Sequencing, De novo Assembly, Functional Annotation and Analysis of Phyllanthus amarus Leaf Transcriptome Using the Illumina Platform - Bose Mazumdar, Aparupa; Chattopadhyay, Sharmila (Frontiers in Plant Science, 2016)
Phyllanthus amarus Schum. & Thonn., a widely distributed annual medicinal herb has a long history of use in the traditional system of medicine for over 2000 years. However, the lack of genomic data for P. amarus, a non-model organism hinders research at the molecular level. In the present study, high-throughput sequencing technology has been employed to enhance better understanding of this herb and provide comprehensive genomic information for future work. Here P. amarus leaf transcriptome was sequenced using the Illumina Miseq platform. We assembled 85,927 non-redundant “unitranscript” sequences with an average length of 1548 bp, from 18,060,997 raw reads. Sequence similarity analyses and annotation of these unitranscripts were performed against databases like green plants non-redundant (nr) protein database, Gene Ontology (GO), Clusters of Orthologous Groups (COG), PlnTFDB, KEGG databases. As a result, 69,394 GO terms, 583 enzyme codes, 134 KEGG maps and 59 Transcription Factor families were generated. Functional and comparative analyses of assembled unitranscripts were also performed with the most closely related species like Populus trichocarpa and Ricinus communis using TRAPID. KEGG analysis showed that a number of assembled unitranscripts were involved in secondary metabolites, mainly phenylpropanoid, flavonoid, terpenoids, alkaloids and lignan biosynthetic pathways that have significant medicinal attributes. Further, Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values of the identified secondary metabolite pathway genes were determined and Reverse Transcription PCR (RT-PCR) of few of these genes were performed to validate the de novo assembled leaf transcriptome dataset. In addition 65,273 simple sequence repeats (SSRs) were also identified. To the best of our knowledge this is the first transcriptomic dataset of P. amarus till date. Our study provides the largest genetic resource that will lead to drug development and pave the way in deciphering various secondary metabolite biosynthetic pathways in P. amarus, especially those conferring the medicinal attributes of this potent herb.