NLR-parser: Rapid annotation of plant NLR complements

Burkhard Steuernagel, Florian Jupe, Kamil Witek, Jonathan D.G. Jones, Brande B.H. Wulff

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Motivation: The repetitive nature of plant disease resistance genes encoding for nucleotide-binding leucine-rich repeat (NLR) proteins hampers their prediction with standard gene annotation software. Motif alignment and search tool (MAST) has previously been reported as a tool to support annotation of NLR-encoding genes. However, the decision if a motif combination represents an NLR protein was entirely manual. Results: The NLR-parser pipeline is designed to use the MAST output from six-frame translated amino acid sequences and filters for predefined biologically curated motif compositions. Input reads can be derived from, for example, raw long-read sequencing data or contigs and scaffolds coming from plant genome projects. The output is a tab-separated file with information on start and frame of the first NLR specific motif, whether the identified sequence is a TNL or CNL, potentially full or fragmented. In addition, the output of the NB-ARC domain sequence can directly be used for phylogenetic analyses. In comparison to other prediction software, the highly complex NB-ARC domain is described in detail using several individual motifs.
Original languageEnglish (US)
Pages (from-to)1665-1667
Number of pages3
JournalBioinformatics
Volume31
Issue number10
DOIs
StatePublished - May 15 2015
Externally publishedYes

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Generated from Scopus record by KAUST IRTS on 2023-02-20

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