期刊
BIOINFORMATICS
卷 31, 期 10, 页码 1665-1667出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv005
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资金
- 2Blades Foundation
- Biotechnology and Biological Sciences Research Council [BB/J003166/1, BB/L011794/1]
- Biotechnology and Biological Sciences Research Council [BB/J003166/1, BB/H019820/1, BB/L009293/1, BB/M003809/1, BB/L011794/1] Funding Source: researchfish
- BBSRC [BB/L011794/1, BB/J003166/1, BB/M003809/1, BB/H019820/1, BB/L009293/1] Funding Source: UKRI
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.
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