Development of an Efficient and Reproducible in Vitro Regeneration and Transformation Protocol for Tropical Maize (zea Mays L.) Using Mature Seed-Derived Nodal Explants
Plant Cell Tissue and Organ Culture (PCTOC)(2022)
Delhi Unit Office
Abstract
Maize is an important crop for billions of people globally. The existing immature embryo-based regeneration protocol of maize has major limitations due to the non-availability of explants throughout the year, limited durability for culturing, and its laborious nature. Mature embryos, especially in tropical maize, are considered recalcitrant towards tissue culture. Therefore, standardization of a robust regeneration and transformation protocol in tropical maize using mature embryos or seeds as starting material is long envisaged. Considering this, in this study, 28 diverse tropical maize genotypes were evaluated for their embryogenic callus induction potential using two different explants (nodal explants and split embryo region) under two different callusing media. Out of 28 genotypes, better callus induction was achieved in four genotypes (BML 6, DHM 117, DMRH 1301, and DMRH 1308) from nodal explants. Further, in vitro regeneration was standardized using 22 different combinations of various auxins and cytokinins. Out of 28 genotypes, two recently commercialized and high-yielding cultivars (DMRH 1301 and DMRH 1308) demonstrated the best callusing and regeneration capability with an average regeneration percentage of 60.4% and 53.6%, respectively. Using the nodal explants-derived embryogenic calli, the genetic transformation was successfully carried out using the ‘Biolistic’ approach, and up to ~ 5% transformation efficiency was achieved. This efficient regeneration and transformation protocol can overcome the major limitations associated with the existing immature embryo-based protocol in tropical maize as mature seeds can be obtained easily in ample quantity round the year. Such a generalized and reproducible protocol has the potential to be a major tool for maize improvement using transgenic and genome-edited techniques. The standardized protocol not only overcomes the major limitations associated with the existing and predominately used immature embryo-based protocol but it is easier, reproducible, and has either higher or comparable callusing, regeneration, and transformation efficiency.
MoreTranslated text
Key words
Maize,Mature seed,Somatic embryogenesis,In vitro regeneration,Biolistic transformation
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined