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Open AccessArticle

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

1
Department of Agricultural Science and Technology, Kenyatta University, Nairobi 43844-00100, Kenya
2
International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya
*
Author to whom correspondence should be addressed.
Genes 2020, 11(1), 16; https://doi.org/10.3390/genes11010016
Received: 27 November 2019 / Revised: 17 December 2019 / Accepted: 18 December 2019 / Published: 23 December 2019
(This article belongs to the Section Plant Genetics and Genomics)
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. View Full-Text
Keywords: GWAS; GP; validation; markers; resistance; maize lethal necrosis GWAS; GP; validation; markers; resistance; maize lethal necrosis
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MDPI and ACS Style

Nyaga, C.; Gowda, M.; Beyene, Y.; Muriithi, W.T.; Makumbi, D.; Olsen, M.S.; Suresh, L.M.; Bright, J.M.; Das, B.; Prasanna, B.M. Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm. Genes 2020, 11, 16. https://doi.org/10.3390/genes11010016

AMA Style

Nyaga C, Gowda M, Beyene Y, Muriithi WT, Makumbi D, Olsen MS, Suresh LM, Bright JM, Das B, Prasanna BM. Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm. Genes. 2020; 11(1):16. https://doi.org/10.3390/genes11010016

Chicago/Turabian Style

Nyaga, Christine; Gowda, Manje; Beyene, Yoseph; Muriithi, Wilson T.; Makumbi, Dan; Olsen, Michael S.; Suresh, L. M.; Bright, Jumbo M.; Das, Biswanath; Prasanna, Boddupalli M. 2020. "Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm" Genes 11, no. 1: 16. https://doi.org/10.3390/genes11010016

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