THE EFFECT OF POTYVIRUS RESISTANCE ON MAIZE LETHAL NECROSIS (MLN)
THESIS
Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University
By
VICTORIA BIKOGWA BULEGEYA
Graduate Program in Horticulture and Crop Science
The Ohio State University
2016
Master's Examination Committee:
Professor DAVID M. FRANCIS “Advisor”
Professor MARGARET G. REDINBAUGH “Co-advisor”
Professor PETER R. THOMISON
Copyrighted by
VICTORIA BIKOGWA BULEGEYA
2016
Abstract
Maize lethal necrosis (MLN) is a viral disease of corn (Zea mays L.) currently affecting farmers in East and Central Africa. MLN is caused by a combined infection of Maize chlorotic mottle virus (MCMV) and any potyvirus. In East Africa, MLN was reported to be caused by a combined infection of MCMV and Sugarcane Mosaic virus (SCMV).
Most of African maize germplasm is susceptible to the disease and there are no known sources of resistance. Resistance to MCMV has not been well studied but tolerant germplasm has been reported in the US. Resistance to the potyvirus pathogens of maize is well studied and sources of resistance are known and published. This study utilize available potyvirus resistance sources to control MLN and to link potyvirus resistance to white maize endosperm color which is preferred by consumers in Sub Saharan Africa.
Lines with different QTL for potyvirus resistance were screened against MLN using artificial inoculation and natural infestation. Genotypes used for the study were
Recombinant inbred lines (RIL) derived from Oh1VI, a line known for multi-virus resistance, and Oh28 which is a susceptible parent. Genotypes, with QTL for potyvirus resistance on chromosome 3, 6 and 10 alone and in combination were selected and screened against MLN. Experiments were set in the growth chamber at OARDC
Wooster, Ohio and MLN was inoculated using US isolates of MCMV and SCMV.
Experiments were also planted in a field at the Naivasha MLN screening facility in
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Kenya, where field inoculation was done using African isolates of MCMV and SCMV.
Experiments were also set in MLN hotspots in Arusha and Babati, Tanzania, under natural infection. Study results show significant differences among genotypes and QTL groups at P=0.05 in experiments in the growth chamber and at Babati under natural infection. In all experiments showing differences among genotype groups with different
QTL, a combination of 3, 6 and 10 provided MLN control as reflected by low MLN scores.
The study also selected for genetic linkage between potyvirus resistance and white endosperm color to bring resistance into the white maize background which is preferred by farmers and consumers in East Africa. The study used a yellow resistant line Pa405 and white susceptible lines CML333 and CML277 to generate F2 progenies which were screened using molecular markers (SSR) to select for recombinants with white endosperm and potyvirus resistance. Twenty one recombinants were selected, self- pollinated, and progeny were screened for resistance to SCMV and MDMV. Six progenies were resistant to MDMV and 4 recombinants were segregating for resistance to
SCMV, suggesting that coupling phase recombination was established in these families.
The recovered recombinants with white endosperm and potyvirus resistance can be used in breeding programs for introgression of resistance into the preferred food-grade genetic backgrounds. The results of this study provide useful baseline information for more research on MLN resistance and MLN control in Sub Saharan Africa.
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Dedicated to my family
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Acknowledgments
I am very thankful to my advisors Dr. David Francis and Dr. Margaret Redinbaugh for their guidance and support in the journey of my coursework and research to complete my degree. My extended gratitude goes to my other committee member Dr. Peter Thomison for his continuous support and advice to ensure I excel in my graduate studies. My sincere thanks go to Mark Jones and to all members of the USDA, ARS Corn, Soybean and
Wheat Quality Research Unit (CSWQRU) in Wooster for their technical and moral support. I am also very grateful to all members of Dr. Francis’ lab at Williams’s hall, OARDC, Wooster for their generous support to accomplish my work in the lab and green house. My thanks also go to my Tanzanian advisor, Dr. George Muhamba for his commitment and support to ensure my work was successful in Tanzania. My gratitude also goes to Kheri Kitenge and his team at ARI-SELIAN in Arusha Tanzania for their support in setting up my field trials. My genuine thanks also go to Dr. Biswanath Das and all member of CIMMYT Kenya for their support to conduct my experiments at Naivasha, Kenya and for mentoring me during my studies. I deeply appreciate the USAID feed the future program under iAGRI-Tanzania for funding my studies and the Borlaug LEAP fellowship for funding part of my research work in Kenya. My extended thanks go to my husband, son, parents and in-laws for their continuous support during the time of my studies. I will always remember your kindness.
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Vita
2010 ...... B.Sc. Environmental science and
management, Sokoine University of
Agriculture, Tanzania.
2012 ...... Agriculture research officer, Ministry of
agriculture livestock and fisheries at Ilonga
agriculture research station, Tanzania.
2014 to present ...... Graduate student, Department of
horticulture and crop science, The Ohio
State University, USA.
Fields of Study
Major Field: Horticulture and Crop Science
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Table of Contents
Abstract ...... ii Acknowledgments ...... v Vita ...... vi Table of Contents ...... vii List of Tables...... xii List of Figures ...... xviii
CHAPTER 1 : INTRODUCTION AND LITERATURE REVIEW ...... 1 1.1. Introduction ...... 1
1.1.2. Research objective ...... 2
1.1.3. Research hypothesis ...... 3
1.1.4. Research significance ...... 3
1.2. Literature review ...... 6
1.2.1. Maize in Sub Saharan Africa and Tanzania...... 6
1.2.2. Maize Lethal Necrosis distribution in Sub Saharan Africa...... 6
1.2.3. Causes of Maize lethal necrosis...... 7
1.2.3.1. Maize chlorotic mottle virus ...... 8
1.2.3.2. Potyviruses ...... 8
1.2.3.3. Synergism...... 9 vii
1.2.4. Host range of Maize lethal necrosis ...... 10
1.2.5.1 Plant disease resistance ...... 10
1.2.5.2. Screening for virus resistance in maize ...... 12
1.2.5.3. Screening for resistance against MLN disease ...... 13
1.2.5.4. Role of potyvirus resistance in Maize lethal necrosis control...... 13
1.2.6 Endosperm color in maize ...... 15
1.2.6.1. Y1 locus...... 16
1.2.6.2. Location of the Y1 gene ...... 17
1.2.6.3. Maize color preference in SSA ...... 17
1.2.6.4. Potyvirus resistance and endosperm color in maize ...... 18
References ...... 20
CHAPTER 2 : Response of potyvirus resistant maize genotypes to inoculation with Maize lethal necrosis (MLN) ...... 30 2. 1. Abstract ...... 30
2.2. Introduction ...... 31
2.3 Materials and methods ...... 34
2.3.1 Plant Germplasm ...... 34
2.3.2 Viral inoculum sources and preparation ...... 35
2.3.2.1 Growth chamber ...... 35
2.3.2.2 Field experiment ...... 36
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2.3.3 Experimental design and data collection ...... 37
2.3.4. Data analysis ...... 38
2.4 Results ...... 39
2.4.1 Response of genotypes to inoculation with MLN under growth chamber
conditions...... 39
2.4.2 Response of genotypes to inoculation with MLN under field conditions...... 40
2.5. Discussion ...... 40
References ...... 44
CHAPTER 3 : Response of Potyvirus resistance lines to natural infestation of maize lethal necrosis (MLN) ...... 53 3.1. Abstract ...... 53
3.2. Introduction ...... 54
3.3. Material and methods ...... 56
3.3.1 Plant material ...... 56
3.3.3. Experimental design and data collection...... 57
3.3.4. Data analysis ...... 59
3.5 Results ...... 59
3.5.1 Response of genotypes to inoculation with MLN under natural infestation. .... 59
3.5.2. Importance of specific QTL combinations in response to MLN infection ...... 60
3.5.3. Importance of QTL interaction for MLN control under natural infestation .... 61
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3.5.4. Agronomic performance of genotypes under natural infection of MLN ...... 62
3.6. Discussion ...... 62
References ...... 66
CHAPTER 4 : Selection for coupling phase recombination between potyvirus resistance and white endosperm color in maize ...... 84 4.1 Abstract ...... 84
4. 2. Introduction ...... 85
4.3 Materials and methods ...... 88
4.3.1 Germplasm materials and DNA extraction ...... 88
4.3.2 Polymerase chain reaction (PCR) ...... 89
4.3.3 Gel electrophoresis ...... 90
4.3.4 Phenotypic evaluation ...... 90
4.4 Results ...... 90
4.4.1 Selection for recombinants using kernel color ...... 90
4.4.2 Selection for recombinants using SSR markers ...... 91
4.4.3 Response of selected recombinants to infection with MDMV and SCMV ...... 91
4.5 Discussion ...... 92
References ...... 95
CHAPTER 5 : CONCLUSION ...... 102
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Bibliography ...... 107
APPENDIX A: Analysis of variance (ANOVA) tables for alpha lattice design ...... 121
APPENDIX B: Analysis of chromosome 2 MCMV QTL interaction with potyvirus resistance QTL on chromosome 3, 6 and 10 ...... 130
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List of Tables
Table 2.1. Analysis of variance for QTL group response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under growth chamber conditions .... 49
Table 2.2. Importance of specific QTL and QTL combinations in response to MLN infection under growth chamber conditions ...... 50
Table 2.3. Analysis of variance for genotype group’s response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under field conditions ...... 51
Table 2.4. Importance of specific QTL and QTL combinations in response to MLN inoculation under field conditions ...... 52
Table 3.1. List of trial site under natural infestation in Tanzania ...... 71
Table 3.2. Analysis of variance for QTL group response to infection with Maize lethal necrosis (MLN) under field conditions in Trial 1, Mlangalini, Arusha during the 2015 long season...... 72
Table 3.3. Importance of specific QTL in response to MLN infection under field conditions in trial 2, a disease hotspot at Mlangalini, Arusha during 2015 long season. .. 73
Table 3.4. Analysis of variance for genotype group response to infection with Maize lethal necrosis in trial 3, a disease hotspot at Krishna seed farm, Babati during 2016 short season...... 74
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Table 3.5. Importance of specific QTL in response to MLN infection in trial 2, a disease hotspot at Krishna Seed Farm, Babati during 2015 short season...... 75
Table 3.6. Analysis of variance for genotype group response to infection with Maize lethal necrosis under field conditions in a disease hotspot at Krishna seed farm, Babati during 2016 main season...... 76
Table 3.7. Importance of specific QTL in response to MLN infection in trial 3,a disease hotspot at Krishna Seed Farm, Babati during 2016 main season...... 77
Table 3.8. Analysis of variance for genotype group response to infection with Maize lethal necrosis in trial 4, a disease hotspot at KIRU-6 village, Babati during 2016 main season...... 78
Table 3.9. Importance of specific QTL in response to MLN infection in trial 4, a disease hotspot at KIRU-6 village, Babati during 2016 main season...... 79
Table 3.10. Analysis of variance for agronomic traits of genotypes groups with potyvirus resistance under natural infection with Maize lethal necrosis in trial 1, a disease hotspot at
Mlangalini, Arusha during 2015 main season...... 80
Table 3.11. Agronomic performance of genotypes with potyvirus resistance under natural
MLN infection in trial 1, a disease hotspot at Mlangalini, Arusha during 2015 main season...... 81
Table 3.12. Analysis of variance for agronomic traits of genotypes groups with potyvirus resistance under natural infection with Maize lethal necrosis in a disease hotspot at
Krishna Seed Farm, Babati during 2016 short season...... 82
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Table 3.13. Agronomic performance of genotypes with potyvirus resistance under natural
MLN infection in trial 2, a disease hotspot at Krishna, Babati during 2016 short season.83
Table 4.1: Marker location for umc2515 and bnlg1600 on chromosome 6 of maize ...... 99
Table 4.2. Selected recombinants with coupling phase between mdm1 loci and y1 loci 100
Table 5.1. Correlation between response of genotypes to MLN under artificial and natural infection ...... 106
Table A1. Analysis of variance for Recombinant Inbred Line (Genotype) response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under growth chamber conditions...... 122
Table A2. Analysis of variance for genotypes response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under field conditions...... 123
Table A3. Analysis of variance for response to natural infection with Maize lethal necrosis under field conditions in trial 1, Mlangalini, Arusha during the 2015 long season.
...... 124
Table A4. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 2, a disease hotspot at Krishna Seed Farm,
Babati during 2016 short season...... 125
Table A5. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 3 a disease hotspot at Krishna Seed Farm,
Babati during 2016 main season...... 126
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Table A6. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 4, a disease hotspot at KIRU-6 village,
Babati during 2016 main season...... 127
Table A7. Analysis of variance for agronomic traits of genotypes with potyvirus resistance under natural infection with Maize lethal necrosis in trial 1, a disease hotspot at
Mlangalini, Arusha during 2015 main season...... 128
Table A8. Analysis of variance for agronomic traits of genotypes with potyvirus resistance under natural infection with Maize lethal necrosis in trial 2, a disease hotspot at
Krishna seed farm, Arusha during 2015 short season...... 129
Table B1. Analysis of variance for chromosome 2 MCMV resistance markers’ response to Maize lethal necrosis (MLN) under growth chamber conditions ...... 131
Table B2. Analysis of variance for QTL groups interaction with chromosome 2 MCMV resistance markers in growth chamber experiment...... 132
Table B3. Important interactions between Potyvirus resistance QTL groups and chromosome 2 MCMV resistance QTL under growth chamber conditions ...... 133
Table B4. Important potyvirus and MCMV resistance QTL combinations for MLN control under growth chamber conditions ...... 134
Table B5. Analysis of variance for chromosome 2 MCMV resistance markers’ response to Maize lethal necrosis (MLN) under field conditions at Naivasha screening facility .. 135
Table B6. Analysis of variance for genotype groups’ interaction with chromosome 2
MCMV resistance markers under field conditions at Naivasha screening facility ...... 136
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Table B7. Important interactions between potyvirus resistance QTL groups and chromosome 2 MCMV resistance QTL under field conditions at Naivasha screening facility ...... 137
Table B8. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis under natural infestation at trial 2, Krishna Seed Farm,
Babati during 2016 short season...... 138
Table B9. Analysis of variance for genotype groups’ interaction with chromosome 2
MCMV resistance markers at trial 2, Krishna Seed Farm, Babati during 2016 short season...... 139
Table B10. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation condition at trial 2, Krishna seed farm,
Babati during 2016 short season...... 140
Table B11. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis (MLN) under natural infestation at trial 3, Krishna Seed
Farm, Babati during 2016 main season...... 141
Table B12. Analysis of variance for genotype groups’ interaction with chromosome 2
MCMV resistance markers under natural infestation at trial 3, Krishna Seed Farm, Babati during 2016 main season...... 142
Table B13. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation at trial 3, Krishna Seed Farm, Babati during 2016 main season...... 143
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Table B14. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis under natural infestation at trial 4, KIRU-6 village,
Babati during 2016 main season...... 144
Table B15. Analysis of variance for genotype groups’ interaction with chromosome 2
MCMV resistance markers under natural infestation at trial 4, KIRU-6 village, Babati during 2016 main season...... 145
Table B16. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation at trial 4, KIRU-6 village, Babati during
2016 main season...... 146
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List of Figures
Figure 4.1. Gel electrophoresis picture of DNA samples from selected F2 progenies displaying recombinant plants using marker umc2515 (top) and marker bnlg1600
(bottom). All progeny are y1y1y1, and heterozygous marker patterns therefore demonstrate the occurrence of a recombination...... 101
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CHAPTER 1
INTRODUCTION AND LITERATURE REVIEW
1.1. Introduction
Maize lethal necrosis (MLN) is a disease currently threatening cultivated corn
(Zea mays) production in east and central Africa (Mahuku et al., 2015a; Wangai et al.,
2012; Adams et al., 2013; Adams et al., 2014; Lukanda et al., 2014; Mahuku et al.,
2015b). MLN is caused by a combined infection of Maize chlorotic mottle virus
(MCMV) and any maize infecting virus in the potyvirus group such as Wheat streak mosaic virus (WSMV), Maize dwarf mosaic virus (MDMV) and Sugarcane mosaic virus
(SCMV) (Niblett & Claflin, 1978; Uyemoto et al., 1980). In East Africa the primary cause of the disease is a co- infection with Maize chlorotic mottle virus and Sugarcane mosaic virus (Wangai et al., 2012; Adams et al., 2014; Lukanda et al., 2014; Mahuku et al., 2015). MLN causes stunted plant growth, premature death or aging, male sterility and failure to tassel, malformed ears or lack of ear formation, chlorotic mottling from the plant base, leaf necrosis from the margins to the midrib and rotten or small cobs with little or no grain fill (Niblett & Claflin, 1978; Wangai et al., 2012). This suite of symptoms leads to MLN being a devastating disease.
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MLN is a problem for maize production sectors in East Africa and Sub Saharan
Africa. Isabirye & Rwomushana (2015) projected an increase of incidence and distribution to other regions of East and Central Africa with similar climatic conditions to the current hotspots and a significant southward movement to Southern African countries like Mozambique, Malawi, Angola, Namibia, Zimbabwe and Madagascar which are among the biggest maize producers (FAOSTAT, 2013). This threat of potential spread is the justification for drastic measures to find a solution to MLN. Development of resistant varieties is a crucial strategy to ensure safe production of maize in the region.
Research at CYMMIT used bi-parental populations and 2 association mapping
(AM) panels and identified major MLN resistance QTLs on chromosome 3 (Gowda et al., 2015). This major QTL for MLN resistance mapped to bin 3.04/3.05 on chromosome
3 which falls in the genomic region reported for resistance to multiple viruses including
SCMV (Zambrano et al., 2014), hence potentially linking MLN resistance to potyvirus resistance. The research described in this thesis focuses on determination of the influence of potyvirus resistance for MLN control in order gain insight into the effect of individual and a combination of potyvirus resistance QTL on MLN resistance.
1.1.2. Research objective
The study has two principal objectives:
I. Determine whether three (3) potyvirus resistance QTL on chromosomes 3, 6 and
10 provide resistance to Maize lethal necrosis (MLN).
