Person: Jumbo, M.B
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Jumbo
First Name
M.B
Name
Jumbo, M.B
ORCID ID
0000-0001-5912-3046 10 results
Search Results
Now showing 1 - 10 of 10
- Maize lethal necrosis (MLN): effort towards containing the spread and impact of a devastating transboundary disease in sub-Saharan Africa(CIMMYT, 2021) Suresh, L.M.; Beyene, Y.; Gowda, M.; Olsen, M.; Jumbo, M.B; Makumbi, D.; Regasa, M.W.; Mugo, S.N.; Mwatuni, F.; Prasanna, B.M.
Publication - Maize lethal necrosis (MLN): effort towards containing the spread and impact of a devastating transboundary disease in sub-Saharan Africa(CIMMYT, 2021) Suresh, L.M.; Beyene, Y.; Gowda, M.; Olsen, M.; Jumbo, M.B; Makumbi, D.; Regasa, M.W.; Mugo, S.N.; Mwatuni, F.; Prasanna, B.M.
Publication - Genetic dissection of resistance to gray leaf spot by combining genome-wide association, linkage mapping, and genomic prediction in tropical maize germplasm(Frontiers, 2020) Kibe, M.; Nair, S.K.; Das, B.; Jumbo, M.B; Makumbi, D.; Kinyua, J.; Suresh, L.M.; Beyene, Y.; Olsen, M.; Prasanna, B.M.; Gowda, M.
Publication - Tackling Maize Lethal Necrosis (MLN), a complex disease in Eastern Africa(CIMMYT, 2020) Suresh, L.M.; Beyene, Y.; Gowda, M.; Olsen, M.; Jumbo, M.B; Makumbi, D.; Regasa, M.W.; Mugo, S.N.; Mwatuni, F.; Prasanna, B.M.
Publication - Hybrid breeding for MLN resistance: heterosis, combining ability, and hybrid prediction(MDPI, 2020) Nyaga, C.; Gowda, M.; Beyene, Y.; Murithi, W.T.; Burgueño, J.; Toledo, F.H.; Makumbi, D.; Olsen, M.; Das, B.; Suresh, L.M.; Jumbo, M.B; Prasanna, B.M.
Publication - Tackling Maize Lethal Necrosis (MLN), a complex disease in Eastern Africa(CIMMYT, 2020) Suresh, L.M.; Beyene, Y.; Gowda, M.; Olsen, M.; Jumbo, M.B; Makumbi, D.; Regasa, M.W.; Mugo, S.N.; Mwatuni, F.; Prasanna, B.M.
Publication - Development and deployment of elite maize lines and hybrids resistant to Maize Lethal Necrosis(CIMMYT, 2019) Beyene, Y.; Suresh, L.M.; Gowda, M.; Makumbi, D.; Olsen, M.; Jumbo, M.B; Regasa, M.W.; Mugo, S.N.; Prasanna, B.M.
Publication - Genetic analysis of QTL for resistance to maize lethal necrosis in multiple mapping populations(MDPI, 2020) Awata, L.A.O.; Beyene, Y.; Gowda, M.; Suresh, L.M.; Jumbo, M.B; Tongoona, P.; Danquah, E.Y.; Ifie, B.E.; Marchelo-D’ragga, P.W.; Olsen, M.; Ogugo, V.; Mugo, S.N.; Prasanna, B.M.
Publication - Genome-wide analyses and prediction of resistance to MLN in large tropical maize germplasm(MDPI, 2020) Nyaga, C.; Gowda, M.; Beyene, Y.; Muriithi, W.T.; Makumbi, D.; Olsen, M.; Suresh, L.M.; Jumbo, M.B; Das, B.; Prasanna, B.M.
Publication - Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm(Springer, 2019) Sitonik, C.; Suresh, L.M.; Beyene, Y.; Olsen, M.; Makumbi, D.; Kiplagat, O.; Das, B.; Jumbo, M.B; Mugo, S.N.; Crossa, J.; Tarekegne, A.T.; Prasanna, B.M.; Gowda, M.Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10−05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.
Publication