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

Abstract

To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem to test how the host's defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA-and SA-signaling mutants, coi1-1 and npr1-1, individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene coexpression networks and two vectors of defense variation triggered by genetic variation in B. cinerea. This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen.

Melatonin enhances cotton immunity to Verticillium wilt via manipulating lignin and gossypol biosynthesis

“…It is worth noting that plant small‐molecule hormones, including jasmonic acid (JA) and salicylic acid (SA), play key roles in the plant response to V. dahliae infection (Glazebrook, ; Campos et al ., ; Zhang et al ., , ). However, we did not observe any significant differences in JA and SA levels (Figure S11) or changes in the expression of genes involved in these hormone signaling pathways between melatonin‐pre‐treated and control samples during V. dahliae infection (Figure S12).…”

Pathogen genetic control of transcriptome variation in the Arabidopsis thaliana – Botrytis cinerea pathosystem

“…In previous work, we had defined key transcript modules within both the host and pathogen transcriptomes that could be linked to virulence. Thus we proceeded to test if any of these trans-eQTL hotspots were associated with the previously defined transcript modules, by comparing gene lists for overlap between module membership and hotspot association (Zhang, Corwin et al 2017, Zhang, Corwin et al 2018 (Table 1). Nine of the 11 B. cinerea eQTL hotspots were enriched for transcripts present in one or more of four major B. cinerea co-expression networks on A. thaliana ( Figure 6).…”

“…To date in plants, co-transcriptome work where both the host's and pathogen's transcripts have been measured has been shown to work in the A. thaliana -B. cinerea system through single sample RNA-Seq (Zhang, Corwin et al 2017, Zhang, Corwin et al 2018. The genetic interactions between the extreme generalist pathogen, B. cinerea, and the model plant host, A. thaliana, are dominated by complex smalleffect loci that display a high degree of interaction between the host and pathogen (Denby, Kumar et al 2004, Rowe and Kliebenstein 2008, Zhang, Corwin et al 2017. Using this co-transcriptome approach to understand this system showed that it was possible to map key virulence networks in the pathogen and resistance responses within the host (Zhang, Corwin et al 2017, Zhang, Corwin et al 2018.…”

“…The genetic interactions between the extreme generalist pathogen, B. cinerea, and the model plant host, A. thaliana, are dominated by complex smalleffect loci that display a high degree of interaction between the host and pathogen (Denby, Kumar et al 2004, Rowe and Kliebenstein 2008, Zhang, Corwin et al 2017. Using this co-transcriptome approach to understand this system showed that it was possible to map key virulence networks in the pathogen and resistance responses within the host (Zhang, Corwin et al 2017, Zhang, Corwin et al 2018. Further, by mapping these transcriptomes together, it was possible coalesce the pathogen and host transcript modules into a single network encompassing both species (Zhang, Corwin et al 2018).…”

“…The genomes of both the host and the pathogen harbor extensive genetic diversity that has been successfully used for GWA to identify loci controlling virulence , Soltis, Atwell et al 2019. Further, the virulence outcome of the interaction is easily measured via high-throughput digital imaging allowing for a large body of molecular information to underpin any hypothesis generation from GWA (Denby, Kumar et al 2004, Rowe and Kliebenstein 2008, Zhang, Corwin et al 2017, Soltis, Atwell et al 2019). These SNPs have an explicit directionality to them, as genetic causality must arise within the pathogen and then extend to the host.…”