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Transcriptome analysis of the Brassica napus – Leptosphaeria maculans pathosystem identifies receptor, signaling and structural genes underlying plant resistance
Author(s) -
Becker Michael G.,
Zhang Xuehua,
Walker Philip L.,
Wan Joey C.,
Millar Jenna L.,
Khan Deirdre,
Granger Matthew J.,
Cavers Jacob D.,
Chan Ainsley C.,
Fernando Dilantha W.G.,
Belmonte Mark F.
Publication year - 2017
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.13514
Subject(s) - leptosphaeria maculans , pathosystem , blackleg , biology , genetics , transcriptome , gene , canola , arabidopsis , plant disease resistance , wrky protein domain , r gene , computational biology , brassica , botany , gene expression , mutant
Summary The hemibiotrophic fungal pathogen Leptosphaeria maculans is the causal agent of blackleg disease in Brassica napus (canola, oilseed rape) and causes significant loss of yield worldwide. While genetic resistance has been used to mitigate the disease by means of traditional breeding strategies, there is little knowledge about the genes that contribute to blackleg resistance. RNA sequencing and a streamlined bioinformatics pipeline identified unique genes and plant defense pathways specific to plant resistance in the B. napus–L. maculans LepR1–AvrLepR1 interaction over time. We complemented our temporal analyses by monitoring gene activity directly at the infection site using laser microdissection coupled to quantitative PCR . Finally, we characterized genes involved in plant resistance to blackleg in the Arabidopsis– L. maculans model pathosystem. Data reveal an accelerated activation of the plant transcriptome in resistant host cotyledons associated with transcripts coding for extracellular receptors and phytohormone signaling molecules. Functional characterization provides direct support for transcriptome data and positively identifies resistance regulators in the Brassicaceae. Spatial gradients of gene activity were identified in response to L. maculans proximal to the site of infection. This dataset provides unprecedented spatial and temporal resolution of the genes required for blackleg resistance and serves as a valuable resource for those interested in host–pathogen interactions.