STATUS and RELATIVE DISTRIBUTION of MAIZE STREAK VIRUS in WESTERN ETHIOPIA M.Sc

STATUS AND RELATIVE DISTRIBUTION OF MAIZE STREAK VIRUS IN WESTERN ETHIOPIA M.Sc. THESIS

DANIEL KETSELA TIRUNEH

JANUARY, 2021

AMBO, ETHIOPIA

AMBO UNIVERSITY SCHOOL OF GRADUATE STUDIES COLLEGE OF AGRICULTURE AND VETERINARY SCIENCES DEPARTMENT OF PLANT SCIENCES

M.Sc. Thesis

Status and Relative Distribution of Maize Streak Virus in Western Ethiopia By

Daniel Ketsela Tiruneh

A Thesis submitted to the School of Graduate Studies in partial fulfillment of the requirements for the Degree of the Master of Science in Plant Pathology

Major Advisor: Berhanu Bekele (PhD) Co-Advisor: Alemu Lencho (PhD)

January, 2021 Ambo, Ethiopa APPROVAL SHEET

Submitted by

______

PG Candidate Signature Date

Approved by

______

Main advisor Signature Date

______

Co-advisor Signature Date

______

Department Head Signature Date

______

College/Institute Dean Signature Date

______

Dean, School of Graduate Studies Signature Date

DEDICATION

I would like to dedicate this thesis to the memory of my father Ketsela Tiruneh. Let God keep his soul in Heaven. His counsel and vision remains my greatest inspiration to go for the stars.

CERTIFICATION SHEET SCHOOL OF GRADUATE STUDIES AMBO UNIVERSITY

As thesis research advisors, we here by certify that we have read and evaluated the thesis prepared by Daniel Ketsela Tiruneh under our guidance, which is entitled Status and Relative Distribution of Maize Streak Virus in Western Ethiopia.

We recommend that the thesis be submitted as it fulfills the requirements for the Degree of Master of Science.

______

Main Advisor Signature Date

______

Co-advisor Signature Date

As members of the Examining Board of the Final M.Sc. open defense, we certify that we have read and evaluated the thesis prepared by Daniel Ketsela and recommended that it is accepted as fulfilling the thesis full requirements for the award of Degree of Master of Science in Plant Pathology

______

Chairman Signature Date

______

External Examiner Signature Date

______

Internal Examiner Signature Date

III

DECLARATION

I declare that, the Status and Relative Distribution of Maize Streak Virus in Western Ethiopia, is my own work, that it has not been submitted for any degree or examination in any other university, and that all the sources I have used or quoted have been indicated and acknowledged by complete references.

Name: Daniel Ketsela, Signature: ______

Place: Ambo University, Ambo, Ethiopia

Date of submission: December, 2020.

BIOGRAPHY

The author, Daniel Ketsela Tiruneh, was born on March 1992 at Gorfo villege in Hageremariam Kesem Woreda, North Shoa zone, Amhara Regional State, Ethiopia from his father, Ketsela Tiruneh and his mother, Ayelech Ymane. He attended his Elementary School education at Gorfo Elementary School and Junior High School education at Bulga Secondary School. He pursued his preparatory school education at Hailemariam Mamo Preparatory School in Debrebirhan town.

After that, he was joined Debrebirhan University, College of Natural and Computational Science for his Under Graduate Studies in Applied Biology from October 2010 to 2013. Then, he graduated with BSc Degree in applied Biology on 30 June 2013. After graduation, he has been joined Ethiopian Institute of Agricultural Research (EIAR), Ambo Agricultural Research Center (AmARC) in the department of Agricultural and Nutritional Research Program as a junior researcher. After three years service at Agricultural and Nutritional Research Program he reassigned in Plant pathology program, Virology research department where he served for one year until he joined the graduate studies program of Ambo University, College of Agriculture and Veterinary Sciences, Department of Plant Sciences to pursue a graduate study leading to a Master of Science degree in plant pathology.

ACKNOWLEDGEMENTS

First and foremost, I would like to thank my Almighty God for His endowment of Grace, Peace, strength and Health to my life and family.

I would like to acknowledge my supervisor Dr.Berhanu Bekele, Senior Researcher of Plant Pathology, for his patience, exceptional guidance and support during the study period. With the deepest gratitude, I wish to thank him for his support in providing reagents like primer, professional expertise and advice from the very planning of this work to its execution and critical review of the manuscript and made it scientifically sound. Without his enlightening guidance and consistent support, I would not have been able to overcome the obstacles I encountered.

My heartful thanks go to Dr. Alemu Lencho, Associate Professor of Plant Pathology, My thesis Co-advisor, for his patience and thoughtful guidance throughout my study. With the deepest gratitude, I wish to thank him for his support, professional expertise and advice from the very planning of this work to its execution and critical review of the manuscript and made it scientifically sound.

Professor Darren Martin and Oyeniran Kehinde, Department of Molecular and Cell Biology, University of Cape Town, South African, highly acknowledged for their support in running rolling circle amplification (RCA) and sequencing of dozens of MSV isolates from Ethiopia.

I would like to extend my gratitude to the Head Department of Plant Sciences, School of Graduate Studies, Ambo University for well-organized and nice facilitations provided during my course work.

My deepest gratitude goes to Ethiopian Institute of Agricultural Research (EIAR), Ambo Agricultural Research Center (AmARC) for allowing me MSc study leave and provisions of full financial and material support for this research work. Last, but not least, I am also very grateful to my family and friends for their love, prayers and unwavering support.

ACRONYMS AND ABBREVIATIONS

AmARC Ambo Agricultural Research Center BLAST Basic Local Alignment Search Tool BLASTn Nucliotied Basic Local Alignment Search Tool CIMMYT International Maize and Wheat Improvement Center CSA Central Statistics Agency CTAB Cetyl trimethyl Ammonium Bromide Cp Coat Protein DNA Deoxyribonucleic Acid dNTP Deoxynucleoside triphosphate FAO Food and Agricultural Organization FAOSTAT Food and Agriculture Organization Corporate Statistical Database EIAR Ethiopian Institute of Agricultural Research EDTA Ethylene di-amine tetra acetic acid ICTV International Committee on Taxonomy of Viruses IITA International Institute of Tropical Agriculture ISAAA International Service for the Acquisition of Agri-biotech Applications LIR Large Intergenic Region MP Movement protein NCBI National Center for Biotechnology Information RCA Rolling Circle Amplification RCR Rolling Circle Replication RepA Replication association protein Rep Replication initiation protein SIR Small Intergenic Region TAE Tris Acetate EDTA TE Tris EDTA

VII

TABLE OF CONTENTES

Table of Contents Pages APPROVAL SHEET ...... I

DEDICATION ...... II

CERTIFICATION SHEET ...... III

DECLARATION ...... IV

BIOGRAPHY ...... V

ACKNOWLEDGEMENTS ...... VI

ACRONYMS AND ABBREVIATIONS ...... VII

TABLE OF CONTENTES ...... VIII

LIST OF TABLES ...... XI

LIST OF FIGURES ...... XII

LIST OF APPENDIXS ...... XIV

ABSTRACT ...... XV

1. INTRODUCTION ...... 1

1.1. Statement of the Problem ...... 4

1.2. Objectives ...... 5

1.2.1. General Objective ...... 5

1.2.2. Specific Objectives ...... 5

2. LITERATURE REVIEW ...... 6

2.1. The Host: Maize/Origin and Distribution of Maize ...... 6

2.2. Production Constraints ...... 7

2.2.1. Abiotic constraints ...... 7

2.2.2. Biotic Constraints...... 7

VIII

2.3. Maize streak virus disease ...... 8

2.4. Morphology of the MSV virus ...... 8

2.5. Origin of Maize streak Virus Disease ...... 9

2.6. Economic Importance of Maize streak Virus Disease ...... 10

2.7. Prevalence and Distribution of MSV ...... 11

2.8. Genome Organization and Molecular Characterization ...... 11

2.9. Virulence of MSV strains ...... 13

2.10. Host Range of MSV ...... 13

2.11. Symptoms Expression ...... 14

2.12. Epidemiology MSVD ...... 16

2.13. Vector Transmission of MSV ...... 17

3. MATERIALS AND METHODS ...... 21

3.1. Assessment and Geographical Distribution of Maize Streak Disease ...... 21

3.2. Assessment of MS Incidence and Severity in the field ...... 22

3.3. Molecular Characterization of Maize Streak Virus ...... 23

3.3.1. Sample Collection and DNA Extraction ...... 23

3.3.2. Polymerase Chain Reaction (PCR) ...... 24

3.3.3. Electrophoresis and UV visualization ...... 24

3.4. Plant DNA extraction and cloning protocol for RCA ...... 24

3.4.1. DNA extraction ...... 24

3.4.2. Rolling circle amplification ...... 25

3.4.3. Sequencing and Phylogenetic Analysis ...... 26

4. RESULTS AND DISCUSSION ...... 28

4.1. Distribution, Incidence and Severity of MSV ...... 28

4.1.1. Distribution, Incidence and Severity of MSV across Location ...... 28

4.1.2. Distribution, Incidence and Severity of MSV across Variety ...... 34

4.2. Molecular Characterization of Maize Streak Virus ...... 34

4.2.1. Amplification of MSV ...... 34

4.2.2. Sequencing and Phylogenetic Analysis ...... 36

5. CONCLUSION ...... 41

6. RECOMMENDATIONS...... 42

7. REFERENCES ...... 43

8. APPENDEXS ...... 57

LIST OF TABLES

Table 1. Origin of Maize Streak Virus isolates and the grouping of strains from different plant host in some African countries...... 13 Table 2. Maize Streak Virus detected from grass hosts in Ethiopia ...... 14 Table 3. Distribution and incidence of Cicadulina species and maize streak virus in different maize growing regionsof Ethiopia ...... 20 Table 4. Major agro-ecological zones of surveyed areas for maize streak in Ethiopia ...... 21 Table 5. Visual rating scale for maize streak disease severity ...... 23 Table 6 Primers used for squensing complete Maize Streak Virus gynome ...... 25 Table 7. Origin and accession numbers of Maize Streak Virus isolates from different countries in Africa earlier deposited in the Genbank for comparison with isolates identified in this study from Ethiopia ...... 27 Table 8. Disease prevalence (%), Incidence (%) and severity (1-5scale) of Maize Streak across different Altitude ranges in Ethiopia...... 29 Table 9. Correlation of Altitude verses Maize Streak Virus disease incidence and severity ...... 30 Table 10. The mean prevalence, incidence and severity of MS across district during 2019 main croping season ...... 31 Table 11. Results of Rolling Circle Amplification of maize streak virus in samples collected from maize plants in Gambella, Oromiya and Benishangule Gumuz Regions of Ethiopia, 2019 main cropping season...... 35

LIST OF FIGURES

Figure 1. Maize streak symptoms ...... 16 Figure 2.Spatial distribution of Maize Streak Virus in surveyed regions of Ethiopia, 2019 main croping season ...... 22 Figure 3. Shows different Maize Sstreak symptoms associated with plant growth stage at the time of infection: (A) no symptoms (no infection), (B) light streaking on old leaves (mild infection); (C) moderate streaking on old and young leaves, slight stunting (severe infection); (D) severe streaking on about 60-75% of leaf area, plants stunted (severe infection); (E1-E3) Severe streaking on more than 75% leaf area, plants severely stunted or dead (very severe infection) .. 28 Figure 4. Shows Average mean Maize Streak Virus disease Incidence (%) and Severity (1-5 scale) across surveyed region...... 29 Figure 5. Shows Average mean Maize Streak Virus disease Incidence (%) and Severity (1-5 scale) across Zone ...... 30 Figure 6. The mean incidence and severity of maize streak disease by varieties sampled across the surveyed locations during the 2019 main croping season...... 34 Figure 7. A 1.3-kilo base product was ampliﬁed using a Maize Streak Virus replicative form- speciﬁc degenerate primer pair, 215–234 and 1770–1792 (Willment et al., 2001). L=The 100 bp DNA Ladder ready-to-use molecular weight marker (Solis BioDyne, Estonia), Size range of 100 – 3,000 bp and 12 numbers of bands. Nos. 1-23 is representative samples collected from surveyed regions...... 35 Figure 8. Phylogenetic tree generated by the Maximum Likelihood method of MEGAX version 10.18 based on full genome sequence alignments of reference sequences in the genus Mastrevirus. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches. The evolutionary history was inferred by using the Maximum Likelihood method and Tamura 3-parameter model (Tamura, 1992). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 51 nucleotide sequences; sixteen from this study, 34 references isolate retrved from Genbanck and one isolate from other masterovirus species used as out group. Isolates determined in this study are indicated in Italic bold fonts. Strain names and

XII

GenBank accession numbers are shown in the phylogenetic tree for each isolate.There were a total of 3612 positions in the final dataset...... 38 Figure 9. The Strain Demarcation Tool interface, Colour-coded pairwise identity matrix generated from 51 Maize streak virus genomes. Each coloured cell represents a percentage identity score between two sequences (one indicated horizontally to the left and the other vertically at the bottom). A coloured key indicates the correspondence between pairwise identities and the colours displayed in the matrix...... 40

XIII

LIST OF APPENDIXS

Appendix 1 PCR Amplification using degenerate and virus-specific primers…………….….…57

Appendix 2 Gel photograph of Genomic DNA extracted by CTAB method ………….……..…57

Appendix 3 MSV Field Survey Form/Sheet…………………………….…………………….…58

Appendix 4 MSV Field Surveyed data……………………………………………………….…59

Appendix 5 Sampling District and results of Rolling Circle Amplification....………………..…65

XIV

ABSTRACT

Maize is a major cereal crop in the world and ranks third in production after wheat and rice. It is a major staple food in Ethiopia and ranks first in production and second in area coverage next to teff. Maize production in Ethiopia is constrained by both biotic and abiotic factors, and diseases of maize caused by viruses are serious threats to maize production. Maize streak virus (MSV), which causes maize streak disease (MSD), is endemic to Africa and the major maize production constraint. An extensive survey was conducted during the 2019 main cropping season in different agro ecological zones of Gambela, Benishangul-Gumez and Oromia regions to determine the current status and distribution of the disease and characterize isolates of MSV employing PCR, Rolling circle amplification and sequencing. Maize and grasses in maize fields with suggestive MS-like symptoms were sampled for laboratory testing. Out of 127 maize fields visited, based on MS-like symptoms, the disease was prevalent in 100 (79%) fields assessed, from which 100 maize and 5 grass samples were collected for laboratory testing. High prevalence, incidence and severity of MS were recorded at low altitude areas; whereas low incidence and severity were rcorded at high altitude maize growing areas. The mean average incidence of 64%, 59% and 33%; and severity of 4.3, 4 and 3 (on 1-5 scoring scale) were, respectively, recorded in Gambela, Benshngul-gumeze and Oromia regions. Results of laboratory testing employing PCR and RCA showed that out of 100 symptomatic maize and 5 grass samples analyzed, MSV was recovered from 95 (90%) maize and none of the grass samples. This result is comparable with visual assesments made in the field, suggesting that MS assessment based on symptoms is diagnostic if attentively done. The results of sequencing and blast search analysis of RCA amplified representative isolates from Ethiopia shared 97-99% nucleotide sequence identity among themselves and with those deposited in the genebank from elsewhere in Africa, depicting that there is no significant varaiation among MSV isolates despite wide geographical isolations. Based on the results of the present study, MS is an economic disease of maize at low and mid altitude growing areas. Hence, disease management options involving development and deployment of resistant vaities along wih cultural practices should be sought.

KEYWORDS: Intensity, Maize, Maize Streak Virus, Mastervirus, Polimrase Chain Reaction Rolling Circle Amplification,

1. INTRODUCTION

Maize (Zea mays L; family Poaceae and tribe Maydeae) is not an indigenous African plant, instead its origins have been traced back to the Mesoamerican region, now Mexico and Central America (Matsuoka et al., 2002; Piperno and Flannery, 2001), and teosinte (Z. mexicana) is believed to be the ancestor of the crop plant (Warburton et al., 2011). Maize arrived in Ethiopia slightly later, around the late 17th century (Huffnagel, 1961), and was mainly grown as a subsistence crop in the mid-altitudes in southern, south-central, and southwestern parts of the country. It is a major cereal crop in the world and ranks third in production after wheat and rice (Muiru et al., 2010; Keya & Rubaihayo, 2013). Maize is one of the three leading global cereals that feed the world (Shiferaw et al., 2011). Maize, together with rice and wheat, dominate human diets (Ignaciuk, 2014) and provide at least 30% of the food calories of more than 4.5 billion.

Maize is important as a staple food in sub-Saharan Africa (SSA), providing food and income to over 300 million resource-poor smallholder farmers (Tefera et al., 2011). The crop provides high yields per unit of land, making it a key crop in ensuring food availability and security for the consumers (Mboya et al., 2011). Maize is a major staple food in Ethiopia and ranks first in production and second in area coverage next to tef (Eragrostis tef) (CSA, 2018). A total of 8.3 million tons have been produced across 2.2 million hectares of land in the 2017 cropping season (CSA, 2018). Despite its importance, however, the national average yield of maize in Ethiopia (3.4 tons/ha) is below the world‟s average (8 tons/ha) (FAOSTAT, 2017).

