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High-Throughput Sequencing Application in the Diagnosis and Discovery of Plant-Infecting Viruses in Africa, A Decade Later

Discipline of Plant Pathology, School of Agricultural, Earth and Environmental Sciences, Agriculture Campus, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa
Author to whom correspondence should be addressed.
Plants 2020, 9(10), 1376;
Received: 22 August 2020 / Revised: 25 September 2020 / Accepted: 29 September 2020 / Published: 16 October 2020
(This article belongs to the Special Issue Diagnosis and Control of Plant Viral Diseases)


High-throughput sequencing (HTS) application in the field of plant virology started in 2009 and has proven very successful for virus discovery and detection of viruses already known. Plant virology is still a developing science in most of Africa; the number of HTS-related studies published in the scientific literature has been increasing over the years as a result of successful collaborations. Studies using HTS to identify plant-infecting viruses have been conducted in 20 African countries, of which Kenya, South Africa and Tanzania share the most published papers. At least 29 host plants, including various agricultural economically important crops, ornamentals and medicinal plants, have been used in viromics analyses and have resulted in the detection of previously known viruses and novel ones from almost any host. Knowing that the effectiveness of any management program requires knowledge on the types, distribution, incidence, and genetic of the virus-causing disease, integrating HTS and efficient bioinformatics tools in plant virology research projects conducted in Africa is a matter of the utmost importance towards achieving and maintaining sustainable food security.

1. Introduction

Viruses were found to cause diseases in plants in the last quarter of the 19th century. This discovery, which also marked the start of the discipline of plant virology, was made from various studies that pinpointed tobacco mosaic virus as the causal agent of a mosaic disease on tobacco plants [1]. Thenceforth, viruses have been identified in most plants including vegetables [2,3], legumes [4,5], cereals [6,7], fruit crops [8], ornamentals [9] and wild species [10] and constitute approximately one-third of plant disease-causing agents. Plant virus particles, frequently referred to as virions, vary in shapes and sizes. They are obligatory intracellular parasites made of a single or multiple DNA or RNA genomic segments enclosed within a protein shell called the capsid. Most plant-infecting viruses have non-enveloped virions except the members of families Firmoviridae [11], Rabdoviridae [12] and Tospoviridae [13]. The host plant cuticle and the cell wall provide a solid natural physical protection that has to be broken to create virus entry point to the plant cell of a susceptible host and cause disease. This is generally achieved through mechanical wounds or the action of vectors such as insects, nematodes, fungi while feeding on the plants. Following the entry into a host cell and genome decapsidation, the infectious cycle includes translation and replication of the viral genome, assembly of progeny virus particles, generalized invasion of the host through cell-to-cell and long-distance movements of viral particles or ribonucleoprotein complexes and finally, transmission to new hosts by vectors [14]. Virus transmission also occurs through the use of infected plant propagation materials, grafting and contaminated tools.
Plant-infecting viruses are of serious concern in agriculture and represent a significant threat to food security worldwide. Virus infection in susceptible host plants results in a series of physiological disorders that have adverse effects on the overall plant heath [14]. The symptoms typical of virus infections are quite diverse and may appear on any part of the infected plants. The severity of these symptoms results from interactions between the virus, the host plant, the virus vector and the environment [15,16]. The family Potyviridae, the largest family of RNA plant-infecting viruses [17] and the second-largest plant virus family after Geminiviridae [18], comprise some of the most damaging and widespread viruses of agronomic crops worldwide. In some instances, over 90% crop yield reduction has been recorded [14]. Such losses have had devastating socio-economic consequences for farmers, producers, distributors and consumers.
Accurate diagnosis of virus diseases is crucial for developing effective and sustainable crop management systems [19], especially considering that several biotic and abiotic factors also produce virus-like symptoms in plants [20,21]. The use of appropriate integrated control strategies upon virus identification will prove effective in mitigating the spread of the virus, thereby reducing further crop damage and yield loss. The other aspect of integrated management approaches is to prevent the dissemination of virus causing diseases through their different modes [22]. One of the ways to achieve this goal has been using certified high-quality virus-tested planting materials. However, the large number and high genetic variability of plant viruses can make their detection cumbersome [23].
The methods of detection and identification of viruses developed heretofore fall into serological techniques, molecular methods, microscopical and physical observations [19,20]. Serological assays such as the enzyme-linked immunosorbent assay and the tissue blot immunoassay, and the polymerase chain reaction and its derivatives from the molecular side, have been commonly used for routine testing [20,21,24]. High sensitivity, specificity, reliability, speed, and cost effectiveness are some of the determinant factors of the success of any method of detection [22,24]. High-throughput sequencing (HTS) has been gaining popularity as a powerful alternative for diagnosis and detection of plant viruses worldwide. This review focuses on the contribution of HTS in Africa in relation to the detection and discovery of plant-infecting viruses based on the peer-reviewed articles published since the beginning of HTS applications in plant virology.

