@article {115259, title = {Exploring the medicinally important secondary metabolites landscape through the lens of transcriptome data in fenugreek (Trigonella foenum graecum L.).}, journal = {Sci Rep}, volume = {12}, year = {2022}, month = {2022 Aug 08}, pages = {13534}, abstract = {

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.

}, keywords = {Diosgenin, Hypoglycemic Agents, Plant Extracts, Plants, Medicinal, Transcriptome, Trigonella}, issn = {2045-2322}, doi = {10.1038/s41598-022-17779-8}, author = {Naika, Mahantesha B N and Sathyanarayanan, Nitish and Sajeevan, Radha Sivarajan and Bhattacharyya, Teerna and Ghosh, Pritha and Iyer, Meenakshi S and Jarjapu, Mahita and Joshi, Adwait G and Harini, K and Shafi, K Mohamed and Kalmankar, Neha and Karpe, Snehal D and Mam, Bhavika and Pasha, Shaik Naseer and Sowdhamini, Ramanathan} } @article {78096, title = {Dataset for the combined transcriptome assembly of and functional annotation.}, journal = {Data Brief}, volume = {30}, year = {2020}, month = {2020 Jun}, pages = {105416}, abstract = {

In this paper, we present the data acquired during transcriptome analysis of the 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).

}, issn = {2352-3409}, doi = {10.1016/j.dib.2020.105416}, author = {Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Pasha, Shaik Naseer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {83641, title = {A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways.}, journal = {MethodsX}, volume = {7}, year = {2020}, month = {2020}, pages = {101053}, abstract = {

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on 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 as described in Pasha et al.{\textbullet}Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.{\textbullet}Use of functionally important residues for screening of true hits.{\textbullet}Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

}, issn = {2215-0161}, doi = {10.1016/j.mex.2020.101053}, author = {Joshi, Adwait G and Harini, K and Meenakshi, Iyer and Shafi, K Mohamed and Pasha, Shaik Naseer and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {57789, title = {The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera).}, journal = {Genomics}, volume = {112}, year = {2020}, month = {01/2020}, pages = {621-628}, abstract = {

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.

}, issn = {1089-8646}, doi = {10.1016/j.ygeno.2019.04.014}, author = {Pasha, Shaik Naseer and Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {60326, title = {Topology prediction of insect olfactory receptors.}, journal = {Curr Opin Struct Biol}, volume = {55}, year = {2019}, month = {2019 Jun 21}, pages = {194-203}, abstract = {

Olfactory receptors are important transmembrane proteins that enable organisms to perceive odours and react to them. Structural understanding of insect olfactory receptors is scarce. In this review, we discuss different transmembrane helix prediction methods, consensus methods, topology prediction methods which can enable topology prediction of these proteins. We discuss the current success rates by applying the algorithms on few G-protein coupled receptors of known structure and olfactory receptor sequences and outstanding challenges. Finally, we discuss the impact of topology prediction on biology and modeling of ORs.

}, issn = {1879-033X}, doi = {10.1016/j.sbi.2019.05.014}, author = {Tiwari, Vikas and Karpe, Snehal D and Sowdhamini, Ramanathan} } @article {45449, title = {An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds}, journal = {Ecology and Evolution}, volume = {8}, year = {2018}, month = {06/2018}, pages = {59242-5935}, abstract = {

Chemical ecology is an ever-expanding field with a growing interest in population- and community-level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large-scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large-scale study of volatiles. A large-scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid-phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large-scale in situ sampling and analysis of volatiles. The protocol for large-scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.

}, doi = {10.1002/ece3.4138}, author = {Nair, Jyothi and Sanmugam, PV and Karpe, Snehal D and Ramakrishnan, Uma and Olsson, Shannon B} } @article {79777, title = {An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds }, journal = {Ecology and Evolution}, volume = {8}, year = {2018}, month = {06/2018}, pages = {5924-5936}, abstract = {

Chemical ecology is an ever-expanding field with a growing interest in population- and community-level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large-scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large-scale study of volatiles. A large-scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid-phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large-scale in situ sampling and analysis of volatiles. The protocol for large-scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.

}, doi = {10.1002/ece3.4138}, author = {Nair, Jyothi and Pragadheesh, V S and Karpe, Snehal D and Ramakrishnan, Uma and Olsson, SB} } @article {23142, title = {Computational genome-wide survey of odorant receptors from two solitary bees Dufourea novaeangliae (Hymenoptera: Halictidae) and Habropoda laboriosa (Hymenoptera: Apidae).}, journal = {Sci Rep}, volume = {7}, year = {2017}, month = {2017 Sep 07}, pages = {10823}, abstract = {

Olfactory/odorant receptors (ORs) probably govern eusocial behaviour in honey bees through detection of cuticular hydrocarbons (CHCs) and queen mandibular gland pheromones (QMP). CHCs are involved in nest-mate recognition whereas QMP acts as sex pheromone for drones and as retinue pheromone for female workers. Further studies on the effect of eusociality on the evolution of ORs are hindered by the non-availability of comprehensive OR sets of solitary species. We report complete OR repertoires from two solitary bees Dufourea novaeangliae (112 ORs) and Habropoda laboriosa (151 ORs). We classify these ORs into 34 phylogenetic clades/subfamilies. Differences in the OR sets of solitary and eusocial bees are observed in individual subfamilies like subfamily 9-exon (putative CHC receptors) and L (contains putative QMP receptor group). A subfamily (H) including putative floral scent receptors is expanded in the generalist honey bees only, but not in the specialists. On the contrary, subfamily J is expanded in all bees irrespective of their degree of social complexity or food preferences. Finally, we show species-lineage specific and OR-subfamily specific differences in the putative cis-regulatory DNA motifs of the ORs from six hymenopteran species. Out of these, [A/G]CGCAAGCG[C/T] is a candidate master transcription factor binding site for multiple olfactory genes.