Maize production in Ethiopia is constrained by both biotic and abiotic factors, and diseases of maize caused by viruses are serious threats to maize production. Earlier studies of maize virus in the country revealed the presence of maize streak virus (MSV; genus Mastrevirus in the family Geminiviridae), maize chlorotic mottle virus (MCMV, genus Machlomovirus in the family Tombusviridae), maize mottle chlorotic stunt virus (MMCSV) and viruses belonging to genus potyvirus, family potyviridae such as sugarcane mosaic virus (SCMV), maize dwarf mosaic virus (MDMV) and johnson grass mosaic virus (JGMV) (Mesfin et al., 1991; Alemu et al., 1997). More than 50 virus species can infect maize (Redinbaugh and Zambrano, 2014) and among these, maize streak virus (MSV), genus Mastrevirus in the family Geminiviridae is one of the top ten economically important plant viruses (Rybicki, 2015).

Geminiviridae have circular single-stranded (ss) DNA genomes and replicate in the nuclei of their host plants via Rolling Circle Replication (RCR) (Jeske et al., 2001). Geminiviruses fall into viruses with monopartite (one circular ssDNA genome component) or bipartite genomes components (two circular ssDNA genomes component with similar size (King et al., 2012).

Virus species in the genus Mastrevirus have monopartite genomes of approximately 2700 nt encapsidated in geminate particles encoding four proteins separated by two intergenic regions (large intergenic region [LIR] and small intergenic region [SIR]. The viron sense strand encodes two proteins; the movement protein (MP), functioning in cell to cell movement, and the coat protein (CP), which encapsidates the virion sense ssDNA and acts as the nuclear shuttle protein (NSP) for viral DNA. The complementary sense strand encodes the replication-associated proteins Rep and Rep A (King et al., 2012). In maize, symptoms of MSD include morphological teratology which is characterized by leaf margin splitting, broad-pale, cream colored to light green or yellow parallel leaf vein streaking, tip twisting, and necrosis of emerging leaves, reduced leaf size, tassel sterility and shoot stunting (Oppong et al., 2015).

Maize streak (MS) is one of the most severe and widespread diseases that adversely reduces maize production thereby posing a threat to food security (Dhau et al., 2017). The most extensively sampled and studied mastrevirus species is maize streak virus: the causal agent of maize streak disease (MSD), the most significant viral disease of maize (Zea mays) in Africa (Harkins et al., 2009; Monjane et al., 2011; Oluwafemi et al., 2014; Oppong et al., 2015; Pande et al., 2017; Varsani et al., 2009). Maize streak disease causes yield losses that range from trace to almost 100% if infection occurs in the ﬁrst three weeks of planting maize (Bosque-Pe´ rez and Buddenhapen, 1999; Kyetere et al., 1999; Alegbejo et al., 2002). The disease is distributed throughout the African continent and surrounding islands (Monjane et al., 2011) and is one of the most economically significant member of the Geminiviridae family (Bosque-Perez, 2000). Globally, MSD is regarded as the third most serious disease of maize after turcicum leaf blight (TLB) and gray leaf spot (GLS) (Pratt & Gordon, 2006). In Africa, however, MSD is a bigger problem than both TLB and GLS (Martin & Shepherd, 2009).

Epidemics resulting in economic losses of up to 100% have been reported in at least 20 African countries including Ethiopia, Nigeria, Ghana, Sudan, Cameroon, Zimbabwe, Tanzania, Togo,

Benin, Burkina Faso, Sao Tome and Uganda (Lagat et al., 2008). In East Africa, MSD has been identified as a major constraint to maize production in Ethiopia (Mesfin et al., 1995; Alemu et al., 1997; Demsachew et al., 2019), Kenya (Magenya et al., 2008; Martin & Shephered, 2009) and Uganda (Owor, 2008). In Ethiopia, the disease was reported to be severe in low to mid altitudes areas and mid highland zones (Demsachew et al., 2019). In situations of severe disease incidence, MSD can result in up to 100% yield loss, especially when susceptible genotypes are infected (Danson et al., 2006), which is a major contributor to shortages of this staple in endemic regions. During the most severe epidemics, the disease frequently causes 100% yield losses in individual fields. However, it will never destroy 100% of the maize yield in an entire country (Martin and Shepherd, 2009).

Taxonomically, viruses within mastrevirus species (i.e., groups of mastreviruses sharing greater than 75% genome-wide sequence similarity) have been subcategorized into strains containing isolates sharing 91% genome-wide sequence similarity and subtypes containing isolates sharing 98% similarity (Fauquet et al., 2008; Martin et al., 2001). Three Mastrevirus species have been reported in maize. MSV and maize streak reunion virus (MSRV) (Pande et al., 2012) are typical African viruses; the recently described maize striate mosaic virus (MSMV) is present in Brazil (Fontenele et al., 2018).

Eleven distinct MSV strains, classified as MSV-A to MSV-K, have been identified, of which only MSV-A is the most prevalent, with a devastating impact on maize crops while majority of the rest are adapted to infecting wild grass species (Willment et al., 2001; Monjane et al., 2011; Yahaya et al., 2016). MSV-A has further been subdivided into five subtypes, MSV-A1 to MSV- A4 and MSV-A6, each being reported in different parts of SSA (Varsani et al., 2008; Monjane et al., 2011). MSV-A is the predominant subtype in Uganda (Owor et al., 2007). MSRV only recently described in 2012 from La Réunion Island (Pande et al., 2012) and later also reported from uncultivated grass species, Setaria barbata and Rottboellia sp. from Nigeria (Oluwafemi et al., 2014), and in addition from maize in China (Chen et al., 2015) indicating its wider geographical distribution and host range. Recently, it also reported in Ethiopia from maize plant in 2019 (Demsachew et al., 2019).

Maize streak virus transmitted persistently by leaf hoppers–Cicadulina species (Mylonas et al., 2014; Thottappilly et al., 1993; Nderitu, 1999). There are 22 recognized species of Cicadulina, 18 of which occur in Africa (Webb, 1987). Nine species have been shown to be important vectors of MSV viz., C. mbila. C. similis, C. arachidis, C. storeyi (= triangula), C. bipunctata, C. latens, C. ghaurii, C. niger, and C. parazeae (Fajinmi et al., 2012; Mesfin et al., 1991; Dabrowski, 1987; Webb, 1987).

1.1. Statement of the Problem

Maize streak (MS) is a serious threat to maize production in Ethiopia. It is an important problem of low and mid-altitudes grown maize in Ethiopia; causing considerable losses to yield and yield components of the crop. However, empirical data on the economic significance of MS was not established through systemic, intensive and extensive surveys representing important maize agro-ecologies. Most what has been known so far was based on symptoms description, which can vary from one agro-ecology to another, from variety to variety and crop growth stage at the time of infection.

The application of molecular tools to diagnose MSV further support to attain the above mentioned lacking information efficiently, as such studies employing molecular tools elsewhere on maize and other crops have benefited not only for more accurate identification of virus species but also for more detailed understanding of the genetic variability within a virus species which is important prerequisite for successful improvement program. Limited research has been done on characterizing MSV isolate in Ethiopia.

This study was conducted to assess the intensity of maize streak diseases and to characterize different MSV isolates collected from western parts of maize growing regions of Ethiopia.

1.2. Objectives

1.2.1. General Objective

 To characterize MSV isolates and determine relative distribution and importance of the disease in major maize growing agroecologies

1.2.2. Specific Objectives

●To assess the status of Maize Streak in Ethiopia

●To detect Maize Streak Virus employing direct polymerase chain reaction (PCR) and rolling circle amplification (RCA).

●To assess MSV distribution in association with altitude range and crop Variety

2. LITERATURE REVIEW

2.1. The Host: Maize/Origin and Distribution of Maize

Maize (Zea mays L.), called corn in some region of the world, is a grass of tropical origin that has become the major grain crop in the world in terms of total production, with recent production around 800 million tons per year. It is one of the oldest human-domesticated plants (Abdolreza Abbassian, 2006). Most maize grain produced is used as animal feed; in less developed countries it is, however, also a staple food. It is also used as raw material for many industrial uses, including bio-fuel production (Mengistu, 2016).The name maize is derived from Arawak-Carib word mahiz and the term corn most likely originates from the Germanic „korn‟ which referred to any edible grass. It is also known as corn in North America. It is important staple crop in east Africa (FAOSTAT, 2017) and is one of the most widely cultivated gramineous plants in the regions due to its ability to grow in diverse climates (Mengistu, 2016).

Maize (family Poaceae and tribe Maydeae) is not an indigenous African plant, instead its origins have been traced back to the Mesoamerican region, now Mexico and Central America (Matsuoka et al., 2002; Piperno and Flannery, 2001), and teosinte (Z. mexicana) is believed to be the ancestor of the crop plant (Warburton et al., 2011).

Maize is the third most important cereal crop next to wheat and rice worldwide (FAOSTAT, 2017). The crop is also the most important grain covering wider areas than other grains in sub- Saharan Africa (Smale et al., 2011), widely grown for food and cash in a broad range of environments (CIMMYT, 2014). In Ethiopia, maize is the most principal crop covering 2.14 million ha of land next to Teff (Eragrostis tef (3.02 million ha)). Out of the total areas covered by maize, 7.85 million tons have been produced in the 2016/17 main cropping season (CSA, 2017). Maize is Ethiopia's largest cereal crop in terms of total production, area planted, and number of farm holdings. Corn accounts for 20 % of the total area covered by cereal and around 30 % of the total cereal production. In addition to the highest total production per year and the highest per 23 hectare yield, corn is also the single most important crop in terms of the number of farmers engaged in cultivation (Tefera et al., 2011).

2.2. Production Constraints

2.2.1. Abiotic constraints

The major abiotic constraint is drought that causes an annual yield loss of about 15% (Kamara et al., 2003), while the second most important constraint is nitrogen and phosphorus deficiency (Whitbread et al., 2004). Soil fertility was one of the most serious constraints to maize production. Due to a number of socio-economic factors, the primary input into maintaining and improving soil fertility is manure/compost. Farmers complained that they do not have access to adequate quantities of manure/compost because of diminishing access to quality fodder for their animals. In comparatively accessible areas, fertilizer is used to supplement manure/compost. Traditional planting, lodging and weeding practices are labor intensive and have significant impact on productivity (Paudyal et al., 2001).

2.2.2. Biotic Constraints

Farmers identified a wide range of field insect pests, including corn borer, cutworm, and corn leaf aphid, which were common across all the maize agro-ecological regions. Problems with other insects such as mole cricket, wireworm, armyworm, and red spiders varied across maize systems. Caterpillars, grasshoppers, and weevils are also among the damaging insects (Meng et al., 2006). White grubs (Phyllophaga spp. and Cyclocephala spp.), stem borers (Chilo partellus), and termites (Microtermes spp. and Macrotermes spp.) were major maize field insects in all agro-ecologies. Army worms (Spodoptera spp.) and cutworms (Agrotis spp. and other species) were also major problems in all agro-ecologies (Paudyal et al., 2001).

Diseases identified by farmers included head smut (Sphacelotheca reiliana), turcicum blight (Helminthosporium turcicum), downy mildew (Sclerospora spp.) and Banded leaf and Sheath blight (Rhizoctonia solani). Turcicum Leaf Blight is ubiquitous in hill environments and can cause severe losses if the variety does not have good genetic resistance. The viral diseases of maize that listed according to the sixth report of the International Committee on Virus Taxonomy (ICTV) (Fauquet et al., 2008) lists maize chlorotic dwarf virus (MCDV); maize chlorotic mottle virus (MCMV); maize dwarf mosaic virus (MDMV, Potyvirus); maize mosaic virus (MMV) and maize sterile stunt virus (MSSV); maize streak virus (MSV, Geminiviridae, Mastrevirus); maize

7 stripe virus (MStV, Tenuivirus) and maize white line stripe viruses (MWLMV, unassigned) as viruses mainly occurring in maize.

2.3. Maize streak virus disease

Mastrevirus are known to infect both monocot and dicot plants. Monocot-infecting mastrevirus are found primarily in Africa and still a major threat in crop productions in the continent. Of mastreviruses, maize streak virus was firstly reported in Natal, South Africa in 1901 (Fuller, 1901). Maize streak virus (MSV) is an economically signiﬁcant plant pathogen because of its detrimental effect on the yields of a variety of cereal crops, including maize, wheat, oats, barley, rye, ﬁnger millet, pearl millet, sorghum and Napier fodder (Willment et al., 2001). Maize streak virus disease was initially named as „mealie variegation,‟ but later renamed „maize streak virus disease’ in 1925 (Storey, 1925). It is the most economically significant member of genus Mastrevirus of the family Geminiviridae (Willment et al., 2001; Bosque-Perez, 2000; Schnippenkoetter et al., 2001; Varsani et al., 2008).

MSV is indigenous to African grasses and is transmitted by leafhoppers of the genus Cicadulina (Homoptera: cicadellidae) (Markham et al., 1984; Bosque-Pérez et al., 1998; Mylonas et al., 2014). Other African streak viruses identified include Panicum streak virus (PanSV), sugarcane streak virus (SSV), sugarcane streak mauritius virus (SSMV) and sugarcane streak Egypt virus (SSEV) (Bigarré et al., 1999; Wilment et al., 2001). Several studies have closely related MSV isolates from Africa and the neighbouring Indian Ocean islands of Madagascar, Mauritius and La Réunion have been Identification (Pernet et al., 1999; Willment et al., 2001).

2.4. Morphology of the MSV virus

Geminiviruses in the genus Mastrevirus are plant-infecting DNA viruses with a monopartite genome consisting of circular single stranded DNA (ssDNA), encapsidated in a characteristic geminate morphology, that has a quasiicosahedral particle of 18 x 30 nm in size (Bosque-Perez, 2000; Alegbejo et al., 2002). The MSV genome is composed of a DNA molecule of ca. 2.6 kb which codes for four potential products (Isnard et al., 1998). These viruses rely on the plant host cell machinery for DNA replication and transcription which takes place in nondividing host cells (Lucy et al., 1996; Munoz-Martin et al., 2003). It is not yet known how mastreviruses achieve

8 replication and expression of their genomes in differentiated cells, but some clues are inferred from the proteins which they encode.

2.5. Origin of Maize streak Virus Disease

Maize streak virus (MSV) belongs to the genus Mastrevirus of the Geminiviridae family. Geminiviridae have circular single-stranded (ss) DNA genomes and replicate in the nuclei of their host plants via Rolling Circle Replication (RCR) (Jeske et al., 2001). Geminiviruses fall into viruses with monopartite (one circular ssDNA genome component) or bipartite genomes components (two circular ssDNA genomes component with similar size) (King et al., 2012). The genus Mastrevirus (family Geminiviridae) contains species that infect monocotyledons or dicotyledons (King et al., 2012). It is an indigenous African virus transmitted by a range of leafhoppers in the genus Cicadulina (Storey, 1925) and causes maize streak disease (MSD), the most damaging viral disease of the crop in Africa (Thottappilly et al., 1993). MSV is indigenous to Africa, including the adjacent Indian Ocean Islands of Reunion, Mauritius and Madagascar (Willment et al., 2001; Fajemisin, 2003). The disease occurs in the forest and the savanna zones from sea level to 1800m (meters above sea level MASL) (Bjarnason, 1986). Disease incidence and destructiveness varies from year to year and from season to season (Rossel and Thottappilly, 1985).

Maize streak virus disease (MSVD) was first reported in South Africa by Claude Fuller, 1901(cited by Shepherd et al., 2010 and Oppong et al., 2013). Fuller also quoted personal sources who noticed the disease of „mealie variegation‟, as it was then described, as early as the 1870s. The disease was therefore not new at that time, and had probably been around as long as maize had been grown in the region. Fuller‟s investigation of MSVD was motivated by an increase in incidence of the disease, marked by a serious outbreak in 1896. Although Fuller was ignorant as to its cause, he thought it was caused either by a soil nutrient deficiency or a „chemical enzyme‟ acquired from the soil, he accurately described many features of the disease as it manifests today.

2.6. Economic Importance of Maize streak Virus Disease

There is a close relationship between plant age, time of infection, and the yield losses that accrue due to maize streak disease (Bosque-Perez et al., 1998). Maize streak disease has played a major role in maize production in Africa although the importance of MSV on maize varies from place to place or location to location (Damsteegt and Igwegbe, 2005). Increased prevalence of maize production is directly correlated to the increases 1in MSV disease (Oppong et al., 2013). MSVD currently remains the most significant viral disease of maize in Africa (Bosque-Pérez, 2000) costing between US$120M and US$480M per year according to a conservative estimate based on average annual yield losses of only 6%–10% (Martin and Shepherd, 2009). In situations of severe disease incidence, the disease can result in up to 100% yield loss especially when susceptible genotypes are infected (Danson et al., 2006), which is a major contributor to shortages of this staple in endemic regions.

Doyle and Autrey (1992) reported a 91% reduction in grain production when plants were infected at 3-5 leaf and a 65% reduction when infection occurred at 7-10 leaf stage. During the most severe epidemics the disease will frequently cause 100% yield losses in individual fields it will never destroy 100% of the maize yield in an entire country (Martin and Shepherd, 2009).What the “100%” statistic usually refers to is that if a susceptible maize seedling is infected with a virulent strain of MSV before it reaches the 2nd leaf stage it will not yield any seed, hence it will suffer a 100% yield loss. If such a susceptible maize seedling is infected at the 4th leaf stage it will yield 45% less and if it is infected still later at the 10th leaf stage it will produce a seed mass that is approximately 25% lower than that produced by an uninfected plant (Bock, 1982).

Plants attacked at early stages of growth (up to seven-leaf stage) sustain losses of 80% or more, while those attacked shortly thereafter (at the nine-leaf stage), incur only 20% yield loss (Oppong et al., 2013). Infection of a maize crop in the first three weeks of planting often results in 100% yield loss (Bosque-Perez and Buddenhagen, 1999), equally, a maize crop that is planted at the end of a rainy season seems to be most severely affected. According to Demsachew et al. (2018) report a high incidence of MSV was found in the Ethiopia (Benishangul-Gumuz region) (58%). Demsachew et al. (2019) as revealed from PCR results, both MSV (100%) and MSRV

(36%) have higher incidence in samples collected during August 2015 (late main rain feed cropping season).

