De novo leaf and root transcriptome analysis identified novel genes involved in Steroidal sapogenin biosynthesis in Asparagus racemosus
© Upadhyay et al.; licensee BioMed Central Ltd. 2014
Received: 13 June 2014
Accepted: 21 August 2014
Published: 30 August 2014
Saponins are mainly amphipathic glycosides that posses many biological activities and confer potential health benefits to humans. Inspite of its medicinal attributes most of the triterpenes and enzymes involved in the saponin biosynthesis remains uncharacterized at the molecular level. Since the major steroidal components are present in the roots of A. racemosus our study is focussed on the comparative denovo transcriptome analysis of root versus leaf tissue and identifying some root specific transcripts involved in saponin biosynthesis using high-throughput next generation transcriptome sequencing.
After sequencing, de novo assembly and quantitative assessment, 126861 unigenes were finally generated with an average length of 1200 bp. Then functional annotation and GO enrichment analysis was performed by aligning all-unigenes with public protein databases including NR, SwissProt, and KEGG. Differentially expressed genes in root were initially identified using the RPKM method using digital subtraction between root and leaf. Twenty seven putative secondary metabolite related transcripts were experimentally validated for their expression in root or leaf tissue using q-RT PCR analysis. Most of the above selected transcripts showed preferential expression in root as compared to leaf supporting the digitally subtracted result obtained. The methyl jasmonate application induces the secondary metabolite related gene transcripts leading to their increased accumulation in plants. Therefore, the identified transcripts related to saponin biosynthesis were further analyzed for their induced expression after 3, 5 and 12 hours of exogenous application of Methyl Jasmonate in tissue specific manner.
In this study, we have identified a large set of cDNA unigenes from A. racemosus leaf and root tissue. This is the first transcriptome sequencing of this non-model species using Illumina, a next generation sequencing technology. The present study has also identified number of root specific transcripts showing homology with saponin biosynthetic pathway. An integrated pathway of identified saponin biosynthesis transcripts their tissue specific expression and induced accumulation after methyl jasmonate treatment was discussed.
KeywordsAsparagus racemosus saponin Transcriptome De novo assembly Unigenes
Asparagus racemosus (A. racemosus) is an important medicinal plant which has been used worldwide. The Asparagus genus (Asparagaceae) has over 300 species which are widely distributed in temperate and tropical regions including India, China, Korea and Japan . Its medicinal properties are reported in traditional systems of medicine such as Ayurveda, Siddha and Unani . The plant is a spinous under shrub with tuberous short rootstock bearing numerous succulent tuberous roots (30–100 cm long and 1–2 cm thick) that are silvery white or ash-colored externally and white internally .
The tuberous root of A. racemosus is used in traditional Indian medicine for the treatment of diverse ailments, including dysentery, tumors, inflammations, neuropathy, nervous disorders, bronchitis, hyperacidity, certain infectious diseases , conjunctivitis , chronic fevers, and rheumatism . Pharmacological studies with animals have manifested the potency of A. racemosus extract as an antioxidant , antianaphylactic , adaptogen , antistress , antiulcer , antidiarrhoeal , antibacterial , antitussive , molluscicide , radioprotective agent , and as a substrate for inulinase production  with the biggest focus being on its ability in modulating the immune system . One human trial confirmed the herb’s potency in treating dyspepsia . Due to its vast medicinal properties it is well known as an antispasmodic, aphrodisiac, demulcent, diuretic, galactagogue and refrigerant in Indian medicine (Ayurveda) .
A limited number of steroidal saponins have been reported previously from the roots of A. racemosus, with the major ones being shatavarins I, IV, V  and immunosides . Taxol, a steroidal saponin of Taxus bravifolia bark is currently being used in cancer chemotherapy . Diosgenin, (25R)-Spirost-5-en-3β-ol, is a steroidal sapogenin isolated from the plants . It is very useful in pharmaceutical industries as a natural source of steroidal hormones. Recent studies have found that steroidal sapogenin can be absorbed through the gut and plays an important role in the control of cholesterol metabolism . Other authors have reported that it has estrogenic effects  and antitumor activity . McAnuff et al. (2002) reported that steroidal sapogenins were effective agents for the treatment of hypocholesterolemia, a disorder often associated with diabetes .
