Aloe

Background Aloe vera is a perennial, succulent, drought-resistant plant that exhibits many pharmacological characteristics such as wound healing ability against skin burns, anti-ulcer, anti-inflammatory, anti-tumor, anti-viral, anti-hypercholesterolemic, anti-hyperglycemic, anti-asthmatic and much more. Despite great medicinal worth, little genomic information is available on Aloe vera. This study is an initiative to explore the full-scale functional genomics of Aloe vera by generating whole transcriptome sequence database, using Illumina HiSeq technology and its progressive annotation specifically with respect to the metabolic specificity of the plant. Results Transcriptome sequencing of root and leaf tissue of Aloe vera was performed using Illumina paired-end sequencing technology. De novo assembly of high quality paired-end reads, resulted into 1,61,733 and 2,21,792 transcripts with mean length of 709 and 714 nucleotides for root and leaf respectively. The non-redundant transcripts were clustered using CD-HIT-EST, yielding a total of 1,13,063 and 1,41,310 unigenes for root and leaf respectively. A total of 6114 and 6527 CDS for root and leaf tissue were enriched into 24 different biological pathway categories using KEGG pathway database. DGE profile prepared by calculating FPKM values was analyzed for differential expression of specific gene encoding enzymes involved in secondary metabolite biosynthesis. Sixteen putative genes related to saponin, lignin, anthraquinone, and carotenoid biosynthesis were selected for quantitative expression by real-time PCR. DGE as well as qRT PCR expression analysis represented up-regulation of secondary metabolic genes in root as compared to leaf. Furthermore maximum number of genes was found to be up-regulated after the induction of methyl jasmonate, which stipulates the association of secondary metabolite synthesis with the plant’s defense mechanism during stress. Various transcription factors including bHLH, NAC, MYB were identified by searching predicted CDS against PlantTFdb. Conclusions This is the first transcriptome database of Aloe vera and can be potentially utilized to characterize the genes involved in the biosynthesis of important secondary metabolites, metabolic regulation, signal transduction mechanism, understanding function of a particular gene in the biology and physiology of plant of this species as well as other species of Aloe genus.