2.7. Prevalence and Distribution of MSV

A survey carried out since 1990‟s in the Sub-Saharan Africa showed the prevalence, and distributions of MSV in the continent (ISAAA, 1999). Maize streak virus (MSV) is one of the most severe and widespread diseases that adversely reduces maize production thereby posing a threat to food security (Dhau et al., 2017).The most extensively sampled and studied mastrevirus species is Maize streak virus: the causal agent of maize streak disease (MSD), the most significant viral disease of maize (Zea mays) in Africa (Harkins et al., 2009; Monjane et al., 2011; Oluwafemi et al., 2014; Oppong et al., 2015; Pande et al., 2017; Varsani et al., 2009).

Serious MSV epidemics have been reported in south Africa, west Africa, central Africa and east Africa, more than 20 African countries including Angola, Benin, Burkina Faso, Cameroon, Democratic Republic of Congo, Ghana, Kenya, Ethiopia, Uganda, Malawi, Mozambique, Nigeria, Zambia and Zimbabwe (Alemu et al., 1997; Demsachew et al., 2018; Owor et al., 2007; Lagat et al., 2008; Magenya et al., 2008). Of the several currently recognized master viruses, maize streak virus (MSV) is widespread across the African continent and ranks among the top 10 economically most important plant viruses (Rybicki, 2015). Up to 11 strains of MSV, named in alphabetical order from MSV-A to MSV-K, have been characterized to date, among which the maize-adapted MSV-A is the most prevalent, with a debilitating impact on maize crops across Africa(table 1) (Martin et al., 2001;Yahaya et al., 2016). The disease has the most devastating effects because it can result in complete crop failure (Bosque-Perez, 2000).

Diseases of maize caused by viruses are serious threats to maize production in Ethiopia. Earlier studies of maize virus in the country revealed the presence of Maize streak virus (MSV). The virus is widely distributed along with leaf hopper vectors and similar isolates were also detected from grass hosts (Alemu et al., 1997; Mesfine et al., 1991; Demsachew et al., 2018).

2.8. Genome Organization and Molecular Characterization

Maize streak virus (MSV) has an approximately 2.7 kilobase sized, circular, single stranded DNA (ssDNA) genome (Howell, 1984; Lazarowitz, 1988; Zhang et al., 2001), that replicates via

11 rolling circle and recombination-dependent mechanisms (Preiss and Jeske, 2003), and encodes four proteins: (i) a Movement protein (MP) through gene V1; (ii) a Coat protein through gene V2; and two Replication associated proteins, (iii) Rep, encoded by post-transcriptionally spliced C1 and C2 genes, and (iv) RepA, which is only encoded by the C1 gene (Pratt and Gordon, 2006). Bidirectional transcription from the long intergenic region (LIR) leads to virion sense expression of the MP and the CP and the complementary-sense expression of the replication- associated proteins, Rep and RepA respectively. These four proteins each play significant roles during host infection.

Movement protein (MP) and coat protein (CP) encoding genes are required for systemic infection of host plants by MSV (Lazarowitz et al., 1989; Woolston et al., 1989; Madzokere, 2015). The MP facilitates cell-to-cell movement of virus within the host, whereas the CP is required both for entry of viral DNA into the nucleus and the inter-cellular movement of viral DNA, whilst the replication-associated proteins, Rep and RepA, enable usurping of the host replication machinery and rapid production of high copy numbers of viral progeny (Preiss and Jeske, 2003; Zhang et al., 2001). Peterschmitt et al. (1991) characterized MSV isolates from 11 African countries and regarded them all as being of the same serotype. The use of RFLP and polymerase chain reaction has been the most applied molecular technique in the characterization of MSV with good results. Martin et al. (2001) described the use of PCR and RFLP in the typing of 49 MSV isolates.

There are 11 known strains of MSV namely MSV-A to MSV-K (Shepherd et al., 2010; Monjane et al., 2011). The MSVA strain causes the most severe and economically relevant form of MSD. It has five strain variants namely: MSV-A1, MSV-A2, MSV-A3, MSV-A4 and MSV-A6. These variants have different geographical ranges. MSV-A1 is the most widely distributed, occurring in every part of sub-Saharan Africa. Zimbabwe has MSV-A1 and MSV-A4 variants while South Africa has MSV-A1, and MSV-A4, in addition to MSV-B, MSV-C, MSV-D and MSV-E (Martin et al., 2001; Varsani et al., 2008). The MSV-A1 and MSV-A2 variants produce the severest symptoms; MSV-A3 and MSV-A6 produce intermediate symptoms and MSV-A4 produces the mildest symptoms (Magenya et al., 2008). The MSV-B to MSV-K strains infects crops other than maize (Willment et al., 2002)

2.9. Virulence of MSV strains

Martin et al. (2001) detected important differences between the virulence of different MSV-A subtypes in maize. Subtypes A1, A2, and A5 isolates produce the severest symptoms, subtypes A3 and A6 isolates produced intermediate symptoms, while subtype A4 isolate produced the mildest symptoms. Severe isolates cause earlier symptoms with wider and more chlorotic streaks than the mild isolates (Bosque-Pérez, 2000; Martin et al., 2001). The MSV-B, -C, -D, and -E isolates on the other hand, were substantially less severe than the MSV-A isolates. The extent of MSV diversity, host specificities, geographical distributions, and virulence in maize is fairly documented (Rybicki et al., 1998; Schnippenkoetter et al., 2001; Martin et al., 2001; Willment et al., 2002). However, little is known about the comparative transmission of the different strains of MSV by the different geographical populations of C. mbila vector.

Table 1. Origin of MSV isolates and the grouping of strains from different plant host in some African countries.

______

Country of origin Host Strain grouping Kenya Maize MSV – A1, A3 Grass host MSV –B Zimbabwe Maize MSV – A1 Nigeria Maize MSV – A2 Réunion Maize MSV – A6 South Africa Maize MSV-C, MSV-A4, A5 Grass hosts MSV - D, E

Source: Martin et al. (2001).

2.10. Host Range of MSV

Maize streak virus infects a range of wild and cultivated grass species. Other than maize, Maize streak virus infects other crops such as rice (Oryza sativa L.), wheat (Triticum aestivum L.), oats (Avena sativa L.), barley (Hordeum vulgare L.), rye (Secale cereale L.), finger millet (Eleusine coracana L.), pearl millet (Pennisetum typhoides L.), sorghum (Sorghum bicolor L.) and

13 sugarcane (Saccharum officinarum L.) (Willment et al., 2001; van Antwerpen et al., 2011; Alegbejo et al., 2015) and wild species belonging to the following genera: Sporobolus, Eleusine, Paspalum, Brachiara, Imperata, Rottboelia, Dactylocterium, Eragrostis, Diplachne, Leptochloa, Setaria, Tragus, Euchlanaena and Coix (Rose, 1978; Mesfin et al., 1992). There were several grass species that were found with symptoms in Nigeria (Oluwafemi et al., 2014). Beside maize other grass hosts also were reported from Ethiopia (Table 3) (Alemu et al., 1997).

Table 2. Maize Streak Virus detected from grass hosts in Ethiopia ______

Region Grass host species Virus Locations ______Wellega Digitaria sp MSV Lugo Eluesine p ″ Haroalalitu Rottboelia exaltata ″ Lugo Panicum sp ″ Bareda Penisetum sp ″ Loko Shewa Eluesine indica ″ Ambo ______Source: Alemu et al. (1997)

2.11. Symptoms Expression

Symptoms of MSV vary according to the MSV isolate. The specificity of MSV infection in maize tissues shows that the virus occurs only in vascular tissues and does not invade the apical meristems within the shoot apex (Lucy et al., 1996; Magenya et al., 2008; Shephered et al., 2010). However, in mature tissues which display streak symptoms, the virus is not restricted to vascular tissues. In fact the MSV coat protein and both positive and negative strands of the MSV genome were detected in mesophyll, bundle sheath cells and vascular-associated parenchyma of the leaf (Lucy et al., 1996; Magenya et al., 2008). Symptoms of MSV tend to appear quicker in younger maize plants: 3 to 5 days in a one-week-old plant, and 7 to 9 days in a 9-week-old plant (Mesfin et al., 1995). Maize streak disease first presents as round yellow spots scattered on the youngest leaves and subsequently streaks develop at an increasing density (Thottapilly et al., 1993).

The symptoms are characterized by broken to almost continuous chlorotic stripes centered on the tertiary leaf veins (Pinner et al., 1988; Karavina, 2014). They first manifest as minute pale circular spots on the lowest exposed part of the leaf. Only new leaves develop the symptoms of virus infection while leaves below the point of infection remain healthy (Hill and Waller, 1998). The spots develop into discontinuous pale yellow streaks, up to several millimeters in length, along the blades, parallel to the veins or broken chlorotic streaks on secondary or tertiary veins with primary veins being less affected than secondary and tertiary veins. The longitudinal chlorotic streaking causes a concomitant reduction in photosynthetic area, growth and yield of the plant. The streaks often fuse laterally to give narrow broken chlorotic stripes which may extend over the entire length of fully affected leaves.

Severe chlorosis occurs in very susceptible maize cultivars, leading to stunted growth and premature death, poor ear formation, reduced seed setting, and heavy yield losses (Monjane et al., 2011). The highly sensitive maize varieties develop chlorosis of the entire leaf lamina, followed by plant death, particularly if infection occurs at an early stage of plant growth (Mesfin et al., 1995; Bosque-Pérez et al., 1998).The chlorosis is caused by failure of chloroplasts to develop in the tissue surrounding the vascular bundles and these results in reduced photosynthesis and increased respiration leading to reduction in leaf length and plant height (Mesfin et al., 1995). Thus maize plants infected within the first three weeks after emergence become severely stunted producing considerable abnormal cobs or giving no yield at all (Okoth et al., 1987). If infection occurs more than eight weeks after plant emergence, the virus does not normally cause significant economic loss (Page et al., 1999). Maize yield reduction due to MSV in susceptible varieties often exceeds 70% (Bosque-Pérez et al., 1998).

Source: Karavina, 2014 Figure 1. Maize streak symptoms

2.12. Epidemiology MSVD

MSVD is endemic to Africa and its adjacent Indian Ocean Islands. The disease occurs in the forest and the savanna zones from sea level to 1800m (meters above sea level MASL) (Bjarnason, 1986). A number of factors that may broadly be classified as ecological, climatic, genetic, sociopolitical, economic, and physical, have been observed to affect and influence MSVD epidemiology (Martin and Shepherd, 2009; Shepherd et al., 2010). Extremely complex interactions between these factors, which appear to converge every three to ten years, are believed to produce conditions that promote MSV dispersal and an increase in MSD incidence on the continent and the adjacent Indian Ocean Islands (Madzokere, 2015).

MSD outbreaks have largely been difficult to predict firstly because of the erratic manner in which they occur, and secondly, because the aforementioned factors include interactions among multiple MSV and African streak virus strains that increase the diversity, distribution and possibly the range of plant hosts accessible to epidemiologically relevant MSV-A strain variants; the distribution, host range and interactions of the nine vector species of leafhoppers in the Genus Cicadulina (Rose, 1974; Dabrowski et al., 1987; Nielson, 1986), and finally the ability of such viruses to persist in over 80 grass species (Konate and Traore, 1992). Furthermore, it is also

16 clear that climatic (temperature, rainfall, relative humidity) and geographical factors that influence the composition of grass and leafhopper populations also add to the complexity of MSD epidemiology (Reynaud et al., 2009).

This is reflected by reports suggesting that MSD outbreaks occur more frequently in locations that lie anywhere from sea level up to an altitude of 2000 meters (Magenya et al., 2008), have high average annual temperatures and precipitation (Asanzi et al., 1994), where drought conditions are followed by irregular rains at the beginning of the growing season (Bjarnason, 1986; Welz et al., 1998), are MSV diversification hotspots (Monjane et al., 2011), and during the second season where there are two maize growing seasons a year (Martin and Shepherd, 2009). One component of the virus-host-vector interaction network that almost certainly plays a predominant role in driving fluctuations in MSD incidence is the density of leafhopper populations.

Of the various leafhopper species that can transmit MSV, Cicadulina mbila is probably the most important mainly because it has both a wider geographical range and a greater capacity to transmit MSV than the other leafhopper species (Martin and Shepherd, 2009). When MSV first enters a susceptible maize crop the secondary transmission of MSD to uninfected plants is influenced by both the population density of viruliferous leafhoppers and the concentrations of viruses within the salivary glands of viruliferous individuals (Rose, 1978). Economic factors that include exorbitant pesticide prices, poorly implemented MSD agronomic management practices, and systematic flooding of the African maize seed-market with low-to-negligible MSV - resistant varieties by seed companies and traders also make it difficult to understand MSD epidemiology and predict the occurrence of outbreaks (Martin and Shepherd, 2009).

2.13. Vector Transmission of MSV

MSV is obligately transmitted by several species of leafhoppers of the genus Cicadulina (Cicadelidae: Homoptera) in a persistent manner (Bosque-Perez et al., 2000; Magenya et al., 2008). The most important vector is Cicadulina mbila (Naude) which has a wider geographical range and greater capacity to transmit the virus than any of other leafhopper species (Karavina, 2014). There are 22 species in the genus, 18 of them occur in Africa, 9 of which are known to be vectors of MSV (Oluwafemi et al., 2007; Mylonas, et al., 2014). In Africa, C. mbila is found in

17 most central and southern sub-Saharan countries, including Angola, Botswana, Congo, Ethiopia, Kenya, Mauritius, Mozambique, Namibia, Nigeria, South Africa, Swaziland, Tanzania, Togo, Uganda, Zaire, Zambia, Zimbabwe, and adjacent islands Cape Verde and Reunion (Reynaud et al., 2009; Mylonas et al., 2014). Female leafhoppers are two to three times more capable of transmitting the virus than males (Oluwafemi et al., 2007). The Cicadulina species are generally considered as grassland species. They are present in wild and pasture throughout the year, but can migrate in large numbers to maize (Mylonas et al., 2014).

According to Mylonas et al. (2014) report indicated the life cycle of C. mbila includes three developmental stages: egg, nymph and adult. The nymphal stage has five instars C. mbila will complete 5-8 generations depending on location, rain and host availability. Females lay their eggs in the leaf tissue, usually near the main vein. Eggs are creamy-white, elliptical and narrow, and their size range is 0.3 to 0.5 mm long by 0.1 mm in diameter. Eggs hatch within 7 to 35 days depending on temperature, and young nymphs take 14 to 20 days to become adults at 25 °C. It is not known to diapause or have any other form of dormancy. It develops throughout the year, with periods of prolonged development. Fertilized leafhoppers prefer wild grassed for oviposition. MSV is neither seed borne nor mechanically transmissible.

Cicadulina mbila occurs in the more humid areas of Ethiopia (Mesfin et al., 1991) and throughout sub-Saharan Africa (Reynaud et al., 2009). The lower threshold was set to approximate the permanent wilting point for plants (Kriticos et al., 2003); the upper threshold makes relatively wet areas suitable. Mylonas et al. (2014) indicates that as temperatures approach freezing, mortality of adult‟s increases, and there is no physiological mechanism to allow overwintering of C. mbila in cold climates. This implies that low temperatures (around 0°C) will induce mortality.

Mesfin et al. (1991) indicated that weed grasses are common on cultivated land and adjacent areas, and play an important role as alternative hosts maintaining the vector populations and acting as virus sources. During and between maize-growing seasons‟ populations of leafhoppers build up on the weeds and move to the maize fields when the crop is planted. The feeding behavior, host preference and fecundity on different hosts were shown to be important factors determining the distribution of the Cicadulina species. MSV disease was very evident on most of the maize fields surveyed in southwestern and western Ethiopia, and was particularly common in

18 late-sown crops. The role of C. mbila as the most important vector was emphasized by subsequent comparisons of transmission efficiency between Ethiopian populations of C. mbila and C. bipunctella which are 70-96% and 16%, respectively.

As Mesfin et al. (1991) indicate in the (Table 3). C. bipunctella, C. ghaurii, C. niger, C. mbila and C. storeyi were identified and only C. bipunctella transmitted MSV in the altitude range of 450-2000m. However other report showed that Cicadulina mbila which has a greater capacity to transmit the virus than any of other leafhopper species (Karavina, 2014) and found in most central and southern sub-Saharan African countries (Reynaud et al., 2009; Mylonas et al., 2014). Comparison of transmission efficiencies of Cicadulina species by Asanzi et al. (1995) showed that C. ghauri and C. arachidis are less efficient vectors; require more acquisition access feeding time than C. mbila and C. storeyi. C. mbila an efficient MSV vector (Rose, 1978), was the most common species in all ecological zones.

The transmission efficiency increases with increasing duration of acquisition and inoculation feedings (Asanzi et al., 1995). The relative abundance of various Cicadulina species with differing abilities to transmit the virus in different parts of Africa is influenced by altitude, temperature and rainfall (Dabrowski et al., 1987). Environmental factors that drive the long distance movement of leafhoppers (Rose, 1978).wind, rainfall shortage of available food sources. A healthy hopper after feeding on a diseased plant did not become infective for approximately 12 hr at temperatures as high as 30°-35°C and this latent period was increased to 85 hr at 16°C. Higher transmission efficiencies of C. mbila and C. storeyi might be linked to longer pathway and shorter time per probe (Rose, 1978). C. storeyi and C. mbila had longer pathway durations than C. arachidis and C. dabrowskii indicating longer salivation and searching for phloem. This might enhance the abilities of C. storeyi and C. mbila to inoculate maize seedlings with MSV, as they spend longer times salivating and searching for phloem cells (Asanzi et al., 1995).

