Molecular identification and phylogenetic characterization of A-strain isolates of Maize streak virus from western Ethiopia

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Previous studies have described different MSV strains of economic importance from southern and eastern African countries, and how eastern African regions are hubs for MSV diversification. Despite these efforts, and lack of extensive sampling, there is limited knowledge about the MSV-A diversity in Ethiopia. Here, field sampling of maize plants and wild grasses with visible MSD symptoms were carried out in western Ethiopian regions of Gambela, Oromia, and Benishangul-Gumuz, during the maize growing season of 2019. The complete genomes of MSV isolates (n = 60) were cloned and Sanger sequenced. We use a model based phylogenetic approach to analyse 725 full MSV genome sequences available in the GenBank together with newly recovered genomes from Ethiopia to determine their subtypes and recombinant lineages. Of the 127 fields accessed, MSD prevalence was highest at 96% in Gambela region, and lowest in Oromia at 66%. Highest mean symptom severity of 4/5, (where 5 is the highest and 1 the lowest) was observed for both Gambela and Benishangul-Gumuz. Our results show that these newly determined MSV isolates belong in the recombinant lineage V of the A 1 subtype with the widest dissemination, and economic significance in the sub-Saharan Africa and the adjacent Indian Ocean islands. Figures Figure 1 Figure 2 Main Text Maize streak virus strain A (MSV-A) (species Maize streak virus ; genus Mastrevirus , family Geminiviridae) is the causal agent of maize streak disease (MSD) in maize plant. In sub-Saharan Africa this disease is of economic importance to large, small, and subsistence scale farmers, because in epidemic years the infection by the virus can cause complete yield loss [1–3]. Infected maize plants display characteristic chlorotic streaks on their leaves, are severely stunted, have low yields and occasionally die [4–6]. The epidemiology and spread of MSV-A is complex and is strongly dependent on the behaviours and population dynamics of the leafhopper species Cicadulina sp . that transmits it. [2, 7–9]. Ethiopia in East Africa, is a large country with suitable climatic conditions for cultivating temperate and tropical crops such as maize, millet, teff, cotton, wheat, potatoes and enset [10–12]. Within Ethiopia, maize is grown primarily in the southern, southwestern and western regions [13–15]. With respect to other cultivated cereals dating back to the 1980s, maize has been the most cultivated per hectare and the country has had a historical dependence on it for food and economic purposes. As a consequence of this, Ethiopia has since experienced on average annual increase in maize production of 7.60% between 1980 and 2020 [16]. During the emergence and spread of MSV throughout continental Africa from the 1920s through to the 1970s, at least five MSV-A subtypes-MSV-A 1 , -A 2 , -A 3 , -A 4 , and -A 6 have emerged, each differing in virulence, and geographical range [6, 17–19]. Since the 1970s East Africa has become both the primary hub of trans-continental MSV-A movements, and this region is also the primary hotspot of MSV-A diversification i.e., it is the present cradle of the virus [19–21]. Within East Africa, the Ugandan and Kenyan regions around Lake Victoria appears to be the primary sources of new MSV-A variants whereas the rift valley and coastal regions of Kenya are sinks of MSV-A diversity [21]. Being a major viral disease of maize in East Africa including Ethiopia [22], little is known about the roles of other East African countries such as Ethiopia due to sparse sampling and sequencing of MSV-A variants in the genesis and dissemination of new MSV-A variants. Here, we assessed MSV-A prevalence in western Ethiopia by field sampling, cloning and sequencing isolates, and performing phylogenetic analyses using nucleotide sequences from this survey together with those available in GenBank in order to properly classify these new isolates. A total of 105 symptomatic leaves that included one or more leaves samples per plant were sampled during the 2019 planting season in western Ethiopia from maize plants showing streak symptoms as part of an epidemiological survey. From these 60 samples were identified as positive for MSV-A from which complete MSV genomes were determined. Visual assessment based on characteristic symptoms described by Mesfin et al . [23] and Shepherd et al . [2] to have been associated with MSV infections in maize were used to determine disease incidence and severity in the field. Disease prevalence was determined as the number of fields where a particular disease was recorded in relation to the number of fields sampled from surveyed regions. MSD incidence was determined by visually observing and recording the number of maize plants showing the disease symptoms and we calculated the percentage incidence as: We assessed disease severity as the area of plant tissue affected by disease, expressed as a percentage of the total area at regular intervals using a 1–5 scale [24]. Circular DNA from total plant DNA extracts was enriched using phi29 DNA polymerase (TempliPhi; GE Healthcare) as described by Shepherd et al [25]. Amplified genome concatemers were digested with BamHI to yield linearized viral genomes (~2.7kb) which were ligated into pUC19 (New England Biolabs) restricted with BamHI. The cloned genomes were Sanger sequenced at Macrogen Inc (South Korea) by primer walking. Viral genome sequences were assembled and edited using Geneious Prime (version 2020.2.4; Biomatters Limited, New Zealand). The 60 MSV-A isolate sequences from Ethiopia were aligned with an additional 665 MSV-A sequences including 182 non-MSV-A sequences (representing strains of MSV-B through -K) that were publicly available in GenBank using MUSCLE [26]. The resulting alignment was further edited by visual inspection in Aliview [27]. This MSV full genome alignment was analysed for recombination using RDP version 4.46 [28] to obtain a recombinant-free, MSV-A only dataset (n = 725) that was subsequently used for downstream phylogenetic inference. Screening for recombinants was accomplished using the default RDP settings and removing all evidence of recombination within the alignment by identifying recombinant sequence fragments and removing these by replacing these sequence tracts with the standard “gap” characters, “-“ with no changes to the alignment of the retained nucleotides. We used jModeltest version 2.1.10 [29] implemented on the CIPRES server at http://phylo.org [30] to determine the best-fitting nucleotide substitution model for the MSV-A dataset and then constructed a maximum likelihood (ML) tree for the MSV-A dataset using IQ-TREE version 1.6.12 [31]. Branch supports in the tree were determined using 2000 replicates of non-parametric Shimodaira-Hasegawa-like approximate likelihood ratio tests (SH-aLRT) [32, 33] as well as 5000 ultrafast bootstrap replicates [34]. The recombinant lineages of these MSV-A isolates were determined based on the methods previously described by Martin et al [6], and Monjane et al [20]. A total of 127 maize fields were visited, from these 100 maize, and five grass samples with MSD-like symptoms were collected. The newly determined 60 genomes from these Ethiopian samples all are MSV-A variants based on relatedness to previously determined MSV-A. Frequently encountered MSD-like symptoms associated with MSV infection are: broken to continuous chlorotic streaks on the leaf veins uniformly distributed across the leaf surface, pale yellow streaks, mosaic and chlorosis on leaf lamellae, broken or longitudinal chlorotic streaks along leaf veins, wilting and drying of leaf margins, necrosis and mottling on the entire plant (Fig. 1). Out of 127 maize fields visited, based on MSD-like symptoms, the disease was prevalent in 98 (77%) fields assessed. The overall mean prevalence of MSD were 96% and 93% in Gambela and Benishangul Gumez regions for 22 and 25 fields respectively, while in Oromia region, mean prevalence of 66% was observed (Table 1). Mean prevalence assessment for Gambela zones of Anuak and Nuer were 93% and 100%, respectively. Of the four Oromia zones of Jimma, Buno Bedele, East and West Wellega, MSD mean prevalence were 64%, 0%, 65% and 85%, respectively. Other than Buno Bedele, where the disease was not identified, MSD was prevalent in three Oromia zones surveyed, the highest prevalence being recorded in West Wellega. The prevalence of MSD was also assessed from Asossa zone of Benishangul-Gumez region where the mean prevalence recorded was 93%. Likewise, MSD incidence was also higher in Gambella, followed by Benishangule-Gumuz and Oromia, where the mean incidences of up to 64% in Gambela, 59% in Benishangul Gumez, and 33% in Oromia regions were recorded (Table 1). Of the surveyed areas in Gambela region, we recorded higher incidences of MSD in Anuak and Nuer zone. In Oromia, low incidences of MSD were observed in Buno Bedele, and Jimma zones, unlike the East and West Wellega zones with relatively higher incidences (Table 1). The severity of MSD was significantly higher in Gambela and Benishangul-Gumz compared to Oromia region. The severity score of MSD was higher in Anuak, Nuer and Asosa zones unlike the relatively low severity recorded in Jimma, East and West Wolega zones. No disease was recorded in Buno Bedele zone of the surveyed regions, the highest severities of 4 to 5 (on 1-5 scoring scale) were recorded in Gambella followed by Benishangule-Gumuz and Oromia regions (Table 1). These MSV isolates from western Ethiopia all belong to recombinant lineage V of the MSV-A 1 subtype (Fig 2A). They share about 98% sequence similarity with MSV-A 1 isolates from Kenya [21] and Rwanda [35]. Here, we used the best fitting DNA substitution model GTR+I+G4 for the MSV-A (n=725) alignment as previously posited by Mojane et al [20], and Harkins et al [21]. GTR is the empirical DNA model of Tavare [36], which allows unequal rates for all six of the possible reversible nucleotide substitutions and unequal base frequencies, with I representing the proportion of invariant sites and G4 the discrete Gamma model of Yang [37] with four rate categories. The best majority-rule consensus ML trees inferred from the MSV-A dataset is presented in Fig 2. Our results show that MSD disease incidence, prevalence, and severity were highest in Gambela region followed by Benishangule-Gumuz and Oromiya regions, respectively (Table 1). Variations exist in the level of disease prevalence and incidence in different altitude ranges assessed. Relatively higher prevalence and incidence were recorded at lower altitudes ranging from 400-1500 metres above sea level and vice versa at higher altitudes ranging from 1800-2400 metres above sea level. For instance, the disease incidence was higher in Benishangul-Gumuz and Gambela regions at locations of 400 to 1600 metres above sea level, while none was recorded in Buno Bedele zone with altitudes ranging from 1500-2200 (Table 1). This could be attributed to warmer climates in these lower altitudes areas that favour vector populations for virus transmission, resulting in more severe disease symptoms development [40]. These findings support those previously reported by Mesfin et al. [10] that exceptionally high MSD outbreak occurred in Gambela region during the 1986 cropping season, and that regions in the West other than Gambela were also affected. MSD prevalence in these regions has also been linked to higher population density of Cicadulina sp. especially C. mbila found mainly at these lower altitude regions [10]. This implies that the altitude ranges that support insect vectors may play a key role in determining MSD distribution and prevalence [38]. Earlier, similar findings in Ethiopia reported the distribution and importance of MSD in other parts of the country [14, 39]. The high disease incidence detected in the field is expected to cause a considerable reduction in yield and quality. In highly susceptible and late sown genotypes, MSD can cause up to 100% yield losses in infected crops [41–43]. Recent report showed that MSD incidence of up to 58% was also found in Ethiopian maize germplasm [14]. In this case, maximum likelihood trees are useful for classifying newly sequenced economically important MSV-A isolates genomes into subtype and recombinant lineages. Based on degree of virulence, host range, geographical clustering, and phylogenetic evidence [6, 19] MSV-A has been previously grouped into subtypes and recombinant lineages. Subtypes share greater than 98% sequence similarity [6, 44]. For MSV-A, five subtypes (MSV-A 1 , MSV-A 2 , MSV-A 3 , MSV-A 4 and MSV-A 6 ) have been identified. Monjane et al . [19] has grouped MSV-A variants into 24 recombinant lineages, 16 (MSV-A 1 I to MSV-A 1 XVI) of which contained predominantly MSV-A 1 sequences. Of all the MSV-A subtypes, it appears that MSV-A 1 has the widest distribution throughout continental Africa and is also found on Madagascar and the Comoros islands [6, 19]. Furthermore, the endemic nature of MSV-A in Ethiopia, like other countries in the sub-Saharan Africa, and the further exacerbation by importations from bordering countries, may play a role in MSV-A spread. Informal trades, formal trades, and porous borders may also significantly impact MSV-A disseminations. This study has further provided information on MSV-A diversity in the East African countries. Declarations Funding KAO was supported by the National Research Foundation (NRF) South Africa and The World Academy of Science (TWAS) grant number 105461. The funders neither had roles in study design, data collection and interpretation nor in the decision to submit the work for publication. Acknowledgements The authors would like to express sincere gratitude to Mr. Tolcha Tufa for developing map of surveyed areas. The facilitation and support provided by Associate Professor Darren Martin in getting samples tested at the University of Cape Town in South Africa deserve our special appreciation. Compliance with ethical standards None required Conflict(s) of interest All authors have declared non-existent conflict of interest References 1. Charles K (2014) Maize streak virus: A review of pathogen occurrence, biology and management options for smallholder farmers. African J Agric Res 9:2736–2742. https://doi.org/10.5897/AJAR2014.8897 2. Shepherd DN, Martin DP, Van Der Walt E, et al (2010) Maize streak virus: an old and complex “emerging” pathogen. Mol Plant Pathol 11:1–12. https://doi.org/10.1111/j.1364-3703.2009.00568.x 3. Martin DP, Shepherd DN (2009) The epidemiology, economic impact and control of maize streak disease. Food Secur 1:305–315. https://doi.org/10.1007/s12571-009-0023-1 4. Martin DP, Willment J a, Rybicki EP (1999) Evaluation of Maize Streak Virus Pathogenicity in Differentially Resistant Zea mays Genotypes. Phytopathology 89:695–700. https://doi.org/10.1094/Phyto.1999.89.8.695 5. Pinner MS, Markham PG, Markham RH, Dekker L (1988) Characterization of maize streak virus: description of strains; symptoms. Plant Pathol 37:74–87. https://doi.org/10.1111/j.1365-3059.1988.tb02198.x 6. Martin DP, Willment JA, Billharz R, et al (2001) Sequence diversity and virulence in Zea mays of Maize streak virus isolates. Virology 288:247–55. https://doi.org/10.1006/viro.2001.1075 7. Magenya OEV, Mueke J, Omwega C (2008) Significance and transmission of maize streak virus disease in Africa and options for management: A review. African J Biotechnol 7:4897–4910. https://doi.org/10.4314/ajb.v7i25.59697 8. Lefeuvre P, Martin DP, Elena SF, et al (2019) Evolution and ecology of plant viruses. Nat Rev Microbiol 1–13. https://doi.org/10.1038/s41579-019-0232-3 9. Reynaud B, Peterschmitt, M. (1992) A study of the mode of transmission of maize streak virus by Cicadulina mbila using an enzyme‐linked immunosorbent assay. Ann Appl Biol 121:85–94. https://doi.org/10.1111/j.1744-7348.1992.tb03989.x 10. Mesfin T, Den Hollander J, Markham PG (1991) Cicadulina species and maize streak virus in Ethiopia. Trop Pest Manag 37:240–244. https://doi.org/10.1080/09670879109371592 11. Abraham A (2019) Emerged Plant Virus Disease in Ethiopian Agriculture : Causes and Control Options. Ethiop J Agric Sci 29:39–55 12. Deribe K, Meribo K, Gebre T, et al (2012) The burden of neglected tropical diseases in Ethiopia, and opportunities for integrated control and elimination. Parasit Vectors 5:240. https://doi.org/10.1186/1756-3305-5-240 13. Bjarnason M (1986) Progress in breeding for resistance to the maize streak virus disease. A Proc first Eastern, Cent South Africa Reg maize Work Lusaka, Zambia, March 10-17 1985 14. Guadie D, Tesfaye K, Knierim D, et al (2019) Molecular analysis of maize (Zea mays L.)