Transcriptome profiling of two Moringa species and insights into their antihyperglycemic activity.

BACKGROUND: Moringa concanensis Nimmo (MC), a plant that resembles Moringa oleifera Lam. (MO), has less scientific information but has traditionally been used as a medicinal plant. Moringa species have long been known for their medicinal qualities, which include antioxidant, anti-inflammatory, anticancer, and antihyperglycemic effects. We investigated the antidiabetic potential of MC and MO species in this study by using transcriptome profiling, metabolite analysis, and in vitro assay studies. RESULTS: Our transcriptome analysis revealed the expression of enzymes involved in the biosynthesis of quercetin, chlorogenic acid, and benzylamine, all of which have previously been shown to have antidiabetic activity. We compared the expression patterns of five different tissues from MC and MO and it was found that the key enzymes involved in the biosynthesis of these compounds were highly expressed in leaf tissue. The expression estimated by MC transcriptome data in different tissues was verified using RT-qPCR analysis. The amount of these compounds was further quantified in the crude leaf extract of both species and found that MC had a higher abundance of quercetin and chlorogenic acid than MO. The crude leaf extract from both MC and MO were further tested in vitro, and the results demonstrated strong inhibitory activity for α-glucosidase and DPP-IV enzymes. Our findings suggest that compounds in leaf tissue, such as quercetin, benzylamine, and chlorogenic acid, could play a significant role in this antidiabetic activity. In addition, when comparing MO plants, we found that MC had a slightly higher effect in expression, abundance, and inhibitory activity. CONCLUSIONS: This study presents the first report of MC transcriptome data, as well as a comparison of its anti-diabetic activity to MO. Our analysis discussed the significance of leaf tissue in antidiabetic activity compared to other tissues of both species. Overall, this study not only provides transcriptome resources for Moringa species, but also sheds light on antidiabetic potential of both species.

Exploring the medicinally important secondary metabolites landscape through the lens of transcriptome data in fenugreek (Trigonella foenum graecum L.).

Fenugreek (Trigonella foenum-graecum L.) is a self-pollinated leguminous crop belonging to the Fabaceae family. It is a multipurpose crop used as herb, spice, vegetable and forage. It is a traditional medicinal plant in India attributed with several nutritional and medicinal properties including antidiabetic and anticancer. We have performed a combined transcriptome assembly from RNA sequencing data derived from leaf, stem and root tissues. Around 209,831 transcripts were deciphered from the assembly of 92% completeness and an N50 of 1382 bases. Whilst secondary metabolites of medicinal value, such as trigonelline, diosgenin, 4-hydroxyisoleucine and quercetin, are distributed in several tissues, we report transcripts that bear sequence signatures of enzymes involved in the biosynthesis of such metabolites and are highly expressed in leaves, stem and roots. One of the antidiabetic alkaloid, trigonelline and its biosynthesising enzyme, is highly abundant in leaves. These findings are of value to nutritional and the pharmaceutical industry.

Computational analysis of potential candidate genes involved in the cold stress response of ten Rosaceae members.

BACKGROUND: Plant species from Rosaceae family are economically important. One of the major environmental factors impacting those species is cold stress. Although several Rosaceae plant genomes have recently been sequenced, there have been very few research conducted on cold upregulated genes and their promoter binding sites. In this study, we used computational approaches to identify and analyse potential cold stress response genes across ten Rosaceae family members. RESULTS: Cold stress upregulated gene data from apple and strawberry were used to identify syntelogs in other Rosaceae species. Gene duplication analysis was carried out to better understand the distribution of these syntelog genes in different Rosaceae members. A total of 11,145 popular abiotic stress transcription factor-binding sites were identified in the upstream region of these potential cold-responsive genes, which were subsequently categorised into distinct transcription factor (TF) classes. MYB classes of transcription factor binding site (TFBS) were abundant, followed by bHLH, WRKY, and AP2/ERF. TFBS patterns in the promoter regions were compared among these species and gene families, found to be quite different even amongst functionally related syntelogs. A case study on important cold stress responsive transcription factor family, AP2/ERF showed less conservation in TFBS patterns in the promoter regions. This indicates that syntelogs from the same group may be comparable at the gene level but not at the level of cis-regulatory elements. Therefore, for such genes from the same family, different repertoire of TFs could be recruited for regulation and expression. Duplication events must have played a significant role in the similarity of TFBS patterns amongst few syntelogs of closely related species. CONCLUSIONS: Our study overall suggests that, despite being from the same gene family, different combinations of TFs may play a role in their regulation and expression. The findings of this study will provide information about potential genes involved in the cold stress response, which will aid future functional research of these gene families involved in many important biological processes.

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).

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.

Decoding systems biology of plant stress for sustainable agriculture development and optimized food production.

Plants are essential facilitators of human life on planet earth. Plants play a critical functional role in mediating the quality of air, availability of food and the sustainability of agricultural resources. However, plants are in constant interaction with its environment and often hampered by various types of stresses like biotic and abiotic ones. Biotic stress is a significant reason for crop-loss and causes yield loss in the range of 31-42%, post-harvest loss due to biotic stress is in the range of 6-20%, and abiotic stress causes 6-20% of the crop damage. Recognizing the molecular factors driving plant stress-related events, and developing molecular strategies to aid plants to tolerate, resist or adapt to biotic and abiotic stress are critical for sustainable agriculture practice. In this review, we discuss how recent advances in bioinformatics, plant genomics, and data science could help to improve our understanding of plant stress biology and improve the scale of global food production. We present various areas of scientific and technological advances, such as increased availability of genomics data through whole genome sequencing that require attention. We also discuss emerging techniques including CRISPR-Cas9 based genome engineering systems to develop plant varieties that can handle combinatorial stress signals. Growing trend of converging multiple omics technologies and availability of accurate, multi-scale models of plant stress through the study of orthologs and synteny studies, would improve our knowledge of how plants perceive, respond, and manage stress to thrive as resilient crop species and thus help to reduce global food crisis.

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.