2. Integration of HTS in Plant Virology in Africa

HTS was initially introduced as next generation sequencing to mark a distinct demarcation from the former sequencing technology commonly known as Sanger sequencing that was introduced in 1977. HTS technologies employ unprecedented parallelization of a high number of sequencing reactions, generating billions of reads that amount to gigabytes of data, in a shorter time and at a much-reduced cost [25]. Either digital single or pair-end reads can be obtained depending on the technology selected. Since their introduction in 2005, many HTS sequencing platforms have been developed including Pyrosequencing, Ion Torrent technology, Illumina/Solexa, and Sequencing by Oligonucleotide Ligation and Detection. Further optimization has led to innovative third- and fourth-generation platforms such as single-molecule real-time sequencing by PacBio and Nanopore sequencing [26]. These platforms differ substantially in terms of their preparatory procedures, sequencing chemistry or technology, nucleotide incorporation technology, read type, length, accuracy, the size of generated data and price. More elaborate information on HTS can be found from previous reviews [25,26,27,28,29,30,31].
The application of HTS combined with the rapid progress in developing bioinformatics tools to simplify data analysis has revolutionized plant virology worldwide. The field of plant virus discovery and diagnosis especially have benefited the most from these technologies with the earliest report dated in 2009 [32,33]. HTS, unlike conventional serological and molecular methods, does not require any knowledge of the suspected causing disease pathogen before being performed. This unique property of unbiased and hypothesis-free testing of plant sample has been the principal reason behind integrating HTS as a method for simultaneous detection of multiple viruses regardless of their genome nature or structure [34]. Consequently, a number of HTS protocols targeting nucleic acid pools such as virion-associated nucleic acids, double-stranded RNAs, total RNAs, ribosomal-RNA-depleted RNAs, messenger RNAs, or small interfering RNAs have been developed concurrently with specific bioinformatics workflows for this purpose [35,36,37,38,39].
The science of plant virology is still in its infancy in several countries across Africa. Only a few countries are reputed to have teaching institutions and modern research facilities. Moreover, Africa as a whole still lags behind developed countries in adopting HTS technologies and has to overcome the shortage of human resources, the limited expenditure in research and equipment, slow internet connectivity, and infrastructural challenges in order to be “omics” ready [40,41,42]. Nonetheless, countries such as South Africa, Kenya, Senegal, Ghana and Nigeria have gained worldwide recognition for establishing HTS platforms and bioinformatics capacities [43,44].
On the matter of the application of HTS to the detection and diagnosis of plant-infecting viruses in Africa, a considerable number of studies, made possible mostly through various collaborations with institutions abroad, have been documented. For clarity, the taxonomic classification and abbreviations of viruses detected using HTS in Africa are indicated in Table 1, and a comprehensive summary of these studies is provided in Table 2. The number of peer-reviewed publications around this theme to date stands just above 60 in total. It is important to note that this number has been increasing over the years with a minimum of 10 articles being published starting in 2018. As a point of precision, the African countries as per the African Union list and classification ( were considered for this review. Twenty countries, out of the 55 that constitute the African continent, have been mentioned in literature on the subject with studies conducted in South Africa, Tanzania and Kenya accounting for more than half of the published articles (Figure 1). South Africa has been the first African country to have locally performed HTS and data analysis related to plant-infecting viruses. Kenya followed some years later. In terms of sequencing platforms, Illumina has been the preferred one for the vast majority of projects. Pyrosequencing platforms have also been used occasionally (Table 2). Satisfactory results were obtained for each study conducted irrespective of the host plant used. Moreover, the choice of the host plants in the HTS related studies in Africa may be closely related to its economic value.

3. Host Plants Subjected to HTS

Twenty-nine host plants, including crops, medicinal and ornamental plants (Table 2) have been used in HTS for virus detection or diagnostic in Africa since 2010. These host plants belong to 18 different families of which five—Poaceae, Fabaceae, Cucurbitaceae, Solanaceae, Convolvulaceae and Euphorbiaceae—took the biggest share (Figure 2), mainly because they contain many economically important crops. While some studies focused on a host plant in a specific country or environment as in the case of papaya [52,53], groundnut [69,83], tannia [74], cabbage [96], cotton [103], grapevine [105,106,113,115] to mention a few; in other studies, the viromics of a host plant was analyzed across different countries in a same survey. The information generated in such analyses has provided a better understanding of the status and distribution of the viruses identified for a specific host plant. Selected case studies will be the focus of the next paragraphs.

3.1. Maize

Maize, Zea mays L., which originated in the Mexican Highlands, has become one of the major staple food crops in most sub-Saharan African countries, being cultivated in both commercial and small-scale farms. It is also important as feed for poultry and other livestock industries [116]. However, its production over the years has remained lower when compared to the average yield worldwide [117].
The first published studies of maize being subjected to HTS dates back to 2013 [112]. HTS was used to elucidate the pathogens causing a new disease of maize, which was first identified in Kenya in 2011. Previous studies of the etiology of this particular disease using ELISA had been unsuccessful. The analysis of the data generated from the sequencing of total RNA on a pyrosequencing platform led to the identification of two viruses, MCMV and SCMV, a combination previously reported to cause maize lethal necrosis disease (MLND). Moreover, the recovery of near-complete genome sequences of the identified virus isolates allowed for their molecular characterization. The MCMV isolate detected, although similar to other previously sequenced strains, was found to be most similar to a Chinese isolate rather than the more widespread American strains based on the complete genome and the translated protein sequences [112]. The SCMV isolate was found to be closely related to a distinct and highly virulent East Asian strain previously found in China, Vietnam and Thailand [112]. MLND is devastating to maize production with losses in East Africa estimated between 25% and 100%.
MLND symptoms were first observed on maize cultivated in Rwanda in 2013. Four maize samples were subjected to HTS to confirm the presence of the viruses associated with the disease, especially after real-time PCR tested negative for the detection of SCMV. The two viruses responsible for MLND previously identified in Kenya were recovered from the analysis of the HTS data. MCMV was closely related to the MCMV from Kenya and China (99% homology) when compared with MCMV from the United States (96–97% homology). Complete SCMV genomes were found in three of the four samples. The SCMV isolated from the Rwandan samples were distinct from that isolated in Kenya (87% identity). Closer examination of the Rwandan SCMV genomes revealed a high degree of divergence as the cause of the negative real-time PCR results [109]. MCMV and SCMV were also the two viruses detected in a similar study that was conducted in Ethiopia on six maize samples. Phylogenetic trees were constructed based on the complete genomes of MCMV and the coat proteins of the SCMV isolates. MCMV isolates in Ethiopia were found to be highly similar to those found previously in East Africa. SCMV isolates from Ethiopia, in contrast, were found to be similar to each other and those found in Rwanda, but relatively distant from those originally found in Kenya [108].
Wamaitha et al. [88] followed a metagenomics analysis based on RNA sequencing, de novo assembly and virus identification to gain insight into viruses associated with MLND in Kenya. The virus survey was extended to sorghum and Napier grass. This time, ScaMV, Hubei Poty-like virus 1, JGMV, MYDV-RMV, Barley virus G, MSV were identified in addition to MCMV and SCMV. Based on the virus prevalence and geographic distribution, four viruses—MCMV, SCMV, MSV and MYDV-RMV—were widespread with MYDV-RMV, always found as part of a complex that included MCMV and SCMV, or MCMV, SCMV and MSV. Stewart et al. [118] also confirmed the involvement of JGMV in MLND in Kenya and Uganda.
The prevalence of poleroviruses infecting maize in East Africa was demonstrated by Massawe et al. [87] from the studies conducted on maize growing areas in Kenya, Uganda, Rwanda, and Tanzania. RNA sequencing and de novo assembly of non-maize sequences yielded contigs that were aligned to plant-infecting viral sequences in the National Center for Biotechnology Information database. Polerovirus matching contigs were subsequently assembled to generate a supercontig consensus sequence that was further ascertained using primer walking followed by rapid amplification of cDNA ends. The complete genome sequence of the MYDV-like polerovirus isolated from East African countries was 5641 nucleotides and similar to other maize, sugarcane, itch grass-, and barley-associated polerovirus. The prevalence of this virus was estimated between 40.3 and 90.0% [87]. Five virus species not previously reported in Tanzania were reported in 2019 from HTS performed in one of the South African facilities using ribo-depleted RNA [56,57,58,59,60]. One of them, MYMV had a broad geographical distribution and was thought to be another MLND-associated virus. MDMV, SrMV, MMaV, and MATV, although found restricted to specific areas in Tanzania, have already spread throughout East Africa as per the results obtained from HTS recently performed on MLND maize samples collected in Rwanda [55].