Table 3. Distribution and incidence of Cicadulina species and maize streak virus in different maize growing regionsof Ethiopia

Region Locality Altitude (m) Habitat Species recorded Number of Mean insects percentage of collected MSV-infected maize Harerghe Alemaya (1)t 1980 C/G C. bipunctella 452 0 Ameresa (2) 1830 G C. bipunctella 23 0 Boreda (3) 2230 G C. bipunctella 10 0 Kulubi (4) 2300 G C. bipunctella 11 0 Gellemso (5) 1760 C/G C. bipunctella 11 0 Aseb Tefferi 1700 C/G C. bipunctella 24 0 (6( Mieso (7) 1600 C C. bipunctella 6 0 Shoa Awash (8) 900 C C. bipunctella 16 0 Wengi (9) 1540 C C. bipunctella 14 0 C. ghaurii 4 0 C. niger 8 0 Sidamo Awassa (10) 1750 C/G C. bipunctella 17 1-5 Dilla (11) 1640 G/C C. bipunctella 4 1-2 Illubabor Metu (12) 1740 G C. bipunctella 7 0 Bedelle (13) 2000 G C. bipunctella 11 2-5 Gore (14) 2000 C/G C. bipunctella 6 1-1 Gambella (15) 480 C/G C. Mbila 1 65 C. bipunctella 12 C. mbila 108 C. storeyi 10

Keffa Jimma (16) 1720 G C.bipunctella 7 1 Agaro (17) 1500 G C.Bipunctella 4 1-3 Gibe (18) 1300 C/G C.bipunctella 6 3 C. mbila 13 Wellega Assossa (19) 1550 C/G C. Bipunctella 16 Gimbi (20) 1800 2000 G C. mbila 45 Nekemete 1250 G C. bipunctella 9 (21) Deddessa 1640 C/G C. bipunctella 5 (22) C/G C. bipunctella 7 Bako (23) C. Mbila 31 C. bipunctella 11 C. mbila 16

Source: Mesfine et al. (1991)  G: gass, C/G crop and grass host

3. MATERIALS AND METHODS

3.1. Assessment and Geographical Distribution of Maize Streak Disease

An extensive field surveys were conducted in Oromia (east Welega, west Welega, Jimma, Buno Bedele), Benishangul-Gumz and Gambela (Agnuwak, Nuer) regions of Ethiopia. In these regions maize, in most cases, is cultivated in monoculture, as the major crop by small holder farmers (CSA 2018). The surveys were made from July to October 2019 main cropping season.

Most of the surveyed maize fields were at a vegetative growth stage ranging in size from knee height to early tasseling. The surveys were made along road-sides with approximately five to ten kilometer intervals wherever the crop was available. Sampling was done using simple random sampling technique, and assessment was made diagonally along field at five spots. At each spot representative symptomatic samples with characteristic MS symptoms was collected and all field collected samples were bulked and desiccated in calcium chloride and silica gel for later laboratory testing. Suspected symptomatic alternative grass hosts of harboring MSV in each field were also collected and preserved as described for maize above for laboratory analysis.

Data related to crop variables such as growth stage, variety, date of sowing, previous crops, crop performance, insect vectors and location, etc... were recorded. Altitude and Geographical position of survey locations was recorded using geographical positioning system (GPS) at each field. Information on agro-ecological zones was obtained from the Ministry of Agriculture (MOA, 2005). A total of 127 maize fields were visited, and 105 maize and 5 grass samples were collected. Leafhoppers suspected of vectoring MSV were also collected from some fields.

Table 4. Major agro-ecological zones of surveyed areas for maize streak in Ethiopia ______

Agro-ecological zone Altitude (m.a.s.l) Regions

Moist lowlands <1000 Gambela Moist lower &dry mid-altitudes 1000-1700 W Oromia & BSG Moist and semi-moist mid-altitudes 1701-2000 W Oromia & BSG Moist upper mid-altitudes 2001-2400 W Oromia

Adapted from (MOA, 2005)

Figure 2.Spatial distribution of MSV in surveyed regions of Ethiopia, 2019 main croping season

3.2. Assessment of MS Incidence and Severity in the field

The incidence of MS were determined by visually observing and recording the number of maize plants showing the disease symptoms and the percentage incidence was calculated as follows:

Disease severity were assessed 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 (Table 4) (Oppong et al., 2013; Blankson et al., 2018).

Table 5. Visual rating scale for maize streak disease severity ______Rating scale Description Expression in terms of Severity ______1. No symptoms No infection 2. Very few streaks on leaves, light streaking on old leaves gradually decreasing on young leaves Mild infection 3. Moderate streaking on old and young leaves Moderate infection Slight stunting 4. Severe streaking on about 60-75% of leaf area, severe infection Plants stunted 5. Severe streaking on more than 75% leafarea, Very severe infection plants severely stunted or dead

3.3. Molecular Characterization of Maize Streak Virus

3.3.1. Sample Collection and DNA Extraction

Young leaf samples were collected from maize plants showing MSD symptoms from different maize growing regions of Ethiopia. Total DNA was extracted using modified CTAB extraction method as described by Doyle and Doyle (1990). About 200 mg of leaf tissue was weighed, frozen in liquid nitrogen and ground using a mortar and pestle. Seven hundred microliter CTAB buffer was added to the leaf sample and the mixture crushed into fluid state. The sample was incubated at 65oc for 30 minutes in water bath and shaken in between. Seven hundred microliter chloroform-iso-amyl alcohol (24:1 ratio) was added to each tube and mixed gently to avoid sharing of gnomic DNA and centrifuged at 12000rpm for 10 minute at room temperature. The supernatant was collected and transferred into sterilized labeled 1.5μl eppendorf tubes. Seven hundred microliter isopropanol was added to eppendorf tube and inverted at once to mix. The sample was incubated in the freezer (-20oc) for at least 2 hours or overnight. The sample was centrifuged at 13000rpm for 20 minute to precipitate the DNA. The supernatant was discarded and 70% ethanol added. The pellet was left on ice for about three minutes to dry. The pellet was then re-suspended in one hundred microliter TE buffer and kept in the freezer until used for PCR.

3.3.2. Polymerase Chain Reaction (PCR)

The extracted genomic DNA was amplified by Polymerase Chain Reaction (PCR) using degenerate Primer pair of 215-234 5‟-CCA AA (GT) (AGT) TC AGC TCC TCC G-3' and Primer 1770-1792 5'-TTG G(CGA)C CG(AC) (ACG)GA TGT A(CG)AG-3'. The primers were expected to amplify a 1300 base pair (bp) fragment. PCR amplification of MSV were performed in 25 μl reaction volume containing 11μl Buffer, 10 μl SDH2O, 1μl each primer, 1μl Taq polymerase and 1μl genomic DNA. PCR was run on standard thermal cycler (PCR sprit thermal cycler) at Ambo Agricultural Research Centre (AmARC), virology laboratory with reaction condition of 94 ℃ for 1min, followed by 30 cycles of 93 ℃ for 45sec, 54 ℃ for 30sec and 72 ℃ for 90sec, and a final extension step of 72℃ for 3 min.

3.3.3. Electrophoresis and UV visualization

PCR products were assessed by electrophoresis in 0.8% agarose gel in TAE (Tris-Acetate- EDETA) buffer, stained with ethidium bromide, and viewed under ultraviolet light trans- illuminator. For reference and comparison of PCR products, 100 bp DNA size markers were used along with the samples.

3.4. Plant DNA extraction and cloning protocol for RCA

3.4.1. DNA extraction

Total genomic DNA was extracted from leaf material of each sample using an Extract-N-AmpTM Plant kit (Sigma-Aldrich, USA) as described by Shepherd et al. (2008) according to the manufacturer‟s instructions. A small (5-25 mm2; 1-2 mg) sample was torn from the dried leaf by clamping the leaf between the lid and the lip of the PCR tube. Seventy microliters (L) of extraction solution (supplied with the kit) was added (enough to cover the leaf sample), and the tube was then heated at 95 ◦C for 10 min using a thermal cycler. Lastly, 50 L of dilution solution (also supplied with the kit) was added. Samples were vortexed and either stored at 4 ◦C or used directly as a template for the RCA of Gemini virus genomes.

3.4.2. Rolling circle amplification

Circular viral DNA genomes were amplified using RCA kit (Illustra TempliPhiTM, GE Healthcare, USA) essentially as described previously for DNA isolated from FTA cards (Owor et al., 2007) with a slight modification for dried leaf samples. Four microliter of the final Extract-n- Amp DNA solution was mixed with 3 L of the TempliPhiTM sample buffer, heated for 3 minutes at 95 °C, and then brought to room temperature. This heating step lyses bacterial cells or phage particles effectively to release the circular template into the liquid thereby dramatically improving the efficiency of the TempliPhiTM reaction for DNA isolated from dried leaf material specifically. Five microliters of reaction buffer and 0.2L of enzyme mix were added to the cooled mixture and the TempliPhiTM extension reaction was run at 30 °C for 20 h after which enzyme was heat-inactivated by incubating at 65 °C for 10 minutes and cooled to 4 °C .

Full viral genomes were isolated using restriction digest. For each restriction digestion reaction, 2.0 µL of RCA DNA was digested using BamHI and Kpnl to yield unit length ~2.7 kb genomes. Resulting restricted products were purified using quick spin (Qiagen) and ligated to analogously digested Puc19 (Inqaba Biotechnical Industries, SA). The identity of cloned genomes/genome components were confirmed by end sequencing. The resulting genome sequenced using M13 forward and reverse primer and additional internal sequencing primer. The resulting mastrevirus genome clones were Sanger sequenced by primer walking by Macrogen Inc. (Korea).

Table 6. Primers used for squensing complete MSV gynome ______S/N Primer name Sequence 1 M13 forward 5‟-CGCCAGGGTTTTCCCAGTCACGAC-3‟ 2 M13 reverse 5‟-CAGGAAACAGCTATGAC-3‟ ______Internal primers 1 MSV_1 5‟-TGTGTCATCGCTTCGTGGT-3‟ 2 MSV_2 5‟-CCAAAGATGAAATAATGCGAGAC-3‟ 3 MSV_3 5‟-GGTGTAATGTGGCTGGTG-3‟ 4 MSV_4 5‟-GGGGTTCATAATTACTGGCA-3‟ 5 MSVK_1 5‟-CTTTTACCTGCTTTACCTTTG-3‟

3.4.3. Sequencing and Phylogenetic Analysis

Nucleotide sequences were determined at Macrogen Inc. (Korea). A phylogenetic analysis was conducted with the genome sequences generated and also including MSV reference genomes. The obtained sequences were compared with corresponding sequences of other MSV infecting maize obtained from the GenBank. Additionally, sequences of mastrevirus type species of Ethiopian isolate Maize streak reunion virus (MSRV) (MK329304) were chosen as out groups to generate a phylogenetic tree. All sequences were verified as MSV in BLASTn tool available online in NCBI (http://blast.ncbi.nlm.nih.gov/). Sequences of virus isolates were initially analyzed using BLASTn algorithm from the GeneBank nucleotide database to determine the virus species with which they shared the highest identities. Sequences that have the highest similarity were accessed from the GeneBank for multiple sequence alignment and phylogenetic analysis. Clustal alignment was done using the online Clustal Omega tool (https: //www.ebi.ac.uk/Tools /msa/clust alo/) to further subject aligned sequences to MEGAX version 10.1.8 using the Maximum Likelihood method (Tamura et al., 2018). Bootstrap with 1000 resampling was applied to generate a phylogenetic tree.

The levels of genetic diversity in the MSV-A dataset A were estimated using both MEGAX versions 10.18 (Tamura et al., 2018) and MUSCLE alignment of the sequence demarcation tool (SDTv1.2) (Muhire et al., 2014) was used to generate a color coded matrix from pairwise similarity calculations.

Table 7. Origin and accession numbers of Maize Streak Virus isolates from different countries in Africa earlier deposited in the Genbank for comparison with isolates identified in this study from Ethiopia ______

Isolate GenBank accession number Origin ______MSV-Et-149 MK329307 Ethiopia MSV-MV-242 MK329309 Ethiopia MSV-Et-136 MK329306 Ethiopia MSV-MV-171 MK329308 Ethiopia MSV_KE_Kir2_K262B_sac_11 KY304935 Kenya MSV_KE_Mig5_K133_10 KY304851 Kenya MSV-A_ZM_Chi3_Z8-2008 HQ693454 Southern Africa Rwanda 20 MN428858 Rwanda MSV-A_MZ_Lib2_Moz31-2007 HQ693348.1 Southern Africa UMasin-144 EF547097 Uganda UKas-76 EF547080 Uganda UBus-255 EF547119.1 Uganda UKas-71 EF547078.1 Uganda UIga-243 EF547116.1 Uganda UKas-75 EF547079.1 Uganda MSV-UWak56 EF015778.1 Uganda R 31 MN428869.1 Rwanda Rwanda 3 MN428841.1 Rwanda Rwanda 14 MN428852.1 Rwanda MSV_KE_Sia14_K83B_09 KY304982 Kenya MSV_KE_Bar1_K163_10 KY304870 Kenya MSV_KE_Sia8_K58_2_09 KY304970.1 Kenya MSV_KE_Elg3_K178B_10 KY304882.1 Kenya MSV-A_MZ_Map6_Moz27-2007 HQ693356.1 South Africa Bambui_MB1K1 FM210279 Cameroon MSV-A_CF_Bos6_Car6-2008 HQ693312.1 South Africa MSVA_ZW_Mas4_Mic6 FJ882145.1 South Africa MSV-A_MZ_Bil2_Moz21-2007 HQ693336.1 South Africa MSV-A_MZ_Xai2_Moz7-2007 HQ693366.1 South Africa MSV-A_CF_Bang1_Car39-2008 HQ693295.1 South Africa MSV-UWak56 EF015778.1 South Africa MDA26-Tz MH667488.1 Tanzania Sc97-MR-1 KX787926.1 Nigeria Mz80-MR-8 KX787931.1 Nigeria MSV-A_GH-gh153-Top-2010 KJ699335.1 Ghana MSV-A_GH-gh157-Sei-2010 KJ699338.1 Ghana MSV_KM_Mra_mad35_09 KY311968.1 Indian Ocean Islands MSV_KE_Tra1_K160_10 KY304867.1 Indian Ocean Islands

4. RESULTS AND DISCUSSION

4.1. Distribution, Incidence and Severity of MSV

4.1.1. Distribution, Incidence and Severity of MSV across Location

During the 2019 main cropping season, an intensive and extensive surveys for Maize streak (MS) were carried out in major maize growing areas in Oromia, Benishangule-Gumuz and Gambella regions, where four, one and three zones, respectively, assessed from selected regions. Most frequebntly encountered MS-like symptoms supposed to have associated with MSV infection are: Broken to almost chlorotic strips centred on the tertiary leaf veins and 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 2).

Figure 3. Shows different MS symptoms associated with plant growth stage at the time of infection: (A) no symptoms (no infection), (B) light streaking on old leaves (mild infection); (C) moderate streaking on old and young leaves, slight stunting (severe infection); (D) severe streaking on about 60-75% of leaf area, plants stunted (severe infection); (E1-E3) Severe streaking on more than 75% leaf area, plants severely stunted or dead (very severe infection)

The characteristic symptoms described in this study have similarly been reported in detail by various researchers in the country and oversea (Shepherd et al., 2010; Mesfin et al., 1995). It is interesting to note that visual assessment of MS based on field symptoms, in most cases, corresponded with laboratory test result (Table 11) substantiating that characteristic symptoms are diagnostic and useful for field assessment.

Table 8. Disease prevalence (%), Incidence (%) and severity (1-5scale) of Maize Streak across different Altitude ranges in Ethiopia ______S.N Altitude Range NFA NFI Prevalence Incidence Severity m.s.a.l (%) (%) (1-5 scale) ______1 <1000 23 22 96 63 4 2 1000–1700 43 39 90 53 4 3 1701–2000 52 36 69 33 3 4 2001–2400 8 1 13 5 1 ______Mean 127 98 78 43 3

NAF- Number of field assessed NIF- Number of field infected

80.00 70.00 4.26 60.00 4.11 50.00 40.00 2.58 30.00 Severity (1-5 scale) 20.00 10.00 Incidence (%) 0.00

Figure 4. Shows Average mean Maize Streak Virus disease Incidence (%) and Severity (1-5 scale) across surveyed region

70.00 4.21 4.33 60.00 4.11 50.00 3.60 40.00 2.6 30.00 2.28 Severity (1-5 scale) 20.00 Incidence (%) 10.00 0.00 0.00

Figure 5. Shows Average mean Maize Streak Virus disease Incidence (%) and Severity (1-5 scale) across Zone

Table 9. Correlation of Altitude verses Maize Streak Virus disease incidence and severity

______

Altitude Incidence Severity ______Altitude 1 -.510** -.446** Incidence -.510** 1 .948** Severity -.446** .948** 1 ______**. Correlation is significant at the 0.01 level (2-tailed).