The diverse structures of steroidal saponins make them valuable in commercial applications, as well as in drugs and medicines. It is thought that steroidal sapogenins are biosynthesized from cholesterol via a series of oxygenation and hydroxylation steps, and that they are then glycosylated to form steroidal saponins . The mevalonate pathway or HMG-CoA reductase pathway or mevalonate-dependent route or isoprenoid pathway, is an important cellular metabolic pathway present in all higher eukaryotes and many bacteria. The mevalonate pathway is responsible for the biosynthesis of numerous essential molecules including prenyl groups, coenzyme Q, dolichol, and sterols such as cholesterol . The knowledge of steroidal biosynthesis is derived from studies of cholesterol production through Acetate → Mevalonate → Isopentenyl pyrophosphate → Squalene pathway. The biosynthesis of cholesterol involves cyclization of aliphatic triterpene-squalene . Cholesterol has been found to be an effective precursor for diosgenin . However, the enzymes and genes involved in the biosynthesis of these complex molecules are largely uncharacterized. Only a limited number of enzymes have been identified and characterized that play an important role in the modification of the saponin backbone structure. This includes enzymes like cytochrome p450 monooxygenase, uridine diphosphate glycosyltransfearse (TGTs) and other enzyme . Secondary metabolic pathway genes are more diverse in comparison with those involved in primary metabolism. The advent of high-throughput sequencing technologies has permitted new approaches to explore functional genomics, including the direct sequencing of complementary cDNA generated from messenger and structural RNAs (RNA-seq). Transcriptome analysis followed by identification of potential candidate genes involved in the secondary metabolic pathway will lead to a better understanding of biosynthesis, its regulation and chemical diversity of secondary metabolites.
A. racemosus is well known medicinal Ayurvedic plant listed in the British Pharmacopoeias. Here we have performed the pair end transcriptome sequencing of root and leaf tissue of A. racemosus. Paired end sequencing improves the efficiency of de novo assembly and also increases the depth of sequencing. Using different assembly programs we have reported the most appropriate, assembled set of non redundant transcripts identified. The resulting assembled transcripts were functionally annotated, and the transcripts involved in secondary metabolic biosynthetic pathway were analyzed. The occurrence and fold induction of differentially expressed transcripts in leaf or root was further analyzed using digital gene expression analysis followed by their validation using q-RT PCR analysis. Sixteen putative transcripts involved in secondary metabolite biosynthesis were analyzed for their relative expression in response to Methyl jasmonate treatment. This data will lead to the advancement in the understanding of saponin biosynthetic pathway. The enzyme/transcript identified will serve the purpose of engineering of steroidal saponin biosynthesis in other medicinal plants.
Sequence quality control and de novoassembly
Functional annotation and classification
Identification of Simple Sequence Repeats (SSRs) and their nature of repeat present in secondary metabolic pathway related genes
SSR markers are the most important molecular markers in plants and have proven to be a valuable tool for various applications in genetics and plant breeding. Therefore, to develop a novel set of functional SSRs all of the 185764 unigenes generated in this study were used to determine potential microsatellite motifs using MIcroSAtellite (MISA) software (http://pgrc.ipk-gatersleben.de/misa). Total number of SSRs found in root tissues was more than SSRs found in leaf tissues. 18107 SSRs in 15338 sequences were recognized in leaf samples (Additional file 2: Table S3). Root samples showed 26733 SSRs in 21369 sequences (Additional file 3: Table S4). Number of sequences containing more than 1 SSR in leaf was 3385 and in root was 5976. Tri-nucleotide repeats were the most abundant SSR motif in leaf tissues followed by di-nucleotide, tetra-nucleotide, penta-nucleotide and hexa-nucleotide motifs (Additional file 1: Figure S3a) but in root tissues di-nucleotide repeats were the most abundant SSR motif followed by tri-nucleotide, tetra-nucleotide, penta- nucleotide and hexa-nucleotide motifs (Additional file 1: Figure S3b). The number of compound SSRs presents in leaf and root samples were 1450 and 2462 respectively. We have checked for the presence of these SSRs motifs in transcripts involved in steroidal sapogenin biosynthetic pathway. HMG Co-A reductase shows both compound SSRs, mono and tri-nucleotide repeats at sequence level. In addition to this Methylsterol Monooxygenase and Cycloartenol C-24 Methyltransferases have mononucleotide repeats in its sequences on the other hand HMG-COA-synthase was found to have di-nucleotide repeat (Additional file 3: Table S5).
Metabolic pathway analysis by KEGG
The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database records the network of molecular interactions in the cells and variants of them specific to particular organisms. Pathway-based analysis helps us to further understand the biological functions and interactions of genes. To further analyze the transcriptome of A. racemosus, all the unigenes were analyzed in KEGG pathway database. First, based on a comparison against the KEGG database using BLASTX with an E-value threshold of 10−5, 162 unigenes in leaf and 156 unigenes in roots were found to have significant matches in the database and were assigned to 124 KEGG pathways that are related to secondary metabolite biosynthesis (Additional file 4: Table S2). It was also observed that there were 50 unigenes in leaf sample and 61 unigenes in root sample, encoding enzymes that were involved in triterpenoid biosynthesis (Additional file 3: Table S8).
Identification and upregulation of Terpenoid backbone biosynthesis genes
Precursor molecules for steroidal saponin biosynthesis belong to the terpenoid backbone, which utilizes isoprenoids synthesized via Mevalonate as well as MEP pathway. In our transcriptome data there were 28 unigenes in leaf and 29 unigenes in root, related to terpenoid backbone biosynthesis. Almost all of the genes encoding the enzymes involved in terpenoid backbone biosynthesis were present in our data. We have identified 20 enzymes (unigenes) in root and 16 enzymes (unigenes) in leaf related to MVA pathway and 9 enzymes in root and 7 enzymes in leaf related to Mevalonate pathway of terpenoid biosynthesis. In most cases, more than one unigenes were assigned to the same enzyme. Such unigenes may represent different fragments of a single transcript, different members of a gene family, or both (Additional file 3: Table S8).