3.2. Common Bean and Cowpea

Common bean (Phaseolus vulgaris L.) and cowpea (Vigna unguiculata Walp.) are some African indigenous vegetables that belong to the Family Fabaceae. These two crops play an important role in both human nutrition, food security and income generation for farmers and food vendors. The 2016 global estimates showed that 12.3 million hectares of land are utilized in the production of cowpea with Western and Eastern Africa [119]. Three East African countries, Kenya, Tanzania and Uganda, are among the global leaders of common bean production [120].
Seed-borne pathogens, including certain viruses, have great potential to reduce growth and yield of common bean because they interfere with plant growth from the beginning [92]. Against that background, seed-borne viruses were surveyed in common bean varieties, landraces and improved common bean varieties that are grown in Tanzania. The testing was obtained from the seeds of symptomatic plants that had been germinated in insect-proof controlled environments. HTS of the small RNAs extracted from the sampled plant materials were performed. VirusDetect [121], an automated bioinformatics pipeline, was used to detect contigs of viral origins. CPMMV was the only pathogenic virus identified among two other non-pathogenic viruses namely PvEV-1 and PvEV-2. These endornaviruses had not been previously detected on the African continent [92].
Another viromics study of common bean published by Mwaipopo et al. [86] provided a different picture. HTS of small RNAs from leaves sampled, this time, from fields across Tanzania followed by data analysis also performed using VirusDetect led to the detection of several viruses belonging to eleven genera. Apart from the cryptic viruses and CPMMV detected by Nordenstedt et al. [92], BCMNV, BCMV, CABMV, SBMV, CMV, ToLCU-related begomovirus and related umbraviruses were detected.
Mulenga et al. [45] published the results of a comprehensive study of virus-infecting common bean conducted in the Eastern Province of Zambia. HTS was done in South Africa using total RNA. Blastn was subsequently used to query GenBank with the de novo-assembled contigs. The detected viruses included SBMV, BCMV, BCMNV, CABMV, and CMV. Out of these viruses, SBMV had never been reported to infect common bean in Zambia. First-generation sequencing of RT-PCR products generated using SBMV specific primers were subsequently conducted to validate the HTS results, thus confirming the incidence of this virus in Zambia.
Kenya is another East African country where HTS has been used for virus identification purposes on common bean. Four studies have been published between 2018 and 2019. Two of these, by Wainaina et al. [71] and Mutuku et al. [84] yielded several viruses while the other two focused on BCMNV [70,72] and CABMV [72]. Wainaina et al. [71] carried out a viral metagenomic analysis using rolling circle amplification to detect possible DNA infecting viruses on symptomatic bean plants. Two approaches were used to identify potential viral sequences within the bean DNA-Seq reads following the quality control check of the reads. Kaiju [122], a program for sensitive taxonomic classification of HTS reads was the method used to determine the taxonomic profile which was visualized in Krona [123]. The other approach consisted in subjecting assembled contigs to blastx searches using a preassembled viral NCBI RefSeq database. PVBV was the only plant-infecting DNA virus detected. Surprisingly some contigs matched BCMNV, a positive single-strand RNA virus [71]. Mutuku et al, [84], on the other hand, utilized shotgun RNA sequencing for metagenomic examination of viruses present in bean plants growing at two locations in Kenya. De novo assembly and blast ( were performed and led to the detection of BCMNV, PvEV1, PvEV2, and CMV. RT-PCR was subsequently done to authenticate the presence of these viruses in the respective samples. Molecular analysis of the CMV strain detected was found most closely related to Asian strains that might have been recently introduced to the region. The detection of PvEV1 and PvEV2 suggested that these seed transmitted viruses may be more prevalent in Eastern African bean germplasm than previously thought [84].
A virion-associated nucleic acid (VANA)-based metagenomics method was used to screen for the presence of cowpea infecting viruses in Burkina Faso, a West African country [104]. The VANA were extracted from plants displaying virus-like symptoms collected from the three agro-climatic zones of the country. The sequencing was carried on a pyrosequencing platform. De novo assembly of cleaned reads was the method opted and the generated contigs and non-assembled reads with a minimum length of 45 bp were compared to sequences in the GenBank database using blastn and blastx. The presence of viruses identified during the metagenomic screen was verified using RT-PCR. Only RNA viruses were identified which included previously reported viruses such as CABMV, BCMV-BlCM, CPMoV and novel virus species provisionally named CPPV-1, CPPV-2, CPTV-1, CPTV-2 and CPaMV-1 [104].