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II. Select genetic linkage between potyvirus resistance and white endosperm color to
create resistant food – grade maize.
1.1.3. Research hypothesis
I. I hypothesize that lines with multiple potyvirus resistance QTL on chromosomes
3, 6 and 10 will perform better than controls lacking potyvirus resistance under
infection with MLN.
II. A recombination between the y1 gene and the mdm1 gene on chromosome 6 of
maize will create coupling phase organization resulting in resistant white maize
for the food-grade market in Tanzania.
1.1.4. Research significance
MLN is a threat to people’s livelihoods, food security, and nutritional well-being.
The disease is also a threat to the economic stability of African countries. MLN is a problem for the maize production sectors in Tanzania, East Africa and Sub-Saharan
Africa. The magnitude of yield loss associated with the disease makes developing cultivars with disease resistance to be used by farmers in the region of great importance.
In Kenya, MLN caused an estimated loss of $187 million equivalent to $364/ton (De
Groote et al., 2016). The loss is of direct impact to farmers because of their complete reliance on the crop for food production and income. Farmers in MLN areas have experienced a significant decrease in yield from 2011-2014 since when MLN was first reported in 2010 (Makone et al., 2014). Hence, MLN is currently the major biotic constraint for maize production in Sub-Saharan Africa.
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A survey was carried out in East African countries to study the distribution of
MLN causing viruses suggested up to 94% incidence in randomly selected and symptomatic plants (Mahuku et al., 2015). Tanzanian samples collected at Arusha and
Mwanza had 60% to 69% incidence with both viruses detected (Mahuku et al., 2015).
The survey indicated wide distribution and high prevalence of MLN viruses in East and
Central Africa emphasizing the urgency of controlling MLN in the region.
In contrast to vector control methods which may require farmers to purchase pesticides for chemical control, use of resistant varieties is considered an effective way to control diseases because it requires less input and hence is more cost effective and environmentally sustainable (Zambrano et al., 2014). This is especially true for small holder farmers in Sub Saharan Africa with little or insufficient capital to acquire chemicals for vector control.
Potyviruses are endemic to East Africa and were observed to cause crop loss of
18% to 46% (Louie, 1980). The introduction of MCMV and co-infection of maize with the endemic potyviruses to cause MLN represents a new threat to maize production in
East African countries (Wangai et al., 2012). There is a great need for identification of
MLN resistance sources, mapping of genomic regions with MLN resistance and intogression of resistance genes into widely used susceptible inbred lines and hybrids in
East Africa (Semagn et al., 2014).
Efforts to control MLN through resistance breeding have begun in individual East
African countries and among international organizations such as International Maize and
Wheat Improvement Center (CIMMYT). Together, the Kenya Agriculture and Livestock
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Research Organization (KALRO) and CIMMYT have evaluated 25,000 accessions for
MLN resistance (Semagn et al., 2014). There is a low level of resistance observed in most of the evaluated germplasm, with a few inbred lines and hybrids showing moderate resistance (Semagn et al., 2014). Preliminary data from bi-parental populations suggest major resistance QTLs occur on chromosome 3 and 6 and minor QTLs occur on all chromosomes except chromosome 8 (Gowda et al., 2015). Each QTL explained 4 to
35% of the phenotypic variation and an average of 45 to 47% of the variation within each population (Gowda et al., 2015). One QTL, in bin 3.04/3.05 on chromosome 3 and explaining 30% of phenotypic variance, was detected across two populations. This major
QTL for MLN resistance falls in the genomic region reported for resistance to multiple viruses including SCMV (Zambrano et al., 2014). This observation suggests a possible mechanism for potyvirus resistance in MLN control. Hence quantifying the influence of potyvirus resistance to MLN control is important to get more insight on the effect of individual and a combination of potyvirus resistance QTL for MLN resistance. Since
MLN is the result of double infection with MCMV and SCMV having resistance to one of the infecting viruses would represent a milestone for development of MLN resistance.
Carrying out an evaluation of maize lines with QTL for potyvirus resistance under natural and artificial infection with MLN viruses will provide more knowledge on the potential of these potyvirus resistance loci, alone or in combination, to control MLN.
The study aimed to evaluate lines with potyvirus resistance QTL in disease hotspots in Tanzania and Kenya and under high disease pressure through field and lab artificial inoculation. The project aimed to fill the knowledge gap concerning the
5 influence of potyvirus resistance QTL for the control of MLN. In addition, the experimental design will clarify how cultural practices such as planting date may contribute to controlling MLN in East Africa. Finally, the study will develop germplasm with known QTL in genetic backgrounds appropriate for food-grade maize in Africa.
1.2. Literature review
1.2.1. Maize in Sub Saharan Africa and Tanzania.
Maize originated in Central Mexico around 7000 years ago and was introduced into Africa around 1500 by the Portuguese travelling from the Americas to the West
Coast of Africa. The crop has been a widely produced food grain in Sub-Saharan Africa replacing the native sorghum and millet. Maize is a dominant and important staple food crop in Sub-Saharan Africa covering 27M hectares accounting for 30% of cereal produced (FA0, 2010). Tanzania is 14th worldwide in maize production and 4th in Africa producing 5,104,248 million tones with the value of 667,338,000USD (FAOSTAT,
2012).
1.2.2. Maize Lethal Necrosis distribution in Sub Saharan Africa.
Isabirye1 and Rwomushana (2015) modeled the current and future distribution of
MCMV/MLN and found the disease distribution as dynamic with a high risk of the disease spreading to other regions of Africa. Current MLN hotspots are located in warm humid and sub humid areas. Given these environmental conditions there is high risk of the disease in the warm environment of Eastern and Central Africa, moderate risk in
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Western and Southern Africa and low risk in Northern Africa. Isabirye & Rwomushana
(2015) showed suitability for MCMV infection was high in Ethiopia, Tanzania, D.R.
Congo, Angola, South Africa and Madagascar. Nearly total losses were predicted for
Rwanda, Burundi, and Swaziland. Substantial losses are predicted for Uganda (88.1%),
Tanzania (65.9%), Ethiopia (59.8%), Malawi (53.8%), Madagascar (45.1%) and Kenya
(41.1%). The study indicated the highest risk in East and central Africa in areas of western Kenya, northern and central Tanzania, most of Uganda, Rwanda, and Burundi, southwestern Democratic Republic of Congo, northern Angola and the Ethiopian highlands. Most of the current reports of MLN are in areas of the Great East African Rift
Valley. These observations are important considerations in describing the epidemiology and ecology of the disease. The effect of climate change on MCMV distribution is predicted to lead to significant losses in areas with potential disease suitability by 2020.
These areas are expected to move southwards to countries like to Mozambique, Angola,
Malawi, Namibia, Zimbabwe and Madagascar.
1.2.3. Causes of Maize lethal necrosis
MLN is caused by a combined infection of MCMV and any virus in the potyviridae family such as SCMV, MDMV and WSMV (Niblett & Claflin, 1978). In
East Africa, although other members of the potyvirus were reported (Louie, 1980), MLN is reported to be caused by a combined infection of MCMV and SCMV (Wangai et al.,
2012).
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1.2.3.1. Maize chlorotic mottle virus
MCMV is the only virus species in the family Tombusviridae, genus
Machlomovirus. The virus has a single-stranded RNA genome with virions that are single
30nm isometric particles with a smooth spherical or hexagonal shape (Scheets, 2010).
Depending on the host genotype, MCMV infection symptoms range from mild to severe chlorotic mottle, leaf necrosis, stunted growth, a shortened male inflorescence with few spikes, malformed or partially filled ears and premature death of plants. (Niblett
& Claflin, 1978; Uyemoto et al., 1981). In natural infections the virus causes 10-15% crop loss and up to 59% loss under inoculated conditions (Castillo & Loayza, 1977).
Maize is the natural host of MCMV. Infection of other members of the
Gramineae (Poaceae) with mechanical transmission has occurred. Recent studies have shown the presence of the virus in sugarcane (Wang et al., 2014) and sorghum (Huang et al., 2016). No dicotyledonous species have been found to be affected by the virus, including experiments with artificial transmission (Bockelman, Claflin & Uyemoto,
1982; Castillo & Hebert, 1974; Niblett & Claflin, 1978). The virus is transmitted by vectors which include chrysomelid beetles (Nault et al., 1978), corn thrips, corn rootworm, and corn flea beetle (Canabas et al., 2011). In East Africa, the commonly identified vector is maize thrips (Frankliniella williamsi) (Wangai et al., 2012; Mahuku et al., 2015).
1.2.3.2. Potyviruses
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Potyviruses (genus Potyvirus; family Potyviridae) are aphid transmitted RNA viruses with non-enveloped flexious virions having an average diameter of 12 to 15 nm and length of 720 to 850 nm. Potyviruses consists of 30% plant infecting viruses
(Riechmann et al., 1992). Potyviruses are the most destructive virus group in crops
(Shunkla et al., 1994) causing diseases major economic importance worldwide (Kuntze,
1995; Shunkla et a.l, 1994; Mahuku et al., 2015). Maize infecting potyviruses include
SCMV (Abbot & Tipet, 1966), MDMV (Williams & Alexander, 1965; Louie & Knoke,
1975), Johnson grass mosaic virus (JGMV), Sorghum mosaic virus (SrMV) (Shunkla,
1989) and Zea mosaic virus (ZeMV) (Seifers., et al, 2000). The related WSMV is classified in the genus Tritimovirus but for simplicity will be included with the potyviruses because of similarities in the resistance responses of maize to the virus.
Portyviruses were first identified in East Africa 1973 (Louie, 1980). SCMV,
Maize streak virus (MSV) and Maize mosaic virus (MMV) were reported in samples collected from 28 districts in 8 surveyed provinces in Kenya (Louie, 1980). SCMV was reported in sugarcane, maize and sorghum. SCMV was found in 15.2% of sampled fields in Nyanza and 15.8% of sampled fields the Rift valley province and 19.6% in Western provinces of Kenya (Louie, 1980). These are areas where the first case of MLN was reported in Kenya by Wangai et al (2012).
1.2.3.3. Synergism.
MCMV acts in synergism with any cereal potyvirus to cause a disease with more damaging impacts (Niblett & Claflin, 1978; Uyemoto, Bockelman & Claflin, 1980;
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Uyemoto et al., 1981). In Hawaii, MMV and MCMV were observed to cause CLN
(Nelson et al., 2011). In East Africa MLN is associated with MCMV and SCMV
The presence of a potyvirus increases the concentration of MCMV particles up to
5 times in a co - infected plant (Goldberg & Brakke, 1987; Scheets 1998). This increase in concentration is termed unilateral synergism and describes a phenomenon where the presence of one virus increases the concentration of the co-infecting virus resulting to more severe symptoms than when an individual virus infects alone (Goldberg & Brakke,
1987; Scheets 1998). The observed increase in concentration of MCMV in a co - infected plant compared to the plant infected by MCMV alone is hypothesized to be due to the ability of the potyvirus to suppress regulatory systems that would normally limit MCMV concentrations in a cell allowing easy transmission of the MCMV and increasing the symptom severity (Goldberg & Brakke, 1987).
1.2.4. Host range of Maize lethal necrosis
MLN has been reported in maize (Niblett and Claflin 1978; Wangai et al., 2012) finger millet (Kusia et al., 2015) and sugarcane (Wang et al., 2014).
1.2.5.1 Plant disease resistance
Plants, like other organisms are affected by environmental challenges both biotic and abiotic. Biotics stress comes from pest and pathogens such as fungi, bacteria, nematodes, viruses, weeds, insects, vertebrates and other plants. Plants are continuously affected by a number of diseases causing up to 100% loss. In order to cope with these
10 challenges plants have developed resistance mechanisms to prevent and resist attacks from pathogens (Dangl & Jones., 2001). Plant disease resistance is an environmentally friendly and cost effective measure to control diseases compared to other methods such as chemical control methods.
Plants prevent infections from pathogens by using mechanisms such as avoidance, resistance and tolerance which protect them before and or after pathogens invasion
(Ribeiro doVale et al., 2001). Genetically, disease resistance in plants can be either qualitative/complete resistance conditioned by a single gene/major gene or quantitative/incomplete resistance conditioned by one to many genes/minor genes
(Poland et al., 2009).
Qualitative resistance involve resistance genes (R-genes) with gene-for-gene action in which pathogen avilurence genes (Avr-gene) interact directly or indirectly with a plant resistance gene (R-gene) to activate resistance mechanism in the host plant. (Flor,
1971) found that each avilurence gene in the pathogen has a corresponding resistance gene in the host and the interaction between them initiates a hypersensitive reaction. Lack of compatibility between avirulence and resistance genes results a susceptible reaction
(Hammond-Kosack & Jones, 1997). Qualitative resistance is specific for each race and strains of a pathogen. Each species has a large number of R-genes with receptors specific to different strains of pathogens (Ellis et al., 2000).
Quantitative disease resistance is conferred by multiple genes (quantitative trait loci, QTL) with minor effects. This type of resistance is known to be non-specific and controlled by environmental factors which make it difficult to know the mechanism
11 underlying resistance by multiple genes. Due to high interaction with environment and incomplete gene effects, it is difficult to fine map and clone genes conferring quantitative disease resistance (Ali & Yan, 2012). QTL are also known to be clustered with the plants genome and R-genes are also found located in QTL location making it difficult to give clear distinction of the two (Poland et al., 2011).
1.2.5.2. Screening for virus resistance in maize
Screening for virus resistance has been done mostly through artificial inoculation
(Jones et al, 2007; Melchinger et al, 1998; Zambrano et al., 2014). Depending on the nature of the experiment, artificial inoculation has been done in the field, the greenhouse or in growth chambers. Artificial inoculation has advantages relative to natural infection due to the efficiency of producing sufficient viral inoculum, high transmission rates, uniform infection, and clear separation among resistant and susceptible plants
(Redinbaugh et al., 2014).
Screening germplasm under natural infection has been done using different approaches. There are disadvantages associated with use of natural infection for disease screening due to the influence of environment, timing of infection relative to plant growth stage and inadequate disease pressure. Despite limitations, the method has been used for identifying disease resistance in maize (Redinbaugh & Zambrano, 2014). Natural infection has provided results for MMV screening (Minge et al., 1997). The research presented in this thesis has used both natural and artificial inoculation to measure the effectiveness of both methods for MLN resistance screening.
12
1.2.5.3. Screening for resistance against MLN disease
Previously, screening for resistance to MLN was done under artificial inoculation in the field (Uyemoto et al., 1980). Currently, identification of MLN resistance germplasm is being done using artificial inoculation under growth-chamber controlled conditions in Ohio and through artificial inoculation in field trials in Kenya (Mahuku et al., 2015; Gowda et al., 2015).
The tendency of plants of a certain variety to be infected by a disease (incidence), the expression of symptoms (severity), and the degree to which a particular plant will grow and yield under the presence of a particular disease (tolerance) are three main parameters useful in evaluating resistance to systemic diseases in plants (Soto et al,
1982).
Plant responses to viral inoculation and symptom development are used to assess successful inoculation. Diagnostic approaches such as serological methods can also be used to confirm and detect infected viruses in asymptomatic plants (Redinbaugh &
Zambrano, 2014). For MLN it is important to confirm the presence of both MCMV and
SCMV to make a correct diagnosis since both viruses produce similar symptoms and
MCMV tend to be in higher concentration compared to SCMV (Mahuku et al, 2015).
1.2.5.4. Role of potyvirus resistance in Maize lethal necrosis control.
Potyvirus resistance genes/QTL have been identified on specific regions of chromosome 3, 6 and 10 (Jones et al., 2004; Jones et al., 2007; Ming et al., 1997;
13
Redinbaugh and Pratt, 2009; Zambrano et al., 2014; Zhang et al., 2003). Resistance mechanisms appear to involve the interaction of major QTLs on chromosome 3 and 6 working through additive and dominance effects depending on the virus isolate with an additional modifier effect from a minor QTL on chromosome 10. (Redinbaugh & Pratt,
2009, Xia et al., 1999; Zambrano et al., 2014). For many viruses, there is an interaction between QTL to achieve maximum resistance (Zambrano et al., 2014). For potyviruses such as SCMV, nearly complete resistance is conferred by QTL on chromosome 3 and 6
(Xia et al., 1999). Resistance to WSMV is conferred by any of three genes on chromosomes 3, 6 and 10 (Stewart et al., 2012).
The Mdm1 locus is located on the short arm of chromosome 6 in bin 01 near the nucleolar organiser region (nor) (Simcox et al, 1994). The locus also contains Scmv1 which confers resistance to SCMV and Wsm1, which confers resistance to WSMV (Jones et al, 2007; Xu et al, 1999; Xia et al, 1999). The genes segregate in a dominant fashion in both US (Louie et al, 1997; McMullen et al, 1994; Jones et al, 2007) and European germplasms (Kuntze et al, 1997; Melchinger et al., 1998). Clustering of resistance loci appears to be common in plants.
SCMV resistance genes have been studied and mapped in different studies. Scmv1 and Scmv2 were mapped on chromosome 6 and 3, respectively (Xu et al., 1999). The study used RFLP and SSR markers and mapped Scmv1 to a position on the reference map of 8.7 cM, between the nucleolus organizer region (NOR) and RFLP marker on the short arm of chromosome 6. Scmv2 mapped to position 26.8 cM flanked by RFLP markers umc92 and umc102 near the centromere of chromosome 3. The two genes are dominant
14 and both are needed to provide resistance to SCMV. The two QTL are consistently detected on chromosome 3 and 6 from different resistant lines identified in the United
States and Europe. There is evidence of epistatic effects when the two genes are in the heterozygous state (Lubberstedt et al, 1998a) with partial dominance (Xia et al, 1999).
Zambrano et al (2014) also mapped major QTLs for potyvirus resistance in a population derived from the multi-virus resistance line (Oh1VI). The study found QTL for potyvirus resistance on chromosomes 3, 6 and 10. A significant interaction of resistance QTL explained 28% of the phenotypic variance of resistance to potyviruses.