Identification and expression analysis of transcripts related to steroidal sapogenin and their specific expression in root of Asparagus racemosus
To identify genes with different expression levels in root as compared to leaf (as control), initially we used the RPKM method (Reads Per kb per Million reads) to calculate the expression levels of the unigenes. The log10 RPKM values were determined which range from less than 0.5 to more than 4.0 with an average of 2.1304 for root and 1.9286 for leaf (Additional file 1: Figure S4). Fold change values were also given in addition to their RPKM values which indicated that most of the genes are expressed with a fold change value ranging between 2–6 (Additional file 1: Figure S5). We used the ratio of RPKMs to calculate the fold-change in the expression (DGE) of each gene in two samples simultaneously. We observed 2934 differentially expressed transcripts by digital gene expression analysis in which 781 (26.61%) transcripts were up regulated in root with log 2 Fold Change value of more than 4 (Additional file 3: Table S6). After BLAST-X search of these Root specific transcripts found to be up regulated in DGE data, we obtained number of them to be functionally involved in Steroidal saponin biosynthetic pathway, such as Cytochrome P450s which showed a fold change value ranging between 277.48 to 2203.81, Methylsterol monooxygenases with a fold change value ranging between 154.54 to 949.06 and UDP-glycosyltransferase with a fold change of 729.15 (Additional file 3: Table S6). A total of 1640 unigenes were identified to be involved in transcription, including DGEs (407 up-regulated and 351 down-regulated) (Additional file 1: Figure S6a). These transcription factors were distributed to 69 families. Some of the largest TF families identified in leaf and root tissues of A. racemosus were the CCAAT-box binding transcription factors i.e. CCAAT , followed by the AP2-EREBP family , MYB family , WRKY family , C3H, HB , SNF2 , Orphans  and NAC  transcription factor super family. Digital gene expression of transcription factors in leaf and root tissues showed that 40 transcripts of MYB superfamily followed by 33 transcripts of AP2-EREBP and 23 transcripts of bHLH superfamily were highly upregulated in root (Additional file 1: Figure S6b).
Steroidal sapogenins are synthesized from cholesterol in several plants but not much information is available about biosynthetic pathways of steroid saponins and related metabolites apart from the knowledge that cholesterol and sitosterol are their cycloartenol-derived precursors. Three pathways namely glycolytic pathway, Mevalonate pathway and steroid biosynthesis pathway involved in steroidal saponin biosynthesis. Integrating these three pathways we arrived at a conclusion that steroidal sapogenins may be formed from squalene 2, 3-oxide in two ways, either from lanosterol via the formation of cholesterol, or from cycloartenol via the formation of sitosterol. The enzymes involved in steroidal sapogenin biosynthesis that were found to be up regulated in root are listed in Additional file 3: Table S7 with their transcript ID and EC numbers. In most cases, more than one unigenes were assigned to the same enzyme. Such unigenes may represent different fragments of a single transcript, different members of a gene family, or both.
Quantitative Real-Time PCR (q RT-PCR) analysis of saponin related gene transcripts in response to methyl jasmonate treatment
De novoassembly and functional annotation
A. racemosus is an important plant used for medicinal and ornamental purposes. Despite pharmacological importance, the transcriptomic and genomic data of A. racemosus are very limited that are available in the National Center of Biotechnology Information (NCBI) database. In NCBI only 97 ESTs and 22 nucleotide sequences are available from A. Racemosus. Characterization of transcriptome is especially important for such a plant species which have a very large genome and present a great challenge for whole genome sequencing. Due to the immense pharmacological importance of saponins found in roots of A. racemosus, de novo transcriptome analysis of leaf vs root tissue was done.
Because of the development of an array of novel assembly methods, short read assembly has become cost-effective. With recent improvements in assembly programs that can effectively assemble relatively short reads, coupled with the great advantage of paired-end sequencing, the short read sequence data generated for transcriptomes or whole genomes have been assembled de novo very successfully for species such as maize , soybean , giant panda , carrot , rubber tree , peanut  safflower , sweet potato , etc. Therefore, de novo sequencing and assembly of transcriptome or genome have been successfully used for model  and non-model  organisms. In this study, more than 57.41 million high-quality reads were used to assemble the leaf and root transcriptome of A. racemosus. The assembly result indicated that the mean length of unigenes was 1200 bp, which was longer than the results shown in previous studies. We obtained more than 100% HQ bases for both root and leaf samples which reflect the high quality sequencing run. Low quality bases as well as the presence of adapters in reads could interfere with the assembly process resulting in misassemblies or truncated contigs. Hence, low quality bases and adapter sequences were trimmed before proceeding with further analysis. These results suggested that the transcriptome sequencing data from A. racemosus were effectively assembled, which was further validated by the high proportion of unigenes matched with known proteins. The observed N50 value was higher which further suggests a better assembly.
