bioRxivPlant BiologyPreprint
A novel allele of Mitogen Activated Protein Kinase 6 is linked to disease resistance and constitutive immunity in rice.
C. G. GokulaniD, Mohammed Jamaloddin, Deepti RaoiD, Namami GauriD, Amita Rani Supriyo, Nisha Sao, Deepak Niranjan, Shrish TiwariiD, G. S. LahaiD, Kalyani Makarand BarbadikariD, Raman Meenakshi SundaramiD, Maganti Sheshu MadhaviD, Hitendra Kumar PateliD, Ramesh Venkata SontiiD
Abstract
Bacterial Blight (BB) is the most serious bacterial disease of rice. Usage of resistant cultivars has been a successful strategy in controlling BB. However, constant selection pressure causes the evolution of hypervirulent pathogenic strains that break down resistance, thus necessitating additional sources of resistance. An induced-mutant line derived from the elite rice cultivar Samba Mahsuri was identified to exhibit broad-spectrum resistance to BB. Using next-generation gene mapping approaches, we identified a genomic interval in chromosome 6 to be linked to BB resistance. Analysis of the SNPs in the locus and subsequent linkage analysis indicated that a missense SNP located in the second exon of the Mitogen-Activated Protein Kinase 6 (OsMAPK6) could be the causal mutation. A detailed examination of OsMAPK6 gene sequences in over 4000 rice genomes revealed that the mutant allele identified in this study is novel to rice germplasm. The candidate SNP causes the substitution of an invariant Serine residue with a Proline residue (S84P), thus likely affecting the protein function. Global transcriptome, metabolome, biochemical, and molecular analyses suggested that BB42 exhibit constitutive immunity. On the mechanistic front, the mutation seems to result in diminished brassinosteroid signaling in BB42. Taken together, we report a novel allele of a highly conserved MAPK gene and provide evidence for its possible association with constitutive immunity and disease resistance in rice.
- organism: plant (other)
- assay: bulk RNA-seq
- assay: metabolomics
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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