These regions were shown to be responsible for resistance to other members of the
Potyviridae family viruses such as MDMV and WSMV and Rhabdoviridae viruses such as MMV and Maize fine streak virus (MFSV).
The potyvirus resistance QTL, described above, which mapped on chromosome 3 and 6 have potential to control MLN in East Africa due to the synergism between SCMV and MCMV. The research undertaken in this project will determine the contribution of potyvirus resistance QTL in providing resistance against MLN infection and the appropriate QTL combination required to attain maximum resistance.
1.2.6 Endosperm color in maize
Endosperm color in maize is controlled by a single gene (Y1) which, when in a dominant state, produces carotenoid pigments resulting into yellow endosperm.
Conversely, a recessive state produces kernels that lack carotenoid pigments hence white
15 endosperm (y1). The outer layer surrounding the endosperm can be pigmented, and hence may mask the endosperm color resulting in red or purple colors in kernels.
1.2.6.1. Y1 locus
The Y1 locus encodes a phytoene synthease which catalyzes the rate-limiting step in the regulation of β - carotenoid biosynthesis in leaves and endosperm (Buckner et al.,
1990). It is also referred as the Phytoene Synthase, PSY1, gene (MGDB,
2015;http://archive.maizegdb.org; URL verified 25/06/2015). PSY1 converts geranylgeranyl pyrophosphate to phytoene an essential compound essential for carotenoid biosynthesis (Palaisa et al., 2003). The presence of the functional allele/enzyme leads to the production of carotenoids in maize endosperm hence yellow endosperm. Conversely, lack of a functional allele/protein results in white maize kernels.
There are several Y1 alleles named on the basis of their phenotype. The dominant allele, Y1, produces yellow endosperm and green leaves, a recessive allele y1 produces white to pale-yellow endosperm and green leaves and a pastel y1 allele which produces a white to pale yellow endosperm and pale green leaves. The pale green leaves of a pastel allele are due to reduced carotenoid level in the leaves in the seedlings resulting to photo- oxidation of chlorophyll in the leaves. At the molecular level there are many allelic variants as described based on DNA sequence (Buckner et al., 1995).
Due to a higher nutritional value, yellow endosperm maize has been a focus of breeding programs (Palaisa et al., 2003). In addition PSY has a high rate of polymorphism per 1000 bp. These data suggest a rapid evolution of PSY1 sequences and
16 imply that white maize might be the ancestral state and yellow endosperm may be a post domestication mutation.
1.2.6.2. Location of the Y1 gene
The Y1 locus is located in bin 6.01 on the long arm of chromosome six of maize.
The locus is estimated to be 3,731 base pairs (MBDB, 2015; http://archive.maizegdb.orghttp://archive.maizegdb.org; URL verified 25/06/2015).
Buckner et al (1990) cloned the Y1 gene based on its map position. Chander et al (2007) mapped a QTL with an effect on total carotenoids to the same region as the PSY1 gene using RILs developed from a cross between two yellow lines By804 and B73. The study detected other loci affecting carotenoids on chromosome 1, 3, 5, 6, 7, 8 and 10. A total of
4 QTL were found for β-carotene and β-cryptoxanthin, 5 for α-carotene, zeaxanthin and lutein and 8 for total carotenoids with additive effects. Most of the QTL for individual and total carotenoids were found on chromosome 6 and 10. The QTL with the largest effect was on the locus on chromosome 6, explaining up to 27.2% of the individual and total carotenoid effects.
1.2.6.3. Maize color preference in SSA
Maize cultivation in Africa has occurred since its introduction from North and
South America in the 16th century along the Western and Eastern coasts during the period of slave trade (Miracle, 1966). Maize production expanded due to agronomic suitability and the British starch market; which has also influenced African preference for white
17 maize compared to yellow maize. The demand was high for white soft dent compared to white flint which led to the replacement of white flint varieties with high yielding white soft dent varieties (Jayne et al., 1995). White maize is exclusively preferred for human consumption in Africa due to historical reasons and palatability preferences (Smale &
Jayne, 2003). Yellow maize is equated with animal feed and has a negative association due to food aid during difficult historical periods. This association makes white maize production crucial to food security in SSA.
Maize constitutes a major part of the meals prepared by over 44 million people in
Tanzania. Over 70% of maize is produced as a source of food mainly in the form of maize flower which makes up the main source of energy in the Tanzanian diet. It is prepared as porridge for breakfast and stiff porridge (ugali) for lunch and dinner. Small holder farmers also depend on selling their maize surplus maize meet their basic needs.
Maize also contributes to the country’s economy through export earning; Tanzania is named among the top 25 maize producers in the world (FAO, 2015; http://www.fao.org/3/a-at481e.pdf; URL verified, 19/08/2015).
1.2.6.4. Potyvirus resistance and endosperm color in maize
As described, above, studies on Potyvirus resistance have often mapped a major effect QTL to the short arm of chromosome 6, in bin 6.01(Xia et al., 1999; Jones et al;
2007; Zambrano et al 2014). The QTL is reported to harbor loci mdm1, smv1, wsm1 which confer resistance to MDMV, SCMV and WSMV respectively (McMullen and
Louie, 1989; Jones et al, 2007; Zambrano et al, 2014).
18
In studying the link between endosperm color and potyvirus resistance in maize
Scott, (1989) crossed lines with potyvirus resistance and yellow endosperm and potyvirus susceptible line with white endosperm. F2 kernels were separated based endosperm color and plants from dark yellow kernels showed low disease incidence than those from white kernels indicating resistance was linked to gene for endosperm color. Scott (1989) found that cross overs between a recessive for of y1 and a dominant mdm1 gene could be identified. Recombination between the mdm1 locus on the short arm of chromosome 6 and the nucleolus organizer region (nor) is suppressed (Simcox, 1994). Simcox recovered recombinants by generating a high resolution map using Pa405 F2 and yM14 as parents.
The locus controlling endosperm color is located -5cM away from the locus controlling potyvirus resistance on the short arm of chromosome 6 (McMullen and Louie, 1989).
Based on these results, there is a potential to select for potyvirus resistance in white kernel maize preferred by farmers and consumers in East Africa. Identifying such recombinants will be a step forward to controlling MLN disease while also providing a platform for breeding MLN resistance varieties which are accepted by farmers. CIMMYT is also currently using MAS to introgress MLN resistance into the white kernelled maize preferred by farmers in sub Saharan Africa (Semagn et al., 2014).
19
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29
CHAPTER 2
Response of potyvirus resistant maize genotypes to inoculation with Maize lethal necrosis (MLN)
2. 1. Abstract
Maize lethal necrosis (MLN) is a new devastating disease in east and central Africa.
MLN causes up to 100% yield loss in farmers’ fields. Most of African maize germplasm is susceptible to MLN and the disease has spread to eight countries in 4 years. The maize inbred line Oh1VI is known for resistance to multiple viruses in different families.
Selected genotypes from a population of recombinant inbred lines (RIL) derived from
Oh1VI and Oh28 and with QTL for potyvirus resistance were evaluated for resistance to
MLN under artificial inoculation. Individual RILs were selected from the population to experimentally compare lines with single QTL on chromosome 3, 6 and 10, as well as all possible double and triple combinations. Experiments were done under growth chamber and field conditions. The inoculum was made by preparing a mixture of MCMV and
SCMV and plant material was inoculated twice in both experiments. Results from the growth-chamber indicate significant differences among genotypes and genotype groups based on specific QTL and QTL combinations at P= 0.05. Genotypes with a combination
30 of QTL from chromosome 3, 6 and 10 developed less MLN symptomology, indicating more resistance to MLN compared to genotypes with single or no resistance sources. No significant differences were observed in the field inoculation. More research is needed to define a clear role for potyvirus resistance QTL on chromosome 3, 6 and 10 so that breeders in Sub Saharan Africa can assess the importance of intogression of these resistances into populations of adapted germplasm.
2.2. Introduction
Maize lethal necrosis (MLN) is a viral disease of cultivated Zea mays caused by a combined infection of Maize chlorotic mottle virus (MCMV) and any maize infecting virus in the potyvirus group such as Wheat streak mosaic virus (WSMV), Maize dwarf mosaic virus (MDMV) and Sugarcane mosaic virus (SCMV). The disease was first reported in Kansas in 1974 (Niblett and Claflin, 1978). In 2011 the disease was first reported in Kenya (Wangai et al., 2012), Tanzania, Rwanda, South Sudan and the
Democratic Republic of Congo (Mahuku et al., 2015). In East Africa the primary cause of the disease is a co- infection with MCMV and SCMV (Wangai et al., 2012).
MLN causes stunted plant growth, premature death or aging, male sterility and failure to tassel, malformed ears or lack of ear formation, chlorotic mottling from the plant base, leaf necrosis from the margins to the midrib and rotten or small cobs with little or no grain fill (Niblett and Claflin, 1978;Wangai et al, 2012). The magnitude of yield loss associated with the disease makes developing cultivars with disease resistance to be used by farmers in the region of great importance. In Kenya alone, MLN caused an
31 estimated loss of with a value estimated at $180 million (De Grote et al., 2015). The loss is of direct impact to maize farmers because of their complete reliance on the crop for food and as a source of income. A survey carried out in East African countries to study the distribution of MLN causing viruses showed an incidence of up to 94% in randomly selected and symptomatic plants (Mahuku et al., 2015). Tanzanian samples collected at
Arusha and Mwanza showed 60% to 69% incidence with both viruses detected (Mahuku et al., 2015). The distribution of MLN causing virus and their prevalence in East and
Central Africa emphasizes the urgency of controlling MLN in the region.
Little is still known about MCMV resistance (Redinbaugh & Zambrano, 2014) but a lot is known about potyvirus resistance (Jones et al, 2007; Redinbaugh and Pratt,
2009; Stewart et al, 2012 and Zambrano et al, 2014; Lubberstedt et al, 2006). Zambrano et al (2014) mapped major QTLs for potyvirus resistance in a population derived from the multi-virus resistant line, Oh1VI. The study found QTL on chromosomes 3, 6 and 10. A significant interaction of resistance QTL explained 28% of the phenotypic variance for potyvirus resistance. These regions were shown to be responsible for resistance to other members of the families Potyviridae, such as MDMV and WSMV, and Rhabdoviridae, such as MMV and MFSV.
Screening for resistance to maize virus diseases using artificial inoculation is an efficient way of elucidating the genetics of virus resistance (Redinbaugh & Zambrano,
2014). Artificial inoculation studies have been preferred for genetic studies because the high rate of transmission minimizes disease escapes (Redinbaugh & Zambrano, 2014).
Artificial inoculation experiments depend on the inoculation method and the environment
32 used, and may require validation in natural environments. Artificial inoculation for viruses has been performed in the field, in the greenhouse and growth chamber depending on the type of virus and mode of transmission. Inoculation protocols may affect host response and symptom expression. Variation is observed based on the number of inoculations per plant and inoculum dilution which reflects virus concentration (Louie,
1986). Thus virus screening under artificial inoculation requires a comparison of methods.
In field environments, artificial inoculation is usually done using vectors for phloem infecting viruses (Zambrano et al., 2013) and using a backpack sprayer for mechanically transmitted viruses. Studies on screening for virus resistance have been done in the field environment under artificial inoculation in Europe for SCMV and
MDMV (Melchinger et al., 1997; Kuntze et al., 1997), in the U.S. for MDMV, SCMV and WSMV (Louie et al, 1993; Jones et al, 2004; Jones et al 2007; Jones et al., 2011), in
Hawaii for MMV (Ming et al., 1996) and in Africa for MSV (Melz et al., 1998; Abolo et al., 2009; Kyetere et al., 1999).
Growth chamber experiments are useful when an experiment requires controlled conditions and to contain pathogens. Growth chambers provide a defined environment for plant growth. In experiments where specific conditions are required, growth chambers can provide desirable temperature and moisture (Xu et al., 2008). Assessment of virus symptoms in maize has been successful in growth chambers especially when involving insect vectors (Louie and Anderson, 1993; Zambrano et al., 2014; Nault., 1980). In addition, growth chambers can be used to gather information on viruses that need to be
33 restricted based on their range. For example, MCMV does not occur in Ohio and cannot be introduced outside the lab environment. Experiments with such a virus can only be done under controlled environments to prevent any chance of a disease escape.
Potyvirus resistances QTL have potential to control MLN resistance in East
Africa due to the synergism between SCMV and MCMV. I hypothesize that potyvirus resistance QTL will contribute to resistance against MLN infection by reducing synergism. The primary objective of this chapter is to evaluate which combinations of three major potyvirus resistance QTL may provide resistance to MLN disease. Results will determine the appropriate QTL combination required to attain maximum resistance.
2.3 Materials and methods
2.3.1 Plant Germplasm
Genetic treatments were partially inbred lines selected from a Recombinant
Inbred line (RIL) population derived from a multi-virus resistant parent Oh1VI and susceptible parent Oh28. The RIL population was generated by the Corn, Soybean and
Wheat Quality Research Unit (CSWQRU) at the Ohio Agricultural Research and
Development Center (OARDC). The RIL population was previously genotyped with 768 single nucleotide polymorphism (SNP) markers and QTL for potyvirus resistance were mapped (Zambrano et al. 2014). Selections were based on molecular markers flanking
QTL for potyvirus resistance on chromosomes 3, 6 and 10 alone and in all possible combinations. Flanking markers PHM13823-7 and PZA00667-1 were used to select for chromosome 3 QTL, markers PHM15961-13 and PZA00540-3 were used to select for
34 chromosome 6 QTL and flanking markers PHM1812-32 and PHM15868-56 selected for a QTL on chromosome 10.
Each individual QTL or combination was represented by 5 independently chosen lines. Treatments were planted for evaluation in a growth chamber at the Department of
Plant Pathology, Ohio State University/OARDC, Wooster, Ohio, May to July, 2015 and at the CYMMIT – KALRO MLN Screening Facility, Naivasha, Kenya in December,
2015 to March, 2016. Both parents were included as resistant and susceptible controls and to provide baseline information on the disease incidence and severity. Oh28 was included in the Naivasha trial, but Oh1VI was omitted. Control lines 80066 and line
80293 from Oh1VI RIL population which lack resistance alleles on all three chromosomes were included in a growth chamber experiment and CML444 and entry73 tropical lines from CIMMYT were included as controls in the field experiment as susceptible local controls.
2.3.2 Viral inoculum sources and preparation
2.3.2.1 Growth chamber
SCMV and MCMV isolates used were maintained by the USDA, CWSQRU. The
SCMV-OH isolate was collected from Ohio (Louie, 1986) and the MCMV-KS isolate was collected from Kansas (Niblett & Claflin, 1978). The sequence of MCMV-KS is
96%-97% identical to the East African isolate which is 98%-99% identical to isolates from China (Mahuku et al., 2015). The SCMV-OH isolate was maintained by serial mechanical transmission to a susceptible maize line, and the MCMV-KS isolate was
35 stored frozen and in liquid nitrogen and transmitted to the susceptible line Oh28 as a source of inoculum. Presence of the viruses in symptomatic plants was confirmed by tissue blot immunoassay as previously described (Jones et al., 2011).
Inoculum made from a mixture of infected leaf tissues for both viruses was prepared in a combination of 1:4 MCMV to SCMV to attain uniform MLN pressure.
Inoculum was prepared and symptomatic leaf tissues were ground in a 0.1 M potassium phosphate in a 1:10 dilution ratio (1 gram of tissue to 10 milliliters of the 0.1M, 7.0 pH potassium phosphate buffers) using mortar and pestle. Carborundum (0.02 g/ml) was added as an abrasive agent. The prepared inoculum was rub inoculated to leaves of 14 days old seedlings (Jones et al., 2007). There were two inoculations per experiment with the second inoculation applied two days after the first to ensure successful infection.
Plants were transferred to a growth chamber with a 25-21oC (day-night), 75% relative humidity, 532 µmol light intensity (microeinsteins) and a 12 hr photoperiod.
2.3.2.2 Field experiment
The inoculum was prepared following the protocol used at the MLN screening facility at Naivasha under CIMMYT and KARLO using East African isolates of SCMV and MCMV maintained through serial transmission to susceptible maize (Gowda et al.,
2015). The inoculum was made from a mixture of symptomatic tissues infected with individual infection of SCMV and MCMV in a combination of 4:1 ratio respectively. The inoculum was prepared by harvesting the plants infected with SCMV and MCMV separately, then the leaves were chopped, weighed and blended in 0.1M potassium
36 phosphate buffer with 1:20 dilution ratio (leaf material: buffer) at a pH of 7.0 and sieved to remove plant debris. The inoculum was mixed in a larger tank and Carborundum
1g/liter was added. Field inoculation was done using a motorized mist blower (Solo423
MistBlower, 11 liter capacity). The inoculum was delivered at a pressure of 10 kg/cm2 with a 2 inch nozzle. Inoculation was carried out at the 4-6 leaf stage, which is 5 – 6 weeks post germination, and repeated after one week.
2.3.3 Experimental design and data collection
Both the growth chamber and the field experiments were arranged in an alpha lattice design of 42 treatments in 3 replications; each replication consisted of six blocks with seven genetic treatments each. The growth chamber experiment was replicated in space and time; with each replication planted on a different date due. Each treatment consisted of a pot with five seeds. The field experiment was replicated in space by planting all 3 replications at one time. Trial design was done by using the design.alpha function in the agricolae package (https://cran.r-project.org/web/packages/agricolae).
Data collection on disease severity was based on symptom observation in the susceptible control. For the growth chamber experiment plants were evaluated for disease development beginning 7 days post second inoculation and rating continued every four days until 23 days post inoculation. For the field experiment disease rating was done 2 weeks post inoculation and continued every 7 days until 42 days post inoculation.
Disease was scored on a scale of 1 to 5 as follows: 1 = no visible MLN symptoms, 2 = fine chlorotic streaks mostly on older leaves, 3 = chlorotic mottling throughout the plant,
37
4 = excessive chlorotic mottling on lower leaves and necrosis of newly emerging leaves
(dead heart), and 5 = complete plant necrosis (Gowda et al, 2015). Severity scores collected were used to generate area under the disease progress curve (AUDPC) values.
