The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera).

Moringa oleifera is a plant well-known for its nutrition value, drought resistance and medicinal properties. cDNA libraries from five different tissues (leaf, root, stem, seed and flower) of M. oleifera cultivar Bhagya were generated and sequenced. We developed a bioinformatics pipeline to assemble transcriptome, along with the previously published M. oleifera genome, to predict 17,148 gene models. Few candidate genes related to biosynthesis of secondary metabolites, vitamins and ion transporters were identified. Expressions were further confirmed by real-time quantitative PCR experiments for few promising leads. Quantitative estimation of metabolites, as well as elemental analysis, was also carried out to support our observations. Enzymes in the biosynthesis of vitamins and metabolites like quercetin and kaempferol are highly expressed in leaves, flowers and seeds. The expression of iron transporters and calcium storage proteins were observed in root and leaves. In general, leaves retain the highest amount of small molecules of interest.

A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways.

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on Moringa oleifera transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of M. oleifera as described in Pasha et al.•Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.•Use of functionally important residues for screening of true hits.•Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

Dataset for the combined transcriptome assembly of M. oleifera and functional annotation.

In this paper, we present the data acquired during transcriptome analysis of the plant Moringa oleifera [1] from five different tissues (root, stem, leaf, flower and seed) by RNA sequencing. A total of 271 million reads were assembled with an N50 of 2094 bp. The combined transcriptome was assessed for transcript abundance across five tissues. The protein coding genes identified from the transcripts were annotated and used for orthology analysis. Further, enzymes involved in the biosynthesis of select medicinally important secondary metabolites, vitamins and ion transporters were identified and their expression levels across tissues were examined. The data generated by RNA sequencing has been deposited to NCBI public repository under the accession number PRJNA394193 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA394193).