Abstract Detail

Host/Plant Pathogen Interactions and Plant Health Management

Girard, Ian J. [1], Becker, Michael G. [1], Fernando, Dilantha [2], De Kievit, Teressa [3], Belmonte, Mark F. [1].

Using Big Data to probe the plant defense response: RNA sequencing of the canola – Sclerotinia pathosystem.

Canola is one of the principal cash crops of Manitoba and the number one oilseed in Canada and is susceptible to the devastating fungal pathogen, Sclerotinia sclerotiorum (Lib.) de Bary. Sclerotinia is a versatile necrotrophic fungus that can cause millions of dollars in crop loss each year. Since the outcome of any host-pathogen interaction is specified at the genetic level, building a solid understanding of how the underlying genetic networks impact canola defense response is pivotal to overcoming the disease. To date, relatively little is known about how defenses are specified in the canola-Sclerotinia pathosystem and nothing about how the defense response is activated directly at the site of infection using the petal inoculation method. In a comparative study we examined global transcriptional responses in a susceptible line of canola (cv. Westar) and a partially resistant line (cv. ZhongYou 821) to infection with Sclerotinia using a combination of Next Generation RNA sequencing and bioinformatics analyses. We identified large sets of co-expressed genes using a modified fuzzy K-means clustering algorithm and predicted key biological processes that are differentially enriched in ZhongYou 821. Using new ways to manage large-scale datasets, we provide biological insights into plant defense responses that can eventually be used by crop breeders and agronomists to combat Sclerotinia.

1 - University of Manitoba, Biological Sciences, 50 Sifton Rd, Winnipeg, Manitoba, R3T 2N2, Canada
2 - University of Manitoba, Plant Science, 222 Agriculture Building, Winnipeg, Manitoba, R3T 2N2, Canada
3 - University of Manitoba, Microbiology, 213 Buller Building, Winnipeg, Manitoba, R3T 2N2, Canada

Keywords:
Plant-Pathogen Interaction
RNA Sequencing
Bioinformatics.

Presentation Type: Oral Paper:Papers for Topics
Session: 57
Location: Salon 9/The Shaw Conference Centre
Date: Wednesday, July 29th, 2015
Time: 8:15 AM
Number: 57002
Abstract ID:127
Candidate for Awards:CSPB President's Award for Best Student Presentation,CPS Best Student Presentation Awards