푛−1 푌푖+푌(푖+1) The equation for AUDPC is ∑ [ ] ∗ [((푡푖 + 1) − 푡푖)] where; Yi is 푖 2 disease assessment (score), at the ith observation, ti is the time of observation (days) at the ith observation and n is the total number of observation. First scores, last scores mean scores and AUDPC values were used to test for differences among treatments under observation.
2.3.4. Data analysis
Analysis was done using the R package version 3.1.1(R Development Core team,
2014). The Agricolae package verion 1.2-3 (de Mendiburu, 2010) was used to test for differences among treatments in measured parameters. The experimental model for the alpha lattice was Yij = µ (Mean effect) + Ɍi (Replicate) +Ƭj (Treatment effect) + βi
(Incomplete Block effect) +Ɛij (Intra –block error effect). The PIBI.test function was used for the partial incomplete block design to correct for incomplete block effects (de
Mendiburu, 2010).
A two-tiered analysis was conducted in which the adjusted means from the alpha- lattice were then used to test the null hypothesis that there are no differences between higher order QTL treatments when comparing 3, 6, and 10 alone; 3 and 6, 3 and 10, 6 and
10, in combinations; and 3, 6 and 10 together. The later model was then tested using a
38 general linear model in the R core package version 3.1.1(R Development Core team,
2014).
2.4 Results
2.4.1 Response of genotypes to inoculation with MLN under growth chamber conditions.
Symptom observation started when susceptible control, Oh28 plants were 100% symptomatic. By 23 dpi, Oh28 plants had reached a score of 5, indicating that the time period was sufficient to evaluate disease development. Adjusted means were obtained from the alpha lattice design, and these were used for analysis of individual QTL and
QTL groups. There was significant variation among 40 genotypes (Appendix A) and among different combinations of potyvirus resistance QTL (Table 2.1).
Genotypes with combinations of QTL group from chromosome 3, 6 and 10 developed less disease symptoms compared to genotypes with single resistance QTL.
Genotypes with QTL from chromosomes 3 + 6, 3 +10 and 3 + 6 + 10 had significantly less disease than susceptible controls and genotypes with single QTL, and were similar to the resistant parent (Table 2.2). Genetic treatments with resistance QTL on chromosome
3 + 10 had less disease with a mean AUDPC of 25.57; those with QTL on 3 + 6 had mean AUDPC of 26.51. Genetic treatments with all three QTL for resistance (3+ 6 +10) had less disease with a mean AUDPC of 25.61 which was lower than the mean of genotypes with individual resistance QTL though not significantly different for combinations of two QTL on 3 + 10 and 3 + 6 (Table 2.2).
39
2.4.2 Response of genotypes to inoculation with MLN under field conditions.
Under field conditions there were no significant differences in MLN symptoms observed between individual RIL genotypes and controls (Appendix A) or for QTL groups (Table 2.3). Field ratings were conducted over an extended 42 day period, which may have affected our ability to discern differences. The second tier analysis based on
QTL groups indicates that genotypes with QTL combinations of 3 + 6 + 10 has significantly lower means and AUDPC scores compared to other genotype groups (Table
2.4). However, the adjusted means for first scores and last scores were not significantly different in the field environment (Table 2.4).
2.5. Discussion
The effect of potyvirus resistance QTL was evaluated for their potential to reduce
MLN symptoms under artificial inoculation in either the growth chamber or the field. The growth chamber study indicated an association between potyvirus resistance genes and reduced symptoms to MLN. Treatments with resistance QTL on 3 + 6, 3 +10 and 3 + 6
+10 had significantly (P = 0.05) lower AUDPC relative to treatments with single QTL resistance. This result shows the importance of interaction between the three QTL in conferring MLN control.
In the growth chamber experiment the susceptible parent control Oh28 differs significantly from all other treatments in response to MLN, supporting the hypothesis that potyvirus resistance reduces disease score. Genotypes with any source of Potyvirus
40 resistance also had less disease compared to a susceptible checks line 80066 and line
80293 which lack resistance QTL (Table 2.2).
The field inoculation experiment was not able to detect differences among individual RIL genotypes in response to MLN infection (Appendix A). Additionally, the analysis variance for QTL groups based on adjusted means extracted from the alpha lattice design failed to detect differences (Table 2.3). Mean separations suggested that genotypes with the 3 + 6 + 10 QTL combination had significantly lower symptoms than susceptible checks based on mean scores and AUDPC scores (Table 2.4). There are several possible reasons for inability to detect differences. Genotypes under study were created by USDA – ARS in Wooster, US (Redinbaugh & Jones, 2011) for research purposes but are not adapted to US or African environment. The lack of adaptability to a tropical environment therefore complicates interpretation. In addition, the Naivasha,
Kenya, screening facility had very high disease pressure which surpasses that observed under natural infection. Resistance may have been overwhelmed. Finally, it is possible that early differences were therefore not observed. These factors may have contributed to the failure to detect statistical differences among genotypes and genotype groups (Table
2.3).
Resistance to potyvirus is clustered in the maize genome (Redinbaugh & Pratt,
2009). Loci on the short arm of chromosome 6 and near the centromere of chromosome 3 have major effect on potyvirus resistance (Jones et al., 2007; Redinbaugh et al., 2004;
Xia et al., 1999; Zambrano et al., 2014). Given the importance of loci on chromosome 6, we expected this QTL to play a major effect in reducing MLN. However, the QTL on
41 chromosome 3 appears to be the most important, either alone or more importantly in combination with QTL on chromosome 6 and 10 because genotypes with 3+10 were similar to 3_6 and had fewer symptoms than 6+10.
There is some indication that specificity of resistance may need to be considered.
The chromosome 10 locus is known to confer resistance to WSMV and not SCMV (Jones et al., 2011; Zambrano et al., 2014). This QTL was not effective alone to reduce MLN symptoms due to a combined infection of MCMV and SCMV/MDMV. The chromosome
10 QTL provided less resistance to MLN compared to other loci (Table 2.2), unless it was combined with the QTL on chromosome 3. In contrast there was a significant contribution of loci on chromosome 3 and 6 in reducing the effect of MLN even when they occur alone. These loci were previously published for conferring resistance to
SCMV, the potyvirus used in this study (Redinbaugh et al., 2009; Melchinger et al.,
1998; Xia et al., 1999; Wang et al., 2003, Zhang et al., 2003). These results indicate the importance of SCMV resistance in controlling MLN.
The locus on chromosome 3 near the centromere at bin 3.04/3.05 in combination with other QTL confers resistance to many viruses including WSMV, SCMV, MMV and
MCDV (Redinbaugh & Zambrano, 2014). The locus overlaps the position of translation factor eIF4e (Zambrano et al., 2014), which is involved in conferring virus resistance by producing proteins which fail to interact with the virus (Gomez et al., 2009). Thus eIF4e is an attractive candidate for MLN control. A recent study of MLN resistance found other candidate genes for resistance to MLN on the same region (Gowda et al., 2015). Other candidate genes include those with a function predicted to restrict virus movement within
42 the plant as demonstrated in arabidopsis by Chrisholm et al (2000). A locus on chromosome 3.05 is known to be responsible in plant defense against pathogens encodes nucleotide-binding site leucine-rich repeat (NBS-LRR) protein (Xiao et al., 2007). The locus has also been discovered to have a minor QTL for resistance to MCMV in the
Oh1VI RIL population (Peg Redinbaugh, unpublished results).
43
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Source DFw SSw MSw F-Value P-Valuex First QTL 10 16.45 1.64 3.61 0.003** scorez groupy Residual 31 14.11 0.46
Last QTL 10 42.09 1.03 3.87 3.1x10-6*** scorez groupy Residual 31 13.80 0.27
Mean QTL 10 12.02 1.20 8.21 2.5x10-6*** scorez groupy Residual 31 4.53 0.14
AUDPCz QTL 10 1909.95 190.95 5.80 7.1x10-5*** groupy Residual 31 1019.8 32.91
w DF: Degrees of freedom, SS: Sum of squares, MS: Mean square x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y QTL group for potyvirus resistance from Chromosome 3, 6 and 10 of maize mapped from a RIL population derived from a cross of Oh1VI and Oh28 z Severity scores collected at different time points under growth chamber conditions.
Table 2.1. Analysis of variance for QTL group response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under growth chamber conditions
49
QTL groups FIRST LAST MEAN AUDPCt SCOREu SCOREv SEVERITYw Oh28x 3.06a 5.17a 4.23a 52.74a 80066z 3.21a 4.70ab 4.08a 46.88ab 80293z 2.76a 4.33abc 3.62ab 43.16abc 10 1.95b 4.04abc 3.09bc 36.63bcd 6 1.91b 4.00abc 3.05bc 34.75bcd 10_6 1.76bc 3.45bc 2.80bc 34.32cd 3 1.72bc 3.26bc 2.66cd 29.58de 3_6 1.43cd 2.90c 2.28d 26.51e 3_6_10 1.21d 3.08c 2.27d 25.61ef 3_10 1.27d 3.16c 2.17de 25.57ef Oh1V1y 1.23d 1.38d 1.35e 13.32f sGroups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. tArea under disease progress curve (AUDPC) values calculate from disease severity scores at different time points. u Disease severity score at 10 days post first inoculation v Disease severity score at 21dpi w Mean severity score from four observations at an interval of 4 days. xOh28: The susceptible parent yOh1V1: The resistant parent z80066 and 80293: Susceptible checks from a Oh1VI RIL population with no resistance QTL from chromosomes 3, 6 and 10
Table 2.2. Importance of specific QTL and QTL combinations in response to MLN infection under growth chamber conditions
50
Source Degrees Sum of Mean F- P- of squares squares Value Valuex Freedom First QTL 10 0.41 0.04 0.67 0.7457 scorez groupy Residual 31 1.88 0.06
Last QTL 10 2.84 0.28 1.494 0.1889 scorez groupy Residual 31 5.89 0.19
Mean QTL 10 1.24 0.12 1.188 0.3361 Severityz groupy Residual 31 3.25 0.1
AUDPCz QTL 10 605.9 60.59 1.185 0.3378 groupy Residual 31 1585.0 51.13 x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y QTL group for Potyvirus resistance from Chromosome 3,6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 z Severity scores collected at different time points under field conditions.
Table 2.3. Analysis of variance for genotype group’s response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under field conditions
51
QTL groupr FIRST LAST MEAN AUDPCs SCOREt SCOREu SEVERITYv Oh28x 3.18a 4.33ab 4.46a 96.20a Entry73y 2.82a 5.00a 4.36a 94.64a 3_10 2.86a 4.68a 4.15a 89.11a 83649w 2.80a 4.50ab 4.14ab 88.74ab 6 2.90a 4.60a 4.09ab 88.32ab CML444z 2.80a 5.00a 4.11ab 87.98ab 3_6 2.86a 4.89a 4.00ab 85.83ab 3 2.96a 4.50ab 4.00ab 85.74ab 10_6 2.76a 4.63a 3.97ab 85.31ab 10 2.86a 4.90a 3.99ab 84.81ab 3_6_10 2.67a 4.07ab 3.62b 78.00b
r Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. s Area under disease progress curve (AUDPC) values calculate from disease severity scores at different time points. t Disease severity score at 10dpi u Disease severity score at 21dpi v Mean severity score from four observations at an interval of 4 days. w 83649: Susceptible checks from a Oh1VI RIL population with no resistance QTL from 3, 6 and 10 xOh28: The susceptible parent yEntry73: The tropical line from CYMMIT susceptible to MLN zCML144: The tropical line from CYMMIT with resistance to MLN
Table 2.4. Importance of specific QTL and QTL combinations in response to MLN inoculation under field conditions
52
CHAPTER 3
Response of Potyvirus resistance lines to natural infestation of maize lethal necrosis
(MLN).
3.1. Abstract
Maize lethal necrosis (MLN) is a threat to food security in Sub Saharan Africa. Since reported in 2011 the disease has spread to over 8 countries in the region. MLN is associated with yield loss of up to 100% causing an estimated reduction of 126,000 metric tons representing equivalent to $52 million in Kenya in 2012 alone. Genotypes with potyvirus resistance QTL derived from a recombinant inbred line (RIL) population developed from a multi-virus resistant line, Oh1VI, were screened for resistance to MLN under natural infestation. Experiments were set in four MLN hotspots in the Arusha and
Babati districts in Tanzania. Significant difference among genotypes and genotype groups were detected P=0.05 in three hotspot with high MLN pressure. Results from one disease hotspot did not show any significant results, likely due to low MLN pressure.
Results indicate genotypes with a combination of resistance QTL on chromosome 3, 6 and 10 had lower MLN symptoms than genotypes with only single resistance QTL.
Agronomic data showed that the genotypes under study were not adapted to the tropical environment in East Africa. None of the experimental RILs perform better than tropical counterparts in agronomic parameters such as plant height, yield and anthesis to silking 53 interval. The results show a role for potyvirus resistance in MLN control and suggest the need for breeding potyvirus resistance into East Africa adapted maize.
3.2. Introduction
Maize lethal necrosis (MLN) is a devastating disease of maize (Zea mays L.) currently reported in East and Central Africa (Mahuku et al., 2015). MLN is a threat to maize production in Sub Saharan Africa (SSA) where a majority of the crop is produced for food. In SSA maize comprises 30% of all cereals produced and account for up to 30% of total calorie intake (FAO, 2010). MLN is a problem to maize production in SSA because it has direct impact on yield (Makone et al., 2014). In 2012 MLN was reported to cause up to 100% yield loss in farmers’ fields in Kenya (De Grote et al., 2016). MLN is characterized by mosaic, chlorosis and necrosis in leaves; stunted growth and early maturation in young plants and sterility and partially filled ears in matured plants (Niblett
& Claflin, 1978; Uyemoto et al., 1980). Together, these symptoms result in massive yield loss in affected fields (Mahuku et al., 2015; Makone et al., 2014).
When first reported in East Africa, MLN was observed in Kenya in areas of
Longisa district, Bomet in 2011 (Wangai et al., 2012). In 2012 similar symptoms were reported in Nyanza, Central, Western and Rift valley provinces of Kenya (Wangai et al.,
2015). In MLN was first observed at Arusha, Babati and Mwanza regions of Tanzania
(Wangai et al., 2012a) but current reports have revealed the spread of MLN to western and central parts of the country (Dr. Ndunguru, personal communication). In Africa,
MLN has also been reported in Uganda, Rwanda, the Democratic Republic of Congo,
54
Ethiopia and South Sudan (Mahuku et al., 2015). MLN was reported in the Northern
Province of Rwanda (Adams et al., 2014), in Beni, Lubero, and Rutshuru territories in
North Kivu Province of Congo (Lukanda et al., 2014), in Busia, Tororo, Iganga and
Mbale ditrict of Uganda (Kagoda et al., 2016) and in areas of Upper Awash Valley of
Ethiopia (Mahuku et al., 2015).
MLN is a viral disease caused by a combined infection of Maize chlorotic mottle virus (MCMV) and any maize infecting virus in the potyvirus group such as Wheat streak mosaic virus (WSMV), Maize dwarf mosaic virus (MDMV) and Sugarcane mosaic virus
(SCMV). The fact that the disease results from the synergism of two viruses suggests the possibility of control through resistance breeding targeted at the components, specifically potyvirus resistance. Experiments under artificial inoculations supported the hypothesis that known potyvirus resistance QTL could reduce symptoms relative to susceptible parents. In order to assess the potential of potyvirus resistance QTL under natural infection, surveys on MLN incidence and prevalence in East Africa were used to identify
MLN hotspot areas in the region. These disease hotspots are used by scientists to screen germplasms for resistance to MLN through natural infestation. In Kenya disease hotspots were identified in the Bomet and Mwea regions. In Tanzania, disease hotspots have been identified in Arusha and Manyara.
Screening for disease resistance under natural infestation in maize has been useful in identifying germplasm with resistance to different pathogens (Mario et al., 2011), insect pests (Malvar et al., 2000; Dhliwayo & Pixley, 2003; Carena & Glogoza, 2004), weeds (Kim et al., 2002) and nematodes (Kagoda et al., 2011). Studies on screening
55 maize lines for virus resistance under natural infestation have long been employed to select plants with resistance (Estakhr et al., 2016; Schenck & Lehrer, 2000). The method is dependent on environmental factors to facilitate disease development including climatic conditions favorable for pathogen and vector growth. Dependence on environmental factors causes a challenge in employing this method because it increases the risk of disease escape and unequal disease pressure. Experimental designs that assess the relative importance of genetic and environmental factors help to ameliorate concerns about variable conditions under natural infection. Despite the influence of environment, screening for resistance under natural infestation has been employed effectively
(Redinbaugh & Zambrano, 2014).
3.3. Material and methods
3.3.1 Plant material
Treatments were selected lines from a recombinant inbred line (RIL) population derived from a multi-virus resistant parent Oh1VI and susceptible parent Oh28 generated by the Corn, Soybean and Wheat Quality Research Unit (CSWQRU) at the Ohio
Agricultural Research and Development Centre (OARDC). Selections were lines containing QTL for potyvirus resistance on chromosome 3, 6 and 10 alone and in all possible combinations. Each individual QTL or combination was represented by 5 independently lines.
Lines were chosen based on flanking molecular markers on chromosome 3, 6 and
10. The chromosome 3 QTL was selected using flanking markers PHM13823-7 and
56
PZA00667-1, the chromosome 6 QTL was selected using markers PHM15961-13 and
PZA00540-3 and the chromosome 10 QTL was selected using flanking markers
PHM1812-32 and PHM15868-56.
Treatments were planted for evaluation in fields at Babati – Manyara (latitude: -
4.20963602, longitude: 35.73990726, elevation: 1378m) and Mlangalini – Arusha
(latitude:-3.3666700, longitude 36.6833300, elevation 1415m), Tanzania. Both parents and local checks were included as resistant and susceptible checks to give baseline information on disease severity and incidence on each location. Local checks used were
CML144, CML197 for the 2015 trials and CML442, CML395, KS23-6 and KS23-5 for the 2016 trials.
