NLR-parser: rapid annotation of plant NLR complements

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. Availability and implementation: The NLR-parser tool can be downloaded from Git-Hub (github.com/steuernb/NLR-Parser). It requires a valid Java installation as well as MAST as part of the MEME Suite. The tool is run from the command line. Contact: burkhard.steuernagel@jic.ac.uk; fjupe@salk.edu Supplementary information: Supplementary data are available at Bioinformatics online.