4.6 Article

RefPlantNLR is a comprehensive collection of experimentally validated plant disease resistance proteins from the NLR family

Journal

PLOS BIOLOGY
Volume 19, Issue 10, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pbio.3001124

Keywords

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Funding

  1. Gatsby Charitable Foundation
  2. Biotechnology and Biological Sciences Research Council (BBSRC) [BB/P012574]
  3. European Research Council [743165]
  4. Japan Society for the Promotion of Plant Science Postdoctoral fellowship
  5. BASF Plant Science
  6. European Research Council (ERC) [743165] Funding Source: European Research Council (ERC)

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Reference datasets are essential in computational biology, with the RefPlantNLR dataset providing a comprehensive resource for experimentally validated plant NLR immune receptors. The dataset is useful for determining canonical features of NLRs, benchmarking annotation tools, and guiding comparative analyses across plant diversity.
Reference datasets are critical in computational biology. They help define canonical biological features and are essential for benchmarking studies. Here, we describe a comprehensive reference dataset of experimentally validated plant nucleotide-binding leucine-rich repeat (NLR) immune receptors. RefPlantNLR consists of 481 NLRs from 31 genera belonging to 11 orders of flowering plants. This reference dataset has several applications. We used RefPlantNLR to determine the canonical features of functionally validated plant NLRs and to benchmark 5 NLR annotation tools. This revealed that although NLR annotation tools tend to retrieve the majority of NLRs, they frequently produce domain architectures that are inconsistent with the RefPlantNLR annotation. Guided by this analysis, we developed a new pipeline, NLRtracker, which extracts and annotates NLRs from protein or transcript files based on the core features found in the RefPlantNLR dataset. The RefPlantNLR dataset should also prove useful for guiding comparative analyses of NLRs across the wide spectrum of plant diversity and identifying understudied taxa. We hope that the RefPlantNLR resource will contribute to moving the field beyond a uniform view of NLR structure and function.

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