3.3.2. Seasons and planting date
In Tanzania maize is planted in two seasons; short rainy season (vuli) and long rainy season (masika/msimu) with different agricultural ecologies. There are two rainfall patterns; a unimodal pattern receiving only long rains and bimodal rainfall pattern receiving both short and long rains (FAO, 2016). MLN hotspots used in this study are located in the Manyara and Arusha regions both which both have bimodal rainfall distribution patterns.
3.3.3. Experimental design and data collection
Trials are designated 1-4 according to Table 1. All field experiments were established following the alpha lattice design. Trials 1-3 had 42 treatments with 3
57 replications; each replication consisted of 6 blocks with seven genetic treatments. Trial 4, had a total of 40 treatments and each replication had 4 blocks of 10 genetic treatments.
Each treatment was planted in a row of 5 m with intra-row spacing of 25 cm and inter- row spacing 75 cm. All 3 replications were planted in the same location in one experiment. All trials were planted under rainfed conditions; irrigation was supplementary in non-rain days and Diammonium phosphate (DAP) at planting and urea as a top dressing added to supplement nitrogen and phosphorus sources using local recommended rates.
Data collection on disease incidence and severity was based on symptom observation in the susceptible control. Disease severity ratings were initially performed every seven days and then extended to 14 days covering a total of 56 days. Disease was scored on a scale of 1 to 5; 1 = no visible MLN symptoms, 2 = fine chlorotic streaks mostly on older leaves, 3 = chlorotic mottling throughout the plant, 4 = excessive chlorotic mottling on lower leaves and necrosis of newly emerging leaves (dead heart) and 5 = complete plant necrosis (Gowda et al., 2015). Severity scores were used to generate area under the disease progress curve (AUDPC) values which were analyzed to measure differences among treatments. The equation for AUDPC was
푛−1 ∑ [ 푌푖+(푌푖+1)] ∗ [((푡푖 + 1) − 푡푖)] where; Yi was disease assessment (score), at the 푖 2 ith observation, ti was the time of observation (days) at the ith observation and n was the total number of observations.
Data on agronomic characteristics such as emergence percentage, days to flowering, yield and ear rot were collected. Percent emergence was calculated from the 58 stand count at first weeding and days to flowering were calculated from dates of 50% anthesis and silking. Plant height and ear height data were measured at harvest using a field ruler. Yield data was calculated from field weight of harvested maize within a row normalized to stand count and ear rot data was collected by measuring the number of cobs affected by ear rot.
3.3.4. Data analysis
Analysis was done using the R package Agricolae (de Mendiburu, 2010). The experimental model for the alpha lattice was Yij = µ (Mean effect) + Лi (Replicate) +Ƭj
(Treatment effect) + βi (Incomplete Block effect) +Ɛij (Intra –block error effect). The
PIBI.test function was used for the partial incomplete block design to correct for incomplete block effect (de Mendiburu, 2010).
A two-tiered analysis was conducted in which the adjusted means from the alpha- lattice were then used to test the null hypothesis that there are no differences between higher order QTL treatments when comparing 3, 6, and 10 alone; 3 and 6, 3 and 10, 6 and
10, in combinations; and 3, 6 and 10 together. The model Yij = µ (Mean effect) + Ƭj
(Treatment effect) +Ɛij (error effect) where Treatment was the QTL group was then tested using a general linear model in the R core package (R Core Team, 2014).
Correlation analysis was done to test the effect of disease on growth and yield.
3.5 Results
3.5.1 Response of genotypes to inoculation with MLN under natural infestation.
59
The experiments described in this chapter do not allow us to distinguish location, year, rainfall season (long/short), or planting date (early/late) due to a lack of replication across those environmental parameters. Rather, the four trials were treated as independent environments. In a joint analysis with data normalized to the susceptible check, significant differences among genotypes were detected (P < 0.0001) and differences between environments were also detected (P = 0.0063). Due to this environmental effect, trial sites were analyzed separately.
There was no significant variation among genotypes with different QTL combinations in trial 1 set at Mlangalini, Arusha (Table 3.1). Significant variation (P =
0.05) among QTL groups was observed in 3 experiments (trials 2 through 4) set at
Krishna seed farm (Table 3.3 and Table 3.5) and KIRU-6 village at Babati, Manyara
(Table 3.7) in the first scores, last scores, mean scores and AUDPC.
3.5.2. Importance of specific QTL combinations in response to MLN infection
There were no significant differences between genotypes with different QTL combinations in trial 1 from the Mlangalini site in Arusha (Table 3.2), presumably due to low incidence. The study detected significant variation between the symptoms exhibited by genotypes with different QTL combinations due to MLN infection in trials 2-4 from
Babati MLN hotspots (Table 3.4, Table 3.6 and Table 3.8).
The analysis indicated differences in disease development for germplasm with potyvirus resistance QTL compared to the susceptible control Oh28 (Table 3.4, Table 3.6 and Table 3.8). In the trial 2, the susceptible parent line, Oh28, and a susceptible local
60 control line, CML197, had significantly higher disease scores compared to lines having single, double or triple QTL for potyvirus resistance (Table 3.4). The resistant parent,
Oh1VI, also had significantly less disease severity when compared to other genotypes in all disease evaluation parameters (Table 3.4). In trial 3 there was a significant difference between QTL groups and the susceptible parent Oh28 (Table 3.6). In this trial, resistant parent Oh1VI had the lowest disease score (Table 3.6). In trial 4, the late long season trial in Babati at KIRU-6, the susceptible parent Oh28 had significantly more disease in all four parameters first score, last score, mean score and AUDPC (Table 3.8).
3.5.3. Importance of QTL interaction for MLN control under natural infestation
In general, genotypes with a combination of three QTL from chromosomes 3, 6, and 10 performed the best across experiments, reducing disease severity by an average of
20%. Combinations of two QTL (3 + 10 and 3 + 6) developed less MLN symptoms compared to genotypes with a single resistance sources. These results indicate a role for
QTL interaction in MLN control.
Results for trial 2, trial 3 and trial 4 in 2016 indicated genotypes with combination of QTL from chromosome 3 + 6 + 10 displayed fewer symptoms when compared to genotypes with single QTL or a combination of two QTL from 3+6 and 3+10 (Table 3.6 and Table 3.8). In trial 2 no significant difference between all QTL groups except for a susceptible control in AUDPC scores and first scores. Despite the lack of significance in the early ratings, differences between different QTL groups are seen in the last score where a combination of 3 + 6 + 10 is significantly different from 3 + 6, 3 + 10 and 10 +
61
6. Also for the parameter of mean score, results indicate that genotypes with combinations of three QTL and two QTL are significantly different than genotypes with single QTL sources of resistance (Table 3.6).
Trial 2 results show that even when existing alone, the chromosome 3 QTL provides MLN resistance which is not significantly different to resistance provided when the QTL exist in a combination with QTL from chromosome 6 or 10 (Table 3.4). Despite trial 4 results showing significant difference between chromosome 3 QTL and other
QTLs in a combination of two and three, the QTL still displayed low disease scores compared to 6 and 10 when alone or in combination of 6+10 (Table 3.8).
3.5.4. Agronomic performance of genotypes under natural infection of MLN
Data on agronomic performance among genotypes shows a clear difference of between RIL genotypes, QTL groups and local checks adapted to a tropical environment.
Agronomic data were not collected from trials 3 and 4. In parameters such as percent emergency, days to flowering and yield there is a significant difference between RIL genotype (Appendix B) and genotype groups in trial 1 (Table 3.9 and Table 3.10) and trial 2 (Table 3.11 and 3.12). In both trials the difference is seen with treatments and local checks since local checks were adapted hence they outweigh genotypes under study.
3.6. Discussion
The study aimed to determine which of three potyvirus resistance QTL on chromosome 3, 6 and 10 might provide resistance to MLN. There was a significant
62 difference among genotypes and genotype groups under natural infection in 3 of four experiments. Trial 1 had low disease incidence, and differences were difficult to detect.
Significant differences between susceptible controls and genotypes with previously identified potyvirus resistance QTL support the main hypothesis of this thesis: potyvirus resistance can play role in reducing the severity of MLN. As observed in trial 2, trial 3 and trial 4 results, genotypes with one, two and three QTL for potyvirus resistance were superior to susceptible controls, including the susceptible parent Oh28 and local checks
CML197, CML442 and CML395.
In all experiments no genotypes were unaffected by MLN, indicating that the
QTL under study were not providing immunity. The best performing genotypes had a combination of potyvirus resistance on chromosomes 3, 6 and 10. The three QTL were previously shown to be important in reducing symptoms to the potyviruses SCMV (Xia et al., 1999; Zambrano, 2014) and MDMV in maize (Jones et al., 2007). The potential role of two QTL interactions cannot be disregarded as combinations of QTL 3 plus 6 and
3 plus 10 were also significantly better than controls. A role for two major QTL on chromosome 3 and 6 has previously been described for SCMV (Lübberstedt et al., 2006;
Xu et al., 2000). For MDMV complete resistance is provided by a single gene on chromosome 6 (McMullen & Louie, 1989), however this QTL was among the least effective alone and in combination with the QTL on chromosome 10. In East Africa,
MLN was reported to be caused by MCMV and SCMV (Wangai et al., 2012), so the lack of effect of the chromosome 6 QTL was puzzling. At the same time the effect of interaction between QTL on 3 and 6 is probably due to the resistance provided to SCMV.
63
During the course of the study marker data for MCMV resistance on the Oh1VI population became available (Dr. Redinbaugh, unpublished results). The unpublished results indicated a QTL for MCMV resistance on chromosome 2. The potential for an interaction with this locus on chromosome 2 and the other QTL in imparting resistance to
MLN are suggested by a marginally significant interaction between chromosome 2 and other regions (P>0.001). However, inspections of mean-separation data suggest that this interaction should be treated with caution as specific contrasts were not significant (data not shown). The exception seems to be that combinations of 6, 10 and 2 were superior to
6 and 10 alone. It is important to note that the study was not designed for evaluation of the effect of chromosome 2 QTL on MLN, and the data set was not balanced. A well designed study is therefore required for the evaluation of the role of MCMV resistance and MLN control.
Studies on resistance to MLN using 289 SNPs scored using genotyping by sequencing using 6 bi-parental populations found 3 major QTL on chromosome 3 and 6 and minor QTL on chromosome 8 and 10 to be associated with MLN tolerance (Semagn et al., 2014). Also, Gowda et al (2015) did a genome wide association study (GWAS) using two association mapping (AM) panels and found SNPs linking resistance to chromosome 3 QTL on bin 3.04/3.05. Candidate genes responsible for disease resistance in plants were identified on chromosome 2 and 3 which are involved in virus movement within the cell. In addition there are two NBS-LRR genes known to be located in chromosome 3 bin 04/05. Thus association of resistance QTL with specific candidate
64 genes may soon provide a mechanistic link for the role of potyvirus resistance and reduced symptoms to MLN.
65
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Trial Site Location Year Planting date
1 MLANGALINI Arusha 1 April 2 KRISHNA-1 Babati 1 January 3 KRISHNA-2 Babati 1 March 4 KIRU- 6 Babati 1 April
Table 3.1. List of trial site under natural infestation in Tanzania
71
Source DF Sum of Mean F- P- squares squares Value Value x First QTL 10 1.75 0.17 1.11 0.38 scorez groupy Residual 31 4.88 0.16
Last QTL 10 2.09 0.21 1.54 0.17 scorez groupy Residual 31 4.20 0.14
Mean QTL 10 1.17 0.11 1.75 0.11 Severityz groupy Residual 31 0.06 0.06
AUDPCz QTL 10 491.87 49.19 1.76 0..11 groupy Residual 31 865.08 27.91
wDF: Degrees of freedom xSignificance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for Potyvirus resistance from Chromosome 3,6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zSeverity scores collected at different time points under natural infestation.
Table 3.2. Analysis of variance for QTL group response to infection with Maize lethal necrosis (MLN) under field conditions in Trial 1, Mlangalini, Arusha during the 2015 long season.
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QTL groupu FIRST LAST MEAN AUDPC v SCOREv SCOREv SEVERITYv Oh28x 2.33a 2.33a 2.08a 41.73a 3_10 1.75ab 1.40b 1.63ab 34.44ab 83649w 1.62ab 1.67ab 1.90ab 41.80a 10 1.54ab 1.67ab 1.71ab 36.74a 3_6_10 1.51ab 1.60ab 1.74ab 37.87a 3_6 1.50ab 1.44ab 1.61ab 34.78ab 6 1.50ab 1.38b 1.63ab 35.51a 10_6 1.39b 1.27b 1.57ab 34.79ab 3 1.32b 1.12b 1.36b 29.17b Pannary 1.00b 1.00b 1.17b 25.67b sc-627z 1.00b 1.00b 1.17b 25.67b uQTL group: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. vSeverity scores collected at different time points under natural infestation w83649: Susceptible checks from a Oh1VI RIL population with no resistance QTL from 3, 6 and 10 xOh28: The susceptible parent yPannar: Local checks, commercial hybrids used by farmers in Tanzania zSc-627: Local checks, commercial hybrids used by farmers in Tanzania
Table 3.3. Importance of specific QTL in response to MLN infection under field conditions in trial 2, a disease hotspot at Mlangalini, Arusha during 2015 long season.
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Source DFw Sum of Mean F-Value P-Valuex squares squares (SS) (MS) First scorez QTL 10 0.32 0.03 1.57 0.16 groupy Residual 31 0.64 0.02
Last scorez QTL 10 9.21 0.10 2.31 9.6x10-5*** groupy Residual 31 6.32 0.19
Mean QTL 10 0.58 0.06 4.94 2.7x10-4*** severityz groupy Residual 31 0.36 0.01
AUDPCz QTL 10 883.95 88.40 3.38 0.04* groupy Residual 31 810.05 26.13 wDF: Degrees of freedom xSignificance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for Potyvirus resistance from Chromosome 3,6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zSeverity scores collected at different time points under natural infestation.
Table 3.4. Analysis of variance for genotype group response to infection with Maize lethal necrosis in trial 3, a disease hotspot at Krishna seed farm, Babati during 2016 short season.
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QTL groupu FIRST LAST MEAN AUDPCv SCOREv SCOREv SEVERITYv Oh28w 1.67a 3.5a 2.46a 101.5a CML197z 1.50ab 3.33ab 2.25ab 92.17ab 6 1.41ab 3.07bc 2.20b 91.73ab 10 1.43ab 3.03bcd 2.19b 91.35ab 3 1.34b 2.93bcd 2.12bc 89.04b 10_6 1.40ab 3.03bcd 2.13b 88.55b 3_6 1.33b 2.81de 2.09bc 88.17b 3_10 1.37ab 2.87cd 2.09bc 87.42b CML144y 1.50ab 2.83cde 2.08bc 86.33b 3_6_10 1.31bc 2.60e 1.99c 84.22b Oh1V1x 1.00c 2.17f 1.58d 66.5b uQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. vSeverity scores collected at different time points under natural infestation wOh28: The susceptible parent xOh1VI: The resistant parent yCML144: The tropical line from CYMMIT with resistance to MLN zCML197: The tropical line from CYMMIT susceptible to MLN
Table 3.5. Importance of specific QTL in response to MLN infection in trial 2, a disease hotspot at Krishna Seed Farm, Babati during 2015 short season.
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Source DFw Sum of Mean F- P-Valuey squares squares Value (SS) (MS) First QTL 10 1.72 0.17 5.45 1.21x10-3*** scorez groupy Residual 31 0.98 0.03
Last QTL 10 3.96 0.39 13.39 1.12x10-8*** scorez groupy Residual 31 0.92 0.02
Mean QTL 10 2.68 0.27 15.04 2.76x10-9*** Severityz groupy Residual 31 0.01 0.02
AUDPCz QTL 10 4800.6 480.06 13.74 8.27x10-9*** groupy Residual 31 1083.4 34.95 wDF: Degrees of freedom xSignificance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for Potyvirus resistance from Chromosome 3,6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zSeverity scores collected at different time points under natural infestation.
Table 3.6. Analysis of variance for genotype group response to infection with Maize lethal necrosis under field conditions in a disease hotspot at Krishna seed farm, Babati during 2016 main season.
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QTL groupu FIRST LAST MEAN AUDPCv SCOREv SCOREv SEVERITYv
Oh28 w 2.00a 4.00a 3.04a 128.3a 10 1.97a 3.77a 2.92a 123.3a 10_6 1.79ab 3.68ab 2.83a 120.0a 6 1.74ab 3.64ab 2.78a 117.8a CML197z 1.34ab 4.00a 2.83a 117.8ab 3 1.80ab 3.58b 2.74a 116.0ab CML144y 1.50bc 3.00cd 2.42bc 103.8bc 3_6 1.58bc 3.18cd 2.43b 102.6c 3_10 1.40c 3.29c 2.38bc 100.6c 3_6_10 1.39c 2.98d 1.22c 93.86c Oh1V1x 1.33c 2.83d 1.17c 92.17c uQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. vSeverity scores collected at different time points under natural infestation wOh28: The susceptible parent xOh1VI: The resistant parent yCML144: The tropical line from CYMMIT with resistance to MLN zCML197: The tropical line from CYMMIT susceptible to MLN
Table 3.7. Importance of specific QTL in response to MLN infection in trial 3,a disease hotspot at Krishna Seed Farm, Babati during 2016 main season.
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Source DFw Sum of Mean F- P-Valuex squares squares Value (SS) (MS)
First QTL 12 2.03 0.17 5.10 2.14x104*** scorez groupy Residual 27 0.89 0.03
Last scorez QTL 12 0.86 0.07 7.83 4.99x10-6*** groupy Residual 27 0.25 0.02
Mean QTL 12 0.08 0.07 17.12 1.35x10-9*** Severityz groupy Residual 27 0.11 0.004
AUDPCz QTL 12 1412.19 117.683 16.95 1.51x10-9*** groupy Residual 27 187.44 6.942 wDF: Degrees of freedom xSignificance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for Potyvirus resistance from Chromosome 3,6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zSeverity scores collected at different time points under natural infestation.
