6-1 Improving bioenergy sorghums for sustainable production on low-productivity land
Tuesday, April 26, 2016: 8:00 AM
Key Ballroom 9-10, 2nd fl (Hilton Baltimore)
W. Vermerris*, A. Abril, T. Felderhoff and S. Shukla, University of Florida, Gainesville, FL, USA; S. Kadam, S. Bardhan, F. Fritschi and S. Jose, University of Missouri, Columbia, MO, USA
Due to its low input requirements compared to sugarcane and maize, and its tolerance to a wide range of growing conditions, sorghum is an attractive second-generation feedstock for the production of fuels and chemicals, especially when it can be grown on low-productivity land that is not suitable for traditional agricultural crops. Such land includes flood planes of the big rivers in the USA, as well as low-fertility reclaimed phosphate mine soils. We are focusing on the genetic improvement of sorghum to ensure economically meaningful crop yields under these suboptimal growing conditions. While sorghum is inherently tolerant to periodic flooding, genetic variation for flooding tolerance exists. Tolerant genotypes develop aerial roots that enable oxygen uptake, are able to maintain photosynthesis and continue to grow. The genetic and physiological mechanisms underlying flooding tolerance are being investigated through a combination of genetic mapping and high-throughput transcriptome profiling with the goal of identifying useful alleles that can be incorporated in breeding programs. Expression analysis of roots from flooding-tolerant and flooding-sensitive plants revealed differential expression of genes involved in several biological processes. A trait that is especially relevant for the Southeastern USA is resistance to the aggressive and omnipresent fungal pathogen Colletotrichum subineolum, that causes stem rot and leaf blight and that can reduce yield by 70%. We have identified two candidate resistance loci through genetic mapping using genotyping-by-sequencing technology and have developed several useful bioinformatics tools to streamline experimental design and data analysis. This research is supported by US DOE projects DE-PI0000031 and DE-SC0014439.