Maize Lethal Necrosis: An Emerging, Synergistic Viral Disease

Redinbaugh, Margaret G.; Stewart, Lucy R.

doi:10.1146/annurev-virology-092917-043413

Cited by 135 publications

(98 citation statements)

References 103 publications

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“…Breeding for MLN resistance is an important goal in SSA in the effort to reduce yield losses and ensure food security [2]. Finding appropriate combinations to form hybrids which contribute to both MLN resistance or tolerance and grain yield is the final goal.…”

Section: Discussionmentioning

confidence: 99%

“…Maize lethal necrosis (MLN) caused by the co-infection of two viruses, Maize chlorotic mottle virus (MCMV) belonging to the Tombusviridae group and any member virus from the Potyviridae group mostly Sugarcane mosaic virus (SCMV) is one of the most important maize diseases in sub Plants 2020, 9, 468 2 of 15 Saharan Africa (SSA) [1]. MLN has been reported to cause up to 100% yield loss making it a serious threat to food security in SSA [2]. Breeding cultivars for MLN resistance is the most economical and environmental friendly way of controlling MLN [3].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Nyaga

Gowda

Beyene

et al. 2020

Plants

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Prior knowledge on heterosis and quantitative genetic parameters on maize lethal necrosis (MLN) can help the breeders to develop numerous resistant or tolerant hybrids with optimum resources. Our objectives were to (1) estimate the quantitative genetic parameters for MLN disease severity, (2) investigate the efficiency of the prediction of hybrid performance based on parental per se and general combining ability (GCA) effects, and (3) examine the potential of hybrid prediction for MLN resistance or tolerance based on markers. Fifty elite maize inbred lines were selected based on their response to MLN under artificial inoculation. Crosses were made in a half diallel mating design to produce 307 F1 hybrids. All hybrids were evaluated in MLN quarantine facility in Naivasha, Kenya for two seasons under artificial inoculation. All 50 inbreds were genotyped with genotyping-by-sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability was moderate to high. We observed that hybrids were superior to the mean performance of the parents for disease severity (−14.57%) and area under disease progress curve (AUDPC) (14.9%). Correlations were significant and moderate between line per se and GCA; and mean of parental value with hybrid performance for both disease severity and AUDPC value. Very low and negative correlation was observed between parental lines marker based genetic distance and heterosis. Nevertheless, the correlation of GCA effects was very high with hybrid performance which can suggests as a good predictor of MLN resistance. Genomic prediction of hybrid performance for MLN is high for both traits. We therefore conclude that there is potential for prediction of hybrid performance for MLN. Overall, the estimated quantitative genetic parameters suggest that through targeted approach, it is possible to develop outstanding lines and hybrids for MLN resistance.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Nyaga

Gowda

Beyene

et al. 2020

Plants

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“…For the last six years, MLN has been recognized as one of the major diseases constraining yield production in SSA. Thus, effective breeding strategies for MLN resistant germplasm have to be employed [3]. In this study, we phenotyped and genotyped a large set of diverse maize lines and applied GWAS and GP in order to understand the genetic architecture of MLN resistance, validate previous findings in subtropical germplasm and analyze population structure.…”

Section: Discussionmentioning

confidence: 99%

“…However, maize productivity is severely affected by abiotic and biotic factors including drought, diseases, pests, and socio-economic factors [2]. Recently, maize lethal necrosis (MLN) has led to complete yield losses and thus affected food security negatively [3]. In 2011, MLN was first reported in Bomet District in Kenya with 30-100% yield losses and in 2012 similar symptoms were observed in Chepalungu, Narok, and Naivasha districts in Kenya [4].…”

Section: Introductionmentioning

confidence: 99%

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Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm

Nyaga

Gowda

Beyene

et al. 2019

Genes

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Maize lethal necrosis (MLN), caused by co-infection of maize chlorotic mottle virus and sugarcane mosaic virus, can lead up to 100% yield loss. Identification and validation of genomic regions can facilitate marker assisted breeding for resistance to MLN. Our objectives were to identify marker-trait associations using genome wide association study and assess the potential of genomic prediction for MLN resistance in a large panel of diverse maize lines. A set of 1400 diverse maize tropical inbred lines were evaluated for their response to MLN under artificial inoculation by measuring disease severity or incidence and area under disease progress curve (AUDPC). All lines were genotyped with genotyping by sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability estimates were moderate to high. GWAS revealed 32 significantly associated SNPs for MLN resistance (at p < 1.0 × 10 −6 ). For disease severity, these significantly associated SNPs individually explained 3-5% of the total phenotypic variance, whereas for AUDPC they explained 3-12% of the total proportion of phenotypic variance. Most of significant SNPs were consistent with the previous studies and assists to validate and fine map the big quantitative trait locus (QTL) regions into few markers' specific regions. A set of putative candidate genes associated with the significant markers were identified and their functions revealed to be directly or indirectly involved in plant defense responses. Genomic prediction revealed reasonable prediction accuracies. The prediction accuracies significantly increased with increasing marker densities and training population size. These results support that MLN is a complex trait controlled by few major and many minor effect genes.

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Virus Diseases of Tropical Crops

Geering

2021

Encyclopedia of Life Sciences

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Virus diseases are serious constraints to the productivity and profitability of a wide range of tropical crops. Identification of the causal viruses and understanding their epidemiology is the key to estimating the incidence and economic impact of the diseases they cause, and to devising virus management strategies. Epidemics result from interactions between virus, host plant, vector and environmental factors, and every epidemic can be considered to be a unique pathosystem in which each of the components contributes to the epidemic, and in which none are limiting. Accurate pathogen diagnosis is the key to managing diseases. The main virus and viroid diseases of 18 different crops are listed and pathosystem descriptors provided for each based on the mode of spread, which in turn informs the different management strategies. The Tenth Report of the International Committee on Taxonomy of Viruses, which is available online at https://talk.ictvonline.org/ictv‐reports/ictv_online_report/ , is an essential reference for virologists working with tropical crops. Key Concepts Identification of viruses or viroids is the key to managing the diseases they cause. Koch's postulates are applied to establish causal associations between viruses/viroids and disease. Viruses/viroids are identified by their biological, morphological and genetic properties using classical and molecular methods. The universal database for viruses/viroids published by the International Committee on Taxonomy of Viruses is the resource for classification. Rapid diagnostic methods rely on nucleotide sequence comparisons with publicly available databases. Epidemics are driven by virus, vector, host, environment, time and human activity. The vector–virus interaction is the main determinant of the rate, range, timing and pattern of disease spread. Viruses/viroids of tropical plants have unique pathosystems. A full description of a pathosystem is required to sustainably manage virus epidemics. Management of epidemics can be achieved by destabilising or downregulating one or more components of the relevant pathosystem.

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Maize Lethal Necrosis: An Emerging, Synergistic Viral Disease

Cited by 135 publications

References 103 publications

Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm

Virus Diseases of Tropical Crops

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