Transcriptome profiling to discover putative genes associated with paraquat resistance in goosegrass (Eleusine indica L.).

• Main Authors: Jing An, Xuefeng Shen, Qibin Ma, Cunyi Yang, Simin Liu, Yong Chen
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2014-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4057336?pdf=render

BACKGROUND: Goosegrass (Eleusine indica L.), a serious annual weed in the world, has evolved resistance to several herbicides including paraquat, a non-selective herbicide. The mechanism of paraquat resistance in weeds is only partially understood. To further study the molecular mechanism underlying paraquat resistance in goosegrass, we performed transcriptome analysis of susceptible and resistant biotypes of goosegrass with or without paraquat treatment. RESULTS: The RNA-seq libraries generated 194,716,560 valid reads with an average length of 91.29 bp. De novo assembly analysis produced 158,461 transcripts with an average length of 1153.74 bp and 100,742 unigenes with an average length of 712.79 bp. Among these, 25,926 unigenes were assigned to 65 GO terms that contained three main categories. A total of 13,809 unigenes with 1,208 enzyme commission numbers were assigned to 314 predicted KEGG metabolic pathways, and 12,719 unigenes were categorized into 25 KOG classifications. Furthermore, our results revealed that 53 genes related to reactive oxygen species scavenging, 10 genes related to polyamines and 18 genes related to transport were differentially expressed in paraquat treatment experiments. The genes related to polyamines and transport are likely potential candidate genes that could be further investigated to confirm their roles in paraquat resistance of goosegrass. CONCLUSION: This is the first large-scale transcriptome sequencing of E. indica using the Illumina platform. Potential genes involved in paraquat resistance were identified from the assembled sequences. The transcriptome data may serve as a reference for further analysis of gene expression and functional genomics studies, and will facilitate the study of paraquat resistance at the molecular level in goosegrass.