Advancing Crop Transformation in the Era of Genome Editing. Issue 7 (22nd June 2016)

• Record Type: Journal Article
• Authors: Altpeter, Fredy; Springer, Nathan M.; Bartley, Laura E.; Blechl, Ann E.; Brutnell, Thomas P.; Citovsky, Vitaly; Conrad, Liza J.; Gelvin, Stanton B.; Jackson, David P.; Kausch, Albert P.; Lemaux, Peggy G.; Medford, June I.; Orozco-Cárdenas, Martha L.; Tricoli, David M.; Van Eck, Joyce; Voytas, Daniel F.; Walbot, Virginia; Wang, Kan; Zhang, Zhanyuan J.; Stewart, C. Neal
• Is Part Of: The Plant Cell. Volume 28:Issue 7(2016)
• Page Start: 1510
• Page End: 1520
• Publication Date: 2016-06-22
• DOI: 10.1105/tpc.16.00196
• Languages: English
• ISSNs: 1040-4651

Abstract

Abstract: Plant transformation has enabled fundamental insights into plant biology and revolutionized commercial agriculture. Unfortunately, for most crops, transformation and regeneration remain arduous even after more than 30 years of technological advances. Genome editing provides novel opportunities to enhance crop productivity but relies on genetic transformation and plant regeneration, which are bottlenecks in the process. Here, we review the state of plant transformation and point to innovations needed to enable genome editing in crops. Plant tissue culture methods need optimization and simplification for efficiency and minimization of time in culture. Currently, specialized facilities exist for crop transformation. Single-cell and robotic techniques should be developed for high-throughput genomic screens. Plant genes involved in developmental reprogramming, wound response, and/or homologous recombination should be used to boost the recovery of transformed plants. Engineering universal Agrobacterium tumefaciens strains and recruiting other microbes, such as Ensifer or Rhizobium, could facilitate delivery of DNA and proteins into plant cells. Synthetic biology should be employed for de novo design of transformation systems. Genome editing is a potential game-changer in crop genetics when plant transformation systems are optimized.