The best hit for each unigene queried against the KEGG and NCBI Nr database was utilized to assign functional GO annotation in terms of biological process, molecular function and cellular component groups. The large number of diverse GO assignments to unigenes highlights the diversity of genes likely represented in Asparagus leaf and root transcriptome data. Mapping these unigenes on to KEGG, we had identified large number of unigenes involved in biosynthesis of various secondary metabolites. The unigenes without hits probably belonged to untranslated regions, noncoding RNA, short sequences not containing a protein domain or assembly mistakes. The functions of the identified genes cover various molecular function categories, and the well-represented categories included plasma membrane, integral membrane, nucleotide binding, structural component of ribosomes and nuclear proteins. The sequences encoded a broad set of transcripts represented within the cellular component category which indicates the need of a large number of transcripts for cellular structure and maintenance. On the basis of the annotation, we found the genes encoding all of the enzymes involved in biosynthesis of triterpenoid backbone, mostly in roots (including MVA and MEP pathways).
Potential candidate genes involved in steroidal saponin biosynthesis
Steroidal sapogenins are synthesized from cholesterol in several plants , through isoprenoid biosynthetic pathway. Cytosolic isoprenoids are synthesized from acetyl CoA through intermediate formations of mevalonate, isopentanyldiphosphate, dimethylallyldiphosphate, isopentenyl diphosphate, geranyldiphosphate, faresnyl diphospahte, squalene, cycloartenol and leads to steroidal sapogenin in broad view.
Most of the known enzymes involved in the MVA pathway for triterpene steroidal biosynthesis were found to be specifically expressing in root in comparision with leaf transcriptome of A. racemosus. Previous studies reported that initial reactions of isoprenoid biosynthetic pathway occur in the leaves, while later step modifications and storage of saponins occurs in the roots  thus the amount of saponins is higher in roots. Mevalonate is the key precursor for synthesis of cholesterol and related isoprenoid compounds. Synthesis of mevalonate starts from acetyl CoA. The conversion of acetyl CoA to acetoacetyl CoA and then to 3-hydroxy-3-methylglutaryl CoA (3-HMG CoA) by HMG Co-A synthase (2 transcripts upregulated) corresponds to the biosynthetic pathway for ketone bodies. In the next step, the 3-HMG group is cleaved from the CoA and at the same time reduced to mevalonate with the help of (NADPH + H+), 3- HMG CoA reductase which is the key enzyme in cholesterol biosynthesis. A. racemosus transcriptome analysis has identified five different forms of 3-HMG CoA reductase and it was found to be specifically expressing in root tissue. Oxidosqualene which is formed by the action of the Squalene epoxidase enzyme from Squalene is the precursor in the biosynthesis of both triterpene and steroidal saponins in plant. We have identified two contigs showing homology with squalene epoxidase during transcriptome analysis, real time analysis further showed the specific expression of these two transcripts in root tissue only. From squalene upto steroidal sapogenin formation a total of 21 transcripts were identified from A. racemosus leaf and root transcriptome analysis (Additional file 3: Table S7).
Methyl jasmonate treatment
Methyl Jasmonate plays critical roles in plant metabolism by up-regulating the expression of genes related to secondary metabolite biosynthesis. We studied transcriptional changes in leaf and root tissues of A. racemosus after methyl jasmonate (MeJA) treatment. In RT-PCR analysis transcripts of UGTs and CyP450 involved in glycosylation and oxygenation steps respectively, have shown induced accumulation after the treatment. The upregulation of these enzymes in response to MeJA treatment may be due to the fact that mono-oxygenases that catalyze oxygenation reactions and glycosyltransferases that catalyze the transfer of sugar molecules to steroidal compounds may produce diverse saponins in different conditions (stress) and control the activities of plants. Similar stimulatory effects of MeJA on the biosynthetic pathway of other triterpenoid saponin compounds have already been reported . It is also reported that transcripts encoding the key triterpene biosynthetic enzyme β-amyrin synthase increased up to 50-fold by introducing MeJA to cell suspension cultures of M. truncatula. It is known that Jasmonic acid upregulates the expression of defense-related genes, so it may be possible that saponin biosynthesis is also related to plant defense responses .
The de novo transcriptome analysis of this very important Indian medicinal ayurvedic herb brings out for the first time novel transcripts related to saponin biosynthesis which has anticancer and anti-oxidant properties. The knowledge of intermediate transcripts identified in this study their functional characterization at biochemical, cellular and molecular level will be useful to metabolically engineer and understand the saponin biosynthetic pathway and its regulation in plants.
Field grown plants of A. racemosus (CIM-SHAKTI), from the experimental plot of CSIR-CIMAP (Lucknow) field was used for transcriptome analysis. Leaf and root tissues from 2 month old healthy plants were harvested in the spring season and were stored at −80°C until used. These samples were further used for RNA extraction.