Table 3.8. Analysis of variance for genotype group response to infection with Maize lethal necrosis in trial 4, a disease hotspot at KIRU-6 village, Babati during 2016 main season.
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QTL groupo FIRST LAST MEAN AUDPCp SCOREp SCOREp SEVERITYp
Oh28 r 2.34a 3.83a 2.91a 120.0a CML442y 2.35a 3.50bcd 2.88ab 120.2a CML395z 2.16ab 3.67ab 2.83abc 117.7ab 10 2.06ab 3.50bc 2.77abc 116.0ab 6_10 2.07ab 3.50bc 2.74bcd 114.5abc 6 1.99ab 3.43cd 2.73cd 114.9ab 3 2.05ab 3.43cd 2.70cd 112.6bc 3_6 1.86bcd 3.47bcd 2.66de 111.5cd 3_10 1.95abc 3.33de 2.50e 108.8de 3_6_10 1.73cd 3.23e 2.50f 105.3ef KS523-6t 1.66cd 3.33de 2.41fg 100.2fg Oh1V1s 1.50de 3.33de 2.34g 97.05gh KS523-5x 0.98e 2.83f 2.08h 89.73h oQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. pSeverity scores collected at different time points under natural infestation. q83649: Susceptible checks from Oh1VI RIL population with no resistance QTL from 3, 6 and 10 rOh28: The susceptible parent sOh1V1: The resistant parent tKS523-6: Resistant check xKS523-5:Resistant check yCML442: Susceptible check zCML395: Susceptible check
Table 3.9. Importance of specific QTL in response to MLN infection in trial 4, a disease hotspot at KIRU-6 village, Babati during 2016 main season.
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Source DF SS MS F-Value P-Valuea
% QTL 10 4190.3 419.03 1.85 0.09* Emergence groupb Residual 31 7029.8 226.77
Antesis date QTL 10 53.48 5.35 1.10 0.39 groupb Residual 31 150.19 4.84
Silking date QTL 10 60.87 6.09 1.27 0.28 groupb Residual 31 148.53 4.79
Yield QTL 10 0.079 0.008 52.22 2.2x10-16 *** groupb Residual 31 0.005 0.0002
Ear rot QTL 10 1.81 0.18 0.71 0.71 groupb Residual 31 7.91 0.26
uDF: Degrees of freedom vSS: Sum of squares wMS: Mean squares x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for potyvirus resistance from chromosome 3, 6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zAgronomic parameters measured under natural infestation.
Table 3.10. Analysis of variance for agronomic traits of genotypes groups with potyvirus resistance under natural infection with Maize lethal necrosis in trial 1, a disease hotspot at Mlangalini, Arusha during 2015 main season.
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QTL Emergence Flowering date (days)u Yield/ear Ear rot u group u (%)u (Kg)u Anthesis Silking Pannary 93.33 69.00b 72.00b 0.1a 0.18b 83649v 83.29 76.94a 80.00a 0.08a 0.05c 3_6 73.45 74.11a 78.86a 0.05b 0.05c 10 72.83 75.90a 80.00a 0.05b 0.05c 3_10 68.58 74.43a 78.80a 0.05b 0.05c 6 66.81 73.63ab 78.87a 0.05b 0.04c 3_6_10 62.51 74.31a 79.17a 0.05b 0.04c 3 62.51 74.14a 78.39a 0.04b 0.04c Oh28x 60.98 75.37a 79.56a 0.04b 0.05c 10_6 52.02 74.18a 79.17a 0.03b 0.04c Sc-627z 28.33 73.33ab 77.33ab 0.03b 0.30a uQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. v83649: Susceptible checks from a Oh1VI RIL population with no resistance QTL from 3, 6 and 10 xOh28: The susceptible parent yPannar: Local check, commercial hybrids used by farmers in Tanzania zSc-627: Local check, commercial hybrids used by farmers in Tanzania
Table 3.11. Agronomic performance of genotypes with potyvirus resistance under natural MLN infection in trial 1, a disease hotspot at Mlangalini, Arusha during 2015 main season.
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Parameterz Source DFw Sum of Mean F-Value P-Valuex squares squares Emergency QTL 10 3130.1 313.01 3.59 0.002** % groupy Residual 31 2699.9 87.09
Anthesis QTL 10 86.67 8.67 2.33 0.035* date groupy Residual 31 115.27 3.72
Silking date QTL 10 66.36 6.64 1.64 0.14 groupy Residual 31 125.32 4.04
Plant height QTL 10 2881.8 298.18 0.87 0.57 groupy Residual 31 10604.8 242.09
Yield QTL 10 0.0053 0.0005 3.18 0.006** groupy Residual 31 0.0053 0.0001
Ear rot QTL 10 50.429 5.04 3.08 0.007** groupy Residual 31 50.802 1.64
wDF: Degrees of freedom xSignificance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> yQTL group for Potyvirus resistance from Chromosome 3, 6 and 10 of maize mapped from a RIL population of Oh1VI and Oh28 zAgronomic parameters measured under natural infestation
Table 3.12. Analysis of variance for agronomic traits of genotypes groups with potyvirus resistance under natural infection with Maize lethal necrosis in a disease hotspot at Krishna Seed Farm, Babati during 2016 short season.
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QTL Emergencev Flowering datev (days) Yield/earv Plant Ear rotv group u (%) (Kg) heightv (cm) Anthesis Silking
CML197w 18.33c 64.33a 67.67a 0.1a 137.5a 2.00c CML144x 45.00abc 62.00ab 65.67ab 0.08a 108.3ab 1.67c 3_6 57.49a 57.20c 61.73bc 0.05b 90.28b 3.83ab 10_6 58.16a 57.04c 61.03c 0.05b 100.3ab 4.60a 3_10 40.44bc 57.45c 61.42bc 0.05b 89.47b 4.60a 3_6_10 41.41bc 56.84c 61.24bc 0.05b 103.7ab 2.06a 10 49.93ab 57.99c 61.78bc 0.05b 93.67b 3.87ab 6 47.76ab 58.42bc 62.67bc 0.04b 94.90b 2.86bc 3 42.54bc 56.84c 60.73c 0.04b 104.1ab 4.00ab Oh1VIy 25.00bc 58.33bc 61.67bc 0.03b 100.0ab 0.67c Oh28z 51.67ab 59.33abc 61.00c 0.03b 90.00b 6.33a uQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. vAgronomic parameters measured under natural infestation w CML197: The tropical line from CYMMIT susceptible to MLN xCML444: The tropical line from CYMMIT with resistance to MLN yOh1VI: The resistant parent zOh28: The susceptible parent
Table 3.13. Agronomic performance of genotypes with potyvirus resistance under natural MLN infection in trial 2, a disease hotspot at Krishna, Babati during 2016 short season.
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CHAPTER 4
Selection for coupling phase recombination between potyvirus resistance and white endosperm color in maize
4.1 Abstract
Maize lethal necrosis (MLN) is a threat to food security in Sub-Saharan Africa where white maize is the main staple food for most families in the region. MLN is caused by a combined infection of Maize chlorotic mottle virus (MCMV) and any potyvirus such as
Sugarcane mosaic virus (SCMV), Maize dwarf mosaic virus (MDMV) and Wheat streak mosaic virus (WSMV). Most of African white maize germplasm is susceptible to MLN and there are no resistance sources known to the disease. The Y1 gene for maize endosperm color is linked to the Mdm1 gene for potyvirus resistance on chromosome 6 of maize. This chapter aimed at selecting for coupling-phase combination of potyvirus resistance from Corn belt germplasm and white endosperm, from East African germplasm to improve the level of potyvirus resistance in food-grade maize for Africa.
The white susceptible maize lines CML333 and CML277 were crossed to a yellow resistant line, Pa405, to produce F1 and F2 progenies. These progeny were screened using molecular markers to recover 22 recombinants with white endosperm. These 22 selections were advanced to F3 recombinant families, and 10 were assayed for their
84 responses to MDMV and SCMV. All families had complete resistance to MDMV as did
CML333 and CML227. Four families segregated for SCMV resistance suggesting that these had favorable recombinant events. Selection of homozygous recombinants within these families will fix the resistance and provide lines appropriate for programs in Africa to improve potyvirus resistance to maize germplasm in Sub Saharan Africa as a potential tool to help control MLN.
4. 2. Introduction
Maize is a very important staple crop in Sub-saharan Africa (SSA) grown on over 27 million hectares and accounting for 30% of cereals produced, with the following regional distribution as a percentage of total cereals: West Africa, 19%; Central Africa, 61%; East
Africa, 29%; and Southern Africa, 65% (FAO, 2010). Maize alone accounts for 30% of total calorie intake in Southern Africa (FAO, 2010). White maize is exclusively preferred for human consumption in Africa due to historical reasons and palatability preferences
(Smale & Jayne, 2003). Yellow maize is equated with animal feed and has a negative association with food aid during difficult historical periods. In Tanzania, maize constitutes a major part of all meals prepared by over 49 million people. Over 70% of maize is produced as a staple food in the form of white maize flower which makes up the main source of energy in the Tanzanian diet.
Since maize is the main source of food for people in SSA, Maize lethal necrosis (MLN) currently reported in the region is a threat to food security and nutritional requirements of
85 people in SSA (Mahuku et al., 2015) Despite Sources of resistance to MLN have not been described, though sources of resistance to individual components have been identified. Genetic studies have found potyvirus resistance genes clustered on maize chromosomes 3, 6 and 10 (Jones et al., 2007; Redinbaugh & Zambrano 2014; Stewart et al., 2013 & Zambrano et al., 2014). Two dominant genes Scmv1 and Scmv2 are known to confer complete expression of resistance to SCMV (Lubberstedt et al., 2006). Scmv1 is located on the short arm of chromosome 6 and Scmv2 is located near the centromere of chromosome 3 (Melchinger et al., 1998; Xia et al., 1999; Zhang et al., 2003.). The Mdm1 locus for controlling MDMV is located on the short arm of chromosome 6 near the nucleolar organiser region (nor) (Simcox et al, 1994). This locus also contains Wsm1 which confers resistance to WSMV (Jones et al, 2007; Xu et al, 1999; Xia et al, 1999).
The genes segregate in a dominant fashion in both US (Louie et al., 1997; McMullen et al., 1994; Jones et al., 2007) and European germplasms (Kuntze et al, 1997; Melchinger et al. (1998).
One of the known sources of resistance to potyviruses, the Mdm1 locus, is linked to the endosperm colour gene (Y1) on chromosome six (6). Several studies have explored the linkage relationship between endosperm color and potyvirus resistance in maize (Scott,
1989; McMullen and Louie, 1989; Simcox, 1994). The locus controlling endosperm colour is located -5cM away from the locus controlling potyvirus resistance on the short arm of chromosome 6 (McMullen and Louie, 1989).; Since both genes are dominant, maize lines with potyvirus resistance tend to have yellow endosperm and lines with white
86 endosperm have little or no Potyvirus resistance. Despite linkage relationships, crossing over between a recessive form of y1 and the dominant Mdm1 gene could be identified
(Scott, 1989; Simcox et al., 1994).
The Y1 locus is also located on the long arm of chromosome 6 of maize. The locus is estimated to be 3,731 base pairs (MGDB, 2015; http://archive.maizegdb.orghttp://archive.maizegdb.org; URL verified 25/06/2015) and encodes phytoene synthetase 1 (PHY1). The locus is the first committed step of the carotenoid biosynthesis pathway and determines endosperm color in maize (Buckner et al., 1990). There are several known alleles of Y1 named on the basis of their phenotype.
The dominant allele, Y1, produces yellow endosperm and green leaves, a recessive allele y1 produces white to pale-yellow endosperm and green leaves and a pastel y1 allele which produces a white to pale yellow endosperm and pale green leaves. The pale green leaves of a pastel allele are due to reduced carotenoid level in the seedling leaves resulting in photo-oxidation of chlorophyll. At the molecular level there are many allelic variants described based on DNA sequence (Buckner et al., 1995).
In efforts to control MLN, it may be important to select for potyvirus resistance in white kernel maize preferred by farmers and consumers in East Africa. Selecting for Mdm1 resistance in a y1 background would be one approach to combine potyvirus resistance and food-grade color. Identifying recombinants that bring resistance and white into coupling phase will be a step forward to controlling MLN disease. The objective of the study described in this chapter was to select for coupling-phase genetic linkage between
87 the Mdm1 locus and white endosperm color to create breeding materials that can be used to develop resistant food-grade maize.
4.3 Materials and methods
4.3.1 Germplasm materials and DNA extraction
Germplasm was derived from a cross of a potyvirus resistance yellow line Pa405 and 2
Potyvirus susceptible white CIMMYT lines, CML333 and CML277. The hybrids were self-pollinated during the winter of 2015. Seed from self-pollinated F1 plants was separated based on kernel color and only white seeds (genotype y1y1y1) were planted.
These F2 progeny were evaluated for a recombination event linking a potyvirus resistance and a recessive form of y1 by using molecular markers.
DNA was extracted using a modified cetyl trimethylammonium bromide (CTAB) extraction protocol (Doyle & Dickson, 1987). Tissue (0.2 g) was collected from young leaves of 1-2 weeks old greenhouse plants into 1.2 ml tubes (8-strip polypropylene cluster tubes, Costar, Corning, Inc.). Tubes were racked in a 96 wells format, and 4 mm metal balls were added to each tube. Extraction buffer 150 µl containing 0.35 M sorbitol, 0.1 M
Tris and 0.005 M EDTA was added in each well. Then 150 µl of the a lysis buffer with
0.2 M Tris, 0.005 M EDTA, 2.0 M NaCl and 2% CTAB was added followed by a 60 μl
5% sarkosyl. The tubes were then shaken using a GenoGrinder (BT&C/OPS Diagnostics,
Bridgewater, NJ) for 3 minutes at a 300 strokes per minute. The samples were incubated for 20 minutes at 65°C, then cooled, and mixed with 350 µl of chloroform with isoamyl alcohol (24:1). The tubes were inverted 3-5 times then centrifuged at 3000 x g for 10
88 minutes. The upper aqueous phase was then removed and transferred to a 96-well plate.
Then, 125 µl of isopropanol was added and the mixture was centrifuged for 15 – 20 minutes for DNA precipitation. The pellets were air dried for 20 to 30 minutes and 200 µl of TE buffer (10 mM Tris-HCl, pH 7.5 to 8.0, and 0.1 mM EDTA) was added to re- suspend the DNA. DNA was stored at 4 C.
4.3.2 Polymerase chain reaction (PCR)
Extracted DNA was used as template for polymerase chain reaction (PCR) to amplify allele differences among F2 plants. Primers amplifying polymorphic markers on chromosome six (6) bin 6.01 were used to identify recombinant plants from F2 population. Short sequence repeat (SSR) primers for umc2515 (forward primer
GCTAGGAGGCGCTAAATCGAG, reverse TCGATCTGCACAGATGAGTCAGTA) and bnlg1600 (forward primer TAGGCATGCATTGTCCATTG reverse primer
CGATCAGTGCGTGGAGAGTA) detected polymorphism among the two parents.
Markers and gene order are described in Table 4.1. The PCR mix contained 4 µl DNA,
0.2 µl each forward and reverse primer (100 mM), 0.8 µl 0.05 mM dNTPs, 0.4 µl Taq polymerase and 12.4 µl of PCR buffer solution (100 mM Tris-HCl, pH 9 at 25°C, 500 mM KCl and 15 mM MgCl2). PCR reactions consisted of an initial denaturation at 95°C for 3 minutes, followed by 40 cycles of 60 second denaturing at 95°C, annealing at 56°C for 45 seconds, extension at 72°C for 30 seconds, and a final extension at 72°C for 10 minutes.
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4.3.3 Gel electrophoresis
PCR products were separated on 3% agarose gels in 1X TBE (0.744 g of EDTA, 10.8 g
Tris base, 5.5 g boric acid and ddH2O to 1 L). The results were scored for recombination of Mdm1-linked markers and the y1 allele.
4.3.4 Phenotypic evaluation
Selected recombinants were self-pollinated and F3 families with white kernels and segregating for markers linked to Mdm1 were assayed for MCMV and SCMV resistance.
Recombinants with coupling-phase allele combination of y1 and Mdm1 resistance alleles were expected to segregate for resistance. Progenies were inoculated with MDMV and
SCMV through rub inoculation separately and grown in the greenhouse. Disease incidence data was collected 7 days post inoculation in an interval of 2 days.
4.4 Results
4.4.1 Selection for recombinants using kernel color
F2 progenies were generated from F1 seeds selected based on kernel color. Since both Y1 and Mdm1 are dominant, initial selection was based on white kernel color. Y1 is expressed in the endosperm, and inheritance was expected to follow a triploid pattern with Y1Y1Y1, Y1Y1y1, Y1y1y1, and y1y1y1 kernels in an expected ratio of 1:3:3:1.
Heterozygous classes were not easily distinguished and therefore the expected segregation was 7:1, yellow: white. The chi-square test showed that progeny from the
CML277 cross segregated as expected with a failure to reject 7:1 segregation (P=0.43). In
90 the CML333 cross, there were more white kernel progeny than expected; hence segregation did not fit the expected 7:1 (P < 0.05). A possible explanation for this result would be that y1y1Y1 endosperm seeds were counted as y1y1y1. A total of 900 y1
(y1y1y1) seeds were selected: 500 from CML333 and 400 from CML277 and were planted to generate F2 seedlings which were screened with molecular markers.
4.4.2 Selection for recombinants using SSR markers
PCR analysis was performed on each selected F2 progeny to detect the presence or absence of recombination between y1 and markers linked to Mdm1. The marker bnlg1600 was amplified at 190 bp for CML333 and CML277 parents and 210 bp for Pa405 parents.
F2 progenies with either a 210 bp amplicon or heterozygous for 210 and 190 bp amplicons were selected (Figure 4.1). Marker umc2515 amplified a 150 bp band from
CML333 and CML277 and 160 bp amplicon from Pa405. No F2 plants homozygous for the desired Pa405 alleles were identified, but 22 plants heterozygous for one or both markers were selected (Table 4.2). Twenty-two selected plants were transplanted into bigger pots and grown in a greenhouse and self-pollinated to generate F3 seeds, which were assayed for disease resistance (Table 4.2).