-infecting mastreviruses in Ethiopia reveals marked diversity of virus genomes and a novel species. Virus Genes 55:339–345. https://doi.org/10.1007/s11262-019-01655-1 15. Dawit A, Chilot Y, Adam B, Agajie T (2014) Situation and Outlook of Maize in Ethiopia of Maize in Ethiopia 16. Knoema (2020) Ethiopia - Maize production quantity. In: https://knoema.com/atlas/Ethiopia/topics/Agriculture/Crops-Production-Quantity-tonnes/Maize-production 17. Harkins GW, Martin DP, Duffy S, et al (2009) Dating the origins of the maize-adapted strain of maize streak virus, MSV-A. J Gen Virol 90:3066–3074. https://doi.org/10.1099/vir.0.015537-0 18. Owor BE, Martin DP, Shepherd DN, et al (2007) Genetic analysis of maize streak virus isolates from Uganda reveals widespread distribution of a recombinant variant. J Gen Virol 88:3154–3165. https://doi.org/10.1099/vir.0.83144-0 19. Monjane AL, Harkins GW, Martin DP, et al (2011) Reconstructing the History of Maize Streak Virus Strain A Dispersal To Reveal Diversification Hot Spots and Its Origin in Southern Africa. J Virol 85:9623–9636. https://doi.org/10.1128/JVI.00640-11 20. Varsani A, Shepherd DN, Monjane AL, et al (2008) Recombination, decreased host specificity and increased mobility may have driven the emergence of maize streak virus as an agricultural pathogen. J Gen Virol 89:2063–2074. https://doi.org/10.1099/vir.0.2008/003590-0 21. Pande D, Madzokere E, Hartnady P, et al (2017) The role of Kenya in the trans-African spread of maize streak virus strain A. Virus Res 232:69–76. https://doi.org/10.1016/J.virusres.2017.02.005 22. Keno T, Azmach G, Wegary D, et al (2018) African Journal of Agricultural Research Major biotic maize production stresses in Ethiopia and their management through host resistance. 13:1042–1052. https://doi.org/10.5897/AJAR2018.13163 23. Mesfin T, Den Hollander J, Markham PG (1995) Feeding activities of Cicadulina mbila (Hemiptera: Cicadellidae) on different host-plants. Bull Entomol Res 85:387–396. https://doi.org/10.1017/S0007485300036129 24. D. B, E. A-B, K. AF, et al (2018) Incidence and severity of maize streak disease: The influence of tillage, fertilizer application and maize variety. African J Agric Res 13:551–560. https://doi.org/10.5897/ajar2017.12873 25. Shepherd DN, Martin DP, Lefeuvre P, et al (2008) A protocol for the rapid isolation of full geminivirus genomes from dried plant tissue. J Virol Methods 149:97–102. https://doi.org/10.1016/j.jviromet.2007.12.014 26. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340 27. Larsson A (2014) AliView: A fast and lightweight alignment viewer and editor for large datasets. Bioinformatics 30:3276–3278. https://doi.org/10.1093/bioinformatics/btu531 28. Martin DP, Murrell B, Golden M, et al (2015) RDP4: Detection and analysis of recombination patterns in virus genomes. Virus Evol 1:1–5. https://doi.org/10.1093/ve/vev003 29. Darriba D, Taboada GL, Doallo R, Posada D (2012) jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9:772. https://doi.org/10.1038/nmeth.2109 30. Miller MA, Pfeiffer W, Schwartz T (2010) Creating the CIPRES Science Gateway for Inference of Large Phylogenetic Trees 31. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ (2015) IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. Mol Biol Evol 32:268–274. https://doi.org/10.1093/molbev/msu300 32. Guindon S, Dufayard J-F, Lefort V, et al (2010) New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst Biol 59:307–321. https://doi.org/10.1093/sysbio/syq010 33. Shimodaira H, Hasegawa M (1999) Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference. Mol Biol Evol 16:1114–1116. https://doi.org/10.1093/oxfordjournals.molbev.a026201 34. Hoang DT, Chernomor O, von Haeseler A, et al (2018) UFBoot2: Improving the Ultrafast Bootstrap Approximation. Mol Biol Evol 35:518–522. https://doi.org/10.1093/molbev/msx281 35. Asiimwe T, Stewart LR, Willie K, et al (2020) Maize lethal necrosis viruses and other maize viruses in Rwanda. Plant Pathol 69:585–597. https://doi.org/10.1111/ppa.13134 36. Tavare S (1986) Some probabilistic and statistical problems in the analysis of DNA sequences. Some Math Quest Biol / DNA Seq Anal Ed by Robert M Miura 37. Yang Z (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods. J Mol Evol 39:306–314. https://doi.org/10.1007/BF00160154 38. Magenya OE V, Mueke J, Omwega C (2009) Association of maize streak virus disease and its vectors (Homoptera: Cicadelidae) with soil macronutrients and altitudes in Kenya 39. Lencho A, Abraham A, … BB-PMJ, 1997 undefined Identification of viruses from maize and grass hosts. agris.fao.org 40. Redinbaugh MG, Zambrano JL (2014) Control of Virus Diseases in Maize 41. Alegbejo MD, Olojede SO, Kashina BD, Abo ME (2002) Maize streak mastrevirus in Africa: Distribution, transmission, epidemiology, economic significance and management strategies. J Sustain Agric 19:35–45. https://doi.org/10.1300/J064v19n04_05 42. Kyetere DT, Ming R, McMullen MD, et al (1999) Genetic analysis of tolerance to maize streak virus in maize. Genome 42:20–26. https://doi.org/10.1139/g98-099 43. Lagat M, Danson J, Kimani M, Kuria A (2008) Quantitative trait loci for resistance to maize streak virus disease in maize genotypes used in hybrid development. African J Biotechnol 7:2573–2577 44. Fauquet CM, Briddon RW, Brown JK, et al (2008) Geminivirus strain demarcation and nomenclature. Arch Virol 153:783–821. https://doi.org/10.1007/s00705-008-0037-6 Table 1 Table 1: Mean prevalence, incidence, and severity of maize streak disease across study area during the 2019 main cropping season Region Zone Altitude range (MASL) NFA NFI Prevalence (%) Incidence (%) Severity(1-5 scale) Gambela Anuak 400-600 14 13 93 64 4 Nuer 400-500 9 9 100 64 4.5 Mean 23 22 96 64 4 Oromia Jimma 1300-2100 25 16 64 28 2 East Wellega 1300-2200 20 13 65 33 3 West Wellega 1200-2000 25 22 88 46 3 Buno Bedele 1500-2200 7 0 0 0 0 Mean 77 51 66 33 3 Benishangul- Gumuz Asosa 1100-1700 27 25 93 59 4 Grand mean for prevalence 127 98 77 NFA- Number of fields assessed NFI- Number of fields infected MASL- Metres above sea level Cite Share Download PDF Status: Under Review Version 2 posted Reviewers agreed at journal 29 Aug, 2022 Reviewers invited by journal 29 Aug, 2022 Editor assigned by journal 27 Aug, 2022 First submitted to journal 26 Aug, 2022 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1815287","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":132490623,"identity":"635685fe-9860-4567-922e-e49b32f622e7","order_by":0,"name":"Daniel Ketsela","email":"","orcid":"","institution":"Ethiopian Institute of Agricultural Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Ketsela","suffix":""},{"id":132490624,"identity":"9141877a-7f7e-43fc-974a-5008faa0f5bf","order_by":1,"name":"Kehinde Adewole