Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions
Low soil nitrogen levels, compounded by the high costs associated with nitrogen supplementation through fertilizers, significantly contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). The discovery of genomic regions a...
| Main Authors: | , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Frontiers Media
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/137362 |
| _version_ | 1855514479209480192 |
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| author | Kimutai, Collins Ndlovu, Noel Chaikam, Vijay Tadesse, Berhanu Das, Biswanath Beyene, Yoseph Kiplagat, Oliver Spillane, Charles Prasanna, Boddupalli M. Gowda, Manje |
| author_browse | Beyene, Yoseph Chaikam, Vijay Das, Biswanath Gowda, Manje Kimutai, Collins Kiplagat, Oliver Ndlovu, Noel Prasanna, Boddupalli M. Spillane, Charles Tadesse, Berhanu |
| author_facet | Kimutai, Collins Ndlovu, Noel Chaikam, Vijay Tadesse, Berhanu Das, Biswanath Beyene, Yoseph Kiplagat, Oliver Spillane, Charles Prasanna, Boddupalli M. Gowda, Manje |
| author_sort | Kimutai, Collins |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Low soil nitrogen levels, compounded by the high costs associated with nitrogen supplementation through fertilizers, significantly contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). The discovery of genomic regions associated with low nitrogen tolerance in maize can enhance selection efficiency and facilitate the development of improved varieties. To elucidate the genetic architecture of grain yield (GY) and its associated traits (anthesis-silking interval (ASI), anthesis date (AD), plant height (PH), ear position (EPO), and ear height (EH)) under different soil nitrogen regimes, four F3 maize populations were evaluated in Kenya and Zimbabwe. GY and all the traits evaluated showed significant genotypic variance and moderate heritability under both optimum and low nitrogen stress conditions. A total of 91 quantitative trait loci (QTL) related to GY (11) and other secondary traits (AD (26), PH (19), EH (24), EPO (7) and ASI (4)) were detected. Under low soil nitrogen conditions, PH and ASI had the highest number of QTLs. Furthermore, some common QTLs were identified between secondary traits under both nitrogen regimes. These QTLs are of significant value for further validation and possible rapid introgression into maize populations using marker-assisted selection. Identification of many QTL with minor effects indicates genomic selection (GS) is more appropriate for their improvement. Genomic prediction within each population revealed low to moderately high accuracy under optimum and low soil N stress management. However, the accuracies were higher for GY, PH and EH under optimum compared to low soil N stress. Our findings indicate that genetic gain can be improved in maize breeding for low N stress tolerance by using GS. |
| format | Journal Article |
| id | CGSpace137362 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1373622025-12-08T10:29:22Z Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions Kimutai, Collins Ndlovu, Noel Chaikam, Vijay Tadesse, Berhanu Das, Biswanath Beyene, Yoseph Kiplagat, Oliver Spillane, Charles Prasanna, Boddupalli M. Gowda, Manje grain nitrogen soil chemicophysical properties maize quantitative trait loci Low soil nitrogen levels, compounded by the high costs associated with nitrogen supplementation through fertilizers, significantly contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). The discovery of genomic regions associated with low nitrogen tolerance in maize can enhance selection efficiency and facilitate the development of improved varieties. To elucidate the genetic architecture of grain yield (GY) and its associated traits (anthesis-silking interval (ASI), anthesis date (AD), plant height (PH), ear position (EPO), and ear height (EH)) under different soil nitrogen regimes, four F3 maize populations were evaluated in Kenya and Zimbabwe. GY and all the traits evaluated showed significant genotypic variance and moderate heritability under both optimum and low nitrogen stress conditions. A total of 91 quantitative trait loci (QTL) related to GY (11) and other secondary traits (AD (26), PH (19), EH (24), EPO (7) and ASI (4)) were detected. Under low soil nitrogen conditions, PH and ASI had the highest number of QTLs. Furthermore, some common QTLs were identified between secondary traits under both nitrogen regimes. These QTLs are of significant value for further validation and possible rapid introgression into maize populations using marker-assisted selection. Identification of many QTL with minor effects indicates genomic selection (GS) is more appropriate for their improvement. Genomic prediction within each population revealed low to moderately high accuracy under optimum and low soil N stress management. However, the accuracies were higher for GY, PH and EH under optimum compared to low soil N stress. Our findings indicate that genetic gain can be improved in maize breeding for low N stress tolerance by using GS. 2023 2024-01-08T22:09:14Z 2024-01-08T22:09:14Z Journal Article https://hdl.handle.net/10568/137362 en Open Access application/pdf Frontiers Media Kimutai, C., Ndlovu, N., Chaikam, V., Ertiro, B. T., Das, B., Beyene, Y., Kiplagat, O., Spillane, C., Prasanna, B. M., & Gowda, M. (2023). Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) Under optimum and low nitrogen conditions. Frontiers in Genetics, 14. https://doi.org/10.3389/fgene.2023.1266402 |
| spellingShingle | grain nitrogen soil chemicophysical properties maize quantitative trait loci Kimutai, Collins Ndlovu, Noel Chaikam, Vijay Tadesse, Berhanu Das, Biswanath Beyene, Yoseph Kiplagat, Oliver Spillane, Charles Prasanna, Boddupalli M. Gowda, Manje Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title | Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title_full | Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title_fullStr | Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title_full_unstemmed | Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title_short | Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions |
| title_sort | discovery of genomic regions associated with grain yield and agronomic traits in bi parental populations of maize zea mays l under optimum and low nitrogen conditions |
| topic | grain nitrogen soil chemicophysical properties maize quantitative trait loci |
| url | https://hdl.handle.net/10568/137362 |
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