}, issn = {2045-2322}, doi = {10.1038/s41598-017-11098-z}, author = {Karpe, Snehal D and Dhingra, Surbhi and Brockmann, Axel and Sowdhamini, R} } @article {16565, title = {Identification of Complete Repertoire of Apis florea Odorant Receptors Reveals Complex Orthologous Relationships with Apis mellifera.}, journal = {Genome Biol Evol}, volume = {8}, year = {2016}, month = {2016 Sep 26}, pages = {2879-2895}, abstract = {

We developed a computational pipeline for homology based identification of the complete repertoire of olfactory receptor (OR) genes in the Asian honey bee species, Apis florea Apis florea is phylogenetically the most basal honey bee species and also the most distant sister species to the Western honey bee Apis mellifera, for which all OR genes had been identified before. Using our pipeline, we identified 180 OR genes in A. florea, which is very similar to the number of ORs identified in A. mellifera (177 ORs). Many characteristics of the ORs including gene structure, synteny of tandemly repeated ORs and basic phylogenetic clustering are highly conserved. The composite phylogenetic tree of A. florea and A. mellifera ORs could be divided into 21 clades which are in harmony with the existing Hymenopteran tree. However, we found a few nonorthologous OR relationships between both species as well as independent pseudogenization of ORs suggesting separate evolutionary changes. Particularly, a subgroup of the OR gene clade XI, which had been hypothesized to code cuticular hydrocarbon receptors showed a high number of species-specific ORs RNAseq analysis detected a total number of 145 OR transcripts in male and 162 in female antennae. Most of the OR genes were highly expressed on the female antennae. However, we detected five distinct male-biased OR genes, out of which three genes (AfOr11, AfOr18, AfOr170P) were shown to be male-biased in A. mellifera, too, thus corroborating a behavioral function in sex-pheromone communication.

}, issn = {1759-6653}, doi = {10.1093/gbe/evw202}, author = {Karpe, Snehal D and Jain, Rikesh and Brockmann, Axel and Sowdhamini, Ramanathan} } @article {161, title = {Genome sequencing of herb Tulsi (Ocimum tenuiflorum) unravels key genes behind its strong medicinal properties.}, journal = {BMC Plant Biol}, volume = {15}, year = {2015}, month = {2015}, pages = {212}, abstract = {

BACKGROUND: Krishna Tulsi, a member of Lamiaceae family, is a herb well known for its spiritual, religious and medicinal importance in India. The common name of this plant is {\textquoteright}Tulsi{\textquoteright} (or {\textquoteright}Tulasi{\textquoteright} or {\textquoteright}Thulasi{\textquoteright}) and is considered sacred by Hindus. We present the draft genome of Ocimum tenuiflurum L (subtype Krishna Tulsi) in this report. The paired-end and mate-pair sequence libraries were generated for the whole genome sequenced with the Illumina Hiseq 1000, resulting in an assembled genome of 374~Mb, with a genome coverage of 61~\% (612~Mb estimated genome size). We have also studied transcriptomes (RNA-Seq) of two subtypes of O. tenuiflorum, Krishna and Rama Tulsi and report the relative expression of genes in both the varieties.

RESULTS: The pathways leading to the production of medicinally-important specialized metabolites have been studied in detail, in relation to similar pathways in Arabidopsis thaliana and other plants. Expression levels of anthocyanin biosynthesis-related genes in leaf samples of Krishna Tulsi were observed to be relatively high, explaining the purple colouration of Krishna Tulsi leaves. The expression of six important genes identified from genome data were validated by performing q-RT-PCR in different tissues of five different species, which shows the high extent of urosolic acid-producing genes in young leaves of the Rama subtype. In addition, the presence of eugenol and ursolic acid, implied as potential drugs in the cure of many diseases including cancer was confirmed using mass spectrometry.

CONCLUSIONS: The availability of the whole genome of O.tenuiflorum and our sequence analysis suggests that small amino acid changes at the functional sites of genes involved in metabolite synthesis pathways confer special medicinal properties to this herb.

}, issn = {1471-2229}, doi = {10.1186/s12870-015-0562-x}, author = {Upadhyay, Atul K and Chacko, Anita R and Gandhimathi, A and Ghosh, Pritha and Harini, K and Joseph, Agnel P and Joshi, Adwait G and Karpe, Snehal D and Kaushik, Swati and Kuravadi, Nagesh and Lingu, Chandana S and Mahita, J and Malarini, Ramya and Malhotra, Sony and Malini, Manoharan and Mathew, Oommen K and Mutt, Eshita and Naika, Mahantesha and Nitish, Sathyanarayanan and Pasha, Shaik Naseer and Raghavender, Upadhyayula S and Rajamani, Anantharamanan and Shilpa, S and Shingate, Prashant N and Singh, Heikham Russiachand and Sukhwal, Anshul and Sunitha, Margaret S and Sumathi, Manojkumar and Ramaswamy, S and Gowda, Malali and Sowdhamini, Ramanathan} }