Next generation sequencing reveals past and current widespread occurrence of maize yellow mosaic virus in South Africa

Soybean (Glycine max) has become an important crop in Manitoba, Canada, with a 10-fold increase in dedicated acreage over the past decade. Given the rapid increase in production, scarce information about foliar diseases present in the province has been recorded. In order to describe the foliar pathogens affecting this legume, we harnessed next-generation sequencing (NGS) to carry out a comprehensive survey across Manitoba in 2016. Fields were sampled during the V2/3 (33 fields) and R6 (70 fields) growth stages, with at least three symptomatic leaves per field collected and subjected to RNA sequencing. We successfully detected several bacteria, fungi, and viruses known to infect soybean, including Pseudomonas savastanoi pv. glycinea, Septoria glycines, and Peronospora manshurica, as well as pathogens not previously identified in the province (e.g., Pseudomonas syringae pv. tabaci, Cercospora sojina, and Bean yellow mosaic virus). For some microorganisms, we were able to disentangle the different pathovars present and/or assemble their genome sequence. Since NGS generates data on the entire flora and fauna occupying a leaf sample, we also identified residual pathogens (i.e., pathogens of crops other than soybean) and multiple species of arthropod pests. Finally, the sequence information produced by NGS allowed for the development of polymerase chain reaction-based diagnostics for some of the most widespread and important pathogens. Although there are many benefits of using NGS for large-scale plant pathogen diagnoses, we also discuss some of the limitations of this technology.

Download Full-text

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

Plant Disease ◽

10.1094/pdis-07-20-1420-re ◽

2021 ◽

Author(s):

Beatrice Mwaipopo ◽

Minna-Liisa Rajamäki ◽

Neema Ngowi ◽

Susan N’chimbi Msolla ◽

P Njau ◽

...

Keyword(s):

Next Generation Sequencing ◽

Common Bean ◽

Mosaic Virus ◽

Viral Disease ◽

Wild Plants ◽

Next Generation ◽

Rt Pcr ◽

Bean Plants ◽

Generation Sequencing ◽

Common Bean Plants

Viral diseases are a major threat for common bean production. In recent surveys, >15 different viruses belonging to 11 genera were shown to infect common bean (Phaseolus vulgaris L.) in Tanzania. Management of viruses requires an understanding of how they survive from one season to the next. In 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-polymerase chain reaction (RT-PCR) 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. RT-PCR analysis of all the 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 in this study are crucial for development of viral disease management strategies and predicting crop viral disease outbreaks in different agricultural regions in Tanzania and beyond.

Download Full-text

Statement on analysis and interpretation of clinical human gastrointestinal microbiome testing using next-generation sequencing in South Africa

South African Medical Journal ◽

10.7196/samj.2021.v111i3.15336 ◽

2021 ◽

Vol 111 (3) ◽

pp. 203

Author(s):

J M Wojno ◽

E Du Toit ◽

A Deffur ◽

A Brink

Keyword(s):

South Africa ◽

Next Generation Sequencing ◽

Next Generation ◽

Gastrointestinal Microbiome ◽

Generation Sequencing

Download Full-text

Diet Determined by Next Generation Sequencing Reveals Pest Consumption and Opportunistic Foraging by Bats in Macadamia Orchards in South Africa

Acta Chiropterologica ◽

10.3161/15081109acc2017.19.2.003 ◽

2017 ◽

Vol 19 (2) ◽

pp. 239-254 ◽

Cited By ~ 12

Author(s):

Peter John Taylor ◽

Emmanuel Matamba ◽

Jacobus Nicolaas (Koos) Steyn ◽

Tshifhiwa Nangammbi ◽

M. Lisandra Zepeda-Mendoza ◽

...