Table 10. The mean prevalence, incidence and severity of MS across district during 2019 main croping season ______Region District Prevallence Incidence Severity (%) (%) (1-5) Abobo 100 63 4 Abol 75 45 4 Gambela Itang 100 63 4 Lare 100 65 5 Gambela 100 85 5 Mean 94 64 4 Gumay 60 26 2 Seka Chekorsa 67 33 3 Shebe Sombo 75 42 3 Kersa 80 29 3 Mana 40 13 1 Didesa 0 0 0 Gechi 0 0 0 Guto Gida 78 44 3 Oromia Diga 100 57 4 Wayu Tuka 50 18 2 Sibu Sire 20 14 2 Gimbi 80 47 3 Lalo Asabi 100 60 4 Boji Dirmeji 67 35 3 Nejo 100 40 4 Leta Sibu 50 22 2 kiltu Kara 100 60 4 Mene Sibu 100 58 4 Mean 65 33 3 Banbasi 100 67 5 Benishangul-Gumuz Homosha 80 51 3 Asosa 100 58 4 Mean 93 59 4

Out of 127 maize fields visited, based on MS-like symptoms, the disease was prevalent in 100 (79%) fields assessed, from which 100 maize and 5 grass samples were collected for laboratory testing. Results of this investigation depicted that the disease prevalence, incidence and severity were highest in Gambella region followed by Benishangule-Gumuz and Oromiya regions, in this order (Fig. 4). This finding is in agreement with what reported by Mesfin et al. (1991) who indicated the exceptionally high MS outbreak in Gambella region during the 1986 crop season. In this work, other regions in the west other than Gambella are also reported as succumbed to the

31 disease. Mesfin et al. (1991) reported that MSV was prevalent at lower altitudes, this being due to higher population density of Cicadulina spp especially C. mbila found at lower alititude. Rose (1978) in Zimbabwe, and Guthrie (1976) in Kenya, have noted that MSV tends to be more severe in lower altitudes. These indicated that the altitude range was one of deriving factors affecting MS distribution and prevalence. Similar findings earlier in Ethiopia reported the distribution and importance of maize streak disease in some parts of the country (Demsachew et al., 2018; Alemu et al., 1997).

From the 127 maize fields assessed in the three regions (Fig. 4), 79% were affected by the disease. The average mean prevalence of MS was, respectively, 94 and 93% in Gambela and Benishangul Gumez regions, while the mean disease prevalence was 65% in Oromia region (Table 10). As for disease prevalence, MS incidence was also higher in Gambella, followed by Benishangule-Gumuz and Oromia, where the average mean incidences of up to 64% in Gambela, 59% in Benishangul Gumez and 33% in Oromia regions were recorded (Table 10). Recent report showed that MS incidence of up to 58% was also found in Ethiopian maize germplasm (Demsachew et al., 2018).

The present study also disclosed the existence of variations in the level of disease prevalence and incidence in different altitude ranges assessed, where relatively higher prevalence and incidence were recorded at lower altitudes ranging from 400-1600 and vice versa at higher altitudes ranging from 2000-2400 masl. For instance, the disease incidence was higher in Benishangul Gumuz and Gambela regions at locations having 400 to 1500 masl (Table 7), which perhaps can be attributed to warmer climates favoring vector populations for virus transmission, which in turn contributing to more severe disease symptoms development (Redinbaugh and Zambrano 2014). The high incidence of diseases detected in the field is expected to cause a considerable reduction in yield and quality. In highly susceptible and late sown genotypes, MS causes up to 100% yield losses in infected crops (Alegbejo et al., 2002; Bosque-Perez and Buddenhagen 1999; Kyetere et al., 1999; Lagat et al., 2008; Page et al., 1999).

The exceptionally high MS incidence and severity recorded in the surveyed locations in Gambella region might have associated with high vector (s) population and activity. For example, earlier report by Mesfin et al. (1991) has shown that efficient MSV vector in the genus

Cicadulina such as C. mabila (Story 1925) is recorded at high intensity in surveyed areas in Gambella, whose activity and population has direct relation to MSV incidence and severity. Furthermore, Mesfin et al. (1991) has also reported cereal (Maize, Triticum sp, Avena sp. and sugar cane) and grass (Digitaria, Setaria, Hyparrhenia, Panicum, Pennisetum and Sorghum spp.) are hosts of Cicadulina spp. vectoring MSV. MSV has also known to have wide host ranges. In addition to maize, cereals such as rice (Oryza sativa L.), wheat (Triticum aestivum L.), oats (Avena sativa L.), barley (Hordeum vulgare L.), rye (Secale cereale L.), finger millet (Eleusine coracana L.), pearl millet (Pennisetum typhoides L.), sorghum (Sorghum bicolor L.) and sugarcane (Saccharum officinarum L.) (Damsgeegt, 1983; Willment et al., 2001; Van Antwerpen et al., 2011) are infected by MSV.

A wide range of grasses in the genera Axonopus, Brachiaria, Coix, Eleusine, Paspalum, Imperata, Rottboellia, Eragrostis and Setaria (Willment et al., 2001; Lett et al., 2002; Fajemisin, 2003), most of which are naturally growing in vleis and irrigation schemes, are also attacked by MSV. All cereals and most grasses identified as hosts for MSV and its insect vectors are widely grown in Ethiopia (Bekele et al., 2017; Stroud and Parker, 1989). Furthermore, some of the grasses just identified as hosts of cicadulina spp. are also known as alternate hosts of MSV (Alemu et al., 1997). Hence, having common hosts for both the virus and its vectors simply imply the presence of suitable substrate/medium for their survival and multiplication serving as sources of inoculum and vectors from which the newly growing maize crop can get infected.

Up to 4.3 average mean severities was recorded in all surveyed regions of Ethiopia on 1-5 severity scoring scale (Table 7) attributing to higher yield loss. From the present result, one can conclude that MS disease is distributed in almost all maize growing agroecologies with higher prevalence and severity recorded at low and mid altitudes. The high prevalence, incidence and severity of MS at lower and mid altitude maize growing agroecologies may partly attributed to the conducive environment for both virus and vectors transmitting MSV. The presence of several grasses in the family poaceae serving as alternate hosts to MSV along with high vector populations and activity at these altitudes may also immensely contributed for high MS prevalence, incidence and severity. The present results support earlier findings that reported the virus was favoured by warmer climate in sub Saharan Africa (Harkins et al., 2009; Monjane et al., 2011; Oluwafemi et al., 2014; Pande et al., 2017; Varsani et al., 2009).

4.1.2. Distribution, Incidence and Severity of MSV across Variety

Similarly, prevalence, disease incidence and severity of Maize Streak were assessed across maize varieties evaluated. Among different varities evaluated in the assessed fields, MS was most prevalently recorded on Gambela composite local and BH540 variety, in order (Fig 6). The study revealed that higer average MS incidence and severity were scored on Gambela composite, local and BH540 varieties than other varieties (Fig 6), implying that these varieties appear more susceptible to Maize Streak disease.

70.00

60.00 4.00 3.77 3.80 50.00 3.38 3.37 40.00 30.00 1.88 20.00 10.00 0.00 BH-540 BH-661 Gambela Limu Local Shone Coposite Incidence (%) Severity (1-5 scale)

Figure 6. The mean incidence and severity of maize streak disease by varieties sampled across the surveyed locations during the 2019 main croping season

4.2. Molecular Characterization of Maize Streak Virus

4.2.1. Amplification of MSV

The collected symptomatic samples were subjected to normal PCR using degenerate primer pairs. Expected product size of 1300 bp was consistently amplified for most representative maize samples (Figure 7). Symptomatic field collected samples also supposed to have been infected by MSV were subjected to Rolling circle amplification (RCA) to amplify full-length viral genome. The virus was detected from all surveyed regions and in all types of maize varieties sampled (Table ). Grass samples suspected of MSV infection and few symptomatic maize samples tested negative.

Figure 7. A 1.3-kilo base product was ampliﬁed using a MSV replicative form-speciﬁc degenerate primer pair, 215–234 and 1770–1792 (Willment et al., 2001). L=The 100 bp DNA Ladder ready-to-use molecular weight marker (Solis BioDyne, Estonia), Size range of 100 – 3,000 bp and 12 numbers of bands. Nos. 1-23 is representative samples collected from surveyed regions.

Table 11. Results of Rolling Circle Amplification of maize streak virus in samples collected from maize plants in Gambella, Oromiya and Benishangule Gumuz Regions of Ethiopia, 2019 main cropping season. ______Surveyed Zone Samples screened for MSV Positive for MSV ______Agnuwak 13 12 Nuer 9 9 Jimma 16 16 East Welega 13 10 West Welega 22 21 Asosa 27 26 Total 100 94 ______

Laboratory study to characterize Ethiopian isolates of MSV using molecular methods showed that normal PCR employing geminivirus degenerate primer pairs resulted in an expected PCR amplicon of approximately 1300 bp for ninety five out of one hundred five samples analyzed. Absence of amplification for five symptomatic maize and five grass samples may be due to

35 misdiagnosis in the field for other viruses which may develop similar or closely related symptoms with MSV such as Maize lethal necrosis (MLN). Furthermore, one hundred symptomatic maize samples were subjected to RCA to amplify full length genome of MSV and produced expected size of 2.7 kb, further confirming the association of MSV with the putative MSV-like symptoms collected in the field. Detection and Amplification of MSV using PCR and RCA complemented each other which gave comparable results, suggesting that both methods can interchangeably be used to diagnose MSV. However, individual preference to use either method may depend on costs for consumbles, higher sensitivity, rapid detection and time with which the test is completed (Lau and Botella 2017).

4.2.2. Sequencing and Phylogenetic Analysis

Among one hundred rolling circle amplified MSV isolates, thirty-two samples were sequenced, of which the nucleotide and derived amino acid sequences of the sixteen Ethiopian MSV isolate were blast searched and compared among themselves and with other MSV isolates earlier deposited in the genebank. The result of blast analysis revealed that MSV isolates identified from Ethiopia in the present study shared 97-99% nucleotide identity among themselves and 95-99% sequence identity with other isolates deposited in the genebank, confirming that Ethiopian isolates are similar with other MSV isolates elsewhere in Africa regardless of geographical isolation. The study further verified that all Ethiopian isolates from this study classified under MSV-A strain. Ethiopian isolates also shared 80-90% nucleotide sequence identity with other MSV (B-K) strains and 63-76% identity with other mastervirus species (Maize streak reunion virus (MSRV) and maize streak dwarfing virus (MSDV), further substantiating that Ethiopian isolates are classified under MSV-A strain based on species demarcation criteria set by ICTV (Brown et al., 2012; Fauquet et al., 2008).

A comparison of MSV isolates from this study with previously identified MSV-A isolates from Ethiopia (MSV-Et-149, MSV- MV-242, MK329306 and MSV-MV-171) (Demsachew et al., 2019) showed 97-99% nucleotide identity, again indicating that the isolates are of the same species. Comparison of isolates with previously characterized African MSV isolate from different African countries showed 95-99% identity/similarity. For example, the isolates of MSV in this study showed 97-99% identity with Kenyan isolates (KY304935, KY304851, KY304982,

KY304870, KY304970.1 and KY304882.1) (Pande et al., 2017) of MSV strain A. The isolates compared with seven isolates from Uganda (Owor et al., 2007) and four isolates from Rwanda (Asiimwe et al., 2019) showed 97-99% and 98-99% identity, respectively. The isolates of this study were also compared with South African, Tanzania, Ghana and Indian Ocean Island isolates and showed 95-99% identity. Similarly, Ethiopian isolates showed 98-99% identity with isolates from Nigeria (KX787926.1 and KX787931.1) (Yahaya et al., 2016). The results indicated that there is no variation among MSV-strain A isolates from Africa at continental level, despite wide geographical variations.

Phylogenetic analysis revealed that MSV isolates from this study fall into four different clusters with different MSV-A phylogroups (Fig. 8). Four of the sixteen isolate from this study (ETH36, ETH89, ETH56 and ETH55) were clustered together with three MSV-A, strain group which was identified from three Rwanda and two Kenyan isolate and shared 99% sequence similarity. Six isolates (ETH3, ETH35, ETH63, ETH7, ETH21 and ETH25) clustered with two Nigerian (KX787926.1 and KX787931.1) (Yahaya et al., 2016) and one earlier identified Ethiopian isolates (Demsachew et al., 2019) and shared 99 percent identity. The other four isolate (ETH18, ETH47, ETH30 and ETH52) were clustered with two Indian Ocean Islands (KY311968.1&KY304867.1), one Tanzanian (MH667488.1) (Kiruwa et al., 2019), two Ugandan (EF547119.1& EF547080) (Owor et al., 2007), two South African (EF015778.1 & HQ693312.1) (Monjane et al., 2011; Owor et al., 2007) and one Kenyan (KY304970.1) (Pande et al., 2017) isolates. The isolates shared 98% similarity with isolates from Indian Ocean Islands and Tanzanian isolate, where as 99 percent identity with Kenyan, Ugandan and South African isolates of MSV strain A.

The other two isolates (ETH37 and ETH57) were clusted with three South African (HQ693366.1, HQ693295.1 & FJ882145.1) (Harkins et al., 2009; Monjane et al., 2011), three Ethiopian (MK329307, MK329306 & MK329308) and three Ugandan (EF547078.1, EF547079.1& EF547116.1) (Owor et al., 2007) isolates. The isolate ETH37 was shared 99%, 97% and 98% sequence identity, respectively, with the isolates HQ693366.1 HQ693295.1 & FJ882145.1 from South Africa. This isolate also shared 97%, 99% and 99% sequence identity with earlier identified Ethiopian isolates named MK329307, MK329306 and MK329308, respectively. The same isolate shared 97% identity with Ugandan isolate (EF547119.1). The

37 isolate ETH57 were shared 98-99% identity with South African isolates, where as 97-99% identity with Ethiopian isolates and 99% identity with Ugandan isolates.

Cluster I

Cluster II

Cluster III

Cluster IV

Figure 8. Phylogenetic tree generated by the Maximum Likelihood method of MEGAX version 10.18 based on full genome sequence alignments of reference sequences in the genus Mastrevirus. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches. The evolutionary history was inferred by using the Maximum Likelihood method and Tamura 3-parameter model (Tamura,

1992). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 51 nucleotide sequences; sixteen from this study, 34 references isolate retrved from Genbanck and one isolate from other masterovirus species used as out group. Isolates determined in this study are indicated in Italic bold fonts. Strain names and GenBank accession numbers are shown in the phylogenetic tree for each isolate.There were a total of 3612 positions in the final dataset.

Pairwise genetic distance comparisons with previously determined MSV isolates indicated that all newly identified MSV from this study belong to the MSV-A. According to mastrevirus strain demarcation threshold suggested by Muhire et al. (2014), Monjane et al. (2011), Martin et al. (2001) an overall mean pairwise genetic distance (0.03) and nucleotide sequence identity (≥ 97%) were estimated (Fig 9). These estimation shows that the isolates used in the study were very closely related. The isolates used displayed low levels of genetic diversity, and a well- structured geographical distribution where all of the 16 isolates clustered together with the MSV -A strains.

Figure 9. The Strain Demarcation Tool interface, Colour-coded pairwise identity matrix generated from 51 Maize streak virus genomes. Each coloured cell represents a percentage identity score between two sequences (one indicated horizontally to the left and the other vertically at the bottom). A coloured key indicates the correspondence between pairwise identities and the colours displayed in the matrix.

5. CONCLUSION

The study revealed that MS disease was distributed in almost all major maize growing agroecologies of Ethiopia from low to high altitude areas assessed. The results of the present study provide broder information on the distribution, incidence, severity and molecular characterization of MSV in surveyed regions of Ethiopia.

High prevalence, incidence and severity of MS were recorded at low and mid-altitude areas surveyed where as low incidence and severity were rcorded at high altitude maize growing areas. The disease recorded in all available local and commercial maize varieties, despite higer MS incidence and severity were recorded on local varitity than improved varieties.

Laboratory testing of field collected samples with putative MS-like symptoms using PCR and RCA gave positive results for more than 90% samples, suggesting sample collection for MS based on characteristic symptoms is acceptable. Furthermore, results of laboratory testing and sequencing confirmed that Ethiopian isolates of MSV are similar with isolates from elsewhere in Africa despite geographical isolation. As a way forward, there is a need to go for MSV strain sub typing and determination of MSV-vector association in Ethiopia.

6. RECOMMENDATIONS

Based on the current findings, the following are recommended for future consideration:

 Maize improvement program at hot spot areas should strictly target development of MS and/or vector resistant maize varieties.

 To apply cultural control methods, there is a need to have an extensive and intensive inventory for alternative annual and perennial grass hosts at diffent altitude ranges on which the pathogen and insect vectors overwinter.

 There is a need to identify Cicadulina spp. occurring in Ethiopia, determine effective MSV vector (s) and the role vectors play in disease epidemiology to use in disease management.

