bioRxivPlant BiologyPreprint
Physical and transcriptional organisation of the bread wheat intracellular immune receptor repertoire
Burkhard SteuernageliD, Kamil WitekiD, Simon G. KrattingeriD, Ricardo H. Ramirez-Gonzalez, Henk-jan Schoonbeek, Guotai YuiD, Erin Baggs, Agnieszka I. WitekiD, Inderjit Yadav, Ksenia V. KrasilevaiD, Jonathan D. G. JonesiD, Cristobal Uauy, Beat KelleriD, Christopher J. Ridout, The International Wheat Genome Sequencing Consortium, Brande B. H. WulffiD
Abstract
Disease resistance genes encoding intracellular immune receptors of the nucleotide-binding and leucine-rich repeat (NLR) class of proteins detect pathogens by the presence of pathogen effectors. Plant genomes typically contain hundreds of NLR encoding genes. The availability of the hexaploid wheat cultivar Chinese Spring reference genome now allows a detailed study of its NLR complement. However, low NLR expression as well as high intra-family sequence homology hinders their accurate gene annotation. Here we developed NLR-Annotator for in silico NLR identification independent of transcript support. Although developed for wheat, we demonstrate the universal applicability of NLR-Annotator across diverse plant taxa. Applying our tool to wheat and combining it with a transcript-validated subset of genes from the reference gene annotation, we characterized the structure, phylogeny and expression profile of the NLR gene family. We detected 3,400 full-length NLR loci of which 1,540 were confirmed as complete genes. NLRs with integrated domains mostly group in specific sub-clades. Members of another subclade predominantly locate in close physical proximity to NLRs carrying integrated domains suggesting a paired helper-function. Most NLRs (88%) display low basal expression (in the lower 10 percentile of transcripts), which may be tissue-specific and/or induced by biotic stress. As a case study for applying our tool to the positional cloning of resistance genes, we estimated the number of NLR genes within the intervals of mapped rust resistance genes. Our study will support the identification of functional resistance genes in wheat to accelerate the breeding and engineering of disease resistant varieties.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
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