3.3. Sweet Potato

Sweet potato (Ipomoea batatas [L.] Lam) is a dicotyledonous plant that belongs to the family Convolvulaceae. It has become an important staple and co-staple food crop in Africa. Orange-fleshed sweet potato varieties, a rich source of vitamin A especially, are important for infants and young children. Africa was the second-largest producer, producing 21 million tons in 2016, behind Asia’s production that was estimated at more than 78 million in the same year [124].
Virus diseases have been identified as the second-most important biotic constraint to sweet potato production. A viral metagenomic approach was adopted in South Africa to understand the progressive deterioration of the yield and quality of sweet potato crops, usually referred to as “cultivar decline” experienced by farmers across the country. Leaf samples collected from different surveys in the major growing regions were subjected to DNA [62,79,80], total RNA [80] and small RNAs extraction [81]. Before HTS, the extracted RNA was depleted of ribosomal RNA while rolling circle amplification was performed on the DNA. Good quality reads were used in both de novo and reference-guided assemblies. The results indicated the presence of two badnaviruses, sweet potato badnavirus A (SPBVA) and sweet potato badnavirus B (SPBVB), which had never been reported [81] along with commonly occurring viruses, i.e., SPFMV, SPVG, SPVC, SPV2, SPCSV, SPMV, SPLCV and SPLCSPV [62,79,80]. SPBVA and SPBVB have collectively been assigned to the species SPPV [125] and their identity in South Africa was confirmed by conventional Sanger sequencing of amplified PCR products [81]. SPBVA, SPBVB, SPVC, SPVG and SPLCV were not as widespread as the rest of the viruses. The studies also revealed that DNA viruses occurred in mixed infections with RNA viruses. Yield reduction of multiple and co-infections under field conditions was evaluated and shown to vary between 28 and 100% depending on the sweet potato varieties and the viruses involved [62].
Tanzania was the second-largest producer of sweet potato in Africa 2016 [124]. Ninety-six symptomatic and asymptomatic sweet potato vines were collected from different locations in Tanzania between December 2012 to January 2013 [110]. Small RNAs were used for HTS. Nucleotide blast and blastx against the sequences in the GenBank database of the de novo-assembled contigs matched sequences of SPCSV, SPFMV, SPLCSPV, SPPV, and SPSMV-1. The presence of these viruses was confirmed using conventional molecular techniques. SPPV and SPSMV-1 were found widespread and co-infecting sweet potato plants in Tanzania [110].

3.4. Cassava

Cassava (Manihot esculenta subspecies esculenta Crantz; Euphorbiaceae), which is currently produced in 40 sub-Saharan African countries, was introduced to that region by Portuguese sailors from Brazil in the sixteenth century [126]. Although the leaves are used as food in some countries, what makes cassava very popular are its roots. According to the 2017 FAOSTAT, cassava was the number one root crop in sub-Saharan Africa ahead of yam and sweet potato with an annual root production exceeding 140 million tons [127]. Tubers, once processed are cooked using various traditional techniques, constitute the major source of carbohydrates in many households across sub-Saharan Africa. Besides being the most important staple food and a significant source of farm income, cassava has also enormous potential for industrial processing [128]. To turn that concept into reality will cause an increase in the demand for high-quality healthy cassava roots.
Africa’s average yield of cassava is far below the predicted yield under optimal conditions of 23.2 tons/ha [129]. The recorded average yield for the period 2015–2018 fluctuated between 8.9 and 9.2 tons/ha [130]. Viral diseases are an impending disaster to cassava production unless proper integrative control strategies are strictly observed. HTS has been used to unravel the etiology of some of the most damaging viral diseases of cassava in Cameroon [101], Comoros [66], Malawi [91], Mozambique [65], Tanzania [107,114], Togo [101] and Uganda [114].
The earliest records of HTS application on cassava are from 2010. Total RNA extracted from symptomatic leaves collected in Uganda, and Tanzania served as template in cDNA synthesis. A Subtractive hybridization designed to enrich the viral cDNA was performed prior to HTS on a pyrosequencing platform. Contig assembly was carried out using a commercial software CLC Genomics Workbench (CLCBio, Denmark). Blast analysis was performed using blastn. Alternately, metagenomic analysis was performed using MEGAN [131]. As the HTS data analysis showed gaps, specific primers were designed to enable the amplification of overlapping PCR products that enabled the construction of the missing portion of the viral genome sequences. The integrity of the 5’end of the genome was checked using rapid amplification of cDNA ends. CBSV was the only identified virus in the analyzed samples. Two distinct isolates, namely, CBSV Ugandan strain and CBSV Tanzanian strain were identified from this study. Sequence comparisons indicated 76% nucleotide identity across the genome and 57–77% protein identity [114]. The discovery of only ipomovirus sequences in that study put an end to the controversy over the causal agent of the cassava brown streak disease (CBSD). However, the sequence comparison results from that study provided enough evidence to consider each described isolate as a distinct species. CBSD was first reported in 1936 from Northeast Tanzania. The disease symptoms vary depending on the viral strain, cassava cultivar, environmental conditions and age of the plant at the time of infection. Symptoms that have been found associated with CBSD include plant root necrosis, radial root constrictions foliar chlorosis, brown streaks and lesions on the stem [132].
CBSD re-emerged at the turn of the 21st century. It has since spread through many East and Central African countries, causing considerable yield losses and jeopardizing the food security of subsistence farmers [132]. A cassava cutting with conspicuous symptoms of CBSD sampled in Nkhata Bay District in Malawi in 2013 was selected for HTS and data analysis. The ribo-depleted RNA of the sample under study was used as a template for double-stranded cDNA synthesis before library preparation for HTS on a MiSeq instrument. Data analysis was done using both CLC Workbench and Geneious (https://www.geneious). One well-supported contig that matched UCBSV genome sequence was selected and compared with all complete UCBSV genome sequences available in GenBank. This 9070-nucleotide contig constituted the genome sequence of an UCBSV isolate called MW-NB7_2013. This isolate was highly similar to an isolate from Tanzania (93.4% pairwise nucleotide identity) than to those previously reported from Malawi (86.9 to 87.0%) [91]. Similar studies have also been performed in Mozambique [65] and Comoros [66] and they strongly support the existence of new isolate lineages. The rampant spread of CBSD has triggered intense scientific mobilization to better understand the epidemiology, sequence diversity, host interactions and integrated control management of the disease.

