Constitutive expression of the L. (maize) morphogenic transcription factors () and () in maize can not only greatly increase transformation efficiency but can also induce phenotypic abnormalities and sterility. In an effort to alleviate the pleiotropic effects of constitutive expression, a genome wide search was undertaken to find suitable maize promoters to drive tissue and timing-specific expression of the transformation enhancing genes and . A promoter from a maize phospholipid transferase protein gene (- ) was identified based on its expression in leaves, embryos, and callus while being downregulated in roots, meristems, and reproductive tissues. When driving was transformed into immature maize embryos along with a expression cassette driven by the nopaline synthase promoter ( ::) abundant somatic embryos rapidly formed on the scutella. These embryos were individual and uniformly transformed and could be directly germinated into plants without a callus phase. Transformed plants could be sent to the greenhouse in as little as 1 mo and regenerated plants matched the seed-derived phenotype for the inbred and were fertile. However, T1 seed from these plants had poor germination. Replacing with a maize auxin-inducible promoter ( ) in combination with ::, allowed healthy, fertile plants to be regenerated. Single-copy T1 seed germinated normally and had a predominantly wild-type inbred phenotype. For maize, this callus-free transformation process has worked in all inbred lines tested.
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http://dx.doi.org/10.1007/s11627-018-9905-2 | DOI Listing |
J Agric Food Chem
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Engineering Research Center of Protection and Utilization of Plant Resources, College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, Liaoning Province 110866, China.
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December 2024
State Key Laboratory of North China Crop Improvement and Regulation, College of Plant Protection, Hebei Agricultural University, Baoding 071001, China.
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College of Food Science and Engineering, Jilin Agricultural University, Changchun, 130118, Jilin, P. R. China.
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Lilongwe University of Agriculture and Natural Resources, Department of Agricultural Economics, and African Center of Excellence, Agricultural Policy Analysis-Big Data, Lilongwe, Malawi.
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