Journal
FRONTIERS IN PLANT SCIENCE
Volume 8, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fpls.2017.01562
Keywords
Setaria; genetic model; agronomically important traits; drought tolerance; inflorescence architecture; C-4 photosynthesis; millet; translational research
Categories
Funding
- National Science Foundation (NSF) [IOS-1413824]
- DDPSC
- US Department of Agriculture - National Institute of Food and Agriculture [2014-67012-22269]
- US Department of Energy [DE-SC0008769]
- U.S. Department of Energy (DOE) [DE-SC0008769] Funding Source: U.S. Department of Energy (DOE)
Ask authors/readers for more resources
Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6-8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here, we highlight topics presented in the conference including inflorescence architecture, C-4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available