RNA extraction and cDNA library construction
TRIzol method was used for RNA isolation from the root and leaf tissues. Transcriptome library for sequencing was constructed according to the Illumina TruSeq RNA library protocol outlined in “TruSeq RNA sample preparation Guide” (Part # 15008136; Rev.A; Nov 2010). Briefly 2.5 μg of total RNA by Qubit was enriched for Poly-A using RNA Purification Beads provided with the kit, enriched RNA was fragmented for 4 minutes at elevated temperature (94°C) in the presence of divalent cations and reverse transcribed with Superscript II Reverse transcriptase by priming with Random Hexamers. Second strand cDNA was synthesized in the presence of DNA polymerase I and RnaseH. The cDNA was cleaned up using Agencourt Ampure XP SPRI beads (Beckman Coulter). Illumina adapters were ligated to the cDNA molecules after end repair and addition of “A” base. SPRI cleanup was performed after ligation. The library was amplified using 11 cycles of PCR for enrichment of adapter ligated fragments. The prepared library was quantified using Nanodrop and validated for quality by running an aliquot on a High Sensitivity Bioanalyzer Chip (Agilent).
De novoassembly and clustering
The leaf and root cDNA library was sequenced using paired end Illumina Hi-seq GAII Analyzer/454 GS FLX/5500 SOLiD System. QC and raw data processing were done by SeqQC-V2.1. Raw reads were cleaned by removing Vector (Adapter/Primer) contaminated reads. Empty reads and reads with unknown sequences ‘N’ was removed before data analysis. Contig assembly was carried out using a de Bruijn graph based de novo genome assembler Velvet_1.2.10 (https://www.ebi.ac.uk/~zerbino/velvet/) with a hash length 47 (Leaf Sample) and 43 (Root Sample). Velvet takes in short reads and assembles them into contigs using paired-end information. A draft assembly was built with hash length of 47 and 43 for leaf and root respectively. This draft assembly was used by observed-insert-length.pl and estimate-exp_cov.pl (from Velvet package) to estimate insert length and expected coverage parameters, which were then used to generate a final assembly. After this Oases_0.1.21 (https://www.ebi.ac.uk/~zerbino/oases/) use dynamic filters to improve the quality of the assembly with a hash length 47 (Leaf Sample) and 43 (Root Sample), and clusters them into small groups (loci). It then uses paired end information to construct transcript isoforms. The transcripts from three individual assemblies were clustered (CD-HIT v4.5.4 http://www.bioinformatics.org/cd-hit/) in order to generate a comprehensive reference. Sequence identity threshold and alignment coverage (for the shorter sequence) were both set at 80% to generate clusters.
Sequence annotation and functional characterization
The contigs and singletons of leaf and root libraries were annotated using BLASTX program against NCBI database and all unigenes were utilized for homology searches against various protein databases such as NCBI nr (http://www.ncbi.nlm.nih.gov/), Swissprot (http://www.expasy.ch/sprot/), and the KEGG pathway (http://www.genome.jp/kegg/) with BLAST program (E-value < 1E-5), and the best aligning results were selected to annotate the unigenes. If the aligning results from different databases are in conflict with each other, the results from nr database were preferentially selected, followed by Swissprot, KEGG database. To further annotate the unigenes in this research, the Blast2GO program was used to get GO annotation according to molecular function, biological process and cellular component ontologies (http://www.geneontology.org/). Secondary metabolic Pathway assignments were performed according to the KEGG pathway database.
To assign functions to each unigene, gene ontology (GO) analysis was performed which classified unigenes of both root and leaf samples under the categories of Cellular component, Molecular Function and Biological Process. Each annotated sequence may have more than one GO term, either assigned in the different GO categories (Biological process, Molecular function and Cellular Component) or in the same category.
Simple sequence repeats (SSRs) identification
All the contigs and singletons of leaf and root assemblies were used in a microsatellite program (MISA) (http://pgrc.ipk-gatersleben.de/misa/misa.html) for identification of SSR motifs. We searched for microsatellites from mononucleotide to hexa-nucleotide. The parameters used for simple sequence repeats were at least 6 repeats for di- and 5 for tri-, tetra, penta and hexa- nucleotide. Both perfect (i.e. contain a single repeat motif) and compound repeats (i.e. composed of two or more motifs separated by 100 bases) were identified.
Digital gene expression profiling
Where C is the number of reads that uniquely aligned to one unigene; N is the total number of reads that uniquely aligned to all unigenes; L is the base number in the CDS of one unigene.
where N is the number of all genes with GO annotation; n is the number of DGEs in N; M is the number of all genes that are annotated to the certain GO terms; m is the number of DGEs in M. Fold change values were calculated as Treated/Control expression values. Up and Down regulation was based on Log2FoldChange values (>1 Up, <−1 Down).
DGEs were also used in pathway enrichment analysis. We calculated the gene numbers in each pathway by mapping all DGEs to KEGG database (http://www.genome.jp/kegg).
