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Insights of Lr28 mediated wheat leaf rust resistance: Transcriptomic approach
Journal article   Peer reviewed

Insights of Lr28 mediated wheat leaf rust resistance: Transcriptomic approach

Dharmendra Singh, Dhananjay Kumar, Lopamudra Satapathy, Jyoti Pathak, Saket Chandra, Adnan Riaz, Govindraj Bhaganagre, Raman Dhariwal, Manish Kumar, Kumble Vinod Prabhu, …
Gene, Vol.637, pp.72-89
30/12/2017
PMID: 28935260

Abstract

Genetics & Heredity Life Sciences & Biomedicine Science & Technology
Leaf rust is a fungal disease that causes severe yield losses in wheat. Resistant varieties with major and quantitative resistance genes are the most effective method to control the disease. However, the main problem is inadequate information for understanding resistance mechanism and its usefulness. This paper presents Lr28 mediated genome-wide response of known and unknown genes during wheat-Puccinia triticina interaction. In this study, we prepared Serial Analysis of Gene Expression (SAGE) libraries using seedling wheat mRNA for infected and mock conditions. The libraries were sequenced on Sequencing by Oligonucleotide Ligation and Detection (SOLiD) system generating 37-48 million reads. After mapping and gene expression analysis of similar to 6-12 million trimmed reads/library, we revealed five major categories comprised of Lr28 controlled transcripts in resistant (+ Lr28) isoline (39), transcripts specific to susceptible (Lr28) isoline (785), transcripts specific to hypersensitive-response (HR) (375), transcripts specific for basal-defense (153) and transcripts for establishment of pathogen (1616). We estimated the impact of specific genes and pathways through mapping on plant resistant gene database (PRGdb), reactive oxygen species (ROS) and phytohormone database. Functional annotation results revealed, receptor binding, homeostatic processes and cytoskeletal components as the major discriminating factors between susceptibility and resistance. We validated 28 key genes using qRT-PCR and found positive results. These findings were projected on hypothetical interaction model to demonstrate interaction mechanism. The study might have significant impact on future rust-resistance breeding through knowledge based smart genetic selection of quantitative resistance genes besides major effect R-gene.

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