Search for: All records

Abstract Arabidopsis thaliana (hereafter Arabidopsis) is a small plant with a fast generation time and a well-annotated genome, which makes it ideal for research labs. It is arguably the most used model species in basic plant sciences. Over the past half century, studies in Arabidopsis have generated enormous insight into fundamental principles of plant life, ranging from mechanistic molecular biology to the complexities of interacting ecosystems. Based on research in Arabidopsis, we now understand that while basic cellular metabolism is generally conserved across species, variation in specialized metabolite enzymes gives rise to complex bouquets of chemical weapons that are tightly interwoven with the environment. Understanding how these are produced, regulated, and—especially—how they are deployed remains a key research area for plant immunity. The breadth of work in Arabidopsis provides a unique window into this complicated aspect of life as a plant. We are happy to have an opportunity to share our common interest in these aspects in this review. Due to space constraints, we focus on compounds produced by Arabidopsis with demonstrated antimicrobial properties. We hope that this focus (despite our eagerness to write more) will inspire new avenues of research that will contribute to a more complete understanding of immunity. 

Abstract Data reduction methods are frequently employed in large genomics and phenomics studies to extract core patterns, reduce dimensionality, and alleviate multiple testing effects. Principal component analysis (PCA), in particular, identifies the components that capture the most variance within omics datasets. While data reduction can simplify complex datasets, it remains unclear how the use of PCA impacts downstream analyses such as quantitative trait loci (QTL) or genome-wide association (GWA) approaches and their biological interpretation. In QTL studies, an alternative to data reduction is the use of post-hoc data summarization approaches, such as hotspot analysis, which involves mapping individual traits and consolidating results based on shared genomic locations. To evaluate how different analytical approaches may alter the biological insights derived from multi-dimensional QTL datasets, we compared individual trait hotspots with PCA-based QTL mapping using transcriptomic and metabolomic data from a structured recombinant inbred line population. Interestingly, these two approaches identified different genomic regions and genetic architectures. These findings suggest that mapping PCA-reduced data does not merely streamline analyses but may generate a fundamentally different view of the underlying genetic architecture compared to individual trait mapping and hotspot analysis. Thus, the use of PCA and other data reduction techniques prior to QTL or GWAS mapping should be carefully considered to ensure alignment with the specific biological question being addressed. 

Abstract Three cross-incompatibility loci each control a distinct reproductive barrier in both domesticated maize (Zea mays ssp. mays) and its wild teosinte relatives. These 3 loci, Teosinte crossing barrier1 (Tcb1), Gametophytic factor1 (Ga1), and Ga2, each play a key role in preventing hybridization between incompatible populations and are proposed to maintain the barrier between domesticated and wild subspecies. Each locus encodes both a silk-active and a matching pollen-active pectin methylesterase (PMEs). To investigate the diversity and molecular evolution of these gametophytic factor loci, we identified existing and improved models of the responsible genes in a new genome assembly of maize line P8860 that contains active versions of all 3 loci. We then examined 52 assembled genomes from 17 species to classify haplotype diversity and identify sites under diversifying selection during the evolution of these genes. We show that Ga2, the oldest of these 3 loci, was duplicated to form Ga1 at least 12 million years ago. Tcb1, the youngest locus, arose as a duplicate of Ga1 before or around the time of diversification of the Zea genus. We find evidence of positive selection during evolution of the functional genes at an active site in the pollen-expressed PME and predicted surface sites in both the silk- and pollen-expressed PMEs. The most common allele at the Ga1 locus is a conserved ga1 allele (ga1-Off), which is specific haplotype containing 3 full-length PME gene copies, all of which are noncoding due to conserved stop codons and are between 610 thousand and 1.5 million years old. We show that the ga1-Off allele is associated with and likely generates 24-nt siRNAs in developing pollen-producing tissue, and these siRNAs map to functional Ga1 alleles. In previously published crosses, the ga1-Off allele was associated with reduced function of the typically dominant functional alleles for the Ga1 and Tcb1 barriers. Taken together, this seems to be an example of an allele at a reproductive barrier locus being associated with an as yet undetermined mechanism capable of silencing the reproductive barrier. 

ABSTRACT Necrotrophic pathogens cause serious threats to agricultural crops, and understanding the resistance genes and their genetic networks is key to breeding new plant cultivars with better resistance traits. AlthoughAlternaria alternatacauses black spot in important leafy brassica vegetables, and leads to significant loss of yield and food quality, little is known about plant–A. alternatainteractions. In this study, we used a unique and large collection of single, double and triple mutant lines of defence metabolite regulators inArabidopsisto explore how these transcription factors and their epistatic networks may influenceA. alternatainfections. This identified nine novel regulators and 20 pairs of epistatic interactions that modulateArabidopsisplants' defence responses toA. alternatainfection. We further showed that the glucosinolate 4‐methoxy‐indol‐3‐ylmethyl is the only glucosinolate consistently responsive toA. alternatainfection in Col‐0 ecotype. With the further exploration of the regulators and the genetic networks on modulating the accumulation of glucosinolates underA. alternatainfection, an inverted triangle regulatory model was proposed forArabidopsisplants' defence responses at a metabolic level and a phenotypic level. 

