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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Crop Improvement and Genetics Research » Research » Publications at this Location » Publication #334207
Title: Deep sequencing and transcriptome analyses to identify genes involved in secoiridoid biosynthesis in Tibetan medicinal plant Sewertia mussotii

Author
item LIU, YUE - Minzu University Of China
item WANG, YI - University Of California
item GUO, FENGXIAN - Minzu University Of China
item ZHAN, LIN - Minzu University Of China
item Mohr, Toni
item Cheng, Prisca
item HUO, NAXIN - University Of California
item GU, RONGHUI - Minzu University Of China
item PEI, DANNING - Minzu University Of China
item SUN, JIAQING - Minzu University Of China
item TANG, LI - Minzu University Of China
item LONG, CHUNLIN - Minzu University Of China
item HUANG, LUQI - Beijing University Of Chinese Medicine
item Gu, Yong

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/19/2017
Publication Date: 2/22/2017
Citation: Liu, Y., Wang, Y., Guo, F., Zhan, L., Mohr, T.J., Cheng, P.K., Huo, N., Gu, R., Pei, D., Sun, J., Tang, L., Long, C., Huang, L., Gu, Y.Q. 2017. Deep sequencing and transcriptome analyses to identify genes involved in secoiridoid biosynthesis in Tibetan medicinal plant Sewertia mussotii. Scientific Reports. 7:43108. doi: 10.1038/srep43108.

Interpretive Summary: With recent advances in high-throughput sequencing technologies, deep sequencing and RNA transcript analyses have become routine experimental approaches to dissect complex gene expression networks. We applied these methods to obtain better understanding of the metabolic pathways leading to the biosyntheses of important plant products with medicinal applicationsRNA samples were isolated from four tissues (stem, root, leaf, and flower) of Swertia mussotii, an important traditional Tibetan medicinal plant with pharmacological properties useful for the treatment of various ailments, such as hepatitis, and a member of the herbaceous genus Swetia in the Gentianaceae family. Deep sequencing of these samples+ and subsequent analyses generated 98,613 unique RNA transcript sequences. Gene annotation analyses identified 7184 genes that could encode proteins that regulate expression of other genesproviding a rich resource for future characterization of their roles in plant growth and development. We also found 654 transcripts associated with 23 biochemical pathways that produce secondary metabolites, including bioactive compounds. Overall, the technologies developed and the genomic data generated here lay a foundation for further research on this important medicinal plant.

Technical Abstract: Swertia mussotii Franch. is an important traditional Tibetan medicinal plant with pharmacological properties useful for the treatment of various ailments, such as hepatitis. Secoiridoids, including swertiamarin, are the major bioactive compounds in S. mussotii. The development of genomic resources will facilitate our understanding of the molecular basis underlying secoiridoid biosynthesis. Using transcriptome sequences from the root, leaf, stem, and flower tissues of S. mussotii, we performed de novo sequence assembly and generated 98,613 unique transcripts with an N50 of 1,085 bp. Putative functions can be assigned to 35,029 transcripts (35.5%) based on BLAST searches against several annotation databases including GO and KEGG. We identified 7,184 transcription factor encoding transcripts along with their expression profiling in individual tissues, providing a rich resource for future characterization of specific transcription factors in various biochemical pathways in S. mussotii. Transcriptome analyses identified 654 transcripts associated with 23 secondary metabolic pathways, including 35 transcripts encoding key enzymes in three specific metabolic pathways involved in secoiridoid biosynthesis. qRT-PCR was employed to examine the expression of enzyme-coding transcripts in the secoiridoid pathway, providing validation of the transcriptome profiling data. Overall, this genomic dataset of S. mussotii lays a foundation for further research on this important medicinal plant.