 Develop and deployment of integrated disease managemt for MS

7. REFERENCES

Abdolreza Abbassian. 2006. Maize International Market Profile Competitive Commercial Agriculture in Sub–Saharan Africa (CCAA) Study Trade and Markets Division Food and Agriculture Organization of the United Nation. Alegbejo M.D., Olojede S.O., Kashina B.D. and Abo M.E. 2015. Maize Streak Mastrevirus in Africa: Distribution, Transmission, Epidemiology, Economic Significance and Management Strategies. Journal of Sustainable Agriculture, Vol. 19(4). Alegbejo M.D., Olojede, S.O., Kashina, B.D., and Abo, M.E. 2002. Maize streak mastrevirus in Africa: Distribution, transmission, epidemiology, economic significance and management strategies. Journal of Sustainable Agriculture, 19, 35-45. Alegbejo M., Ogunlana M. and Banwo O. 2008. Short communication. Survey for incidence of Okra mosaic virus in northern Nigeria and evidence for its transmission by beetles. Spanish Journal of Agricultural Research 2008 6(3), 408-411. Alemu L., Adane A., Berahanu B., and Mesfin T. 1997. Identification of viruses from maize and grass hosts. Pest Managnmentt Jornal of Ethiopia 1:73–76. Asanzi C.M., Bosque-Perez N.A., Buddenhagen I.W., Gordon D.T., and Nault L.R. 1994. Interactions among maize streak virus disease, leafhopper vector populations and maize cultivars in forest and savanna zones of Nigeria. Plant Pathology, 43(1): 145 - 157. Asanzi C.M., Bosque-Perez N.A. & Nault L.R. 1995. Movement of Cicadulina storeyi (Homoptera: Cicadellidae) in maize fields and its behaviour in relation to maize growth sstage. Insect. Scince. & Applic. 16,39--44. Asiimwe T., Stewart L.R., Willie K., Massawe D.P., Kamatenesi J. and Redinbaugh M.G. 2019. Maize lethal necrosis viruses and other maize viruses in Rwanda. Plant Pathology, 69 (3), 585-597. Bekele B., Kumari S., Ahmed S., Fininsa C., Yusuf A., and Abraham A. 2017. Non-cultivated grass hosts of yellow dwarf viruses in Ethiopia and their epidemiological consequences on cultivated cereals. J. Phytopatholo. 00:1–13. https://doi.org/10.1111/jph.12666

Bigarré L., Salah M., Granier M., Frutos R., Thouvenel J.C. and Peterschmitt M. 1999. Nucleotide sequence evidence for three distinct sugarcane streak mastreviruses. Archives of Virology, 144: 2331-2344.

Bjarnason M.S. 1986. Progress in breeding for resistance to the maize streak virus disease. In: Gelow, B. (ed.) 1st Eastern, Central, Southern Africa Regional Maize Workshop To Feed Ourselves. Lusaka Zambia, March 10-17, 1985: CIMMYT, Mexico D.F. Blankson D., Asare-Bediako E., Frimpong K.A., Ampofo E., Taah K.J. and Van der Puije G.C. 2018. Incidence and severity of maize streak disease: The influence of tillage, fertilizer application and maize variety. African Journal of Agricultural Research. Vol. 13(12), pp. 551-560. DOI: 10.5897/AJAR2017.12873 Bock K.R. 1982. Geminivirus diseases in tropical crops. Plant Disease. 66, 266–270 Bosque-Perez N.A. and Buddenhagen I.W. 1999. Biology of Cicadulina leafhoppers and epidemiology of maize streak virus disease in West Africa. South African Jornal of Plant Soil 16:50–55. Bosque-Perez N.A., Olojede S.O. and Buddenhagen I.W. 1998. Effect of maize streak virus disease on the growth and yield of maize as influenced by varietal resistance levels and plant stage at time of challenge. Euphytica 101: 307-317. Bosque-Perez N.A. 2000. Eight decades of Maize streak virus research. Virus Research, 71, 107- 121. https://doi.org/10.1016/S0168-1702 (00)00192-1. Brown J.K., Fauquet C.M., Briddon R.W., Zerbini M., Moriones E., Navas-Castillo J. 2012 Virus taxonomy: ninth report of the international committee on taxonomy of viruses. Academic Press, Waltham. Chaboussou F. 2004. Healthy Crops: A new agricultural revolution. p. 244. Chen S., Huang Q., Wu L., Qian Y. 2015. Identification and characterization of a maize- associated mastrevirus in China by deep sequencing small RNA populations. Virology Journal 12:156. CIMMYT Maize Program. 2002. Maize Diseases: A Guide for Field Identification (3rd ed.). Mexico, D.F.: CIMMYT. CIMMYT. 2014. Improved maize varieties and poverty in rural Ethiopia. Standing Panel on Impact Assessment (SPIA). Brief Number 45. CGIAR Independent Science and Partnership Council (ISPC) Secretariat, FAO. Rome, Italy CSA. 2018. Agricultural sample survey 2017/2018: Report on area and production of major crops (private, peasant holdings, „Meher‟season). Statistical bulletin, 584, Addis Ababa: CSA.

Dabrowski Z.T. 1987. Cicadulina ghaurii (Hem., Euscelidae): distribution, biology and maize streak virus (MSV) transmission. Journal of Applied Entomology, 103, 489–496. Dabrowski Z.T., Nwilene F. and Kumar R. (1991). First regular observations on leafhoppers, Cicadulina spp., vectors of maize streak virus (MSV) in southeastern Nigeria. Insect Scince. Applied. 12, 249–261. Damsteegt V.D. 1983. Maize streak virus: I.Host range and vulnerability of maize germ plasm. Plant Disiease. 67, 734–737. Danson J., Lagat M., Ininda J. and Kimani M. 2006. Application of simple sequence repeats (SSRs) markers to study the resistance of locally adapted maize hybrids to damaging Maize streak virus disease. African Journal of Biotechnology, 5:1430–1434. Demsachew G., Adane A., Kassahun T., Dennis K., Stephan W. 2018. First report of maize yellow mosaic virus infecting maize (Zea mays) in Ethiopia. Plant Disease, 102(5), 1044 1044. Demsachew G., Kassahun T., Dennis K., Stephan W. and Adane A. 2019. Molecular analysis of maize (Zea mays L.) infecting mastreviruses in Ethiopia reveals marked diversity of virus genomes and a novel species. Virus Genes. https://doi.org/10.1007/s11262-019- 01655-1. Dhau I., Adam E., Mutanga O. and Ayisi K. 2017. Detecting the severity of maize streak virus infestations in maize crop using in situ hyperspectral data. Transactions of the Royal Society of South Africa. https://doi.org/10.1080/0035919X.2017.1370034 Doyle M.M. and Autrey L.J.C. 1992. Assessment of yield losses as a result of co-infection by maize streak virus and maize stripe virus in Mauritius. Annals of Applied Biology 120: 443-450. Doyle J.I, Doyle L.H. 1990. Isolation of plant DNA from fresh tissue. Bailey Hortorium 466 Mann Library building Cornell University Ithaca, New York 14853. Fajemisin J.M. 2003. Overview of maize viruses in sub-saharan Africa. In:J.H. Hughes and J.odu (eds.) Plant virology in sub-saharan Africa. International Institutes of Tropical Agriculture Conference, llesa, Naigeria. Pp. 158-178. Fajemisin J.M., G.E., Cook F., Okunyasa and Shoyinka S.A. 1976. Maize streak virus epiphytotic in Nigeria. Plant Disease Reporter 60: 443-447.

Fajemisin, J.M. and Shoyinka, S.A. 1976. Maize streak and other maize virus disease in West Africa. In: Proceedings of the International maize virus disease colloquium and workshop (Williams, L.E., Gordon, D.T., Nault, L.R. eds), pp. 52–60. Wooster USA: Ohio Agricultural Research and Development Center. Fajinmi A.A., Dokunmu A.O., Akheituamen D.O. and Onanuga K.A. 2012. Incidence and infection rate of maize streak virus disease by Cicadulina triangular on maize plants and its distribution from the lowest disease leaf under tropical conditions. Archives of Phytopathology and Plant Protection 45: 1591-1598 FAOSTAT. 2017. Maize yield in Africa. http://www.fao.org/ faost at/en/#data/PM. Accessed 27 may 2019. FAOSTAT. 2017. Maize yield in Ethiopia. http://www.fao.org/ faost at/en/#data/PM. Accessed 27 may 2019. Fauquet C.M., Briddon R.W., Brown J.K., Moriones E., Stanley J., Zerbini M, Zhou X. 2008 Geminivirus strain demarcation and nomenclature. Archives Virology 153:783–821 Fontenele R.S., Alves-Freitas D.T., Silva P.T., Foresti J., Silva P.R., Godinho M.T., Varsani A.and Ribeiro S.G., 2018. Discovery of the first maize-infecting mastrevirus in the Americas using a vectorenabled metagenomics approach. Archives of Virology 163:263– 267. Fuller C. 1901. Mealie variegation. In: 1st Report of the Government Entomologist, Natal, 1899– 1900. Pietermaritzburg, Natal, South Africa: P. Davis & Sons, Government Printers. Gupta M.and Pawar A.D. 1989. Biological control of rice leafhoppers and planthoppers in Andhra Pradesh, Plant Protection. Bull. 41(1-2): 6-11. Guthrie E. J. 1976. Virus disease of maize in east Africa. Proceedings of the International Maize Virus Diseases Colloquium and Workshop (L. E. Williams, D. D. T. Gordon and L. R. Nault, Eds) Wooster, Ohio, USA, 16-19 August. Vol. 1, pp. 62-68. Harkins G.W., Martin D.P., Duffy S., Monjane A.L., Shepherd D.N., Windram O.P., Owor B.E., Donaldson L., van Antwerpen T., Sayed R.A.., Flett B, Ramusi M., Rybicki E.P., Peterschmitt M.and. Varsani A. 2009. Dating the origins of the maize-adapted strain of maize streak virus, MSV-A. Jornal of Gen Virology, 90:3066–3074.

Heong K.L., Aquino G.B.and Barrion A.T. 1992. Population dynamics of plant and leafhoppers and their natural enemies in rice ecosystems in the Philippines. Crop Protecton. 11(4): 371-379. Hill D.S.and Waller J.M. 1998. Pests and diseases of tropical crops. Field Handbook. UK, Longman. 6:454. Howell S. H. 1984. Physical structure and genetic organization of the genome of maize streak virus (Kenyan isolate). Nucleic Acids Research, 12: 7359 - 7375. Huffnagel H. P. 1961. Agriculture in Ethiopia. Rome: FAO. Ignaciuk A., and Mason-D'Croz D. 2014. “Modelling Adaptation to Climate Change in Agriculture”, OECD Food, Agriculture and Fisheries Papers, No. 70, OECD Publishing. Ininda J., Gichuru L., Njuguna G.M. and Lorroki P., 2006. Performance of three- way cross hybrid for agronomic traits and resistance to maize streak viruses disease in Kenya. African crop science journal vol. 14. Pp 287-296. ISAAA. 1999. Global Review of Commercialized Transgenic Crop. ISBN: 1-892456-16-8. Isnard M., Granter M., Frutos R., Reynaud B. and Peterschmitt M., 1998. Quasi-species nature of the maize streak virus isolates obtained from a population used to assess maize cultivar response to infection. Jornal of Gen Virology. 79, 3091–3099. Jeske H., Lutgemeier M. and Preiss W. 2001. Distinct DNA forms indicates rolling circle and recombination-dependent replication of Abutilon mosaic geminivirus. EMBO 20(21):6158–6167. Kamara A.Y., Menkir A., Badu-Apraku B.and Ibikunle O. 2003. The influence of drought stress on growth, yield and yield components of selected maize genotypes. Jornalof Agriculture Science. 141: 43-50. Karavina C. 2014. Maize streak virus: A review of pathogen occurrence, biology and management options for smallholder farmers. African Journal of Agricultural Research.Vol. 9(36), pp. 2736-2742. Keya S., and Rubaihayo P. 2013. Progress on on-farm production and productivity in East Africa Community; 50 years after independence (Kilimo trust technical paper No. 8). International Symposium on Agriculture, EAC Partner States at 50 Years. Kim S.K., Efron Y., Khadr F.H., Fajemisin J.M. and Lee M.H. 1989. Registration of 16 maize streak-virus resistant tropical maize parental inbred lines. Crop Science. 27, 824–825.

King A.M., Adams M.J., Carstens E.B., Lefkowitz E.J. 2012. Virus taxonomy: ninth report of the International Committee on Taxonomy of Viruses, vol 9. Elsevier pp, New York, pp 352–355. Kiruwa F.H., Njuguna J., Machuka E., Senay S.D., Mutiga S.K., Feyissa T., Ndakidemi P.A. and Stomeo F. 2019. Survey and characterization of the viruses causing Maize Lethal Necrotic Disease in Northern Tanzania. Pathogens 2020, 9, 4. Konate G. and Traore O. 1992. Reservoir hosts of maize streak virus (MSV) in the Sudan–Sahel zone: identiﬁcation spatio-temporal distribution. Phytoprotection, 73, 111–117. Kriticos D.J., Sutherst R.W., Brown J.R., Adkins S.A., and Maywald G.F. 2003. Climate change and biotic invasions: A case history of a tropical woody vine. Biological Invasions 5: 145165. Kumar S., Stecher G., Li M., Knyaz C., and Tamura K. 2018. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Molecular Biology and Evolution 35:1547-1549. Kyetere D. T., Ming R., McMullen M. D., Pratt R. C., Brewmaker, J. and Musket T. 1999. Genetic analysis of tolerance to Maize streak virus in maize. Genome, 42, 20-26. https://doi.org/10.1139/g98-099 Kyetere D., Ming R., McMullen M., Pratt R., Brewbaker J., Musket T., Pixley K. and Moon H. 1995. Monogenic tolerance to maize streak virus maps to the short arm of chromosome. Maize Genet. Coopration News Letter. 69, 136–137. Lagat M., Danson J., Kimani M. and Kuria A. 2008. Quantitative trait loci for resistance to maize streak virus disease in maize genotypes used in hybrid development. African Journal of Biotechnology 7:2573–2577. Lau H. Y. and Botella J. R. 2017. Advanced DNA-based point-of-care diagnostic methods for plant diseases detection. Frontiers in plant science, 8, 2016. Lazarowitz S. G. 1988. Infectivity and complete nucleotide sequence of the genome of a South African isolate of maize streak virus. Nucleic Acids Research, 16: 229 – 249 Lazarowitz S. G., Pinder A. J., Damsteegt V. D. and Rogers, S. G. 1989. Maize streak virus genes essential for systemic spread and symptom development. EMBO Journal 8: 1023 – 1032.

Lett JM, Granier M, Hippolyte I, Grondin M, Royer M, Blanc S, Reynaud B, Peterschmitt M. 2002. Spatial and temporal distribution of geminiviruses in leafhoppers of the genus Cicadulina monitored by conventional and quantitative polymerase chain reaction. Phyto pathology. V. 92(1): 65-74. Lucy A.P., Boulton M.I., Davies J.W., Maule A.J. 1996. Tissue specificity of Zea mays infection by maize streak virus. Molecular Plant Microbiol Interaction. V. 9(1): 22-31. Madzokere T.E. 2015. The Phylogeography, Epidemiology and Determinants of Maize streak virus dispersal across Africa and the adjacent Indian Ocean Islands. A thesis submitted in partial fulfilment of the requirements for the degree of (M.Sc.). South African National Bioinformatics Institute (SANBI). Magenya O.E.V., Mueke J. and Omwega C. 2008. Signiﬁcance and transmission of maize streak virus disease in Africa and options for management: a review. African Jornal of Biotechnoogyl. 7, 4897–4910. Markham P.G., Pinner M.S., Boulton M.I. 1984. The transmission of maize streak virus by leafhoppers, a new look at host adaptation. Mitt. Schweiz Entomol. Ges. Bull. Soc. Entomol. V. 57(4): 431-432. Martin D.P. and Shepherd D.N. 2009. The epidemiology: economic impact and control of maize streak disease. Food Security 1:305–315. Martin D.P., Willment J.A., Billharz R., Velders R., Odhiambo B., Njuguna J., James D and Rybicki E.P. 2001. Sequence diversity and virulence in Zea mays of Maize streak virus isolates. Jornal of Virology 288(2):247-255 Matsuoka Y., Vigouroux Y., Goodman M. M., Sanchez J., Buckler E., Doebley J. F. 2002. A single domestication for maize shown by multilocus microsatellite genotyping. Proceedings of National Academy of Science, 99: 6080 – 6084. Matthews G, Wiles T, Baleguel P (2003). A survey of pesticide application in Cameroon. Crop Protection. 22(5): 707-714. Mboya R., Tongoona P., Derera J., Mudhara M., and Langyintuo A. 2011. The dietary importance of maize in Katumba ward, Rungwe district, Tanzania, and its contribution to household food security. African Journal of Agricultural Research. 6, 2617-2626.

Mengistu F.M. 2016. Identification and Characterization of Maize Chlorotic Mottle Virus and Sugarcane Mosaic Virus Associated with Maize Lethal Necrosis Disease in Benishangul- Gumuz and Oromia Regions of Ethiopia. Thesis Mesbah H.A. Mourad A.K., El-Nimr H.M., El-Kady M.B.and Haroun N.S. 2002. Effect of sequential applications of foliar nutrients, biofertilizers and sowing dates on the incidence of corn stem borers in Egypt. Mededelingen Faculteit Landbouwkundige en Toegepaste Biologische Wetenschappen, Universiteit Gent. 67(3): 487-497. Mesfin T, Hollander J.D. and Markham P.G. 1995. Feeding activities of Cicadulina mbila (Hemiptera: Cicadellidae) on different host-plants. Bull. Entomology Research. V. 85(3): 387-396. Mesfin T., Bosque-Perez N. A., Buddenhaggen I.W., Thottappilly G. and Olojede S. O. 1992. Studies of maize streak virus isolates from grass and cereal hosts in Nigeria. Plant disease. 76: 789-795. Mesfin T., Hollander D. and Markham, P. G. 1991. Cicadulina species and Maize streak virus in Ethiopia. Tropical Pest Management, 37(3), 240–244. Mitsuhashi W., Saiki T., Wei W., Kawakita H. and Sato M. 2002. Two novel strains of Wolbachia coexisting in both species of mulberry leafhoppers. Insect molecular Boilogy. V. 11(6): 577-584. MOA. 2005. New agro-ecological zones of Ethiopia. Addis Ababa: Ministry of Agriculture. Monjane A.L., Harkins G.W., Martins D.P., Lemey P., Lefeuvre P. and Shepherd D.N. 2011. Reconstructing the history of Maize streak virus strain A dispersal to reveal diversification hot spots and its origin in southern Africa. Jornal of Virology. 85(18):9233-9636. Morales H., Perfecto I. and Ferguson B. 2001. Traditional fertilization and its effect on corn insect populations in the Guatemalan highlands. Agricultural Ecosystem. Environ. 84: 145-155. Muiru W. M., Koopmann B., Tiedemann A. V., Mutitu E. W., and Kimenju J. W. 2010. Race typing and evaluation of aggressiveness of Exserohilum turcicum isolates of Kenya, German and Austrian Origin. World Journal of Agricultural Sciences, 6, 277-284. Munoz-Martin A., Collin S., Herreros E., Mullineaux P.M., Fernandez L.M. and Fenoll C. 2003. Regulation of MSV and WDV virion-sense promoters by WDV non-structural proteins: a role for their retinoblastoma protein-binding motifs. Virology. V. 306(2): 313-323.