4.4.3 Response of selected recombinants to infection with MDMV and SCMV
Seedlings from 25 kernels for each of six F3 recombinant plants were assayed for their responses to inoculation with MDMV and SCMV. Of the six selected recombinant families, two were derived from CML333 and four from CML277. There is variation to
91 response of F3 progenies to inoculation with MDMV and SCMV. No seedlings developed symptoms after inoculation with MDMV. Control plants CML333 and
CML277 failed to also develop MDMV symptoms suggesting that these lines already possessed resistance from another locus. This virus was therefore not useful to verify recombinants with Mdm1.
Seedlings derived from two F3 families were completely susceptible to SCMV, suggesting that these families derived from an F2 plant where the recombination event detected based on the marker did not include the resistance gene. Four families showed segregation for resistance to SCMV. These four families were evenly divided between
CML333 and CML277 parentage, and selection of homozygotes for the recombinant chromosome will provide y1 (white) – Mdm1 (resistant) coupling phase material for future breeding efforts.
4.5 Discussion
Conventional breeding can be time consuming and resource intensive. Use of molecular markers in plant breeding has been a useful tool used in for selection in conjunction with increased breeding cycles per unit time. Markers can also minimize resources required for selection relative to conventional breeding. The selection of recombinants is one example of where marker assisted selection (MAS) can provide a resource benefit relative to conventional breeding. Resistance to MDMV and SCMV in line Pa405 is conferred by a dominant gene linked to a dominant gene for yellow endosperm
92
(McMullen & Louie, 1989). Lines CML333 and CML277 have white endosperms conferred by a recessive y1 gene and lack resistance to MDMV/SCMV conferred Mdm1.
This study aimed at breaking the linkage between the dominant Mdm1 and Y1 in order to recover recombinant plants with a dominant Mdm1 and a recessive y1.
Various studies suggest the possibility of detecting desirable recombinants on chromosome 6 (Simcox, 1994; McMullen and Louie, 1989). The loci are approximately
3.3 cM apart (McMullen and Louie, 1989) indicating a 1.65% probability of recovering recombinants with a dominant Mdm1 and a recessive y1 from a cross of yellow endosperm (Y1/Mdm1) to white endosperm (y1/mdm1). In the work above, the recovery of 22 putative recombinants out of 900 progeny indicateed a 2.4% recovery and a recombination fraction of 4.8 cM. For this study two flanking markers were used to ensure a successful selection of the recombinant plants. Marker umc2515 and marker bnlg1600 flank the Mdm1 locus and the two markers distal to the Y1 locus. Detection of recombinants with markers does not guarantee recombination between Y1 and Mdm1 due to the possibility that the recombination event was distal to MdmI relative to YI, or due to double recombinants.
When recombinant F3 families were assayed for potyvirus resistance with SCMV and MDMV, all progenies were resistant to MDMV despite the expectation of segregation in the families. This result was explained by the fact that CML333 and
CML277 were also resistant, suggesting that genes other than Mdm1 are contributing to resistance in these populations. Results also indicate that four of 6 progenies were segregating for resistance to SCMV, suggesting that this test was useful for phenotypic
93 verification of coupling phase recombination between Mdm1 and y1. Two of the families were completely susceptible to SCMV, suggesting that these recombinants failed to retain the resistant allele.
The results suggest that up to 2/3 of the recombinants detected with molecular markers established the desired coupling phase. The four families identified based on phenotypic evaluation are equally divided between the two genetic backgrounds. Thus, objectives of the research were met and germplasm is now available that combines Mdm1 with white endosperm.
We successfully moved the Mdm1 locus from yellow endosperm maize to white endosperm maize through recombination. The selected recombinants will need to undergo another breeding cycle to fix the Mdm1 allele to be available for use in breeding programs. The results are expected to be useful for breeding programs in Africa where
MLN is a threat to maize production and white maize is preferred for food (Mahuku et al., 2015). The majority of tropical maize lines currently showing resistance or tolerance to MLN are yellow (Gowda et al., 2015). Moving potyvirus resistance to a white endosperm background is steps towards ensuring a food secure Sub Saharan Africa with preferred maize food grade maize.
94
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Locus Position (cM) Distance (bp) Function umc2515 68.9 9499043 - 9499063 Marker Mdm1 69.1 9,491,573 – 14,940,074 Gene (resistance) bnlg1600 75.8 29,798,872 – 29,798,891 Marker Y1 120.5 82,017,148 – 82,020,879 Gene (endosperm)
Table 4.1. Marker location for umc2515 and bnlg1600 on chromosome 6 of maize
99
umc2515d bnlg1600d Y1e MDMV SCMV genotype genotype 1 CML333 Aa Aa y1y1y1 N.D f N.D 2 CML333 Aa Aa y1y1y1 N.D N.D 3 CML333 Aa Aa y1y1y1 N.D N.D 4 CML333 Aa AA y1y1y1 N.D N.D 5 CML333 Aa Aa y1y1y1 N.D N.D 6 CML333 Aa Aa y1y1y1 N.D N.D 7 CML333 Aa Aa y1y1y1 N.D N.D 8 CML333 Aa AA y1y1y1 N.D N.D 9 CML333 AA Aa y1y1y1 N.D N.D 10 CML333 AA Aa y1y1y1 0/25 1/25 11 CML333 Aa Aa y1y1y1 N.D N.D 12 CML333 Aa Aa y1y1y1 0/25 3/25 13 CML277 Aa Aa y1y1y1 N.D N.D 14 CML277 Aa AA y1y1y1 N.D N.D 15 CML277 Aa Aa y1y1y1 0/25 N.D 16 CML277 Aa Aa y1y1y1 0/25 23/25 17 CML277 Aa AA y1y1y1 N.D N.D 18 CML277 Aa AA y1y1y1 N.D N.D 19 CML277 Aa AA y1y1y1 0/25 3/25 20 CML277 Aa AA y1y1y1 0/25 3/25 21 CML277 Aa AA y1y1y1 N.D N.D 22 CML277 AA Aa y1y1y1 0/25 13/13 23 CML333 (parent) AA AA y1y1y1 0/12 6/12 24 CML277 (parent) AA AA y1y1y1 0/11 8/11 25 Pa405 (parent) aa Aa y1y1y1 0/12 0/12
Allele genotypes form marker umc2515 and bnlg1600: AA: Homozygous CML333/CML277, Aa: Heterozygous CML333/CML277 and aa: Homozygous Pa405 a Parent: CML333 and CML277 susceptible parents for potyvirus resistance. b F3 recombinants : Selected F3 plants from a population of CML333/CML277 X Pa405 using markers dumc 2515 and bnlg1600 flanking Mdm1 locus eY1: Endosperm color allele f N.D: Not done
Table 4.2. Selected recombinants with coupling phase between mdm1 loci and y1 loci
100
Figure 4.1. Gel electrophoresis picture of DNA samples from selected F2 progenies displaying recombinant plants using marker umc2515 (top) and marker bnlg1600 (bottom). All progeny are y1y1y1, and heterozygous marker patterns therefore demonstrate the occurrence of a recombination.
101
CHAPTER 5
CONCLUSION
Maize lethal necrosis (MLN) caused by a combined infection of Maize chlorotic mottle virus (MCMV) and Sugarcane mosaic virus (SCMV) is a threat to maize production in
Sub-Saharan Africa. No sources of resistance to the MLN and MCMV have been reported, but resistance to SCMV and other potyviruses has been well studied in Europe and US maize germplasm and resistance genes are known. In Sub Saharan Africa (SSA), current efforts have been emphasized on looking for sources of resistance to MLN and
MCMV but the role of potyvirus resistance in MLN control is not known. This study aimed at looking into the role of potyvirus resistance in MLN control by screening germplasm with potyvirus resistance under artificial and natural infection to determine the role of individual and a combination of potyvirus resistance QTL in MLN control.
The study objective was to determine whether combinations of loci previously implicated in potyvirus resistance provide more resistance to MLN and to select for genetic linkage between potyvirus resistance and endosperm color to create resistant food-grade maize.
The study used recombinant inbred lines (RIL) with one, two and three QTL for potyvirus resistance from a multi-virus resistance line OH1VI. The line, Oh1VI is
102 resistant to viruses in different families and was used to generate the RIL population.
Selected genotypes were screened for resistance to MLN under artificial inoculation in growth chamber and field environment and under natural infestation in disease hotspot in
Tanzania. There was variation in disease incidence and severity in all environments.
Under artificial inoculation experiments successful inoculation was achieved in both growth chamber and field environment although the response was different. In the growth chamber environment there was a fast disease development and data collection was done in an interval of 4 days. In a period of 28 days post inoculation a susceptible control was dead. In the field inoculation experiment disease development was also fast and data collection was done in an interval of 7 days in 56 days post inoculation all susceptible materials were dead. Experiments set under natural infestation were different because there was variation in disease development in all experiments. There was low to high
MLN incidence in different hotspots leading to difference in response of genetic treatments to MLN infection. At low incidence, differences were not observed among genotypes and at high incidence hotspots differences were observed among genotypes and genotype groups. Disease development is slow in natural infection trials data collection was done after every 14 days. There is little correlation between trials under artificial and natural infection (Table 5.1). This is due to different disease pressure imposed on genetic treatments, in a field inoculation trial no difference were observed due to high disease pressure and lack of adaptability of genetic materials. Under natural infestation a trial set at a disease hotspot with low MLN incidence did not show any variation among genotypes.
103
General results from all experiments under natural and artificial inoculation indicate the role of potyvirus resistance in MLN control. Although none of the genotype were immune to MLN there is differences in response of genotypes and QTL to MLN infection. Genotypes with all three potyvirus resistance QTL on chromosome 3, 6 and 10 had more resistance to MLN those genotypes with only single QTL of the above. Also genotypes with a combination of 2 QTL especially 3 +6 and 3 +10 had significant less
MLN symptoms than when exist alone. This lead to a conclusion that, there is a role played potyvirus resistance in MLN control especially in reducing MLN effect. More studies are needed to know the exatly what role do potyvirus resistance play and how much MLN effects are reduced with the presence of potivirus resistance QTL.
In carrying out future studies, especially in field conditions in East Africa, materials used should be tropical adapted materials which were developed for use in Tropical environment. The RIL populations used for the study were derived from Oh1VI and
Oh28 which are used in temperate environment hence did not perform well in tropical environment. Agronomically, genotypes performed poorly compared to the tropical control in parameter measured such as plant height, ear height, yield and days to anthesis and silking. The gap between anthesis and silking was also big indicating materials were under physiological stress which could hinder reproduction and the plants were hit by a lot of other disease such as maize streak virus, northern corn leaf blight, gray leaf spot and a variety of insects and vectors.
In Sub Saharan Africa, white maize is preferred for food compared to yellow maize.
During early research on screening African germplasm for resistance to MLN it was also
104 observed that, most lines with tolerance to MLN have yellow endosperm. This linked to a hypothesis that endosperm color might be linked to MLN resistance sources. This study second objective focused on breaking genetic linkage between Y1 locus and Mdm1 locus which are linked to move the resistance loci into a white endosperm background. The study used molecular markers (SSR) to select for F2 recombinant from a cross of white susceptible and yellow resistant parents. 4 recombinants with complete resistance to
MDMV and incomplete resistance to SCMV were recovered. These recombinants will need to undergo another breeding cycle to fix the Mdm1 loci for recombinants to be used in breeding cycles to introgress potyvirus resistance in white endosperm adapted maize.
In sub Saharan Africa food security is being threatened by abiotic and biotic stress such as plant diseases. Diseases like MLN are setbacks to achieving the global goal of feeding a population of 9 billion people by 2050. Measures to find solutions to these problems are needed to ensure sustainability of food production in the region. This study is a platform for more research on the subject to make sure MLN is controlled and eradicated to create a food secure Africa.
105
GC KENYA ARUSHA BBT1 BBT2 BBT3 GC 1 KENYA 0.04149832 1 ARSH -0.05729181 -0.190352 1 BBT1 0.329543889 0.00603091 0.0701669 1 BBT2 0.413376041 0.09174324 0.0660209 0.452686 1 BBT3 0.484017788 -0.0128718 0.2714327 0.560508 0.6026317 1
Table 5.1. Correlation between response of genotypes to MLN under artificial and natural infection
106
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APPENDIX A: Analysis of variance (ANOVA) tables for alpha lattice design
121
SEVERITY Source DFw Sum of Mean F- Pr (>F)x SCORE squares square value
FIRST Genotypesy 41 30.13 0.73 5.12 2.2x10-8*** SCOREz Residuals 54 7.75 0.14
LAST Treatmentsy 41 68.21 1.66 2.43 0.001** SCOREz Residuals 49 33.53 0.68
MEAN Treatmentsy 41 42.09 1.03 3.87 3.1x10-6*** SCOREz Residuals 52 13.80 0.27
AUDPCz Treatmentsy 41 6138.2 149.71 3.62 1.173***
Residuals 49 2022.5 41.28 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 and parents as controls. z Severity scores collected at different time points under growth chamber conditions.
Table A1. Analysis of variance for Recombinant Inbred Line (Genotype) response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under growth chamber conditions.
122
SEVERITY Source DFw Sum of Mean F-value Pr (>F)x SCORE squares square (SS) (MS)
FIRST Genotypesy 41 5.18 0.13 0.923 0.6019 SCOREz Residuals 54 7.40 0.14
LAST Genotypesy 41 20.15 0.49 0.6927 0.6019 SCOREz Residuals 54 29.80 0.57
MEAN Genotypesy 41 10.26 0.25 0.8795 0.6631 SCOREz Residuals 54 15.36 0.28
AUDPCz Genotypesy 41 5106.7 124.56 0.8875 0.6519
Residuals 54 7578.2 140.34 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 and parents as controls. z Severity scores collected at different time points under field conditions.
Table A2. Analysis of variance for genotypes response to inoculation with Maize chlorotic mottle virus and Sugarcane mosaic virus under field conditions.
123
SEVERITY Source DFw Sum of Mean F-value P-valuex SCORE squares square (SS) (MS)
FIRST Genotypesy 41 17.93 0.44 1.63 0.03* SCOREz Residuals 65 17.38 0.27
LAST Genotypesy 41 18.86 0.46 1.37 0.12 SCOREz Residuals 65 21.86 0.33
MEAN Genotypesy 41 9.14 0.22 2.19 0.002** SCOREz Residuals 65 6.63 0.10
AUDPCz Genotypesy 41 3849.2 93.88 1.92 0.009**
Residuals 65 3176.9 48.88 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls zSeverity scores collected at different time points under natural infestation.
Table A3. Analysis of variance for response to natural infection with Maize lethal necrosis under field conditions in trial 1, Mlangalini, Arusha during the 2015 long season.
124
SEVERIY Source Degrees Sum of Mean F- Pr (>F)x SCORE of squares squares value freedom
FIRST Genotypesy 41 2.80 0.07 1.82 0.02* SCOREz Residuals 65 2.44 0.04
LAST Genotypesy 41 9.21 0.22 2.31 0.001** SCOREz Residuals 65 6.32 0.10
MEAN Genotypesy 41 2.81 0.07 3.13 2.07x10-5*** SCOREz Residuals 65 1.42 0.02
AUDPCz Genotypesy 41 4981.6 121.50 2.82 9.8x10-5***
Residuals 65 2802.5 43.12 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls z Severity scores collected at different time points under natural infestation.
Table A4. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 2, a disease hotspot at Krishna Seed Farm, Babati during 2016 short season.
125
SEVERITY Source DFw Sum of Mean F- Pr (>F)x SCORE squares squares value
FIRST Genotypesy 41 7.78 0.19 3.26 1.12x10-5*** SCOREz Residuals 65 3.78 0.06
LAST Genotypesy 41 13.97 0.34 3.10 2.43x10-5*** SCOREz Residuals 65 7.15 0.11
MEAN Genotypesy 41 9.11 0.22 5.47 8.3x10-10*** SCOREz Residuals 65 2.64 0.04
AUDPCz Genotypesy 41 16545 403.55 5.08 3.87x10-9*** Residuals 65 5163 79.43 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls z Severity scores collected at different time points under natural infestation.
Table A5. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 3 a disease hotspot at Krishna Seed Farm, Babati during 2016 main season.
126
SEVERITY Source DFw Sum of Mean F- Pr (>F)x SCORE squares square value (SS) (MS)
FIRST Genotypesb 39 7.78 0.20 3.46 2.02x10-5*** SCORE Residuals 51 2.94 0.06
LAST Genotypesb 39 3.33 0.09 2.50 0.001*** SCORE Residuals 51 1.74 0.03
MEAN Genotypesb 39 2.90 0.07 5.55 1.2x 10-8*** SCORE Residuals 51 0.68 0.01
AUDPC Genotypesb 39 4633.6 118.81 4.71 1.95x 10-7***
Residuals 51 1284.0 25.12 w DF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls z Severity scores collected at different time points under natural infestation.
Table A6. Analysis of variance for genotypes response to natural infection with Maize lethal necrosis under field conditions in trial 4, a disease hotspot at KIRU-6 village, Babati during 2016 main season.
127
SEVERITY Source DFw Sum of Mean F-value Pr (>F)x SCORE squares square (SS) (MS) % Genotypesy 41 32395 790.11 4.59 2.87x10-8 *** Emergencez Residuals 65 11195 172.23
Anthesis Genotypesy 41 516.33 12.59 3.86 7.58x10-3*** datez Residuals 65 208.68 3.26
Silking Genotypesy 41 540.59 13.19 3.35 7.88x10-6 *** datez Residuals 65 251.67 3.93
Anthesis- Genotypesy 41 34.41 0.84 1.35 0.13 silking intervalz Residuals 65 40.28 0.62
Yieldz Genotypesy 41 0.23 0.01 30.46 2.2x10-16 ***
Residuals 65 0.01 0.0001
Ear rotz Genotypesy 41 29.19 0.71 1.58 0.05*
Residuals 65 28.89 0.45 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls. z Agronomic parameters measured
Table A7. Analysis of variance for agronomic traits of genotypes with potyvirus resistance under natural infection with Maize lethal necrosis in trial 1, a disease hotspot at Mlangalini, Arusha during 2015 main season.