Oyeniran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYLCCBCCWYOBhOMDAxiAHEjjwgBQtxmAtCcTYBNLCANSS2AAzBBfgl0g+9uDhHrs8yfbeg4cLymzS54cdfgi0xU5OtwG7FskZaekGCc+Si6V5ziUcnnEuLXfj7TQDoJZkY7MD2LUY3Mgxk0g4wJw4TyLH4DBv2+HcjbMTQFoOJG7DqSX/G1BLfeI8+TcgLf/TDWenfyCgJYcNqOVw4mwJHpCWAwny0jn4bZHseQZy2PHEmT1Ah/GcSzbcIJ1TcCDBALdf+NmTn0n+OFCdOOP4GePPPGV28vKz0zd/+FBhJ4dLC4NAArpTwSoNcCgHW4NulnwDHtWjYBSMglEwIgEAahJmKr5zlQIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-1754-6184","institution":"UCT IDM: University of Cape Town Institute of Infectious Disease and Molecular Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kehinde","middleName":"Adewole","lastName":"Oyeniran","suffix":""},{"id":132490625,"identity":"b7381c5c-9dc4-45d6-ac7f-28c32151cbd2","order_by":2,"name":"Berhanu Bekele","email":"","orcid":"","institution":"EIAR: Ethiopian Institute of Agricultural Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Berhanu","middleName":"","lastName":"Bekele","suffix":""},{"id":132490626,"identity":"693fadb7-f534-4215-866e-8a8a13cf6e1b","order_by":3,"name":"Rafaela S Fontenele","email":"","orcid":"","institution":"NIH: National Institutes of Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rafaela","middleName":"S","lastName":"Fontenele","suffix":""},{"id":132490627,"identity":"79335f76-0e13-4887-9604-6f0c06e994d7","order_by":4,"name":"Simona Kraberger","email":"","orcid":"","institution":"Arizona State University Biodesign Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Simona","middleName":"","lastName":"Kraberger","suffix":""},{"id":132490628,"identity":"64558786-56be-4f37-a119-779c66a7f8ed","order_by":5,"name":"Arvind Varsani","email":"","orcid":"","institution":"Arizona State University Biodesign Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Arvind","middleName":"","lastName":"Varsani","suffix":""}],"badges":[],"createdAt":"2022-07-01 11:10:42","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-1815287/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-1815287/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":26704860,"identity":"192b84e1-798e-49e6-8f1b-057d8d3381d8","added_by":"auto","created_at":"2022-09-20 12:21:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":864779,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Spatial distribution of \u003cem\u003eMaize streak virus\u003c/em\u003e in surveyed regions of Ethiopia, 2019 main cropping season (B) Different \u003cem\u003eMaize streak virus\u003c/em\u003e symptoms associated with infected plants: (i) uninfected plant (control), (ii) light streaking on old leaves (mild infection); (iii) moderate streaking on old and young leaves, slight stunting (severe infection); (iv) severe streaking on about 60-75% of leaf area, plants stunt (severe infection); (v-viii) severe streaking on more than 75% leaf area, plants either stunt severely or die.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1815287/v2/c9ea7b0ef931f82d2e2f839a.jpg"},{"id":26704861,"identity":"8de1ec4d-57d7-4cab-bcbc-0e569fdd4769","added_by":"auto","created_at":"2022-09-20 12:21:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":323709,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood phylogeny trees constructed using the best fit model GTR+I+G4. The bar indicates the number of nucleotide substitutions per site. (A) MSV-A phylogeny (n=725) was rooted using the Reunion and Mauritius isolates as outgroups and coloured according to countries of sampling origin and labelled with their International Organization for Standardization (ISO) two-letter codes as: Burkina Faso [BF], Benin [BJ], Central African Republic [CF], Ethiopia [ET], Ghana [GH], Kenya [KE], Comoros [KM], Lesotho [LS], Madagascar [MG], Mauritius [MU], Mozambique [MZ], Nigeria [NG], Reunion Island [RE], Rwanda [RW], Chad Republic [TD], Tanzania [TZ], Uganda [UG], South Africa [ZA], Zambia [ZM], and Zimbabwe [ZW]. (B) Phylogenetic tree (n= 111) for full 51 mastrevirus reference genomes available in the GenBank, and 60 MSV-A isolates in this study. Numbers shown on major nodes are bootstrap supports from 5000 ultrafast replicates. Species/strain names on the tree include GenBank accession numbers, isolates from this study are presented in bold blue font.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1815287/v2/286400607e74b7473216699b.png"},{"id":26704863,"identity":"f81c4686-0f56-4447-88c0-4d221db1947b","added_by":"auto","created_at":"2022-09-20 12:22:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":738547,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1815287/v2/0e3b0b02-c117-47ba-85cb-fcd6df354ea5.pdf"}],"financialInterests":"","formattedTitle":"Molecular identification and phylogenetic characterization of A-strain isolates of Maize streak virus from western Ethiopia","fulltext":[{"header":"Main Text","content":"\u003cp\u003eMaize streak virus strain A (MSV-A) (species \u003cem\u003eMaize streak virus\u003c/em\u003e; genus \u003cem\u003eMastrevirus\u003c/em\u003e, \u0026nbsp;family \u003cem\u003eGeminiviridae)\u003c/em\u003e is the causal agent of maize streak disease (MSD) in maize plant. In sub-Saharan Africa this disease is of economic importance to large, small, and subsistence scale farmers, because in epidemic years the infection by the virus can cause complete yield loss\u0026nbsp;[1\u0026ndash;3]. Infected maize plants display characteristic chlorotic streaks on their leaves, are severely stunted, have low yields \u0026nbsp;and occasionally die\u0026nbsp;[4\u0026ndash;6]. The epidemiology and spread of MSV-A is complex and is strongly dependent on the behaviours and population dynamics of the leafhopper species \u003cem\u003eCicadulina\u0026nbsp;\u003c/em\u003esp\u003cem\u003e.\u0026nbsp;\u003c/em\u003ethat transmits it.\u0026nbsp;[2, 7\u0026ndash;9].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthiopia in East Africa, is a large country with suitable climatic conditions for cultivating temperate and tropical crops such as maize, millet, teff, cotton, wheat, potatoes and enset\u0026nbsp;[10\u0026ndash;12]. Within Ethiopia, maize is grown primarily in the southern, southwestern and western regions\u0026nbsp;[13\u0026ndash;15]. With respect to other cultivated cereals dating back to the 1980s, maize has been the most cultivated per hectare and the country has had a historical dependence on it for food and economic purposes. As a consequence of this, Ethiopia has since experienced on average annual increase in maize production of 7.60% between 1980 and 2020\u0026nbsp;[16]. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring the emergence and spread of MSV throughout continental Africa from the 1920s through to the 1970s, at least five MSV-A subtypes-MSV-A\u003csub\u003e1\u003c/sub\u003e, -A\u003csub\u003e2\u003c/sub\u003e, -A\u003csub\u003e3\u003c/sub\u003e, -A\u003csub\u003e4\u003c/sub\u003e, and -A\u003csub\u003e6\u003c/sub\u003e have emerged, each differing in virulence, and geographical range\u0026nbsp;[6, 17\u0026ndash;19]. \u0026nbsp;Since the 1970s East Africa has become both the primary hub of trans-continental MSV-A movements, and this region is also the primary hotspot of MSV-A diversification i.e., it is the present cradle of the virus\u0026nbsp;[19\u0026ndash;21].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin East Africa, \u0026nbsp;the Ugandan and Kenyan \u0026nbsp;regions around Lake Victoria appears to be the primary sources of new MSV-A variants whereas the rift valley and coastal regions of Kenya are sinks of MSV-A diversity\u0026nbsp;[21]. \u0026nbsp;Being a major viral disease of maize in East Africa including Ethiopia\u0026nbsp;[22], little is known about the roles of other East African countries such as Ethiopia due to sparse sampling and sequencing of MSV-A variants in the genesis and dissemination of new MSV-A variants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHere, we assessed MSV-A prevalence in western Ethiopia by field sampling, cloning and sequencing isolates, and performing phylogenetic analyses using nucleotide sequences from this survey together with those available in GenBank in order to properly classify these new isolates. A total of 105 symptomatic leaves that included one or more leaves samples per plant were sampled during the 2019 planting season in western Ethiopia from maize plants showing streak symptoms as part of an epidemiological survey. From these 60 samples were identified as positive for MSV-A from which complete MSV genomes were determined. Visual assessment based on characteristic symptoms described by Mesfin \u003cem\u003eet al\u003c/em\u003e.