Transcription factor analysis
Transcription factors were predicted according to protein sequences obtained from CDS prediction. We used hmmsearch to search the domain of the plant transcription factors (http://plntfdb.bio.unipotsdam.de/v3.0/) and classified unigenes according to the gene family information.
Quantitative Real-Time PCR (qRT-PCR) analysis
Twenty seven up regulated transcripts in root with potential roles in secondary metabolite biosynthesis were chosen for validation using qRT-PCR (primers designed for qRT-PCR analysis was shown in Additional file 5: Table S1). Field grown two months old Asparagus racemosus plants were harvested and washed with DEPC treated water. The leaf and root tissues were dried and separated before freezing in liquid nitrogen and were stored at −80°C until used. Total RNA was extracted from leaf and root tissues separately by RNeasy Mini Kit (Qiagen, USA).
In order to study the role of MeJA on the expression of potential transcripts related to steroidal saponin biosynthesis, 16 out of 27 transcripts were selected. Two months old field grown A. racemosus plants were used for MeJA treatment. A solution was prepared in DMSO and Triton-X containing 250 μM MeJA. The treatment was given by spraying the solution on aerial parts of the plant for 2–3 minutes; plants were sprayed again after 1 hour with the similar solution. For control, plants were sprayed with the solution containing only DMSO and Triton- X. After spraying the samples were covered with perforated autoclavable bags to maintain proper transpiration. After 3, 5 and 12 hours of treatment the samples were collected and washed properly with MQ to remove any contaminant or soil. Total RNA of leaf and root samples was extracted separately by RNeasy Mini Kit (Qiagen, USA) according to manufacturer's instructions. The RNA was quantified using Nanodrop and validated for quality by running an aliquot on a High Sensitivity Bioanalyzer Chip (Agilent). Approximately 1 μg of total RNA of each sample was converted into single-stranded cDNA using High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). The cDNA products were then diluted 100-fold with deionized water. The reaction was performed on a 7500 FAST Real-Time PCR System (Applied Biosystems, USA) using the RealMasterMix (SYBR Green, Applied Biosystems). Expression levels of the selected unigenes were normalized to that of Actin, an internal reference gene. The relative expression is determined by raising 2 to the power of the negative value of ∆∆Ct for each sample. All the experiments were repeated using three biological and three experimental replicates and the data were analyzed statistically.
The author’s acknowledge Director, CSIR-Central Institute of Medicinal & Aromatic Plants, Lucknow, India for providing the necessary facilities. Authors also acknowledge the National Gene Bank for Medicinal and Aromatic Plants of CSIR-CIMAP Lucknow for providing the A. racemosus seedlings. RKS acknowledges INSA young Scientist project for funding and Genotypic Technology (P) Ltd (Bangalore, India) for NGS. Swati, Ujjal and Sonal acknowledge CSIR and UGC for fellowship.
- Kim GS, Kim HT, Seong JD, Oh SR, Lee CO, Bang JK, Seong NS, Song KS: Cytotoxic steroidal saponins from the rhizomes of Asparagus oligoclonos. J Nat Prod. 2005, 68: 766-768. 10.1021/np040128k.PubMedView ArticleGoogle Scholar
- Sharma M, Sharma A, Kumar A: Ethnopharmacological importance of Asparagus racemosus: A review. J Pharm Biomed Sci. 2011, 6: 1-12.Google Scholar
- Bopana N, Saxena S: Asparagus racemosus–ethnopharmacological evaluation and conservation needs. J Ethnopharmacol. 2007, 110: 1-15. 10.1016/j.jep.2007.01.001.PubMedView ArticleGoogle Scholar
- Goyal RK, Singh J, Lal H: Asparagus racemosus–an update. Indian J Med Sci. 2003, 57: 408-414.PubMedGoogle Scholar
- Sharma P, Singh GA: A review of plant species used to treat conjunctivitis. Phytother Res. 2002, 16: 1-22.PubMedView ArticleGoogle Scholar
- Chadda YR: The wealth Of India: A Dictionary of Indian Raw Materials and Industrial Products, Volume IA. 2003, New Delhi, India: National Institute of Science Communication and Information resources, Council of Scientific and Industrial Research, 470-471.Google Scholar
