The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics

Abstract

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Plastic Transcriptomes Stabilize Immunity to Pathogen Diversity: The Jasmonic Acid and Salicylic Acid Networks within the Arabidopsis/Botrytis Pathosystem

“…By contrast, the Arabidopsis response to the 96 diverse B. cinerea isolates is quantitative and showed no evidence of bimodality or multimodality (Table 1, Figures 2 and 3A). This suggests that this collection of B. cinerea genotypes does not contain large-effect qualitative virulence loci; instead, this generalist uses a highly polygenic virulence architecture (Denby et al, 2004;Finkers et al, 2007b;Rowe and Kliebenstein, 2008;Corwin et al, 2016b;Zhang et al, 2016). This agrees with previous B. cinerea mechanistic studies that identify a large collection of standing genetic variation that controls a wide range of specific virulence mechanisms (Choquer et al, 2007;Rowe and Kliebenstein, 2007;Noda et al, 2010;Rowe et al, 2010;Dalmais et al, 2011;Michielse et al, 2011;Shlezinger et al, 2011;Windram et al, 2012;Pearson and Bailey, 2013;Kumari et al, 2014;An et al, 2015;Atwell et al, 2015;Hevia et al, 2015;Plaza et al, 2015;Schumacher et al, 2015;Zhang et al, 2015a;Corwin et al, 2016aCorwin et al, , 2016bLopezCruz et al, 2017;Zhang et al, 2016).…”

“…Previous studies using one or a few B. cinerea isolates to focus on genetic difference in the Arabidopsis host have shown a negative correlation between camalexin content and lesion area across host genotypes (Ferrari et al, 2003;Denby et al, 2004;Corwin et al, 2016aCorwin et al, , 2016b. This larger population of B. cinerea isolates allows us to test how genetic diversity in the pathogen influences the effectiveness of plant molecular defenses, specifically camalexin.…”

“…B. cinerea has elevated natural genetic variation that results in multiple major-effect polymorphisms in known virulence mechanisms, including the production of phytotoxic metabolites (Colmenares et al, 2002;Dalmais et al, 2011), enzymes that detoxify plant defense metabolites (Ferrari et al, 2003;Pedras et al, 2005Pedras et al, , 2007Pedras et al, , 2008Pedras et al, , 2009Pedras et al, , 2011Stefanato et al, 2009;Rowe et al, 2010), and the ability to degrade plant cell walls (Rowe and Kliebenstein, 2007;Schumacher et al, 2012Schumacher et al, , 2015Kumari et al, 2014). Because wild B. cinerea isolates have recombination and random mating, a population of isolates is a random intermixed sample of the diverse virulence mechanisms (Rowe and Kliebenstein, 2007;Kretschmer et al, 2009;Rowe et al, 2010;Kumari et al, 2014;Atwell et al, 2015;Corwin et al, 2016aCorwin et al, , 2016bZhang et al, 2016). This allows us to use a population of isolates to challenge a plant's innate immune system with a diverse array of natural inputs from a single pathogen species and assess the flexibility of the signaling network (Finkers et al, 2007a(Finkers et al, , 2007bRowe and Kliebenstein, 2008;Davis et al, 2009;Corwin et al, 2016b;Zhang et al, 2016).…”

“…Because wild B. cinerea isolates have recombination and random mating, a population of isolates is a random intermixed sample of the diverse virulence mechanisms (Rowe and Kliebenstein, 2007;Kretschmer et al, 2009;Rowe et al, 2010;Kumari et al, 2014;Atwell et al, 2015;Corwin et al, 2016aCorwin et al, , 2016bZhang et al, 2016). This allows us to use a population of isolates to challenge a plant's innate immune system with a diverse array of natural inputs from a single pathogen species and assess the flexibility of the signaling network (Finkers et al, 2007a(Finkers et al, , 2007bRowe and Kliebenstein, 2008;Davis et al, 2009;Corwin et al, 2016b;Zhang et al, 2016).…”

Unraveling the molecules hidden in the gray shadows of quantitative disease resistance to pathogens

“…Thus new molecules, which previously have not been described as important during plant-microbe interactions, could be responsible for resistance (Roux et al, 2014b). Nevertheless, it seems that R genes actually have roles in QDR, but with a weak contribution, as compared to other genes with different structures and functions (Corwin et al, 2016).…”