Keyword(s):

South Africa ◽

Next Generation Sequencing ◽

Next Generation ◽

Generation Sequencing

Download Full-text

Next generation sequencing reveals a high frequency of CXCR4 utilizing viruses in HIV-1 chronically infected drug experienced individuals in South Africa

Journal of Clinical Virology ◽

10.1016/j.jcv.2018.02.008 ◽

2018 ◽

Vol 103 ◽

pp. 81-87 ◽

Cited By ~ 2

Author(s):

Nontokozo D. Matume ◽

Denis M. Tebit ◽

Laurie R. Gray ◽

Marie-Louise Hammarskjold ◽

David Rekosh ◽

...

Keyword(s):

South Africa ◽

Next Generation Sequencing ◽

High Frequency ◽

Next Generation ◽

Generation Sequencing ◽

Hiv 1

Download Full-text

A bioinformatics pipeline for rare genetic diseases in South African patients

South African Journal of Science ◽

10.17159/sajs.2019/4876 ◽

2019 ◽

Vol 115 (3/4) ◽

Author(s):

Maryke Schoonen ◽

Albertus S. Seyffert ◽

Francois H. van Der Westhuizen ◽

Izelle Smuts

Keyword(s):

South Africa ◽

Next Generation Sequencing ◽

South African ◽

Rare Diseases ◽

Next Generation Sequencing Data ◽

Common Disease ◽

Next Generation ◽

Sequencing Data ◽

Bioinformatics Pipeline ◽

Generation Sequencing

The research fields of bioinformatics and computational biology are growing rapidly in South Africa. Bioinformatics pipelines play an integral part in handling sequencing data, which are used to investigate the aetiology of common and rare diseases. Bioinformatics platforms for common disease aetiology are well supported and continuously being developed in South Africa. However, the same is not the case for rare diseases aetiology research. Investigations into the latter rely on international cloud-based tools for data analyses and ultimately confirmation of a genetic disease. However, these tools are not necessarily optimised for ethnically diverse population groups. We present an in-house developed bioinformatics pipeline to enable researchers to annotate and filter variants in either exome or amplicon next-generation sequencing data. This pipeline was developed using next-generation sequencing data of a predominantly African cohort of patients diagnosed with rare disease. Significance: We demonstrate the feasibility of in-country development of ethnicity-sensitive, automated bioinformatics pipelines using free software in a South African context. We provide a roadmap for development of similarly ethnicity-sensitive bioinformatics pipelines.

Download Full-text

Evolutionary study of maize dwarf mosaic virus using nearly complete genome sequences acquired by next-generation sequencing

Scientific Reports ◽

10.1038/s41598-021-98299-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Dulanjani Wijayasekara ◽

Akhtar Ali

Keyword(s):

Next Generation Sequencing ◽

Mosaic Virus ◽

Complete Genome ◽

Evolutionary Relationship ◽

Fixation Index ◽

Maize Dwarf Mosaic Virus ◽

Next Generation ◽

Genome Sequences ◽

The Usa ◽

Generation Sequencing

AbstractNext-generation sequencing is a robust approach to sequence plant virus genomes in a very short amount of time compared to traditional sequencing methods. Maize dwarf mosaic virus (MDMV) is one of the most important plant viruses worldwide and a significant threat to maize production. In this study, we sequenced 19 MDMV isolates (10 from Johnsongrass and 9 from maize) collected in Oklahoma and Missouri during 2017–2019 using Illumina sequencing and determined the genetic diversity. Sequence reads were assembled and 19 nearly complete genome sequences of MDMV isolates were obtained. Phylogenetic analysis based on complete genomes nucleotide and amino acid sequences revealed two main clusters and a close evolutionary relationship among 19 MDMV isolates. Statistical analysis of individual genes for site-specific selection revealed that all genes are under negative selection. The fixation index (FST) analysis of the MDMV isolates revealed no gene flow between the two main phylogenetic clusters, which emphasizes the divergence of MDMV isolates from the USA. Among the USA MDMV isolates, the mean genetic distance (d) and nucleotide diversity ((π) were highest in the P1 gene coding region. This is the first detailed study on the evolutionary relationship of MDMV isolates based on the nearly complete genome analysis from maize and Johnsongrass.

Download Full-text