- Parihar MS, Hemnani T: Experimental excitotoxicity provokes oxidative damage in mice brain and attenuation by extract of Asparagus racemosus. J Neural Transm. 2004, 111: 1-12. 10.1007/s00702-003-0069-8.PubMedView ArticleGoogle Scholar
- Padmalatha K, Venkataraman BV, Roopa R: Antianaphylactic effect of DLH-3041 (polyherbal formulation) on rat mesenteric mast cell degranulation. Ind J Pharm. 2002, 34: 119-122.Google Scholar
- Bhattacharya SK, Bhattacharya A, Chakrabarti A: Adaptogenic activity of siotone, a polyherbal formulation of ayurvedic rasayanas. Ind J Exp Biol. 2000, 38: 119-121.Google Scholar
- Muruganandam AV, Kumar V, Bhattacharya SK: Effect of poly herbal formulation, EuMIl, on chronic stress-induced homeostatic pertubations in rats. Ind J Exp Biol. 2002, 40: 1151-1160.Google Scholar
- Sairam K, Priyambada S, Aryya NC, Goel RK: Gastroduodenal ulcer protective activity of Asparagus racemosus: an experimental, biochemical and histology study. J Ethnopharmacol. 2003, 86: 1-10. 10.1016/S0378-8741(02)00342-2.PubMedView ArticleGoogle Scholar
- Trick M, Long Y, Meng J, Bancroft I: Single nucleotide polymorphism (SNP) discovery in the polyploid Brassica napus using Solexa transcriptome sequencing. Plant Biotechnol J. 2009, 7 (4): 334-346. 10.1111/j.1467-7652.2008.00396.x.PubMedView ArticleGoogle Scholar
- Mandal SC, Nandy A, Pal M, Saha BP: Evaluation of antibacterial activity of Asparagus racemosus Willd root. Phytother Res. 2000, 14: 118-119. 10.1002/(SICI)1099-1573(200003)14:2<118::AID-PTR493>3.0.CO;2-P.PubMedView ArticleGoogle Scholar
- Mandal SC, Ashok Kumar CK, Lakshmi SM, Sinha S, Murugesan T, Saha BP, Pal M: Antitussive effect of Asparagus racemosus root against sulfur dioxide-induced cough in mice. Fitoterapia. 2000, 71: 686-689. 10.1016/S0367-326X(00)00151-9.PubMedView ArticleGoogle Scholar
- Chifundera K, Baluku B, Mashimango M: Phytochemical screening and molluscicidal potency of some Zairean medicinal plants. Pharmacol Res. 1993, 28: 333-340. 10.1006/phrs.1993.1135.PubMedView ArticleGoogle Scholar
- Arora R, Gupta D, Chawla R, Sagar R, Sharma A, Kumar R, Prasad J, Singh S, Samanta N, Sharma RK: Radioprotection by plant products: present status and future prospects. Phytother Res. 2005, 19: 1-22. 10.1002/ptr.1605.PubMedView ArticleGoogle Scholar
- Singh RS, Dhaliwal R, Puri M: Production of inulinase from Kluyveromyces marxianus YS-1 using root extracts of Asparagus racemosus. Process Biochem. 2006, 41 (7): 1703-1707. 10.1016/j.procbio.2006.03.005.View ArticleGoogle Scholar
- Gautam M, Diwanay S, Gairola S, Shinde Y, Patki P, Patwardhan B: Immunoadjuvant potential of Asparagus racemosus aqueous extract in experimental system. J Ethnopharmacol. 2004, 91: 251-10.1016/j.jep.2003.12.023.PubMedView ArticleGoogle Scholar
- Dalvi SS, Nadkarni PM, Gupta KC: Effect of Asparagus racemosus (Shatavari) on gastric emptying time in normal healthy volunteers. J Postgraduate Med. 1990, 36: 91-94.Google Scholar
- Sharma PC, Yelne MB, Dennis TJ: Database on Medicinal Plants Used in Ayurveda, Volume I. Central Council for Research in Ayurveda and Siddha. 2000, New Delhi: Yugantar Prakashan (P.) Ltd, 418-430.Google Scholar
- Hayes PY, Jahidin AH, Lehmann R, Penman K, Kitching W, De Voss JJ: Asparinins, asparosides, curillins, curillosides, and shavatarins: Structural clarification with the isolation of shatavarin V, a new steroidal saponin from the root of Asparagus racemosus. Tetrahedron Lett. 2006, 47 (49): 8683-8687. 10.1016/j.tetlet.2006.10.030.View ArticleGoogle Scholar
- Gautam M, Saha S, Bani S, Kaul A, Mishra S, Patil D, Satti NK, Suri KA, Gairola S, Suresh K, Jadhav S, Qazi GN, Patwardhan B: Immunomodulatory activity of Asparagus racemosus on systemic Th1/Th2 immunity: implications for immunoadjuvant potential. J Ethnopharmacol. 2009, 121: 241-247. 10.1016/j.jep.2008.10.028.PubMedView ArticleGoogle Scholar
- Kim J, Park EJ: Cytotoxic anticancer candidates from natural resources. Curr Med Chem Anticancer Agents. 2002, 2: 485-537. 10.2174/1568011023353949.PubMedView ArticleGoogle Scholar
- Marker RE, Tsukamoto T, Turner DL: Sterols. C. Diosgenin. J Am Chem Soc. 1940, 62: 2525-2532. 10.1021/ja01866a072.View ArticleGoogle Scholar