Mylonas P., Yonow T. and Kriticos D. J. 2014. Cicadulina mbila (Naude). Harvest Choice Pest Geography, St. Paul, MN: InSTePP-HarvestChoice. Nielson M.W. 1986. The leafhopper vectors of phytopathogenic viruses. Taxonomy, biology and virus transmission. U.S. Department of Agriculture Technical Bulletin. 1382. Okoth V.A.O., Dabrowski Z.T., Thottappilly G., Emden H.F. 1987. Comparative analysis of some parameters affecting maize streak virus (MSV) transmission of various Cicadulina spp. populations., Insect Science Applayed. V. 8(3): 295-300. Olaniya B.A. 2015. Maize:Panacea for hunger in Nigeria. Department of Agronomy, faculty agriculture and forestry University of Ibadan, Nigeria. African journals of plant science. Vol.9 (3). Pp.155-174. Oluwafemi S., Kraberger S., Shepherd D.N., Martin D.P. and Varsani A. 2014. A high degree of African streak virus diversity within Nigerian maize fields includes a new mastrevirus from Axonopus compressus. Archives of Virology 159:2765–2770. Oppong A., Offei S.K., Ofori K., Adu-Dapaah H., Lamptey J.N., Kurenbach B., Walters M., Shepherd D.N., Martin D.P. and Varsani A. 2013. Mapping the distribution of maize streak virus genotypes across the forest and transition zones of Ghana. Archives of Virology. 160(2), 483-492. Orians C.M., Jones C.G. 2001. Plants as resource mosaics: a functional model for predicting patterns of within-plant resource heterogeneity to consumers based on vascular architecture and local environmental variability. Oikos. 94(3): 493-504. Owor B., Shepherd D., Taylor N., Edema R., Monjane A.,Thomson J.A., Martin D.P. and Varsani A.2007. Successful application of FTA Classic Card technology and use of bacteriophage phi29 DNA polymerase for large-scale field sampling and cloning of complete maize streak virus genomes. Jornal of Virology Methods 140 (1-2), 100-105. Owor B. 2008. Maize streak virus (MSV) diversity in Uganda and the assessment of gene silencing as a tool for development of resistance to MSV (PhD Thesis, University of Cape Town). Page W.W, Smith M.C., Holt J. and Kyetere D. 1999. Intercrops, Cicadulina spp., and maize streak virus disease. Ann Applyed Biology. 135:385–393.

Pande D., Kraberger S., Lefeuvre P., Lett J.M., Shepherd D.N., Varsani A. and Martin D.P. 2012. A novel maize-infecting mastrevirus from La Reunion Island. Arch Virol 157:1617– 1621 Pande D., Madzokere E., Hartnady P., Kraberger S., Hadfield J., Rosario K., Jaschke A., Monjane A.L., Owor B.E., Dida M.M., Shepherd D.N., Martin D.P., Varsani A. and Harkins G.W. 2017. The role of Kenya in the trans-African spread of maize streak virus strain A. Virus Research. 232:69–76. Paudyal K.R., Ransom J.K., Rajbhadari N.P., Adhikari K., Gerpacio R.V.and Pingali P.L. 2001. Maize in Nepal: Production Systems, Constraints and Priorities for Research. Kathmandu: Nepal Agricultural Research Council and International Maize and Wheat ImprovementCenter. Pernet A., Hoisington D., Franco J., Isnard M., Jewell D., Jiang C., Marchand J.L., Reynaud B., Glaszmann J.C., Gonzalez de Leon D. 1999. Genetic mapping of maize streak virus resistance from the Mascarene source. I. Resistance in line D211 and stability against different virus clones. Theor Applied Genetics. 99(3/4): 524-539. Peterschmitt M., Reynaud B., Sommermeyer G.and Baudin P. 1991. Characterization of maize streak virus isolates using monoclonal and polyclonal antibodies and by transmission to a few hosts SO: Plant Disease. V. 75(1): 27-32. Pinner M.S., Markham P.G., Markham R.H. and Dekker L. 1988. Characterization of maize streak virus: description of strains; symptoms. Plant Pathology. 37(1):74-87. Piperno D. R. and Flannery K. V. 2001. The earliest archeological maize (Zea mays L.) from highland Mexico: New accelerator mass spectrometry dates and their implications. Proceedings of National Academy of Science, 98: 2101 - 2103. Pratt R., Gordon S., Lipps P., Asea G., Bigirwa G.and Pixley K. 2003. Use of IPM in the control of multiple diseases in maize: strategies for selection of host resistance. African Crop Science of Jornal. 11(3):189-198. Pratt R.C. and Gordon S.G. 2006. Breeding for resistance to maize foliar pathogens. Plant Breeding Review, 27, 119-174. Preiss W. and Jeske H. 2003. Multitasking in replication is common among geminiviruses. Journal of Virology, 77: 2972 - 2980.

Redinbaugh M.G. and Zambrano J.L. 2014. Control of virus diseases in maize. Advanced Virus Research. 90:391–429 Reynaud B., Delatte H., Peterschmitt M. and Fargette D. 2009. Effects of temperature increase on the epidemiology of three major vectorborne viruses. Europian Jornal of Plant Pathollogy. 123:269–280. Rodier A., Assié J., Marchand J.L. and Hervé Y. 1995. Breeding maize lines for complete and partial resistance to maize streak virus (MSV). Euphytica, 81, 57–70. Rose D.J.W. 1974. Epidemiology of Maize Streak Disease in Relation to PopulationDensities of Cicadulina Spp. An Applied Biology. 76(2), 199-207. Rose D.J.W. 1978. Epidemiology of maize streak disease. Ann. Rev. Entomollogy. 23, 250–282. Rossel H.W., Thottappilly G. 1985. Virus diseases of important food crops in tropical Africa IITA Ibadan, Nigeria. pg 61. Ryb icki E., Dennis S., Napier G. and Hughes F.L. 1998. Novel grass and wheat strains of maize streak virus detected by DNA amplification and sequencing. Molecular Plant Pathology. Rybicki E. P. 2015. A top ten list for economically important plant viruses. Archives of Virology, 160, 17 –20 Sanford J.C. and Johnson S.A. 1985. The concept of parasite-derived resistance-deriving resistance genes from the parasite‟s own genome. Jornal of Theor Biology. 113:395–405. Schnippenkoetter W.H., Martin D.P., Willment J.A. and Rybicki E.P. 2001. Forced recombination between distinct strains of Maize streak virus. Jornal of Gen Virology. V. 82: 3081-3090. Shepherd D.N., Mangwende T., Martin D.P., Bezuidenhout M., Kloppers F.J., Carolissen C.H., Monjane A.L., Rybicki E.P. and Thomson J.A. 2007. Transgenic resistance to msv in maize. Maize streak virus-resistant transgenic maize: A first for African Plant Biotechnology. Jnl, 5: 759–767. Shepherd D.N., Martin D.P., Van Der Walt E., Dent K., Varsani A. and Rybicki E.P. 2010. Maize streak virus: an old and complex 'emerging' pathogen. Molecular Plant Pathology. 11(1), 1-12. Shiferaw B., Prasanna B.M., Hellin J., Bänziger M. 2011. Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security. Food Security 3: 307-327.

Singh S.P., Rao N.S. and Henneberry T.J. 1993. Leafhoppers and their natural enemies Technical Bulletin Project Directorate of-Biological Control, ICAR. (6): 65. Sinha G. 2007. GM technology develops in the developing world. Science. 315:182–18. Smale M., Byerlee D.and Jayne T., 2011. Maize revolutions in Sub-Saharan Africa (World Bank PolicyResearch Working Paper, No. 5659). Storey H.H. 1925. The transmission of streak disease of maize by the leafhopper Balclutha mbila Naude. Ann Applied Biology. 12: 422-439. Sugarcane Mosaic Virus Associated with Maize Lethal Necrosis Disease. In Benishangul- Gumuz and Oromia Regions of Ethiopia. Stroud A. and Parker C. 1989. A weed identification guide for Ethiopia. Food and Agriculture Organization of the United Nations. Tamura K. 1992. Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G + C-content biases. Molecular Biology and Evolution. 9:678-687. Tefera T., Mugo S., Tende R.and Likhayo P. 2011. Methods of screening maize for resistance to stem borers and post-harvest insect pests (pp. 90-115). The 30th Annual Corn and Sorghum Research Conference, CIMMYT, Nairobi, Kenya. Thottappilly G., Bosque-Perez N. A. and Rossel H. W. 1993. Viruses and virus diseases of maize in tropical Africa. Plant Physiology, 42(4): 494 - 509. Van Antwerpen T., Macfarlane S.A., Govender P., Potier B.A.M., Way M.J., flett B. 2011. Report on maize streak virus in the South Africa sugarindustry. Proc.S Afr. Sug.Technology Association.V 84:240-250. Vanderschuren H., Stupak M., Fütterer J., Gruissem W. and Zhang P. 2007. Engineering resistance to geminiviruses – review and perspectives. Plant Biotechnology Journal. 5, pp. 207–220. doi: 10.1111/j.1467-7652.2006.00217.x. Varsani A., Monjane A.L., Donaldson L., Oluwafemi S., Zinga I., Komba E.K., Plakoutene D., Mandakombo N., Mboukoulida J., Semballa S., Briddon R.W., Markham P.G., Lett J.M., Lefeuvre P., Rybicki E.P. and Martin, D.P. 2009. Comparative analysis of Panicum streak virus and Maize streak virus diversity, recombination patterns and phylogeography. Virology Jornal. 6(1), 194.

Varsani A., Shepherd D.P., Monjane A.L., Owor B.E., Erdmann J.B. and Rybicki E.P. 2008. Recombination, decreased host specificity and increased mobility may have driven the emergence of maize streak virus as an agricultural pathogen. Jornal of Gene Virology. 89:2063-2074. Warburton M., Wilkes G., Taba S., Charcosset A., Mir C., Dumas F., Madur D., Dreisigacker, S., Bedoya C., Prasanna B. M., Xie C.X. and Hearne S. 2011. Gene flow among different teosinte taxa and into the domesticated maize gene pool. Genetic Resources and Crop Evolution, 58: 1243 - 1261. Webb M.D. 1987. Species recognition of Cicadulina leafhoppers (Hemiptera: Cicadellidae) vectors of pathogens of Graminae. Bulletin of Entomological Research 77: 683-712. Welz H.G., Schechert A., Pernet A., Pixley K.V. and Geiger, H.H. 1998. A gene for resistance to the maize streak virus in the African CIMMYT maize inbred line CML 202. Molecular. Breeding. 4, 147–154. Whitbread A.M., Jiri O. and Maasdorp B. 2004. The effect of managing improved fallows of Mucuna pruriens on maize production and soil carbon and nitrogen dynamics in sub- humid Zimbabwe. Nutrient Cycling in Agro-ecosystems. 69(1): 59-71. Willment J.A., Martin D.P. and Rybicki E.P. 2001. Analysis of the diversity of African streak mastreviruses using PCR-generated RFLP's and partial sequence data. Journal of Virology Methods, 93, 75-87. https://doi.org/10.1016/S0166-0934(00)00299-8. Willment J.A., Martin D.P., Van der Walt E., Rybicki E.P. 2002. Biological and genomic sequence characterization of Maize streak virus isolates from wheat. Phytopathology 92(1):81-86. Woolston C.J., Reynolds H.V., Stacey N.J. and Mullineaux P.M. 1989. Replication of Wheat dwarf virus DNA in protoplasts and analysis of coat protein mutants in protoplasts and plants. Nucleic Acids Research, 17: 6029 - 6041. Yahaya A., Dangora D.B., Alegbejo M.D., Kumar P.L. and Alabi O.J. 2016. Identification and molecular characterization of a novel sugarcane streak mastrevirus and an isolate of the A- strain of Maize streak virus from sugarcane in Nigeria. Archives of Virology. 162(2):597– 602.

Zerbini F.M., Briddon R.W., Idris A., Martin D.P., Moriones E., Navas-Castillo J., Rivera- Bustamante R., Roumagnac P., Varsani A. and Ictv Report C. 2017. ICTV virus taxonomy profile: geminiviridae. Jornal of Genetical Virology. 98:131–133. Zhang W., Olson N.H., Baker T. S., Faulkner L., Agbandje-McKenna M., Boulton M.I., Davies J.W., and McKenna, R. 2001. Structure of the Maize streak virus Germinate Particle. Virology, 279: 471 - 477.

8. APPENDEXS

Appendix 1 PCR Amplification using degenerate and virus-specific primers

PCR amplification of DNA samples was performed with 15µl reaction volume using the following components.

PCR components 15 µl reaction volume 5X PCR buffer 3 µl Forward primer 0.5 µl Reverse primer 0.5 µl Taq DNA polymerase 0.15 µl sdH2o 8.85 µl CDNA 2 µl

 Thermocyling programs

94 °C 1 min 93 °C 45 second 54 °C 30 second 30 cycles 72 °C 90 min 72 °C 5 min

Appendix 2 Gel photograph of Genomic DNA extracted by CTAB method

Appendix 3 MSV Field Survey Form/Sheet

Surveyor Name

Date of Survey / / Region Zone District Location

Latitude (decimal degrees): N S ●

Longitude (decimal degrees): E W ● Elevation (meters above sea level)

Survey site: □ Farmer field □ Seed production field □ Maize trial

Growth stage: Vegetative (VE-VT) Reproductive: R1.Silk R2.Blister R3. Milk R4.Dough R5. Dent R6. Maturity

Date of planting (d/m/y): / /

Field area size: ha Variety:

Incidence (%): Severity (1-5 scale):

Grass host present:

Insect (vectors) present: Leafhopper: □ High □ Moderate □Low others insect Present:

Appendix .4 MSV Field Surveyed data

Sample Inidence Severity( SN Regions Zones Districts Locations Altitude Latitude Longitude Variety Code (%) 1-5 scale) 1 GS#1 Gambela Agnuwak Abobo Mender-7 540 08. 07 324 034. 34 859 Local 70 5 2 GS#2 Gambela Agnuwak Abobo Mender-7 539 08. 03 667 034. 35 098 Local 45 4 3 GS#3 Gambela Agnuwak Abobo Mender-7 502 08. 00 989 034. 34 324 Local 60 4 4 GS#4 Gambela Agnuwak Abobo Mender-13 475 07. 58 178 034. 33 474 Local 64 4 5 GS#5 Gambela Agnuwak Abobo Mender-13 478 07. 57 560 034. 33 750 Local 75 5 Gambela 6 GS#6 Gambela Agnuwak Abobo Mender-13 472 07. 55 973 034. 33 298 75 5 Coposite 7 GS#7 Gambela Agnuwak Abobo Mender-17 460 07. 53 215 034. 30 492 Local 55 4 Gambela 8 GS#8 Gambela Agnuwak Abol Pinykew 430 08. 14 514 034. 29 466 50 4 Coposite Gambela 9 GS#9 Gambela Agnuwak Abol Kebele-02 472 08. 15 990 034. 27 728 73 5 Coposite Gambela 10 GS#10 Gambela Agnuwak Abol Kebele-01 452 08. 15 949 034. 27 106 55 5 Coposite Gambela 11 GS#11 Gambela Agnuwak Abol Pinykew 456 08. 17 021 034. 24 008 N N Coposite 12 GS#12 Gambela Nuer Itang Pulkot 437 08. 15 960 034. 15 673 Local 75 5 Gambela 13 GS#13 Gambela Nuer Itang Pulkot 435 08. 16 565 034. 14 016 75 5 Coposite 14 GS#14 Gambela Nuer Itang Wathgach 434 08. 17 589 034. 10 583 Local 35 3 15 GS#15 Gambela Nuer Itang Wathgach 427 08. 18 039 034. 08 798 Local 55 4 Gambela 16 GS#16 Gambela Nuer Itang Ware 421 08. 18 400 034. 07 256 75 4 Coposite 17 GS#17 Gambela Nuer Lare Kuthunys 417 08. 19 319 034. 00 129 Local 58 5 18 GS#18 Gambela Nuer Lare Koatmanchung 415 08. 19 737 033. 58 536 Local 73 4 19 GS#19 Gambela Nuer Lare Teluth 414 08. 20 581 033. 57 367 Local 55 4 20 GS#20 Gambela Nuer Lare Bilinkun 420 08. 22 685 033. 58 571 Local 75 5 21 GS#21 Gambela Gambela Gambela New land 447 08. 14 472 034. 36 207 Local 84 4