\u0026nbsp;[23]\u0026nbsp;and Shepherd \u003cem\u003eet al\u003c/em\u003e.\u0026nbsp;[2]\u0026nbsp;to have been associated with MSV infections in maize were used to determine disease incidence and severity in the field. Disease prevalence was determined as the number of fields where a particular disease was recorded in relation to the number of fields sampled from surveyed regions. MSD incidence was determined by visually observing and recording the number of maize plants showing the disease symptoms and we calculated the percentage incidence as:\u003c/p\u003e\n\u003cp\u003e\u003cspan style='font-size:15px;line-height:115%;font-family:\"Calibri\",sans-serif;'\u003e\u003cimg src=\"https://myfiles.space/user_files/89043_013bc31cb0099197/89043_custom_files/img1663676233.png\"\u003e\u003c/span\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eWe assessed disease severity as the area of plant tissue affected by disease, expressed as a percentage of the total area at regular intervals using a 1\u0026ndash;5 scale\u0026nbsp;[24].\u003c/p\u003e\n\u003cp\u003eCircular DNA from total plant DNA extracts was enriched using phi29 DNA polymerase (TempliPhi; GE Healthcare) as described by Shepherd \u003cem\u003eet al\u003c/em\u003e [25]. Amplified genome concatemers were digested with BamHI to yield linearized viral genomes (~2.7kb) which were ligated into pUC19 (New England Biolabs) restricted with BamHI. The cloned genomes were \u0026nbsp;Sanger sequenced at Macrogen Inc (South Korea) by primer walking. Viral genome sequences were assembled and edited using Geneious Prime (version 2020.2.4;\u0026nbsp;Biomatters Limited, New Zealand).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe 60 MSV-A isolate sequences from Ethiopia were aligned with an additional 665 MSV-A sequences including 182 non-MSV-A sequences (representing strains of MSV-B through -K) that were publicly available in GenBank using \u0026nbsp;MUSCLE\u0026nbsp;[26]. The resulting alignment was further edited by visual inspection in Aliview\u0026nbsp;[27]. This MSV full genome alignment was analysed for recombination using RDP version 4.46\u0026nbsp;[28]\u0026nbsp;to obtain a recombinant-free, MSV-A only dataset (n = 725) that was subsequently used for downstream phylogenetic inference. Screening for recombinants was accomplished using the default RDP settings and removing all evidence of recombination within the alignment by identifying recombinant sequence fragments and removing these by replacing these sequence tracts with the standard \u0026ldquo;gap\u0026rdquo; characters, \u0026ldquo;-\u0026ldquo; with no changes to the alignment of the retained nucleotides.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe used jModeltest version 2.1.10\u0026nbsp;[29]\u0026nbsp;implemented on the CIPRES server at\u0026nbsp;\u003ca href=\"http://phylo.org\"\u003ehttp://phylo.org\u003c/a\u003e [30]\u0026nbsp;to determine the best-fitting nucleotide substitution model for the MSV-A dataset and then constructed a maximum likelihood (ML) tree for the MSV-A dataset using IQ-TREE version 1.6.12\u0026nbsp;[31]. Branch supports in the tree were determined using 2000 replicates of non-parametric Shimodaira-Hasegawa-like approximate likelihood ratio tests (SH-aLRT)\u0026nbsp;[32, 33]\u0026nbsp;as well as 5000 ultrafast bootstrap replicates\u0026nbsp;[34]. The recombinant lineages of these MSV-A isolates were determined based on the methods previously described by Martin \u003cem\u003eet al\u003c/em\u003e [6], and Monjane \u003cem\u003eet al\u003c/em\u003e [20].\u003c/p\u003e\n\u003cp\u003eA total of 127 maize fields were visited, from these 100 maize, and five grass samples with MSD-like symptoms were collected. The newly determined 60 genomes from these Ethiopian samples all are MSV-A variants based on relatedness to previously determined MSV-A. Frequently encountered MSD-like symptoms associated with MSV infection are: broken to continuous chlorotic streaks on the leaf veins uniformly distributed across the leaf surface, pale yellow streaks, mosaic and chlorosis on leaf lamellae, broken or longitudinal chlorotic streaks along leaf veins, wilting and drying of leaf margins, necrosis and mottling on the entire plant (Fig. 1). Out of 127 maize fields visited, based on MSD-like symptoms, the disease was prevalent in 98 (77%) fields assessed. The overall mean prevalence of MSD were 96% and 93% in Gambela and Benishangul Gumez regions for 22 and 25 fields \u0026nbsp;respectively, while in Oromia region, mean prevalence of 66% was observed (Table 1). Mean prevalence assessment for Gambela zones of\u0026nbsp;Anuak and Nuer were 93% and 100%, respectively. Of the four Oromia zones of Jimma, Buno Bedele, East and West Wellega, MSD mean prevalence were 64%, 0%, 65% and 85%, respectively. Other than Buno Bedele, where the disease was not identified, MSD was prevalent in three Oromia zones surveyed, the highest prevalence being recorded in West Wellega. The prevalence of MSD was also assessed from Asossa zone of\u0026nbsp;Benishangul-Gumez region where the mean prevalence recorded was 93%. Likewise, MSD incidence was also higher in Gambella, followed by Benishangule-Gumuz and Oromia, where the mean incidences of up to 64% in Gambela, 59% in Benishangul Gumez, and 33% in Oromia regions were recorded (Table 1). Of the surveyed areas in Gambela region, we recorded higher incidences of MSD in\u0026nbsp;Anuak and Nuer zone. In Oromia, low incidences of MSD were observed in Buno Bedele, and Jimma zones, unlike the East and West Wellega zones with relatively higher incidences (Table 1).\u0026nbsp;The severity of MSD was significantly higher in Gambela and Benishangul-Gumz compared to Oromia region. The severity score of MSD was higher in Anuak, Nuer and Asosa zones unlike the relatively low severity recorded in Jimma, East and West Wolega zones. \u0026nbsp;No disease was recorded in Buno Bedele zone\u0026nbsp;of the surveyed regions, the highest severities of \u0026nbsp;4 to 5 (on 1-5 scoring scale) were recorded in Gambella followed by Benishangule-Gumuz and Oromia regions (Table 1).\u003c/p\u003e\n\u003cp\u003eThese MSV isolates from western Ethiopia all belong to recombinant lineage V of the MSV-A\u003csub\u003e1\u003c/sub\u003e subtype (Fig 2A). They share about 98% sequence similarity with MSV-A\u003csub\u003e1\u003c/sub\u003e isolates from Kenya\u0026nbsp;[21]\u0026nbsp;and Rwanda\u0026nbsp;[35]. Here, we used the best fitting DNA substitution model GTR+I+G4 for the MSV-A (n=725) alignment as previously posited by Mojane \u003cem\u003eet al\u003c/em\u003e [20], and Harkins \u003cem\u003eet al\u003c/em\u003e [21]. GTR is the empirical DNA model of Tavare\u0026nbsp;[36], which allows unequal rates for all six of the possible reversible nucleotide substitutions and unequal base frequencies, with \u003cu\u003eI\u003c/u\u003e representing the proportion of invariant sites and G4 the discrete Gamma model of Yang\u0026nbsp;[37]\u0026nbsp;with four rate categories. The best majority-rule consensus ML trees inferred from the MSV-A dataset is presented in Fig 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur results show that MSD disease incidence, prevalence, and severity were highest in Gambela region followed by Benishangule-Gumuz and Oromiya regions, respectively (Table 1). Variations exist in the level of disease prevalence and incidence in different altitude ranges assessed. Relatively higher prevalence and incidence were recorded at lower altitudes ranging from 400-1500 metres above sea level and vice versa at higher altitudes ranging from 1800-2400 metres above sea level. For instance, the disease incidence was higher in Benishangul-Gumuz and Gambela regions at locations of 400 to 1600 metres above sea level, while none was recorded in\u0026nbsp;Buno Bedele zone\u0026nbsp;with altitudes ranging from 1500-2200\u0026nbsp;(Table 1). This could be attributed to warmer climates in these lower altitudes areas that favour vector populations for virus transmission, resulting in more severe disease symptoms development\u0026nbsp;[40].