Next-Generation Sequencing-Based Detection of Common Bean Viruses in Wild Plants from Tanzania and Their Mechanical Transmission to Common Bean Plants

Author:

Mwaipopo Beatrice12,Rajamäki Minna-Liisa3ORCID,Ngowi Neema1,Nchimbi-Msolla Susan2,Njau Paul J. R.2,Valkonen Jari P. T.3,Mbanzibwa Deusdedith R.1ORCID

Affiliation:

1. Disease Control Unit, Tanzania Agricultural Research Institute — Mikocheni Centre, Dar es Salaam, Tanzania

2. Department of Crop Science and Horticulture, Sokoine University of Agriculture, Morogoro, Tanzania

3. Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland

Abstract

Viral diseases are a major threat for common bean production. According to recent surveys, >15 different viruses belonging to 11 genera were shown to infect common bean (Phaseolus vulgaris L.) in Tanzania. Virus management requires an understanding of how viruses survive from one season to the next. During this study, we explored the possibility that alternative host plants have a central role in the survival of common bean viruses. We used next-generation sequencing (NGS) techniques to sequence virus-derived small interfering RNAs together with conventional reverse-transcription PCRs (RT-PCRs) to detect viruses in wild plants. Leaf samples for RNA extraction and NGS were collected from 1,430 wild plants around and within common bean fields in four agricultural zones in Tanzania. At least partial genome sequences of viruses potentially belonging to 25 genera were detected. The greatest virus diversity was detected in the eastern and northern zones, whereas wild plants in the Lake zone and especially in the southern highlands zone showed only a few viruses. The RT-PCR analysis of all collected plant samples confirmed the presence of yam bean mosaic virus and peanut mottle virus in wild legume plants. Of all viruses detected, only two viruses, cucumber mosaic virus and a novel bromovirus related to cowpea chlorotic mottle virus and brome mosaic virus, were mechanically transmitted from wild plants to common bean plants. The data generated during this study are crucial for the development of viral disease management strategies and predicting crop viral disease outbreaks in different agricultural regions in Tanzania and beyond. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Funder

Program for Emerging Agricultural Research Leaders

Bill and Melinda Gates Foundation

Helsinki Institute of Life Science

Publisher

Scientific Societies

Subject

Plant Science,Agronomy and Crop Science

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