4. Conclusions

The HTS for viromics studies performed on different host plants in the African continent has led to the detection of known and novel viruses. This observation is consistent in all hosts tested and across all the countries where the technology has been used. Molecular and serological detection methods remain relevant, especially in cases of novel viruses and viruses not previously reported. The unprecedented increase of novel viruses detected using HTS once again accentuates the need for a uniform and practical way of naming plant viruses. This call has been echoed several times in the scientific communities [133,134,135,136,137,138]. Plant-infecting viruses have been formerly named based on the host they were found to infect at the time of their discoveries and the type of symptoms they induced. Using such a method requires a thorough investigation of the virus symptoms in regards of the Koch’s postulates. However, the speed at which novel viruses are detected and reported outruns the follow-up studies on their biological properties. Furthermore, it has been proven through comprehensive HTS studies that plants are often infected with multiple viruses under natural field conditions. In some instances, co-infections with multiple unrelated viruses have turned into synergistic interactions that are characterized by an increase in viral replication or movement in the host plant, and the development of more severe symptoms. The revision of the current naming of plant-infecting viruses using a system independent of symptomatology may restore order and accuracy in that regard.
It is apparent that biological characterization of plant-infecting viruses has remained relevant throughout the history of plant virology. This is all the more true in this age of HTS and bioinformatics. In the past virus discovery was symptoms driven thus strongly relying on combinations of biological techniques, morphology and conventional targeted methods. The advent of HTS has resulted in an alteration of this pattern and preeminence has unintentionally been given to the molecular component. It is therefore critical to link molecular observations to their corresponding effects in the host plants. Taking multiple virus infections as an example, follow-up studies should be conducted to understand the host response to single and multiple infections. Plant health risk assessment should actually be carried out for every HTS detected virus more especially that there is evidence of the existence of cryptic [139,140,141] and even beneficial viruses [142]. The availability of scientific knowledge as such will enable plant health, policymakers and regulators to make correct decisions. Recommended literature on this topic includes Adams et al. [143] and Massart et al. [144].
The progress made in the field of plant virology throughout the African continent is quite tangible, albeit happening slowly. However, the nescience of the existence of plant-infecting viruses does not in any way prevent their spread. The detection of virus strains infecting maize and common bean in Africa that are similar to Asian strains is an obvious illustration of viruses readily spreading across continents probably through anthropogenic activities. The continual presence of plant-infecting viruses unknown to scientists on the African soil could, in the long term, have devastating consequences for agricultural production. Although the integration of HTS and bioinformatics tools in plant virology research projects in Africa will require substantial financial investments, its implementation and uptake in more countries than the case presently, will go a long way towards the development of effective and sustainable strategies to manage/control viral diseases infecting major crops. This will ensure food security for many food-insecure people on the continent.

