RefPlantNLR: a comprehensive collection of experimentally validated plant NLRs

The Backstory

The nucleotide-binding leucine-rich repeat (NLR) is a large family of intracellular receptors involved in pathogen recognition, functioning as gatekeepers of plant immunity. The activation of NLRs by pathogen effectors, directly or indirectly, induces plant immune responses referred to as effector-triggered immunity (ETI) that prevents the proliferation of the pathogen. Though some “singleton” NLRs achieve pathogen sensing as well as immune signaling, many NLRs are either dedicated sensors or helpers in downstream signalling, functioning through gene clusters and networks.

With an impact on disease resistance, NLRs are a factor in crop breeding and believed to be involved in a co-evolution arms race with pathogen effectors through rapid variation in sequence and copy number, across species. Classically, plant NLRs are known to have a tripartite domain architecture with an N-terminal domain, a central NB-ARC domain (involved in nucleotide binding and oligomerization – NOD) and a C-terminal LRR domain. However, recent studies have uncovered plant NLRs with many different domains. For instance, the rice protein Pb1 has a NOD domain different from the canonical NB-ARC, but maintains overall NLR structure. The variable N terminal domain forms the basis of the classification of NLRs into four sub-clades, CC-NLR, TIR-NLR, CC_R-NLR and the recent addition, the CC_G10 NLR clade.

The study puts together an extensive reference dataset of experimentally validated 415 NLRs across 31 plant genera and 4 NLR clades by manually screening literature for genes associated with disease resistance or susceptibility, effector-triggeredimmune responses or their regulation and downstream signaling, necrosis and allelic series of NLRs, followed by annotation to ensure the presence of a NB-ARC domain along with additional domains. It is the first dataset of the OpenPlantNLR community. The study also provides a more compact set of 235 proteins after factoring in redundancies.

  

Key Findings

The dataset incorporates information about a wide range of aspects such as amino acid and coding sequences, plant source, pathogen, effectors, associated helper components and domain structure, uncovering 407 unique NLRs and 347 distinct NB-ARC domains. NLRs like RPP7 with identical sequences highlight the importance of context dependent regulation in different plant backgrounds.

The study describes the plant-wise distribution of validated NLRs drawing our attention to a skew towards the well-studied plants, with a substantial proportion of plant diversity not accounted for and clearly no members from non-flowering plants(Fig1A). The plant laboratory workhorse Arabidopsis, economically important cereals, rice, wheat and barley, and Solanaceae account for three-fourths of the NLRs in this set, a fraction that does not change much even in the 235 protein dataset. The fact that Arabidopsisis the only taxon with members from all NLR clades and the cereals show a bias towards CC-NLRs,highlights the current gaps, but also potential areas for the way forward in NLR biology.

 

The over-representation is also seen with respect to NLR clades. CC-NLR and TIR NLR are the most common domain combinations making up almost 80% of the validated NLRs. The remaining 20% forms a unique and interesting set, covering novel and non-canonical domain combinations, duplications and arrangements, at both the N and/or C-terminal domains (Fig 1B). For all those interested, the preprint has many interesting examples and details.The diversity is also seen in NLR protein lengths which vary between clades. NB-ARC domains show a tighter distribution barring a few extremely short and long one that stretched the boundaries of NLR domain diversity.

Domain gains are a recurrent feature of NLR evolution making prediction of plant NLR stricky. Though there are several NLR extractors that identify canonical NLR characteristics, this comprehensive dataset of functionally validated proteins with all its diversity could prove an important benchmarking resource for future NLR annotation tools.

 

Why I like it

The study provides a phylogenetic framework of experimentally validated NLRs, encouraging us to appreciate the structural diversity and directs the field towards the potential of under-studied plant groups and NLR clades. The authors are crowdsourcing for suggestions to improve the study with more comprehensive analysis which will be incorporated in the subsequent version to be submitted to the journal.

Tags: annotation, dataset, disease, plant, resistance, resource

doi: https://doi.org/10.1242/prelights.23291

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