E 3 Meta-analysis of publicly available data of eight microsatellites in Botrytis cinerea from six countries (China, Cyprus, France, Greece, Hungary, United States) compiled from seven publications (Diao et al, 2019;Fournier et al, 2013;Hu et al, 2018;Makris et al, 2022;Naegele et al, 2021;Vaczy et al, 2008;Walker, 2013). to CRISPR/Cas editing (Frandsen et al, 2008;Hahn & Scalliet, 2021;Schumacher, 2012).…”

“…These large collections of studies provide the ability to conduct a meta‐analysis of the factors influencing B. cinerea's extensive genetic diversity. To summarize findings of these studies, we performed a meta‐analysis by compiling the publicly available data for >10,000 strains across 58 publications (Abdel Wahab, 2015; Acosta Morel et al., 2018; Albertini & Leroux, 2004; Albertini et al., 2002; Aliaga, 2013; Amiri et al., 2018; Asadollahi et al., 2013; Beever & Parkes, 1993; Ben Ahmed & Hamada, 2005; Campia, 2014; Cettul et al., 2008; Ciliberti et al., 2016; DeLong et al., 2020; Diao et al., 2019; Emilda, 2015; Esterio et al., 2011; Fan et al., 2015; Fekete et al., 2012; Fournier et al., 2005, 2013; Giraud et al., 1997; Giraud et al., 1999; Hu et al., 2018; Isenegger et al., 2008; Johnston et al., 2013; Kecskeméti et al., 2014; Kumari et al., 2014; Kuzmanovska et al., 2012; Leyronas et al., 2014; Lorenzini & Zapparoli, 2014; Ma & Michailides, 2005; Makris et al., 2022; Martinez et al., 2003; Mercier et al., 2019; Moparthi et al., 2023; Muñoz & Campos, 2013; Muñoz et al., 2002, 2016; Naegele et al., 2021; Pei et al., 2019; Polat et al., 2018; Rajaguru & Shaw, 2010; Román Ramos, 2013; Tanović et al., 2009, 2014; Testempasis et al., 2020; Toffolatti et al., 2020; Topolovec‐Pintarić et al., 2004; Törün & Biyik, 2022; Vaczy et al., 2008; Vatsa‐Portugal et al., 2014; Vercesi et al., 2014…”

“… Meta‐analysis of publicly available data of eight microsatellites in Botrytis cinerea from six countries (China, Cyprus, France, Greece, Hungary, United States) compiled from seven publications (Diao et al., 2019 ; Fournier et al., 2013 ; Hu et al., 2018 ; Makris et al., 2022 ; Naegele et al., 2021 ; Vaczy et al., 2008 ; Walker, 2013 ). (a) Principal component analysis of a subset of five microsatellites (BC1, BC3, BC6, BC7, BC10) for 845 strains.…”

An Effect and Less Spraying Control Method Successfully Controls Botrytis cinerea on Grapes in China

“…To determine the stages when fungicide application is required, the epidemiological development of the pathogen must be considered. This is driven by many factors, such as the genetic structure of the B. cinerea population [8], weather conditions [9,10], plant architecture [11,12] and grape susceptibility [13]. The susceptible level of grape growth stages to B. cinerea affects early infection and later disease expression.…”