Author Contributions

Conceptualization, J.D.I.; writing—original draft preparation, J.D.I.; writing—review and editing, A.G. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. African countries that have been mentioned in high-throughput sequencing (HTS) studies related to the detection and diagnosis of plant-infecting viruses.
Figure 1. African countries that have been mentioned in high-throughput sequencing (HTS) studies related to the detection and diagnosis of plant-infecting viruses.
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Figure 2. Host plants families that have been subjected to HTS for detection or diagnosis of plant-infecting virus.
Figure 2. Host plants families that have been subjected to HTS for detection or diagnosis of plant-infecting virus.
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Table 1. Names, abbreviations and taxonomic status of viruses identified in Africa by HTS means.
Table 1. Names, abbreviations and taxonomic status of viruses identified in Africa by HTS means.
Virus NameAbbreviationGenusFamily
African cassava mosaic virusACMVBegomovirusGeminiviridae
African eggplant yellowing virusAeYVPolerovirusLuteoviridae
Arctopus echinatus-associated virusAeaVN/AN/A
Barley virus GBVGPolerovirusLuteoviridae
Barley yellow dwarf virusBYDVLuteovirusLuteoviridae
Bean common mosaic virusBCMVPotyvirusPotyviridae
Bean common mosaic virus strain blackeye lackeye cowpea mosaicBCMV-BlCMPotyvirusPotyviridae
Bean common mosaic necrosis virusBCMNVPotyvirusPotyviridae
Bean yellow disorder virusBnYDVCrinivirusClosteroviridae
Cacao swollen shoot virusCSSVBadnavirusCaulimoviridae
Cacao swollen shoot CD virusCSSCDVBadnavirusCaulimoviridae
Cacao swollen shoot CE virusCSSCEVBadnavirusCaulimoviridae
Cacao swollen shoot Ghana M virusCSSGMVBadnavirusCaulimoviridae
Cacao swollen shoot Ghana N virusCSSGNVBadnavirusCaulimoviridae
Cacao swollen shoot Ghana Q virusCSSGQVBadnavirusCaulimoviridae
Cacao swollen shoot Ghana R virusCSSGRVBadnavirusCaulimoviridae
Cacao swollen shoot Togo A virusCSSTAVBadnavirusCaulimoviridae
Cassava brown streak virusCBSVIpomovirusPotyviridae
Chickpea chlorotic dwarf virus tomato strainCpCDV-TMastrevirusGeminiviridae
Coccinia mottle virusCocMoVIpomovirusPotyviridae
Cotton yellow mosaic virusCYMVBegomovirusGeminiviridae
Cowpea aphid-borne mosaic virusCABMVPotyvirusPotyviridae
Cowpea associated mycotymovirid 1CPaMV-1N/ATymoviridae
Cowpea mild mottle virusCPMMVCarlavirusBetaflexiviridae
Cowpea mottle virusCPMoVGammacarmovirusTombusviridae
Cowpea polerovirus 1CPPV-1PolerovirusLuteoviridae
Cowpea polerovirus 2CPPV-2PolerovirusLuteoviridae
Cowpea tombusvirid 1CPTV-1N/ATombusviridae
Cowpea tombusvirid 2CPTV-2N/ATombusviridae
Cucumber mosaic virusCMVCucumovirusBromoviridae
Cucumber vein yellowing virusCVYVIpomovirusPotyviridae
Dioscorea bacilliform RT virus 3DBRTV3BadnavirusCaulimoviridae
Dioscorea mosaic-associated virusDMaVSadwavirusSecoviridae
Grapevine endophyte alphaendornavirusGEEVAlphaendornavirusEndornaviridae
Grapevine leafroll-associated virus 3GLRaV-3AmpelovirusClosteroviridae
Grapevine rupestris stem pitting-associated virusGRSPaVFoveavirusBetaflexiviridae
Grapevine virus AGVAVitivirusBetaflexiviridae
Grapevine virus EGVEVitivirusBetaflexiviridae
Grapevine virus FGVFVitivirusBetaflexiviridae
Groundnut rosette virusGRVUmbravirusTombusviridae
Groundnut rosette assistor virusGRAVN/ALuteoviridae
Iris yellow spot virusIYSVOrthotospovirusTospoviridae
Ivy ringspot-associated virusIRSaVBadnavirusCaulimoviridae
Johnsongrass mosaic virusJGMVPotyvirusPotyviridae
Lolium perenne-associated virusLpaVN/AN/A
Maize-associated betaflexivirusMaBVChordovirusBetaflexaviridae
Maize-associated pteridovirusMaPVPteridovirusMayoviridae
Maize-associated totivirusMATVTotivirusTotiviridae
Maize-associated totivirus-1-TanzMATV-1-TanzTotivirusTotiviridae
Maize-associated totivirus-4-TanzMATV-4-TanzTotivirusTotiviridae
Maize dwarf mosaic virusMDMVPotyvirusPotyviridae
Maize chlorotic mottle virusMCMVMachlomovirusTombusviridae
Maize pteridovirus 1MPtV-1PteridovirusMayoviridae
Maize streak virusMSVMastrevirusGeminiviridae
Maize yellow dwarf virus RMV2MYDV-RMV2PolerovirusLuteoviridae
Maize yellow mosaic virusMaYMVPolerovirusLuteoviridae
Moroccan watermelon mosaic virusMWMVPotyvirusPotyviridae
Morogoro maize-associated virusMMaVAlphanucleorhabdovirusRhabdoviridae
Ornithogalum mosaic virusOrMVPotyvirusPotyviridae
Ornithogalum virus 3OV-3PotyvirusPotyviridae
Ornithogalum virus 5OV-5PolerovirusLuteoviridae
Panicum ecklonii-associated virusPeaVN/AN/A
Papaya mild mottle-associated virusPaMMVCarlavirusBetaflexiviridae
Papaya mottle-associated virusPaMVCarlavirusBetaflexiviridae
Papaya virus APaVAAllexivirusAlphaflexiviridae
Passiflora virusPVPotyvirusPotyviridae
Peanut mottle virusPeMoVPotyvirusPotyviridae
Pelargonium vein-banding virusPVBVBadnavirusCaulimoviridae
Pepo aphid-borne yellows virusPABYVPolerovirusLuteoviridae
