Person: Babu, R.
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Babu
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R.
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Babu, R.
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0000-0001-8954-5020 31 results
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- Desarrollo de marcadores para mejoramiento de maíz con proteína de calidad y estudio de interacción entre los genes Opaco-2 y Ask2(Sociedad Mexicana de Fitogenetica, 2022) Hernández-Rodríguez, M.; Babu, R.; Skinner, D.; Palacios-Rojas, N.; Martins, M.C.M.; García Zavala, J.J.; Lobato-Ortiz, R.; Santacruz-Varela, A.; Castillo-González, F.; Yunbi Xu; Prasanna, B.M.
Publication - GBS-based SNP map pinpoints the QTL associated with sorghum downy mildew resistance in maize (Zea mays L.)(Frontiers, 2022) Jadhav, K.P.; Gajanan, S.; Tamilarasi, P.M.; Devasree, S.; Ranjani, R.V.; Chandran, S.; Pukalenthy, B.; Adhimoolam, K.; Arulselvi, S.; Vijayagowri, E.; Ganesan, K.N.; Paranidharan, V.; Nair, S.K.; Babu, R.; Ramalingam, J.; Raveendran, M.; Senthil, N.
Publication - Genetic gains with genomic versus phenotypic selection for drought and waterlogging tolerance in tropical maize (Zea mays L.)(Elsevier, 2021) Das, R.R.; Vinayan, M.T.; Seetharam, K.; Patel, M.B.; Ramesh Kumar Phagna; Singh, S.B.; Shahi, J.P.; Sarma, A.; Barua, N.S.; Babu, R.; Zaidi, P.
Publication - Genomic regions associated with heat stress tolerance in tropical maize (Zea mays L.)(Nature Publishing Group, 2021) Seetharam, K.; Kuchanur, P.; Koirala, K.B.; Tripathi, M.P.; Patil, A.; Sudarsanam, V.; Das, R.R.; Chaurasia, R.; Pandey, K.; Vemuri, H.; Vinayan, M.T.; Nair, S.K.; Babu, R.; Zaidi, P.
Publication - Genetic gains in grain yield through genomic selection in eight bi-parental maize populations under drought stress(CSSA, 2015) Beyene, Y.; Semagn, K.; Mugo, S.N.; Tarekegne, A.T.; Babu, R.; Meisel, B.; Sehabiague, P.; Makumbi, D.; Magorokosho, C.; Oikeh, S.O.; Gakunga, J.; Vargas Hernández, M.; Olsen, M.; Prasanna, B.M.; Banziger, M.; Crossa, J.
Publication - Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation(CSSA, 2014) Hickey, J.; Dreisigacker, S.; Crossa, J.; Hearne, S.; Babu, R.; Prasanna, B.M.; Grondona, M.; Zambelli, A.; Windhausen, V.S.; Mathews, K.L.; Gorjanc, G.
Publication - Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.)(Nature Publishing Group, 2021) Vinayan, M.T.; Seetharam, K.; Babu, R.; Zaidi, P.; Blummel, M.; Nair, S.K.
Publication - Genetic gains with rapid-cycle genomic selection for combined drought and waterlogging tolerance in tropical maize (Zea mays L.)(CSSA, 2020) Das, R.R.; Vinayan, M.T.; Patel, M.B.; Ramesh Kumar Phagna; Singh, S.B.; Shahi, J.P.; Sarma, A.; Barua, N.S.; Babu, R.; Seetharam, K.; Burgueño, J.; Zaidi, P.
Publication - Identification of donors for low-nitrogen stress with maize lethal necrosis (MLN) tolerance for maize breeding in sub-Saharan Africa(Springer, 2019) Das, B.; Atlin, G.; Olsen, M.; Burgueño, J.; Tarekegne, A.T.; Babu, R.; Ndou, E.; Mashingaidze, K.; Lieketso Moremoholo; Ligeyo, D.; Matemba-Mutasa, R.; Zaman-Allah, M.; San Vicente Garcia, F.M.; Prasanna, B.M.; Cairns, J.E.After drought, a major challenge to smallholder farmers in sub-Saharan Africa is low-fertility soils with poor nitrogen (N)-supplying capacity. Many challenges in this region need to be overcome to create a viable fertilizer market. An intermediate solution is the development of maize varieties with an enhanced ability to take up or utilize N in severely depleted soils, and to more efficiently use the small amounts of N that farmers can supply to their crops. Over 400 elite inbred lines from seven maize breeding programs were screened to identify new sources of tolerance to low-N stress and maize lethal necrosis (MLN) for introgression into Africa-adapted elite germplasm. Lines with high levels of tolerance to both stresses were identified. Lines previously considered to be tolerant to low-N stress ranked in the bottom 10% under low-N confirming the need to replace these lines with new donors identified in this study. The lines that performed best under low-N yielded about 0. 5Mgha(-1) (20%) more in testcross combinations than some widely used commercial parent lines such as CML442 and CML395. This is the first large scale study to identify maize inbred lines with tolerance to low-N stress and MLN in eastern and southern Africa.
Publication - Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and flowering time under drought and heat stress conditions in maize(Blackwell Verlag, 2019) Yibing Yuan; Cairns, J.E.; Babu, R.; Gowda, M.; Makumbi, D.; Magorokosho, C.; Ao Zhang; Yubo Liu; Nan Wang; Zhuanfang Hao; San Vicente Garcia, F.M.; Olsen, M.; Prasanna, B.M.; Yanli Lu; Xuecai ZhangDrought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.
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