New 22 GS#22 Gambela Gambela Gambela 457 08. 14 452 034. 36 877 Local 85 5 university 23 GS#23 Gambela Gambela Gambela Kebele-01 455 08. 14 317 034.37 232 Local 85 5 24 JS#24 Oromia Jimma Gumay Lima Tawo 1686 08. 00 884 036. 28 318 Shone 48 4 25 JS#25 Oromia Jimma Gumay yefo Yachi 1660 07. 59 453 036. 30 641 Shone 50 4 26 JS#26 Oromia Jimma Gumay Dabu 1767 07. 55 841 036. 30 790 Shone 30 3 27 JS#27 Oromia Jimma Gomma Kilole 1664 07. 54 529 036. 33 253 Shone N N 28 JS#28 Oromia Jimma Gomma Bubulo 1583 07. 51 580 036. 38 625 Limu N N Seka 29 JS#29 Oromia Jimma Kofe 1790 07. 38 948 036. 47 517 Local 51 4 Chekorsa Seka Buyo 30 JS#30 Oromia Jimma 1782 07. 37 139 036. 45 664 BH-661 66 4 Chekorsa Kechema Seka 31 JS#31 Oromia Jimma Gibe Boso 1880 07. 34 980 036. 42 178 BH-661 50 4 Chekorsa Seka 32 JS#32 Oromia Jimma Shashemne 1903 07. 33 975 036. 39 654 BH-661 N N Chekorsa Seka 33 JS#33 Oromia Jimma Shashemne 1917 07. 33 901 036. 38 501 BH-661 28 3 Chekorsa Seka 34 JS#34 Oromia Jimma Atiro Gefere 2001 07. 33 511 036. 36 332 Local N N Chekorsa Shebe 35 JS#35 Oromia Jimma Halo sebaka 1787 07. 29 812 036. 29 578 Shone N N Sombo Shebe 36 JS#36 Oromia Jimma Sebak Wala 1680 07. 29 200 036. 28 799 BH-540 68 5 Sombo Shebe 37 JS#37 Oromia Jimma Halo sebaka 1445 07. 28 807 036. 26 889 Local 34 3 Sombo Shebe 38 JS#38 Oromia Jimma Kishe 1388 07. 28 104 036. 25 455 Shone 67 4 Sombo 39 JS#39 Oromia Jimma Kersa Merewa 1807 07. 40 754 036. 54 104 BH-661 32 3 40 JS#40 Oromia Jimma Kersa Merewa 1810 07. 41 703 036. 54 955 BH-661 46 4 41 JS#41 Oromia Jimma Kersa Babo Sete 1812 07. 42 299 036. 57 454 BH-661 N N 42 JS#42 Oromia Jimma Kersa Tikur Balto 1778 07. 42 749 037. 00 182 BH-661 35 3 43 JS#43 Oromia Jimma Kersa Kitimbile 1734 07. 42 621 036. 02 420 BH-661 30 3 44 JS#44 Oromia Jimma Mana Gudeta Bula 1992 07. 43 750 036. 46 795 BH-661 N N 45 JS#45 Oromia Jimma Mana Gube Muleta 2005 07. 44 299 036. 46 377 BH-661 N N

46 JS#46 Oromia Jimma Mana Somodo 1989 07. 44 668 036. 47 532 BH-661 32 3 47 JS#47 Oromia Jimma Mana Somodo 1988 07. 46 321 036. 47 999 BH-661 34 3 48 JS#48 Oromia Jimma Mana Belida 1863 07. 48 457 036. 47 784 BH-661 N N Buno 49 JS#49 Oromia Didesa Sobo 1519 08. 02 859 036. 28 629 Shone N N Bedele Buno 50 JS#50 Oromia Didesa Sobo 1825 08. 03 928 036. 27 421 Shone N N Bedele Buno 51 JS#51 Oromia Didesa Saso 2067 08. 06 290 036. 27 529 BH-661 N N Bedele Buno 52 JS#52 Oromia Didesa Yembero 2194 08. 09 357 036. 28 367 BH-661 N N Bedele Buno 53 JS#53 Oromia Gechi Bido 2127 08. 12 776 036. 26 736 Local N N Bedele Buno 54 JS#54 Oromia Gechi Keko 2170 08. 17 815 036. 26 941 Local N N Bedele Buno 55 JS#55 Oromia Gechi Jisa 1925 08. 22 818 036. 24 318 BH-661 N N Bedele East Guto 56 S#1 Oromiya Ambeleta 1560 09. 16 289 036. 31 089 Local 75 4 Wollega Gida East Guto 57 S#2 Oromiya Mede Jalela 1380 09. 18 901 036. 30 665 Shone 73 5 Wollega Gida East Guto 58 S#3 Oromiya Uke 1368 09. 22 078 036. 31 024 Shone 30 3 Wollega Gida East Guto 59 S#4 Oromiya Uke Badiya 1364 09. 21 947 036. 31 074 Shone 68 4 Wollega Gida East Guto 60 S#5 Oromiya Uke Badiya 1342 09. 24 164 036. 32 317 Shone N N Wollega Gida East Guto 61 S#6 Oromiya Meti 1325 09. 26 163 036. 34 354 Shone 48 4 Wollega Gida East Guto 62 S#7 Oromiya Horo 1366 09. 27 430 036. 38 426 Shone 50 4 Wollega Gida East Guto Limu + 63 S#8 Oromiya Meti 1320 09. 26 143 036. 34 587 52 5 Wollega Gida Shone East Guto 64 S#9 Oromiya Jirata 2224 09. 01 563 036. 28 897 BH-661 N N Wollega Gida East 65 S#10 Oromiya Diga Gudisa 2057 09. 02 121 036. 24.495 BH-661 35 4 Wollega East 66 S#11 Oromiya Diga Bikila 1697 09. 04 291 036. 22 200 Limu 49 4 Wollega

East 67 S#12 Oromiya Diga Bikila 1436 09. 03 077 036. 19 296 Shone 70 5 Wollega East 68 S#13 Oromiya Diga Oda 1330 09. 02 047 036. 13 607 Shone 72 4 Wollega West 69 S#15 Oromiya Gimbi Shene 1252 09. 03 677 036. 05 921 Shone 75 5 Wollega West 70 S#16 Oromiya Gimbi Abasena 1647 09. 01 448 035. 59 339 BH-540 N N Wollega West 71 S#17 Oromiya Gimbi Lelisa Yesus 1877 09. 11 532 035. 46 766 Shone 55 4 Wollega West Lalo 72 S#18 Oromiya Gerjo Siben 1839 09. 12 308 035. 43 572 BH-661 58 4 Wollega Asabi West Lalo 73 S#19 Oromiya Aroji Harowa 1886 09. 13 991 035. 41 971 Limu 62 4 Wollega Asabi West Boji 74 S#20 Oromiya Bobine 1743 09. 16 845 035. 39 287 BH-661 65 4 Wollega Dirmeji West Boji 75 S#21 Oromiya Leta Bobine 1907 09. 18 390 035. 37 299 Limu 40 4 Wollega Dirmeji West Boji 76 S#22 Oromiya Bikiltu Dila 1903 09. 26 158 035. 34 394 BH-661 N N Wollega Dirmeji West 77 S#23 Oromiya Nejo Kumbi 1879 09. 28 944 035.31 663 BH-661 45 4 Wollega West 78 S#24 Oromiya Nejo Woligelte 1896 09. 31 643 035. 29 220 Shone 46 4 Wollega West 79 S#25 Oromiya Nejo Kote Genasi 1908 09. 33 647 035. 25 623 Shone 30 3 Wollega West Leta 80 S#26 Oromiya Gori keble 01 1778 09. 36 990 035. 20 265 Limu 44 4 Wollega Sibu West Leta 81 S#27 Oromiya Gori keble 02 1647 09. 38 196 035. 19 146 Shone N N Wollega Sibu West kiltu 82 S#28 Oromiya Dandi Gudi 1637 09. 39 655 035. 18 754 Limu 66 4 Wollega Kara West kiltu Kiltu kara 83 S#29 Oromiya 1579 09. 40 943 035. 16 912 Limu 48 4 Wollega Kara Badiya West kiltu 84 S#30 Oromiya Bato Dale 1611 09. 40 647 035. 14 697 Limu 65 5 Wollega Kara West Mene 85 S#31 Oromiya Biyo Sechi 1577 09. 42 458 035. 12 234 Shone 55 4 Wollega Sibu West Mene 86 S#32 Oromiya Rega Sechi 1623 09. 44 174 035. 10 009 Limu 65 4 Wollega Sibu

West Mene 87 S#33 Oromiya Kersa 1750 09. 49 655 035. 04 662 Limu 48 4 Wollega Sibu West Mene 88 S#60 Oromiya Kela Dabus 1371 09. 45 410 034. 49 235 Shone 72 4 Wollega Sibu West Mene 89 S#61 Oromiya Kela Dabus 1959 09. 46 497 034. 52 658 Shone 45 4 Wollega Sibu West Mene 90 S#62 Oromiya Bengua 1418 09. 47 113 034. 55 897 Shone 65 5 Wollega Sibu West Mene 91 S#63 Oromiya Teyibaba 1608 09. 48 166 035. 00 998 Limu 56 4 Wollega Sibu West 92 S#64 Oromiya Gimbi Melka Gasi 1911 09. 08 841 035. 51 451 Local 50 4 Wollega West 93 S#65 Oromiya Gimbi Shone 1804 09. 05 070 035. 54 278 Shone 53 4 Wollega East Wayu 94 S#66 Oromiya Gute Badiya 1896 09.01 838 036. 38 795 BH-661 N N Wollega Tuka East Wayu Worebabo 95 S#67 Oromiya 1884 09. 02 061 036. 41 034 Shone 36 3 Wollega Tuka Migna East 96 S#68 Oromiya Sibu Sire Chingi 1796 09. 02 868 036. 43 665 Limu N N Wollega East 97 S#69 Oromiya Sibu Sire Jalele 1828 09. 03 234 036. 47 170 Shone N N Wollega East 98 S#70 Oromiya Sibu Sire Lelisa 1845 09. 02 705 036. 53 464 BH-661 N N Wollega East 99 S#71 Oromiya Sibu Sire Chiri Jarso 1760 09. 02 647 036. 50 309 BH-661 33 3 Wollega East 100 S#72 Oromiya Sibu Sire Lelisa 1730 09. 04 397 036. 55 081 Limu N N Wollega Belo Belo 101 S#14 Benishangul Shene 1187 09. 02 196 036. 08 741 Shone 76 5 Gigafo Gigafo 102 S#34 Benishangul Asosa Banbasi Dabus 1396 09. 45 952 034. 48 002 Shone 60 4 103 S#35 Benishangul Asosa Banbasi Mutsa 1440 09. 44 716 034. 45 393 Shone 68 4 104 S#36 Benishangul Asosa Banbasi Mender-44 1424 09. 47 737 034. 42 857 Shone 50 5 105 S#37 Benishangul Asosa Banbasi Mender-46 1444 09. 50 859 034. 41 354 Shone 67 4 106 S#38 Benishangul Asosa Banbasi Mender-16 1426 09.56 752 034. 39 751 BH-540 72 5 107 S#39 Benishangul Asosa Banbasi Shekole 1253 10. 22. 909 034. 35 822 Shone 75 5 108 S#40 Benishangul Asosa Homosha Shula 1328 10. 24 636 034. 34 073 Local 72 4

109 S#41 Benishangul Asosa Homosha Bemdon 1448 10. 27 574 034. 32 368 BH-540 73 5 110 S#42 Benishangul Asosa Homosha Gima 1720 10. 21 347 034. 37 156 Shone 60 4 111 S#43 Benishangul Asosa Homosha Alegala 1387 10. 19 014 034. 38 479 BH-540 50 4 112 S#44 Benishangul Asosa Homosha Dare Selam 1382 10. 19 537 034. 40. 275 Shone N N 113 S#45 Benishangul Asosa Asosa Asosa 01 1567 10. 03 278 034. 31 629 Local 35 3 114 S#46 Benishangul Asosa Asosa Mengele 32 1513 10. 01 870 034. 31 343 Limu 70 5 115 S#47 Benishangul Asosa Asosa Mengele 33 1504 09. 59 532 034. 31 546 Limu 50 4 116 S#48 Benishangul Asosa Asosa Mengele 37 1515 09. 57 272 034. 31 649 Local 65 4 117 S#49 Benishangul Asosa Asosa Shedriya 1548 10. 02 339 034. 33 816 Local 72 5 118 S#50 Benishangul Asosa Asosa Amba 14 1509 10. 00 783 034. 36 289 Shone 60 4 119 S#51 Benishangul Asosa Asosa Gambela 1484 09. 59 836 034. 37 368 Shone 70 4 120 S#52 Benishangul Asosa Asosa Amba 16 1386 09. 57 100 034. 39 446 Shone 30 3 Bambasi 121 S#53 Benishangul Asosa Banbasi 1482 09. 44 004 034. 43 268 Local 65 4 Badiya Nebar 122 S#54 Benishangul Asosa Banbasi 1455 09. 41 635 034. 42 628 Limu 55 4 Keshimando 123 S#55 Benishangul Asosa Banbasi Keshmando 2 1388 09. 36 652 034. 41 507 Shone 75 5 124 S#56 Benishangul Asosa Asosa Amba 5 1611 10. 06 249 034. 35 739 Local 50 4 125 S#57 Benishangul Asosa Asosa Baro 1569 10. 05 343 034. 36.652 Local 68 4 126 S#58 Benishangul Asosa Asosa Amba 23 1562 10. 04 683 034. 38 339 Shone 70 5 127 S#59 Benishangul Asosa Asosa Selega 22 1540 10. 04 192 034. 40 450 Shone 55 4

Appendix. 5 Sampling District and results of Rolling Circle Amplification

Sample number Sample code Sampling district Host RCA 1 GS#01 Abobo Maize + 2 GS#02 Abobo Maize - 3 GS#03 Abobo Maize + 4 GS#04 Abobo Maize + 5 GS#05 Abobo Maize + 6 GS#06 Abobo Maize + 7 GS#07 Abobo Maize + 8 GS#08 Abol Maize + 9 GS#09 Abol Maize + 10 GS#10 Abol Maize + 11 GS#11 Abol Maize + 12 GS#12 Itang Maize + 13 GS#13 Itang Maize + 14 GS#14 Itang Maize + 15 GS#15 Itang Maize + 16 GS#16 Itang Maize + 17 GS#17 Lare Maize + 18 GS#18 Lare Maize + 19 GS#19 Lare Maize + 20 GS#20 Lare Maize + 21 GS#22 Gambela Maize + 22 GS#23 Gambela Maize + 23 JS#24 Gumay Maize + 24 JS#25 Gumay Maize + 25 JS#26 Gumay Maize + 26 JS#29 Seka Chekorsa Maize + 27 JS#30 Seka Chekorsa Maize + 28 JS#31 Seka Chekorsa Maize + 29 JS#33 Seka Chekorsa Maize + 30 JS#36 Shebe Sombo Maize + 31 JS#37 Shebe Sombo Maize + 32 JS#38 Shebe Sombo Maize + 33 JS#39 Kersa Maize + 34 JS#40 Kersa Maize + 35 JS#42 Kersa Maize + 36 JS#43 Kersa Maize + 37 JS#46 Mana Maize +

38 JS#47 Mana Maize + 39 WS#01 Guto Gida Maize + 40 WS#02 Guto Gida Maize + 41 WS#03 Guto Gida Maize - 42 WS#04 Guto Gida Maize + 43 WS#06 Guto Gida Maize - 44 WS#07 Guto Gida Maize + 45 WS#08 Guto Gida Maize + 46 WS#10 Diga Maize + 47 WS#11 Diga Maize + 48 WS#12 Diga Maize + 49 WS#13 Diga Maize + 50 WS#14 Belo Gigafo Maize + 51 WS#15 Gimbi Maize + 52 WS#17 Gimbi Maize + 53 WS#18 Lalo Asabi Maize + 54 WS#19 Lalo Asabi Maize + 55 WS#20 Boji Dirmeji Maize + 56 WS#21 Boji Dirmeji Maize + 57 WS#23 Nejo Maize + 58 WS#24 Nejo Maize + 59 WS#25 Nejo Maize + 60 WS#26 Leta Sibu Maize + 61 WS#28 kiltu Kara Maize + 62 WS#29 kiltu Kara Maize + 63 WS#30 kiltu Kara Maize + 64 WS#31 Mene Sibu Maize + 65 WS#32 Mene Sibu Maize + 66 WS#33 Mene Sibu Maize + 67 BS#34 Banbasi Maize + 68 BS#35 Banbasi Maize + 69 BS#36 Banbasi Maize + 70 BS#37 Banbasi Maize + 71 BS#38 Banbasi Maize + 72 BS#39 Banbasi Maize + 73 BS#40 Homosha Maize + 74 BS#41 Homosha Maize + 75 BS#42 Homosha Maize + 76 BS#43 Homosha Maize + 77 BS#44 Homosha Maize + 78 BS#45 Asosa Maize +

79 BS#46 Asosa Maize + 80 BS#47 Asosa Maize + 81 BS#48 Asosa Maize + 82 BS#49 Asosa Maize + 83 BS#50 Asosa Maize + 84 BS#51 Asosa Maize + 85 BS#52 Asosa Maize + 86 BS#53 Banbasi Maize + 87 BS#54 Banbasi Maize + 88 BS#55 Banbasi Maize + 89 BS#56 Asosa Maize + 90 BS#57 Asosa Maize + 91 BS#58 Asosa Maize + 92 BS#59 Asosa Maize - 93 BS#60 Mene Sibu Maize + 94 WS#61 Mene Sibu Maize - 95 WS#62 Mene Sibu Maize + 96 WS#63 Mene Sibu Maize + 97 WS#64 Gimbi Maize + 98 WS#65 Gimbi Maize + 99 WS#67 Wayu Tuka Maize + 100 WS#70 Sibu Sire Maize - Wild 101 GS#01 Abobo grasses - Wild 102 GS#08 Abol grasses - Wild 103 GS#09 Abol grasses - Wild 104 GS#10 Abol grasses - Wild 105 GS#11 Abol grasses -