Phaseolus vulgaris alphaendornavirus 1PvEV-1alphaendornavirusEndornaviridae
Phaseolus vulgaris alphaendornavirus 2PvEV-2alphaendornavirusEndornaviridae
Potato Virus YPVYPotyvirusPotyviridae
Plum bark necrosis stem-pitting-associated virusPBNSPaVAmpelovirusClosteroviridae
Pumpkin polerovirusPuPVPolerovirusLuteoviridae
Scallion mosaic virusScaMVPotyvirusPotyviridae
Sorghum mosaic virusSrMVPotyvirusPotyviridae
Southern bean mosaic virusSBMVSobemovirusSolemoviridae
Southern cowpea mosaic virusSCPMVSobemovirusSolemoviridae
Soybean chlorotic blotch virusSbCBVBegomovirusGeminiviridae
Squash chlorotic leaf spot virusSCLSVTorradovirusSecoviridae
Stipagrostis-associated virusSaVN/AN/A
Sudan watermelon mosaic virusSuWMVPotyvirusPotyviridae
Sugarcane mosaic virusSCMPotyvirusPotyviridae
Sugarcane streak Egypt VirusSSEVMastrevirusGeminiviridae
Sugarcane white streak VirusSCWSVMastrevirusGeminiviridae
Sweet potato chlorotic fleck virusSPCFVCarlavirusBetaflexiviridae
Sweet potato chlorotic stunt virusSPCSVCrinivirusClosteroviridae
Sweet potato feathery mottle virusSPFMVPotyvirusPotyviridae
Sweet potato leaf curl virusSPLCVBegomovirusGeminiviridae
Sweet potato leaf curl Sao Paulo virusSPLCSPVBegomovirusGeminiviridae
Sweet potato leaf curl Uganda virusSPLCUVBegomovirusGeminiviridae
Sweet potato mosaic virusSPMVBegomovirusGeminiviridae
Sweet potato pakakuy virusSPPVBadnavirusCaulimoviridae
Sweet potato virus 2SPV2PotyvirusPotyviridae
Sweet potato virus CSPVCPotyvirusPotyviridae
Sweet potato virus GSPVGPotyvirusPotyviridae
Sweet potato symptomless virus 1SPSMV-1MastrevirusGeminiviridae
Telfairia mosaic virusTelMVBegomovirusGeminiviridae
Tobacco mottle virusTMoVUmbravirusTombusviridae
Tomato chlorosis virusToCVCrinivirusClosteroviridae
Tomato leaf curl Uganda virusToLCUVBegomovirusGeminiviridae
Tomato mosaic virusToMVTobamovirusVirgaviridae
Tomato spotted wilt orthotospovirusTSWVOrthotospovirusTospoviridae
Turnip yellows virusTuYVPolerovirusLuteoviridae
Ugandan cassava brown streak virusUCBSVIpomovirusPotyviridae
Ugandan cassava brown streak virus ComorosUCBSV-KMIpomovirusPotyviridae
West African Asystasia virus 1WAAV1BegomovirusGeminiviridae
Yam mosaic virusYMVPotyvirusPotyviridae
Yam virus YYVYN/ABetaflexiviridae.
Zea mays chrysovirus 1ZMCV1AlphachrysovirusChrysoviridae
Zucchini shoestring virusZSSVPotyvirusPotyviridae
N/A: not assigned yet.
Table 2. Summary of published HTS studies conducted in African countries in relations to the detection and diagnosis of plant-infecting viruses.
Table 2. Summary of published HTS studies conducted in African countries in relations to the detection and diagnosis of plant-infecting viruses.
Year !Country #Sequencing PlatformCountry Where HTS Was PerformedNucleic Acid TargetHost PlantPlant-Infecting Virus IdentifiedReferences
2020ZambiaIllumina MiSeqSouth AfricaTotal RNACommon beanSBMV*; BCMNV; BCMV; CABMV; CMV[45]
2020South AfricaIllumina NovaSeqSouth AfricaRibo-depleted RNAJapanese plum (Prunus salicina)PBNSPaV*[46]
2020South AfricaIllumina MiSeqSouth AfricaRibo-depleted RNAOrnithogalum thyrsoidesOrMV; OV-3; OV-5+[47]
2020South AfricaIllumina NextSeqSouth AfricaRibo-depleted RNAivy (Hedera helix)IRSaV+[48]
2020ZimbabweIllumina HiSeqSouth AfricaRibo-depleted RNADendranthema morifoliumTSWV[49]
2020ZimbabweIllumina HiSeqSouth AfricaRibo-depleted RNAZucchiniZSSV*[50]
2020KenyaIllumina MiSeqKenyaGenomic DNATomatoCpCDV-T+[51]
2020KenyaIllumina MiSeqKenyamRNAPapayaMWMV*; CPMMV*; PaMV+ PMMaV+[52]
2020KenyaIllumina HiSeqSouth AfricaRibo-depleted RNAPapayaMWMV; PaVA+[53]
2020Kenya; Rwanda; Tanzania; UgandaIllumina MiSeqKenyamRNASweet potatoSPFMV[54]
2020RwandaIllumina MiSeqUSARibo-depleted RNAMaizeMCMV; SCMV; MSV; MYDV-RMV2; MYDV-like; MaYMV; BYDV; MATV+; MPtV-1+; ZMCV1*; MaBV+[55]
2019TanzaniaIllumina MiSeqKenyaTotal RNAMaizeMCMV; SCMV; MSV; MYDV-RMV; BYDV; MDMV; SrMV[56]
2019TanzaniaIllumina HiSeqSouth AfricaRibo-depleted RNAMaizeMaPV+; MCMV; MSV; MaYMV[57]
2019TanzaniaIllumina HiSeqSouth AfricaRibo-depleted RNAMaizeMATV-1-Tanz*; MATV-4-Tanz+;[58]
2019TanzaniaIllumina HiSeqSouth AfricaRibo-depleted RNAMaizeMMaV+; MCMV; MaYMV[59]
2019TanzaniaIllumina HiSeqSouth AfricaRibo-depleted RNAMaizeMaYMV*; MCMV[60]
2019South AfricaIllumina HiSeqSouth AfricaRibo-depleted RNATomatoToCV; Other viruses not mentioned[61]
2019South AfricaIllumina MiSeqSouth AfricaRibo-depleted RNA; RCA dsDNASweet potatoSPFMV; SPVG; SPVC; SPV2; SPLCSPV; SPMV[62]
2019South Africa454 pyrosequencingUSAVANAArctopus echinatus; Lolium perenne; Panicum ecklonii; Stipagrostis sp.AeaV; SaV; PeaV; LpaV[63]
2019ZimbabweIllumina HiSeqSouth AfricaRibo-depleted RNAGarlicIYSV[64]
2019MozambiqueIllumina MiSeqSouth AfricaRibo-depleted RNACassavaCBSV; UCBSV[65]
2019ComorosIllumina HiseqSwitzerlandsiRNAs; VANA; dsRNAsCassavaUCBSV-KM+; CBSV*[66]
2019SudanIllumina MiSeqSwitzerlandsmall RNAsCucurbitCVYV[67]
2019KenyaIllumina MiSeqKenyaRibo-depleted RNAPumpkinPuPV+; MWMV[68]
