Genetic manipulation of bermudagrass photosynthetic biosynthesis using Agrobacterium‐mediated transformation

Authors:
Publisher website
Google Scholar
Abstract
Bermudagrass is one of the most extensively used warm‐season grasses. It is widely used in landscaping, stadium construction and soil remediation due to its excellent regeneration, trampling and stress tolerances. However, studies on its regulatory mechanism and variety improvement by genetic engineering are still at a standstill, owing to its genetic variability and intrinsic limits linked with some resistance to Agrobacterium infection. In this study, we established a higher efficient Agrobacterium‐mediated transformation via screening for vital embryogenic callus and improving infection efficiency. The superior callus was light yellow, hard granular and compact, determined with a differentiation rate of more than 95%. The optimized infestation courses by gentle shaking, vacuuming and sonicating were used. The infested calluses were co‐cultured for 3 days, followed by desiccation treatments for 1 day to get higher infection efficiency. Then the CdHEMA1 gene, essential for chlorophyll biosynthesis, was cloned and transferred into bermudagrass to validate the aforementioned optimization procedures integrally. Molecular‐level analyses indicated that the CdHEMA1 gene had successfully integrated and was greatly increased in transgenic seedlings. Results of the photosynthetic capacity assessment showed that CdHEMA1 overexpression may considerably enhance the contents of photosynthetic pigments, OJIP curve and reaction center density (RC/CSo) to absorb (ABS/CSo, ABS/CSM) and capture (TRo/CSo) more light energy, hence improve the performance indices PIABS and PICS compared to the wild type. The successful completion of this project would provide a solid platform for further gene function study and molecular breeding of bermudagrass.
Funding Information
  • Agricultural Variety Improvement Project of Shandong Province (2019LZGC010)
  • Dalian National Laboratory for Clean Energy (QIBEBT I201930)

This publication has 51 references indexed in Scilit: