Abstract
Senescence in biofuel grasses is a critical issue because early senescence decreases potential biomass production by limiting aerial growth and development. 2-Dimensional, differential in-gel electrophoresis (2D-DIGE) followed by mass spectrometry of selected protein spots was used to evaluate differences between leaf proteomes of early (ES)- and late- senescing (LS) genotypes of Prairie cordgrass (ES/LS PCG) and switchgrass (ES/LS SG), just before and after senescence was initiated. Analysis of the manually filtered and statistically evaluated data indicated that 69 proteins were significantly differentially abundant across all comparisons, and a majority (41%) were associated with photosynthetic processes as determined by gene ontology analysis. Ten proteins were found in common between PCG and SG, and nine and 18 proteins were unique to PCG and SG respectively. Five of the 10 differentially abundant spots common to both species were increased in abundance, and five were decreased in abundance. Leaf proteomes of the LS genotypes of both grasses analyzed before senescence contained significantly higher abundances of a 14-3-3 like protein and a glutathione-S-transferase protein when compared to the ES genotypes, suggesting differential cellular metabolism in the LS vs. the ES genotypes. The higher abundance of 14-3-3 like proteins may be one factor that impacts the senescence process in both LS PCG and LS SG. Aconitase dehydratase was found in greater abundance in all four genotypes after the onset of senescence, consistent with literature reports from genetic and transcriptomic studies. A Rab protein of the Ras family of G proteins and an s-adenosylmethionine synthase were more abundant in ES PCG when compared with the LS PCG. In contrast, several proteins associated with photosynthesis and carbon assimilation were detected in greater abundance in LS PCG when compared to ES PCG, suggesting that a loss of these proteins potentially contributed to the ES phenotype in PCG. Overall, this study provides important data that can be utilized toward delaying senescence in both PCG and SG, and sets a foundational base for future improvement of perennial grass germplasm for greater aerial biomass productivity.