2019KenyaIllumina MiSeqKenyaTotal RNAGroundnutGRAV; Other viruses not mentioned[69]
2019KenyaIllumina MiSeqKenyamRNACommon beanBCMNV[70]
2019KenyaIllumina HiSeqSouth KoreaRCA dsDNACommon beanPVBV*; BCMNV[71]
2019KenyaIllumina HiSeqSouth KoreaRibo-depleted RNACommon bean; CowpeaBCMNV; CABMV[72]
2019KenyaIllumina MiSeqKenyaRibo-depleted RNAPassion fruitCABMV[73]
2019UgandaIllumina MiSeqKenyaRibo-depleted RNATannia (Xanthosoma sp.)CMV*[74]
2019UgandaIllumina MiSeqKenyaTotal RNAPassion fruitPV+[75]
2019NigeriaIllumina HiSeqUKTotal RNADioscorea rotundata (Yam)YMV+; DBRTV3-[2RT]+; DBRTV3-[3RT]+[76]
2019Nigeria; GhanaIllumina HiSeqUKTotal RNADioscorea rotundataYVY+; YMV; DMaV; Yam badnavirus[77]
2018ZimbabweIllumina MiSeqSouth AfricaRibo-depleted RNATomatoToMV[78]
2018South AfricaIllumina MiSeqSouth AfricaRCA dsDNASweet PotatoSPLCV+; SPLCSPV; SPMV[79]
2018South AfricaIllumina MiSeqSouth AfricaRibo-depleted RNA; RCA dsDNASweet potatoSPCSV; SPFMV; SPVC; SPVG; SPMV; SPLCSPV[80]
2018South AfricaIllumina MiSeqSouth AfricasiRNAsSweet potatoSPPV*[81]
2018KenyaIllumina HiseqSouth KoreaRibo-depleted RNASweet potatoSPCFV; SPFMV; SPVC; SPCSV[82]
2018KenyaIllumina HiseqSouth KoreaRibo-depleted RNAGroundnutGRV[83]
2018KenyaIllumina MiSeqKenyaTotal RNACommon beanPvEV-1+; PvEV-2+ BCMNV, CMV[84]
2018UgandaIllumina MiSeqKenyamRNACowpeaCABMV[85]
2018TanzaniaIllumina HiSeqSwitzerlandsiRNAsCommon BeanUmbraviruses+; ToLCUV*; PeMoV; BnYDV; TMmV SBMV*; BCMNV; BCMV; PvEV-1; PvEV-2; CpMMV; CMV; CABMV[86]
2018Uganda; Kenya; Rwanda; TanzaniaIllumina HiseqUSAmRNAMaizeMYDV-like polerovirus*; East African JGMV; SCMV; MCMV [87]
2018KenyaIllumina MiSeqKenyaTotal RNAMaize; Sorghum; Napier grassHubei Poty-like virus 1; BVG; ScaMV; MCMV; SCMV; MSV; MYDV-RMV; JGMV[88]
2018Côte d’Ivoire; GhanaIllumina HiSeq Illumina MiSeqFranceRCA dsDNACacaoCSSCEV+; CSSGMV+; CSSGNV+; CSSGQV+; CSSGRV+; CSSV; CSSTAV; CSSCDV[89]
2017Benin; MaliIllumina MiSeqGermanyRibo-depleted RNASolanum aethiopicum; Pepper (Capsicum spp.)AeYV+[90]
2017MalawiIllumina MiSeqGermanyRibo-depleted RNACassavaUCBSV[91]
2017TanzaniaIllumina HiSeqSwitzerlandsiRNAsCommon beanPvEV-1; PvEV-2; CPMMV[92]
2017SudanIllumina HiSeqSwitzerland.siRNAsCucumberSuWMV+[93]
2017South AfricaIllumina HiSeqSouth AfricaRibo-depleted RNAZucchiniPABYV+[94]
2017South AfricaIllumina HiSeqSouth AfricaRibo-depleted RNAPotatoPVY[95]
2016South AfricaIllumina HiSeqSouth AfricaTotal RNACabbageTuYV*[96]
2016South AfricaIllumina HiSeqSouth AfricaRibo-depleted RNAPattypan; ZucchiniZSSV+; MWMV[97,98]
2016SudanIllumina HiSeqSwitzerlandsiRNAsSquashSCLSV+[99]
2016SudanIllumina HiSeqSwitzerlandsiRNAsWild cucurbitCocMoV[100]
2016Cameroon; TogoIllumina HiSeqUSARCA dsDNACassavaSbCBV*; WAAV1*; ACMV[101]
2016CameroonIllumina MiSeqUSARCA dsDNAPumpkinTelMV+[102]
2016BeninIllumina MiSeqUSARCA dsDNACottonCYMV+[103]
2016Burkina Faso454 pyrosequencingUSAVANACowpeaCPPV-1+; CPPV-2+; CPTV-1+; CPTV-2+; CPaMV-1+; SCPMV*; BCMV-BlCM; CPMoV; CABMV [104]
2015South AfricaIllumina HiSeqSouth AfricadsRNAsGrapevineGLRaV-3 isolate GH24[105]
2015South AfricaIllumina HiSeqSouth AfricadsRNAsGrapevineGVF; GLRaV-3[106]
2015TanzaniaIllumina MiSeqKenyaRibo-depleted RNACassavaCBSV; UCBSV+[107]
2015EthiopiaIllumina MiSeq Illumina HiSeqUKTotal RNAMaizeMCMV*; SCMV[108]
2014RwandaIllumina MiSeqUKTotal RNAMaizeMCMV*; SCMV*[109]
2014TanzaniaIllumina HiSeqSwitzerlandsiRNAsSweet potatoSPPV; SPSMV-1; SPLCUV; SPCSV; SPFMV; SPLCSPV+; SPCFV[110]
2014EgyptIllumina HiSeq; Roche 454 GS FLX TitaniumUSAsiRNAs; VANASugarcaneSSEV; SCWSV+[111]
2013KenyaRoche 454 GS-FLX+UKTotal RNA; dsRNAsMaizeMCMV*; SCMV[112]
2012South AfricaIllumina HiSeqSouth AfricadsRNAsGrapevine.GEEV+[113]
2010Uganda; TanzaniaRoche
UKTotal RNACassavaCBSV; UCBSV[114]
2010South Africa.IlluminaSouth AfricadsRNAsGrapevineGVE+; GRSPaV; GVA; GLRaV-3[115]
!: Year of publication of the study; #: Country where the study was conducted or where the studied material originated from; *: First report of the virus in the respective country; +: Novel or previously unknown strain or species; RCA dsDNA: Rolling circle amplification double stranded DNA; siRNAs: virus-derived small interfering RNAs; VANA: Virion-associated nucleic acid; dsRNAs: Double-stranded RNAs.
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Ibaba, J.D.; Gubba, A. High-Throughput Sequencing Application in the Diagnosis and Discovery of Plant-Infecting Viruses in Africa, A Decade Later. Plants 2020, 9, 1376.

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Ibaba JD, Gubba A. High-Throughput Sequencing Application in the Diagnosis and Discovery of Plant-Infecting Viruses in Africa, A Decade Later. Plants. 2020; 9(10):1376.

Chicago/Turabian Style

Ibaba, Jacques Davy, and Augustine Gubba. 2020. "High-Throughput Sequencing Application in the Diagnosis and Discovery of Plant-Infecting Viruses in Africa, A Decade Later" Plants 9, no. 10: 1376.

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