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese findings support those previously reported by Mesfin \u003cem\u003eet al.\u003c/em\u003e [10]\u0026nbsp;that exceptionally high MSD outbreak occurred in Gambela region during the 1986 cropping season, and that regions in the West other than Gambela were also affected. MSD prevalence in these regions has also been linked to higher population density of \u003cem\u003eCicadulina\u0026nbsp;\u003c/em\u003esp. especially \u003cem\u003eC. mbila\u003c/em\u003e found mainly at these lower altitude regions\u0026nbsp;[10]. This implies that the altitude ranges that support insect vectors may play a key role in determining MSD distribution and prevalence\u0026nbsp;[38]. Earlier, similar findings in Ethiopia reported the distribution and importance of MSD in other parts of the country\u0026nbsp;[14, 39].\u0026nbsp;The high disease incidence detected in the field is expected to cause a considerable reduction in yield and quality. In highly susceptible and late sown genotypes, MSD can cause up to 100% yield losses in infected crops\u0026nbsp;[41\u0026ndash;43]. Recent report showed that MSD incidence of up to 58% was also found in Ethiopian maize germplasm\u0026nbsp;[14].\u003c/p\u003e\n\u003cp\u003eIn this case, maximum likelihood trees are useful for classifying newly sequenced economically important MSV-A isolates genomes into subtype and recombinant lineages. Based on degree of virulence, host range, geographical clustering, and phylogenetic evidence\u0026nbsp;[6, 19]\u0026nbsp;MSV-A has been previously grouped into subtypes and recombinant lineages. Subtypes share greater than 98% sequence similarity\u0026nbsp;[6, 44]. For MSV-A, five subtypes (MSV-A\u003csub\u003e1\u003c/sub\u003e, MSV-A\u003csub\u003e2\u003c/sub\u003e, MSV-A\u003csub\u003e3\u003c/sub\u003e, MSV-A\u003csub\u003e4\u003c/sub\u003e and MSV-A\u003csub\u003e6\u003c/sub\u003e) have been identified. Monjane \u003cem\u003eet al\u003c/em\u003e.\u0026nbsp;[19]\u0026nbsp;has grouped MSV-A variants into 24 recombinant lineages, 16 (MSV-A\u003csub\u003e1\u003c/sub\u003eI to MSV-A\u003csub\u003e1\u003c/sub\u003eXVI) of which contained predominantly MSV-A\u003csub\u003e1\u003c/sub\u003e sequences. Of all the MSV-A subtypes, it appears that MSV-A\u003csub\u003e1\u003c/sub\u003e has the widest distribution throughout continental Africa and is also found on Madagascar and the Comoros islands [6, 19]. Furthermore, the endemic nature of MSV-A in Ethiopia, like other countries in the sub-Saharan Africa, and the further exacerbation by importations from bordering countries, may play a role in MSV-A spread. Informal trades, formal trades, and porous borders may also significantly impact MSV-A disseminations. This study has further provided information on MSV-A diversity in the East African countries.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKAO was supported by the National Research Foundation (NRF) South Africa and The World Academy of Science (TWAS) grant number\u0026nbsp;105461. The funders neither had roles in study design, data collection and interpretation nor in the decision to submit the work for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express sincere gratitude to Mr. Tolcha Tufa for developing map of surveyed areas. The facilitation and support provided by Associate Professor Darren Martin in getting samples tested at the University of Cape Town in South Africa deserve our special appreciation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with ethical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone required\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict(s) of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have declared non-existent conflict of interest\u003c/p\u003e"},{"header":"References","content":"\n\u003cp\u003e1. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Charles K (2014) Maize streak virus: A review of pathogen occurrence, biology and management options for smallholder farmers. African J Agric Res 9:2736\u0026ndash;2742. https://doi.org/10.5897/AJAR2014.8897\u003c/p\u003e\n\u003cp\u003e2. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Shepherd DN, Martin DP, Van Der Walt E, et al (2010) Maize streak virus: an old and complex \u0026ldquo;emerging\u0026rdquo; pathogen. Mol Plant Pathol 11:1\u0026ndash;12. https://doi.org/10.1111/j.1364-3703.2009.00568.x\u003c/p\u003e\n\u003cp\u003e3. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Martin DP, Shepherd DN (2009) The epidemiology, economic impact and control of maize streak disease. Food Secur 1:305\u0026ndash;315. https://doi.org/10.1007/s12571-009-0023-1\u003c/p\u003e\n\u003cp\u003e4. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Martin DP, Willment J a, Rybicki EP (1999) Evaluation of Maize Streak Virus Pathogenicity in Differentially Resistant Zea mays Genotypes. Phytopathology 89:695\u0026ndash;700. https://doi.org/10.1094/Phyto.1999.89.8.695\u003c/p\u003e\n\u003cp\u003e5. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pinner MS, Markham PG, Markham RH, Dekker L (1988) Characterization of maize streak virus: description of strains; symptoms. Plant Pathol 37:74\u0026ndash;87. https://doi.org/10.1111/j.1365-3059.1988.tb02198.x\u003c/p\u003e\n\u003cp\u003e6. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Martin DP, Willment JA, Billharz R, et al (2001) Sequence diversity and virulence in Zea mays of Maize streak virus isolates. Virology 288:247\u0026ndash;55. https://doi.org/10.1006/viro.2001.1075\u003c/p\u003e\n\u003cp\u003e7. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Magenya OEV, Mueke J, Omwega C (2008) Significance and transmission of maize streak virus disease in Africa and options for management: A review. African J Biotechnol 7:4897\u0026ndash;4910. https://doi.org/10.4314/ajb.v7i25.59697\u003c/p\u003e\n\u003cp\u003e8. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lefeuvre P, Martin DP, Elena SF, et al (2019) Evolution and ecology of plant viruses. Nat Rev Microbiol 1\u0026ndash;13. https://doi.org/10.1038/s41579-019-0232-3\u003c/p\u003e\n\u003cp\u003e9. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Reynaud B, Peterschmitt, M. (1992) A study of the mode of transmission of maize streak virus by Cicadulina mbila using an enzyme‐linked immunosorbent assay. Ann Appl Biol 121:85\u0026ndash;94. https://doi.org/10.1111/j.1744-7348.1992.tb03989.x\u003c/p\u003e\n\u003cp\u003e10. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mesfin T, Den Hollander J, Markham PG (1991) Cicadulina species and maize streak virus in Ethiopia. Trop Pest Manag 37:240\u0026ndash;244. https://doi.org/10.1080/09670879109371592\u003c/p\u003e\n\u003cp\u003e11. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Abraham A (2019) Emerged Plant Virus Disease in Ethiopian Agriculture : Causes and Control Options. Ethiop J Agric Sci 29:39\u0026ndash;55\u003c/p\u003e\n\u003cp\u003e12. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Deribe K, Meribo K, Gebre T, et al (2012) The burden of neglected tropical diseases in Ethiopia, and opportunities for integrated control and elimination. Parasit Vectors 5:240. https://doi.org/10.1186/1756-3305-5-240\u003c/p\u003e\n\u003cp\u003e13. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Bjarnason M (1986) Progress in breeding for resistance to the maize streak virus disease. A Proc first Eastern, Cent South Africa Reg maize Work Lusaka, Zambia, March 10-17 1985\u003c/p\u003e\n\u003cp\u003e14. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Guadie D, Tesfaye K, Knierim D, et al (2019) Molecular analysis of maize (Zea mays L.)-infecting mastreviruses in Ethiopia reveals marked diversity of virus genomes and a novel species. Virus Genes 55:339\u0026ndash;345. https://doi.org/10.1007/s11262-019-01655-1\u003c/p\u003e\n\u003cp\u003e15. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Dawit A, Chilot Y, Adam B, Agajie T (2014) Situation and Outlook of Maize in Ethiopia of Maize in Ethiopia\u003c/p\u003e\n\u003cp\u003e16. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Knoema (2020) Ethiopia - Maize production quantity. In: https://knoema.com/atlas/Ethiopia/topics/Agriculture/Crops-Production-Quantity-tonnes/Maize-production\u003c/p\u003e\n\u003cp\u003e17. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Harkins GW, Martin DP, Duffy S, et al (2009) Dating the origins of the maize-adapted strain of maize streak virus, MSV-A. J Gen Virol 90:3066\u0026ndash;3074. https://doi.org/10.1099/vir.0.015537-0\u003c/p\u003e\n\u003cp\u003e18. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Owor BE, Martin DP, Shepherd DN, et al (2007) Genetic analysis of maize streak virus isolates from Uganda reveals widespread distribution of a recombinant variant. J Gen Virol 88:3154\u0026ndash;3165. https://doi.org/10.1099/vir.0.83144-0\u003c/p\u003e\n\u003cp\u003e19. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Monjane AL, Harkins GW, Martin DP, et al (2011) Reconstructing the History of Maize Streak Virus Strain A Dispersal To Reveal Diversification Hot Spots and Its Origin in Southern Africa. J Virol 85:9623\u0026ndash;9636. https://doi.org/10.1128/JVI.00640-11\u003c/p\u003e\n\u003cp\u003e20. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Varsani A, Shepherd DN, Monjane AL, et al (2008) Recombination, decreased host specificity and increased mobility may have driven the emergence of maize streak virus as an agricultural pathogen. J Gen Virol 89:2063\u0026ndash;2074. https://doi.org/10.1099/vir.0.2008/003590-0\u003c/p\u003e\n\u003cp\u003e21. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pande D, Madzokere E, Hartnady P, et al (2017) The role of Kenya in the trans-African spread of maize streak virus strain A. Virus Res 232:69\u0026ndash;76. https://doi.org/10.1016/J.virusres.2017.02.005\u003c/p\u003e\n\u003cp\u003e22. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Keno T, Azmach G, Wegary D, et al (2018) African Journal of Agricultural Research Major biotic maize production stresses in Ethiopia and their management through host resistance. 13:1042\u0026ndash;1052. https://doi.org/10.5897/AJAR2018.13163\u003c/p\u003e\n\u003cp\u003e23. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mesfin T, Den Hollander J, Markham PG (1995) Feeding activities of Cicadulina mbila (Hemiptera: Cicadellidae) on different host-plants. Bull Entomol Res 85:387\u0026ndash;396. https://doi.org/10.1017/S0007485300036129\u003c/p\u003e\n\u003cp\u003e24. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;D. B, E. A-B, K. AF, et al (2018) Incidence and severity of maize streak disease: The influence of tillage, fertilizer application and maize variety. African J Agric Res 13:551\u0026ndash;560. https://doi.org/10.5897/ajar2017.12873\u003c/p\u003e\n\u003cp\u003e25. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Shepherd DN, Martin DP, Lefeuvre P, et al (2008) A protocol for the rapid isolation of full geminivirus genomes from dried plant tissue. J Virol Methods 149:97\u0026ndash;102. https://doi.org/10.1016/j.jviromet.2007.12.014\u003c/p\u003e\n\u003cp\u003e26. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792\u0026ndash;1797. https://doi.org/10.1093/nar/gkh340\u003c/p\u003e\n\u003cp\u003e27. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Larsson A (2014) AliView: A fast and lightweight alignment viewer and editor for large datasets. Bioinformatics 30:3276\u0026ndash;3278. https://doi.org/10.1093/bioinformatics/btu531\u003c/p\u003e\n\u003cp\u003e28. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Martin DP, Murrell B, Golden M, et al (2015) RDP4: Detection and analysis of recombination patterns in virus genomes. Virus Evol 1:1\u0026ndash;5. https://doi.org/10.1093/ve/vev003\u003c/p\u003e\n\u003cp\u003e29. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Darriba D, Taboada GL, Doallo R, Posada D (2012) jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9:772. https://doi.org/10.1038/nmeth.2109\u003c/p\u003e\n\u003cp\u003e30. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Miller MA, Pfeiffer W, Schwartz T (2010) Creating the CIPRES Science Gateway for Inference of Large Phylogenetic Trees\u003c/p\u003e\n\u003cp\u003e31. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ (2015) IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. Mol Biol Evol 32:268\u0026ndash;274. https://doi.org/10.1093/molbev/msu300\u003c/p\u003e\n\u003cp\u003e32. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Guindon S, Dufayard J-F, Lefort V, et al (2010) New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst Biol 59:307\u0026ndash;321. https://doi.org/10.1093/sysbio/syq010\u003c/p\u003e\n\u003cp\u003e33. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Shimodaira H, Hasegawa M (1999) Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference. Mol Biol Evol 16:1114\u0026ndash;1116. https://doi.org/10.1093/oxfordjournals.molbev.a026201\u003c/p\u003e\n\u003cp\u003e34. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Hoang DT, Chernomor O, von Haeseler A, et al (2018) UFBoot2: Improving the Ultrafast Bootstrap Approximation. Mol Biol Evol 35:518\u0026ndash;522. https://doi.org/10.1093/molbev/msx281\u003c/p\u003e\n\u003cp\u003e35. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Asiimwe T, Stewart LR, Willie K, et al (2020) Maize lethal necrosis viruses and other maize viruses in Rwanda. Plant Pathol 69:585\u0026ndash;597. https://doi.org/10.1111/ppa.13134\u003c/p\u003e\n\u003cp\u003e36. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tavare S (1986) Some probabilistic and statistical problems in the analysis of DNA sequences. Some Math Quest Biol / DNA Seq Anal Ed by Robert M Miura\u003c/p\u003e\n\u003cp\u003e37. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Yang Z (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods. J Mol Evol 39:306\u0026ndash;314. https://doi.org/10.1007/BF00160154\u003c/p\u003e\n\u003cp\u003e38. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Magenya OE V, Mueke J, Omwega C (2009) Association of maize streak virus disease and its vectors (Homoptera: Cicadelidae) with soil macronutrients and altitudes in Kenya\u003c/p\u003e\n\u003cp\u003e39. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lencho A, Abraham A, \u0026hellip; BB-PMJ, 1997 \u0026nbsp;undefined Identification of viruses from maize and grass hosts. agris.fao.org\u003c/p\u003e\n\u003cp\u003e40. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Redinbaugh MG, Zambrano JL (2014) Control of Virus Diseases in Maize\u003c/p\u003e\n\u003cp\u003e41. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Alegbejo MD, Olojede SO, Kashina BD, Abo ME (2002) Maize streak mastrevirus in Africa: Distribution, transmission, epidemiology, economic significance and management strategies. J Sustain Agric 19:35\u0026ndash;45. https://doi.org/10.1300/J064v19n04_05\u003c/p\u003e\n\u003cp\u003e42. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Kyetere DT, Ming R, McMullen MD, et al (1999) Genetic analysis of tolerance to maize streak virus in maize. Genome 42:20\u0026ndash;26. https://doi.org/10.1139/g98-099\u003c/p\u003e\n\u003cp\u003e43. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lagat M, Danson J, Kimani M, Kuria A (2008) Quantitative trait loci for resistance to maize streak virus disease in maize genotypes used in hybrid development. African J Biotechnol 7:2573\u0026ndash;2577\u003c/p\u003e\n\u003cp\u003e44. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Fauquet CM, Briddon RW, Brown JK, et al (2008) Geminivirus strain demarcation and nomenclature. Arch Virol 153:783\u0026ndash;821. https://doi.org/10.1007/s00705-008-0037-6\u003c/p\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1:\u0026nbsp;Mean prevalence, incidence, and severity of maize streak disease across study area during the 2019 main cropping season\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"106%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eZone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAltitude range\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(MASL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncidence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeverity(1-5 scale)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGambela\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003eAnuak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e400-600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.753086419753085%\"\u003e\n \u003cp\u003eNuer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"20.987654320987655%\"\u003e\n \u003cp\u003e400-500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOromia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003eJimma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1300-2100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.753086419753085%\"\u003e\n \u003cp\u003eEast Wellega\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"20.987654320987655%\"\u003e\n \u003cp\u003e1300-2200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.753086419753085%\"\u003e\n \u003cp\u003eWest Wellega\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"20.987654320987655%\"\u003e\n \u003cp\u003e1200-2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.753086419753085%\"\u003e\n \u003cp\u003eBuno Bedele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"20.987654320987655%\"\u003e\n \u003cp\u003e1500-2200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.641975308641975%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.580246913580247%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e33\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenishangul- Gumuz\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003eAsosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e1100-1700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"32.98969072164948%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrand mean for prevalence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"17.52577319587629%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e127\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e\u003cstrong\u003e98\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3828125%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.5234375%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.109375%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.5625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.640625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.2265625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.0390625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.4765625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.0390625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNFA- Number of fields assessed\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNFI- Number of fields infected\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMASL- Metres above sea level\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-virology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arvi","sideBox":"Learn more about [Archives of Virology](https://www.springer.com/journal/705)","snPcode":"705","submissionUrl":"https://submission.nature.com/new-submission/705/3","title":"Archives of Virology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-1815287/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1815287/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe A-strain of \u003cem\u003eMaize streak virus\u003c/em\u003e (MSV) causes maize streak disease (MSD) which is a major biotic threat to maize production in sub-Saharan Africa. Previous studies have described different MSV strains of economic importance from southern and eastern African countries, and how eastern African regions are hubs for MSV diversification. Despite these efforts, and lack of extensive sampling, there is limited knowledge about the MSV-A diversity in Ethiopia. Here, field sampling of maize plants and wild grasses with visible MSD symptoms were carried out in western Ethiopian regions of Gambela, Oromia, and Benishangul-Gumuz, during the maize growing season of 2019. The complete genomes of MSV isolates (n\u0026thinsp;=\u0026thinsp;60) were cloned and Sanger sequenced. We use a model based phylogenetic approach to analyse 725 full MSV genome sequences available in the GenBank together with newly recovered genomes from Ethiopia to determine their subtypes and recombinant lineages. Of the 127 fields accessed, MSD prevalence was highest at 96% in Gambela region, and lowest in Oromia at 66%. Highest mean symptom severity of 4/5, (where 5 is the highest and 1 the lowest) was observed for both Gambela and Benishangul-Gumuz. Our results show that these newly determined MSV isolates belong in the recombinant lineage V of the A\u003csub\u003e1\u003c/sub\u003e subtype with the widest dissemination, and economic significance in the sub-Saharan Africa and the adjacent Indian Ocean islands.\u003c/p\u003e","manuscriptTitle":"Molecular identification and phylogenetic characterization of A-strain isolates of Maize streak virus from western Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-09-20 12:21:53","doi":"10.21203/rs.3.rs-1815287/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2022-08-29T13:17:46+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-08-29T12:08:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-08-27T06:05:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Virology","date":"2022-08-26T14:52:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-virology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arvi","sideBox":"Learn more about [Archives of Virology](https://www.springer.com/journal/705)","snPcode":"705","submissionUrl":"https://submission.nature.com/new-submission/705/3","title":"Archives of Virology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}},{"code":1,"date":"2022-07-22 17:49:31","doi":"10.21203/rs.3.rs-1815287/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2022-07-23T08:17:50+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-07-15T08:55:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-07-14T09:05:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Virology","date":"2022-07-14T02:24:50+00:00","index":"","fulltext":""},{"type":"decision","content":"Minor Revision","date":"2022-07-12T15:10:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-virology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arvi","sideBox":"Learn more about [Archives of Virology](https://www.springer.com/journal/705)","snPcode":"705","submissionUrl":"https://submission.nature.com/new-submission/705/3","title":"Archives of Virology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cda1b549-296a-410d-8e46-eae6b5fae92e","owner":[],"postedDate":"September 20th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-09-13T10:42:41+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-20 12:21:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-1815287","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1815287","identity":"rs-1815287","version":["v2"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}