De Novo Transcriptome Profiling for the Generation and Validation of Microsatellite Markers, Transcription Factors, and Database Development for Andrographis paniculata .

Andrographis paniculata belongs to the family Acanthaceae and is known for its medicinal properties owing to the presence of unique constituents belonging to the lactones, diterpenoids, diterpene glycosides, flavonoids, and flavonoid glycosides groups of chemicals. Andrographolide, a major therapeutic constituent of A. paniculata, is extracted primarily from the leaves of this plant and exhibits antimicrobial and anti-inflammatory activities. Using 454 GS-FLX pyrosequencing, we have generated a whole transcriptome profile of entire leaves of A. paniculata . A total of 22,402 high-quality transcripts were generated, with an average transcript length and N50 of 884 bp and 1007 bp, respectively. Functional annotation revealed that 19,264 (86%) of the total transcripts showed significant similarity with the NCBI-Nr database and were successfully annotated. Out of the 19,264 BLAST hits, 17,623 transcripts were assigned GO terms and distributed into three major functional categories: molecular function (44.62%), biological processes (29.19%), and cellular component (26.18%) based on BLAST2GO. Transcription factor analysis showed 6669 transcripts, belonging to 57 different transcription factor families. Fifteen TF genes that belong to the NAC, MYB, and bHLH TF categories were validated by RT PCR amplification. In silico analysis of gene families involved in the synthesis of biochemical compounds having medicinal values, such as cytochrome p450, protein kinases, heat shock proteins, and transporters, was completed and a total of 102 different transcripts encoding enzymes involved in the biosynthesis of terpenoids were predicted. Out of these, 33 transcripts belonged to terpenoid backbone biosynthesis. This study also identified 4254 EST-SSRs from 3661 transcripts, representing 16.34% of the total transcripts. Fifty-three novel EST-SSR markers generated from our EST dataset were used to assess the genetic diversity among eighteen A. paniculata accessions. The genetic diversity analysis revealed two distinct sub-clusters and all accessions based on the genetic similarity index were distinct from each other. A database based on EST transcripts, EST-SSR markers, and transcription factors has been developed using data generated from the present study combined with available transcriptomic resources from a public database using Meta transcriptome analysis to make genomic resources available in one place to the researchers working on this medicinal plant.