Evolutionary insights of Bean common mosaic necrosis virus and Cowpea aphid-borne mosaic virus

PeerJ. 2019 Feb 13:7:e6297. doi: 10.7717/peerj.6297. eCollection 2019.

Abstract

Plant viral diseases are one of the major limitations in legume production within sub-Saharan Africa (SSA), as they account for up to 100% in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out to gain insights into the molecular evolution and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV) present within symptomatic common bean and cowpea. Eleven near-complete genomes of BCMNV and two for CABMV were obtained from western Kenya. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes were carried out. Three well-supported clades in BCMNV and one supported clade for CABMNV were resolved and in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. The results will contribute greatly to the knowledge gap involving the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and inform the current breeding efforts towards resistance for BCMNV and CABMV.

Keywords: Genomics; Kenya; Next-generation sequencing (NGS); Phylogenomics of BCMNV and CABMV; Smallholder farmer; Virus evolution.

Grants and funding

Laboratory consumables were purchased through the Rising Star grants by the faculty of Science University of Western Australia to Laura M Boykin. Pawsey supercomputing Centre provided supercomputer resources for data analysis with funding from the Australian Government and the Government of Western Australia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.