A novel study on bean common mosaic virus accumulation shows disease resistance at the initial stage of infection in Phaseolus vulgaris

Front Genet. 2023 Mar 20:14:1136794. doi: 10.3389/fgene.2023.1136794. eCollection 2023.

Abstract

Accurate and early diagnosis of bean common mosaic virus (BCMV) in Phaseolus vulgaris tissues is critical since the pathogen can spread easily and have long-term detrimental effects on bean production. The use of resistant varieties is a key factor in the management activities of BCMV. The study reported here describes the development and application of a novel SYBR Green-based quantitative real-time PCR (qRT-PCR) assay targeting the coat protein gene to determine the host sensitivity to the specific NL-4 strain of BCMV. The technique showed high specificity, validated by melting curve analysis, without cross-reaction. Further, the symptoms development of twenty advanced common bean genotypes after mechanical BCMV-NL-4 infection was evaluated and compared. The results showed that common bean genotypes exhibit varying levels of host susceptibility to this BCMV strain. The YLV-14 and BRS-22 genotypes were determined as the most resistant and susceptible genotypes, respectively, in terms of aggressiveness of symptoms. The accumulation of BCMV was analyzed in the resistant and susceptible genotypes 3, 6, and 9 days following the inoculation by the newly developed qRT-PCR. The mean cycle threshold (Ct) values showed that the viral titer was significantly lower in YLV-14, which was evident in both root and leaf 3 days after the inoculation. The qRT-PCR thus facilitated an accurate, specific, and feasible assessment of BCMV accumulation in bean tissues even in low virus titers, allowing novel clues in selecting resistant genotypes in the early stages of infection, which is critical for disease management. To the best of our knowledge, this is the first study of a successfully performed qRT-PCR to estimate BCMV quantification.

Keywords: BCMV; SYBR green; common bean; real-time PCR; viral load.

Grants and funding

This research was funded by Bolu Abant Izzet Baysal University (Project ID: 2022.10.06.1550) and Basic Science Research Program supported this research through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (2019R1A6A1A11052070).