Abstract Detail



Comparative Genomics/Transcriptomics

Hernandez-Gonzalez, Alam [1].

Transcriptomic analysis of asymptomatic variety pepper (Capsicum annuum) against the tomato brown rugose fruit virus (ToBRFV).

Tomato (Solanum lycopersicum L) and pepper (Capsicum annuum) are among the most important vegetables in the world, have reached an average annual production of 180 million tonnes (2019) and 538,000 tonnes (2021), respectively but its production is threatened by the spread of novel pathogens introduced due to rapid expansion of international trade. One such pathogen is a new virus of tobamovirus named Tomato Brown Rugose Fruit Virus (ToBRFV) reported in 2014 in Israel and Jordan. Afterwards it has spread rapidly to other countries and has since been detected in the US, China, Spain, and Mexico, among others. While new resistances are deployed, the only means of control is the implementation of effective prevention and eradication strategies. Therefore, the knowledge of resistant cultivars is crucial to halt its spread, which has affected tomato and pepper production dramatically. Recently, we have observed that Bell pepper (C. annuum) shows far less symptoms than other susceptible cultivars, such as Habanero (C. chinense). In order to determine the genes that are differentially expressed between both cultivars, RNA was obtained in mock-inoculated and ToBRFV-infected plants from both sets of plants. Using RNAseq and bioinformatic tools the dfferentially-expressed transcripts are being analyzed. These data can be used to reveal the systemic changes in host gene expression profiles during the process of viral infection, and could contribute to provide information to better understand host-pathogen interaction. The results will be discussed further.


1 - CINVESTAV Zacatenco, Av. Instituto Politécnico Nacional 2508, San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México, CDMX, Mexico city, mx, 07360, Mexico

Keywords:
RNA-Seq
Transcriptomics
bell pepper
bioinformatic.

Presentation Type: Oral Paper
Number: CGT3007
Abstract ID:897
Candidate for Awards:None


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