128
SEVERITY Source DFw Sum of Mean F- Pr (>F)x SCORE squares square value
Germination Genotypesy 41 16475 401.84 2.20 0.002***
Residuals 65 11848 182.27
Anthesis Genotypesy 41 521.63 12.72 2.39 8.5x10-3***
Residuals 65 345.98 5.32
Silking Genotypesy 41 505.76 12.38 2.15 0.002**
Residuals 65 374.17 5.76
Interval Genotypesy 41 34.41 0.84 1.35 0.13
Residuals 65 40.28 0.62
Yield Genotypesy 41 0.03 0.00 3.31 9.9x10-6 ***
Residuals 65 0.01 0.00
Ear rot Genotypesy 41 303.69 7.41 1.70 0.0272*
Residuals 64 282.46 4.35 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Selected Recombinant Inbred Line (RIL) population with Potyvirus resistance sources from chromosome 3,6 and 10 alone and in combination from a RIL population of Oh1VI and Oh28 with controls. z Agronomic parameters
Table A8. Analysis of variance for agronomic traits of genotypes with potyvirus resistance under natural infection with Maize lethal necrosis in trial 2, a disease hotspot at Krishna seed farm, Arusha during 2015 short season.
129
APPENDIX B: Analysis of chromosome 2 MCMV QTL interaction with potyvirus
resistance QTL on chromosome 3, 6 and 10
130
SEVERITY Source DFw Sum of Mean F-value Pr (>F)x SCORE squares square (SS) (MS)
FIRST Markery 1 0.00 0.00 0.02 0.88 SCOREz Residuals 36 6.22 0.17
LAST Markery 1 0.87 0.87 1.56 0.22 SCOREz Residuals 36 20.13 0.56
MEAN Markery 1 0.21 0.21 0.81 0.38 SCOREz Residuals 36 9.27 0.26
AUDPCz Markery 1 137.41 137.4 3.09 0.09 1 Residuals 36 1602.63 44.52 wDF: Degrees of freedom x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Markers on chromosome 2 QTL for resistance to Maize chlorotic mottle virus z Severity scores collected at different time points under growth chamber conditions.
Table B1. Analysis of variance for chromosome 2 MCMV resistance markers’ response to Maize lethal necrosis (MLN) under growth chamber conditions
131
Source Degrees Sum of Mean F- P-Valuex of squares squares Value Freedom (SS) (MS) (DF) First scorez Interactiony 13 3.49 0.27 2.36 0.03*
Residual 24 2.73 0.11
Last scorez Interactiony 13 10.34 0.80 1.79 0.12 Residual 24 10.67 0.44
Mean Interactiony 13 6.10 0.47 3.34 0.005* Scorez Residual 24 3.37 0.14
AUDPCz Interactiony 13 981.39 75.49 2.38 0.03* Residual 24 758.64 31.61 x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Interaction between Potyvirus resistance QTL on chromosome 3,6 and 10 groups and MCMV resistance QTL on chromosome 2 zMLN severity scores collected at different time points under growth chamber conditions.
Table B2. Analysis of variance for QTL groups interaction with chromosome 2 MCMV resistance markers in growth chamber experiment.
132
QTL FIRST LAST MEAN AUDPC z group y SCORE z SCORE z SEVERITY z 10aw 0.77 0.98 0.91 0.64 10_6a 0.90 0.87 0.77 0.24 3a 0.67 0.96 0.39 0.77 3_10a 0.01* 0.17 0.01* 0.09. 3_6a 0.08. 0.11 0.11 0.51 3_6_10a 0.06. 0.48 0.12 0.39 6a 0.60 0.66 0.39 0.45 10bx 0.50 0.71 0.52 0.33 10_6b 0.16 0.02* 0.02* 0.12 3b 0.42 0.10 0.32 0.25 3_10b 0.14 0.19 0.02* 0.15 3_6b 0.15 0.04* 0.01* 0.05. 3_6_10b 0.01* 0.07. 0.02* 0.06. 6b NA NA NA NA
Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> w QTL groups for genotypes with Oh28 (a susceptible parent) allele on chromosome 2 MCMV resistance QTL) x QTL groups for genotypes with Oh1VI (a resistant parent) allele on chromosome 2 MCMV resistance QTL) y QTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. z MLN severity scores collected at different time points under growth chamber conditions
Table B3. Important interactions between Potyvirus resistance QTL groups and chromosome 2 MCMV resistance QTL under growth chamber conditions
133
QTL group y FIRST LAST MEAN AUDPC z SCORE z SCORE z SEVERITY z 6_10 1.87a 3.81ab 3.02ab 37.64a 10_2 2.00a 4.08a 3.12a 36.81a 6 1.98a 4.13ab 3.19a 36.18ab 10 1.73ab 3.92ab 2.99abc 35.91abc 3 2.00a 3.83ab 2.58abc 34.79abc 6_2 1.84a 3.90ab 2.95abc 32.92abc 3_6 1.30a 2.94b 2.42bc 29.69abc 3_2 1.65ab 3.10ab 2.58abc 28.29bc 3_6_10 1.10b 3.37ab 2.29bc 27.54bc 3_10_2 1.40ab 3.13ab 2.18c 25.78bc 3_10 1.18b 3.18ab 2.15c 25.43c 3_6_10_2 1.24ab 3.01b 2.26c 25.14c 3_6_2 1.49ab 2.88b 2.21c 24.92c 6_10_2 1.30ab 1.99b 1.92c 22.97c y Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. z MLN severity scores collected at different time points under growth chamber conditions with mean separation scores for QTL groups (Groups with the same letters are not significantly different)
Table B4. Important potyvirus and MCMV resistance QTL combinations for MLN control under growth chamber conditions
134
SEVERITY Source DFw Sum of Mean F-value Pr (>F)x SCORE squares square (SS) (MS)
FIRST Markery 1 0.00 0.00 1.0X10- 0.99 SCOREz 4 Residuals 36 2.18 0.16
LAST Markery 1 0.06 0.06 0.26 0.61 SCOREz Residuals 36 8.28 0.22
MEAN Markery 1 0.10 0.10 0.87 0.35 SCOREz Residuals 36 4.01 0.11
AUDPCz Markery 1 44.87 44.87 0.83 0.37
Residuals 36 1945.69 54.05 x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Markers on chromosome 2 QTL for resistance to MCMV z Severity scores collected at different time points under field conditions.
Table B5. Analysis of variance for chromosome 2 MCMV resistance markers’ response to Maize lethal necrosis (MLN) under field conditions at Naivasha screening facility
135
Severity Source Degrees Sum of Mean F- P-Valuex score of squares squares Value Freedom (SS) (MS) (DF) First Interactiony 13 0.56 0.04 0.65 0.79 scorez Residual 24 1.61 0.07
Last Interactiony 13 3.87 0.29 1.60 0.15 scorez Residual 24 4.47 0.19
Mean Interactiony 13 1.20 0.09 0.76 0.69 Scorez Residual 24 2.90 0.12
AUDPCz Interactiony 13 566.94 43.61 0.73 0.71 Residual 24 1423.62 59.31 x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Interaction between Potyvirus resistance QTL on chromosome 3,6 and 10 groups and MCMV resistance QTL on chromosome 2 z MLN severity scores collected at different time points under field conditions.
Table B6. Analysis of variance for genotype groups’ interaction with chromosome 2 MCMV resistance markers under field conditions at Naivasha screening facility
136
QTL group y FIRST LAST MEAN AUDPC z SCORE z SCORE z SEVERITY z
10aw 0.54 0.80 0.93 0.99 10_6a 0.52 0.29 0.88 0.84 3a 1.00 0.80 0.81 0.91 3_10a 0.89 0.59 0.90 0.97 3_6a 0.37 0.58 0.72 0.65 3_6_10a 0.88 0.20 0.94 0.89 6a 0.47 0.06. 0.56 0.60 10bx 0.68 1.00 0.82 0.63 10_6b 0.80 0.80 0.73 0.66 3b 0.40 0.11 0.80 0.74 3_10b 0.69 0.58 0.37 0.40 3_6b 0.73 0.69 0.93 0.97 3_6_10b 0.28 0.009** 0.06. 0.06. 6b NA NA NA NA
Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> w QTL groups for genotypes with Oh28 (a susceptible parent) allele on chromosome 2 MCMV resistance QTL) x QTL groups for genotypes with Oh1VI (a resistant parent) allele on chromosome 2 MCMV resistance QTL) yQTL GROUP: Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. z MLN severity scores collected at different time points under field conditions
Table B7. Important interactions between potyvirus resistance QTL groups and chromosome 2 MCMV resistance QTL under field conditions at Naivasha screening facility
137
SEVERITY Source DF Sum of Mean F- Pr (>F)x SCORE squares square value (SS) (MS)
FIRST Markery 1 2.8x10-5 4.0x10-4 0.02 0.90 SCOREz Residuals 36 0.70 0.02
LAST Markery 1 0.03 0.03 0.47 0.50 SCOREz Residuals 36 1.96 0.05
MEAN Markery 1 0.01 0.01 0.79 0.38 SCOREz Residuals 36 0.51 0.01
AUDPCz Markery 1 24.51 24.50 0.89 0.35
Residuals 36 995.46 27.65
Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Markers on chromosome 2 QTL for resistance to MCMV z Severity scores collected at different time points under field conditions.
Table B8. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis under natural infestation at trial 2, Krishna Seed Farm, Babati during 2016 short season.
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Severity Source Degrees Sum of Mean F-Value P-Valuex score of squares squares Freedom First Interactiony 13 0.13 0.01 0.44 0.94 scorez Residual 24 0.57 0.03
Last Interactiony 13 1.19 0.09 2.77 0.01* scorez Residual 24 0.79 0.03
Mean Interactiony 13 0.30 0.02 2.44 0.02* Scorez Residual 24 0.22 0.01
AUDPCz Interactiony 13 552.43 42.50 2.18 0.05* Residual 24 467.53 19.48 x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Interaction between Potyvirus resistance QTL on chromosome 3,6 and 10 groups and MCMV resistance QTL on chromosome 2 zMLN severity scores collected at different time points under field conditions.
Table B9. Analysis of variance for genotype groups’ interaction with chromosome 2 MCMV resistance markers at trial 2, Krishna Seed Farm, Babati during 2016 short season.
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QTL groupy FIRST LAST MEAN AUDPC z SCORE z SCORE z SEVERITY z 6_10_2 1.50a 3.17a 2.33a 98.00a 10 1.50a 2.67ab 2.21a 94.5ab 6 1.44a 3.11a 2.25a 94.11ab 3_6_10 1.33a 2.67ab 2.13abc 91.00abc 10_2 1.42a 3.13a 2.18ab 90.71abc 3_2 1.33a 2.96a 2.16ab 90.71abc 3_10 1.33a 2.94a 2.16ab 90.61abc 3_6 1.25a 2.92a 2.13abc 89.83abc 6_2 1.38a 3.04a 2.16ab 89.83abc 3_6_2 1.38a 2.75ab 2.07bc 87.21bc 6_10 1.38a 3.00a 2.08bc 86.04bc 3_10_2 1.42a 3.75ab 2.00bc 82.83c 3 1.33a 2.83ab 2.00bc 82.83c 3_6_10_2 1.29a 2.58b 1.958c 82.54c y Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. z MLN severity scores collected at different time points under field conditions with mean separation scores for QTL groups (Groups with the same letters are not significantly different)
Table B10. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation condition at trial 2, Krishna seed farm, Babati during 2016 short season.
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SEVERITY Source DF Sum of Mean F-value P-valuex SCORE squares square (SS) (MS)
FIRST Markery 1 0.002 0.001 0.02 0.90 SCOREz Residuals 36 2.41 0.07
LAST Markery 1 0.19 0.19 1.98 0.16 SCOREz Residuals 36 3.50 0.09
MEAN Markery 1 0.03 0.03 0.41 0.52 SCOREz Residuals 36 2.73 0.08
AUDPCz Markery 1 52.7 52.73 0.87 0.54
Residuals 36 5078.8 141.08 x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Markers on chromosome 2 QTL for resistance to MCMV z Severity scores collected at different time points under field conditions.
Table B11. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis (MLN) under natural infestation at trial 3, Krishna Seed Farm, Babati during 2016 main season.
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Severity Source DFw Sum of Mean F- P-Valuea score squares squares Value (SS) (MS) First Interactiony 13 1.69 0.13 4.33 9.4x10-3*** scorez Residual 24 0.72 0.03
Last Interactiony 13 3.11 0.24 9.90 1.0x10-6*** scorez Residual 24 0.58 0.02
Mean Interactiony 13 2.27 0.18 11.22 3.2x10-7*** Scorez Residual 24 0.39 0.01
AUDPCz Interactiony 13 4329.4 333.03 9.96 9.84x10-7*** Residual 24 802.1 33.42 w DF: Degrees of freedom x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Interaction between Potyvirus resistance QTL on chromosome 3,6 and 10 groups and MCMV resistance QTL on chromosome 2 z MLN severity scores collected at different time points field conditions.
Table B12. Analysis of variance for genotype groups’ interaction with chromosome 2 MCMV resistance markers under natural infestation at trial 3, Krishna Seed Farm, Babati during 2016 main season.
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QTL group FIRST LAST MEAN AUDPC x y SCORE x SCORE x SEVERITY x 10_2 2.01a 3.85a 2.96a 125.1a 3 1.84a 3.80a 2.91ab 125.1ab 6_10 1.82ab 3.75a 2.87ab 121.7ab 6 1.72b 3.78a 2.82ab 119.7ab 6_2 1.74b 3.53ab 2.74bc 116.5b 10 1.82ab 3.70ab 2.76abc 116.30bc 3_2 1.79ab 3.51abc 2.70bc 114.10bc 6_10_2 1.67bc 3.42abcd 2.65bcd 113.00bcd 3_10_2 1.58bc 3.32bcd 2.48cde 104.8cde 3_6 1.75ab 3.13de 2.48cde 104.5cde 3_6_2 1.50bc 3.212d 2.40de 101.6def 3_10 1.28c 3.26cd 2.31ef 97.78ef 3_6_10 1.48bc 3.13de 2.27ef 95.36ef 3_6_10_2 1.28c 2.95e 2.21f 93.48f y Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. x MLN severity scores collected at different time points under field conditions with mean separation scores for QTL groups (Groups with the same letters are not significantly different)
Table B13. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation at trial 3, Krishna Seed Farm, Babati during 2016 main season.
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SEVERITY Source DF Sum of Mean F-value Pr(>F) x SCORE squares square
FIRST Markery 1 0.02 0.02 0.36 0.55 SCOREz Residuals 32 1.33 0.04
LAST Markery 1 0.01 0.01 0.42 0.52 SCOREz Residuals 32 0.51 0.02
MEAN Markery 1 0.002 0.002 0.20 0.65 SCOREz Residuals 32 0.011 0.011
AUDPCz Markery 1 164.3 164.3 1.10 0.30
Residuals 32 4771.6 149.1 x Significance levels: ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Markers on chromosome 2 QTL for resistance to MCMV z Severity scores collected at different time points under field conditions.
Table B14. Analysis of variance for chromosome 2 MCMV resistance QTL markers’ response to Maize lethal necrosis under natural infestation at trial 4, KIRU-6 village, Babati during 2016 main season.
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Severity Source DFw Sum of Mean F- P-Valuex score squares squares Value (SS) (MS) First Interactiony 13 0.98 0.02 0.36 0.002*** scorez Residual 20 0.36 0.04
Last Interactiony 13 0.33 0.01 2.89 0.01* scorez Residual 20 0.50 0.02
Mean Interactiony 13 2.27 0.18 11.22 3.36x10-5*** Scorez Residual 24 0.39 0.01
AUDPCz Interactiony 13 4200.2 323.09 8.78 1.21x10-5*** Residual 20 735.7 36.78 x Significance levels = ***= <0.001, ** = 0.01, * = 0.05, NS = 0.1> y Interaction between potyvirus resistance QTL on chromosome 3,6 and 10 groups and MCMV resistance QTL on chromosome 2 z MLN severity scores collected at different time points under field conditions.
Table B15. Analysis of variance for genotype groups’ interaction with chromosome 2 MCMV resistance markers under natural infestation at trial 4, KIRU-6 village, Babati during 2016 main season.
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QTL group FIRST LAST MEAN AUDPC y x SCORE y SCORE y SEVERITY y
10_2 2.09abc 3.50a 2.79a 127.50a 3 1.82c 3.33abc 2.58def 123.30ab 6_10 2.08ab 3.50a 2.74abc 121.10ab 6 1.97abc 3.39ab 2.70abcd 119.80ab 6_2 2.01abc 3.46a 2.75ab 116.30ab 10 2.01abc 3.50a 2.71abcd 112.30ac 3_2 2.11a 3.46a 2.73abc 114.00bc 6_10_2 2.01abc 3.50a 2.75abc 112.90bcd 3_10_2 1.82c 3.25bc 2.56ef 104.90cd 3_6 1.81c 3.42ab 2.62cdef 104.60cd 3_6_2 1.89bc 3.50a 2.68bcd 98.81de 3_10 2.07abc 3.42ab 2.64cde 97.86de 3_6_10 1.18d 3.33abc 2.37g 95.29de 3_6_10_2 1.87c 3.20c 2.53f 93.49e x Groups of maize genotypes with Potyvirus resistance QTL on chromosome 3, 6 and 10 alone or in a combination of 2 and 3 QTL group. y MLN severity scores collected at different time points field conditions with mean separation scores for QTL groups (Groups with the same letters are not significantly different)
Table B16. Important potyvirus and MCMV resistance QTL combinations for Maize lethal necrosis control under natural infestation at trial 4, KIRU-6 village, Babati during 2016 main season.
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