Abstract Botrytis cinereaPers. Fr. (teleomorph:Botryotinia fuckeliana) is a necrotrophic fungal pathogen that attacks a wide range of plants. This updated pathogen profile explores the extensive genetic diversity ofB. cinerea, highlights the progress in genome sequencing, and provides current knowledge of genetic and molecular mechanisms employed by the fungus to attack its hosts. In addition, we also discuss recent innovative strategies to combatB. cinerea. TaxonomyKingdom: Fungi, phylum: Ascomycota, subphylum: Pezizomycotina, class: Leotiomycetes, order: Helotiales, family: Sclerotiniaceae, genus:Botrytis, species:cinerea. Host rangeB. cinereainfects almost all of the plant groups (angiosperms, gymnosperms, pteridophytes, and bryophytes). To date, 1606 plant species have been identified as hosts ofB. cinerea. Genetic diversityThis polyphagous necrotroph has extensive genetic diversity at all population levels shaped by climate, geography, and plant host variation. PathogenicityGenetic architecture of virulence and host specificity is polygenic using multiple weapons to target hosts, including secretory proteins, complex signal transduction pathways, metabolites, and mobile small RNA. Disease control strategiesEfforts to controlB. cinerea, being a high‐diversity generalist pathogen, are complicated. However, integrated disease management strategies that combine cultural practices, chemical and biological controls, and the use of appropriate crop varieties will lessen yield losses. Recently, studies conducted worldwide have explored the potential of small RNA as an efficient and environmentally friendly approach for combating grey mould. However, additional research is necessary, especially on risk assessment and regulatory frameworks, to fully harness the potential of this technology. 

SUMMARY Eudicot plant species have leaves with two surfaces: the lower abaxial and the upper adaxial surface. Each surface varies in a diversity of components and molecular signals, resulting in potentially different degrees of resistance to pathogens. We tested howBotrytis cinerea, a necrotroph fungal pathogen, interacts with the two different leaf surfaces across 16 crop species and 20 Arabidopsis genotypes. This showed that the abaxial surface is generally more susceptible to the pathogen than the adaxial surface. In Arabidopsis, the differential lesion area between leaf surfaces was associated with jasmonic acid (JA) and salicylic acid (SA) signaling and differential induction of defense chemistry across the two surfaces. When infecting the adaxial surface, leaves mounted stronger defenses by producing more glucosinolates and camalexin defense compounds, partially explaining the differential susceptibility across surfaces. Testing a collection of 96B. cinereastrains showed the genetic heterogeneity of growth patterns, with a few strains preferring the adaxial surface while most are more virulent on the abaxial surface. Overall, we show that leaf–Botrytis interactions are complex with host‐specific, surface‐specific, and strain‐specific patterns. 

Abstract Recent technical and theoretical advances have generated an explosion in the identification of specialized metabolite pathways. In comparison, our understanding of how these pathways are regulated is relatively lagging. This and the relatively young age of specialized metabolite pathways has partly contributed to a default and common paradigm whereby specialized metabolite regulation is theorized as relatively simple with a few key transcription factors and the compounds are non-regulatory end-products. In contrast, studies into model specialized metabolites, such as glucosinolates, are beginning to identify a new understanding whereby specialized metabolites are highly integrated into the plants’ core metabolic, physiological, and developmental pathways. This model includes a greatly extended compendium of transcription factors controlling the pathway, key transcription factors that co-evolve with the pathway and simultaneously control core metabolic and developmental components, and finally the compounds themselves evolve regulatory connections to integrate into the plants signaling machinery. In this review, these concepts are illustrated using studies in the glucosinolate pathway within the Brassicales. This suggests that the broader community needs to reconsider how they do or do not integrate specialized metabolism into the regulatory network of their study species. 

This article is a Commentary onYounkinet al. (2024),242: 2719–2733. 

Plant specialized metabolites shape plant interactions with the environment including plant–microbe interactions. While we often group compounds into generic classes, it is the precise structure of a compound that creates a specific role in plant–microbe or–pathogen interactions. Critically, the structure guides definitive targets in individual interactions, yet single compounds are not limited to singular mechanistic targets allowing them to influence interactions across broad ranges of attackers, from bacteria to fungi to animals. Further, the direction of the effect can be altered by counter evolution within the interacting organism leading to single compounds being both beneficial and detrimental. Thus, the benefit of a single compound to a host needs to be assessed by measuring the net benefit across all interactions while in each specific interaction. Factoring this complexity for single compounds in plant–microbe interactions with the massive expansion in our identification of specialized metabolite pathways means that we need systematic studies to classify the full breadth of activities. Only with this full biological knowledge we can develop mechanistic, ecological, and evolutionary models to understand how plant specialized metabolites fully influence plant–microbe and plant–biotic interactions more broadly. 

Abstract Bidirectional flow of information shapes the outcome of the host–pathogen interactions and depends on the genetics of each organism. Recent work has begun to use co-transcriptomic studies to shed light on this bidirectional flow, but it is unclear how plastic the co-transcriptome is in response to genetic variation in both the host and pathogen. To study co-transcriptome plasticity, we conducted transcriptomics using natural genetic variation in the pathogen, Botrytis cinerea, and large-effect genetic variation abolishing defense signaling pathways within the host, Arabidopsis thaliana. We show that genetic variation in the pathogen has a greater influence on the co-transcriptome than mutations that abolish defense signaling pathways in the host. Genome-wide association mapping using the pathogens’ genetic variation and both organisms’ transcriptomes allowed an assessment of how the pathogen modulates plasticity in response to the host. This showed that the differences in both organism's responses were linked to trans-expression quantitative trait loci (eQTL) hotspots within the pathogen's genome. These hotspots control gene sets in either the host or pathogen and show differential allele sensitivity to the host’s genetic variation rather than qualitative host specificity. Interestingly, nearly all the trans-eQTL hotspots were unique to the host or pathogen transcriptomes. In this system of differential plasticity, the pathogen mediates the shift in the co-transcriptome more than the host.