Association of gene expression with biomass content and composition in sugarcane.

• Main Authors: Nam V Hoang, Agnelo Furtado, Angela J O'Keeffe, Frederik C Botha, Robert J Henry
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2017-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC5560616?pdf=render

About 64% of the total aboveground biomass in sugarcane production is from the culm, of which ~90% is present in fiber and sugars. Understanding the transcriptome in the sugarcane culm, and the transcripts that are associated with the accumulation of the sugar and fiber components would facilitate the modification of biomass composition for enhanced biofuel and biomaterial production. The Sugarcane Iso-Seq Transcriptome (SUGIT) database was used as a reference for RNA-Seq analysis of variation in gene expression between young and mature tissues, and between 10 genotypes with varying fiber content. Global expression analysis suggests that each genotype displayed a unique expression pattern, possibly due to different chromosome combinations and maturation amongst these genotypes. Apart from direct sugar- and fiber-related transcripts, the differentially expressed (DE) transcripts in this study belonged to various supporting pathways that are not obviously involved in the accumulation of these major biomass components. The analysis revealed 1,649 DE transcripts between the young and mature tissues, while 555 DE transcripts were found between the low and high fiber genotypes. Of these, 151 and 23 transcripts respectively, were directly involved in sugar and fiber accumulation. Most of the transcripts identified were up-regulated in the young tissues (2 to 22-fold, FDR adjusted p-value <0.05), which could be explained by the more active metabolism in the young tissues compared to the mature tissues in the sugarcane culm. The results of analysis of the contrasting genotypes suggests that due to the large number of genes contributing to these traits, some of the critical DE transcripts could display less than 2-fold differences in expression and might not be easily identified. However, this transcript profiling analysis identified full-length candidate transcripts and pathways that were likely to determine the differences in sugar and fiber accumulation between tissue types and contrasting genotypes.