- Roman ID, Thewles A, Coleman R: Fractionation of livers following diosgenin treatment to elevate biliary cholesterol. Biochim Biophys Acta. 1995, 1255: 77-81. 10.1016/0005-2760(94)00212-H.PubMedView ArticleGoogle Scholar
- Aradhana, Rao AR, Kale RK: Diosgenin–a growth stimulator of mammary gland of ovariectomized mouse. Indian J Exp Biol. 1992, 30: 367-370.Google Scholar
- Corbiere C, Liagre B, Bianchi A, Bordji K, Dauca M, Netter P, Beneytout JL: Different contribution of apoptosis to the antiproliferative effects of diosgenin and other plant steroids, hecogenin and tigogenin, on human 1547 osteosarcoma cells. Int J Oncol. 2003, 22: 899-905.PubMedGoogle Scholar
- Raju J, Patlolla JMR, Swamy MV, Rao CV: Diosgenin, a Steroid Saponin of Trigonella foenum-graecum (Fenugreek), Inhibits Azoxymethane-Induced Aberrant Crypt Foci Formation in F344 Rats and Induces Apoptosis in HT-29 Human Colon Cancer Cells. Cancer Epidemiol. 2004, 13 (8): 1392-1398.Google Scholar
- Dewick PM: Medicinal Natural Products: A Biosynthetic Approach. 2002, Chichester, UK: John Wiley & Sons, 237-289. 2Google Scholar
- Gardner RG, Hampton RY: A highly conserved signal controls degradation of 3- Hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase in Eukaryotes. J Biol Chem. 1999, 274 (44): 31671-31678. 10.1074/jbc.274.44.31671.PubMedView ArticleGoogle Scholar
- Khanam S: Pharmacognosy: general study of formation of secondary metabolites. Dept. of Pharmacognosy, Al-Ameen college of Pharmacy. 2007, 24-25.Google Scholar
- Dewick PM: Medicinal natural products: a biosynthetic approach (3rd Edition). 2009, Ltd: John Wiley & Sons, 546-547.View ArticleGoogle Scholar
- Haralampidis K, Trojanowska M, Osbourn AE: Biosynthesis of triterpenoid saponins in plants. Adv Biochem Eng Biotechnol. 2002, 75: 31-49.PubMedGoogle Scholar
- Mishra S, Triptahi V, Seema Singh S, Phukan UJ, Gupta MM, Shanker K, Shukla RK: Wound induced tanscriptional regulation of benzylisoquinoline pathway and characterization of wound inducible PsWRKY transcription factor from papaver somniferum. PLoS One. 2013, 8 (1): e52784-10.1371/journal.pone.0052784.PubMed CentralPubMedView ArticleGoogle Scholar
- Wang Y, Zeng X, Iyer NJ, Bryant DW, Mockler TC, Mahalingam R: Exploring the Switchgrass transcriptome using second-generation sequencing technology. PLoS One. 2012, 7: 34225-10.1371/journal.pone.0034225.View ArticleGoogle Scholar
- Wang XW, Luan JB, Li JM, Bao YY, Zhang CX, Liu SS: De novo characterization of a whitefly transcriptome and analysis of its gene expression during development. BMC Genomics. 2010, 11: 400-410. 10.1186/1471-2164-11-400.PubMed CentralPubMedView ArticleGoogle Scholar
- Blanca J, Canizares J, Roig C, Ziarsolo P, Nuez F: Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae). BMC Genomics. 2011, 12: 104-10.1186/1471-2164-12-104.PubMed CentralPubMedView ArticleGoogle Scholar
- Eisenreich W, Schwarz M, Cartayrade A, Arigoni D, Zenk MH: The deoxyxylulose phosphate pathway of terpenoid biosynthesis in plants and microorganisms. Chem Biol. 1998, 5: 221-233. 10.1016/S1074-5521(98)90002-3.View ArticleGoogle Scholar
- Kalra S, Kumar S, Lakhanpal N, Kaur J, Singh K: Characterization of Squalene synthase Gene from Chlorophytum borivilianum (Sant. and Fernand.). Mol Biotechnol. 2013, doi:10.1007/s12033-012-9645-1Google Scholar
- Xia ZH, Xu HM, Zhai JL, Li DJ, He CZ, Huang X: RNA-Seq analysis and de novo transcriptome assembly of Hevea brasiliensis. Plant Mol Biol. 2011, 77: 299-308. 10.1007/s11103-011-9811-z.PubMedView ArticleGoogle Scholar
- Wang QQ, Liu F, Chen XS, Ma XJ, Zeng HQ, Yang ZM: Transcriptome profiling of early developing cotton fiber by deep-sequencing reveals significantly differential expression of genes in a fuzzless/lintless mutant. Genomics. 2010, 96 (6): 369-376. 10.1016/j.ygeno.2010.08.009.PubMedView ArticleGoogle Scholar
- Shukla AK, Mall M, Rai SK, Singh S, Nair P, Parashar G, Shasany AK, Singh SC, Joshi VK, Khanuja SPS: A taranscriptomic approach for exploring molecular basis for dosha-balancing property-based classification of plants in Ayurveda. Mol Biol Rep. 2013, 40 (4): 3255-3262. 10.1007/s11033-012-2400-7.PubMedView ArticleGoogle Scholar
- Li YJ, Fu YR, Huang JG, Wu CA, Zheng CC: Transcript profiling during the early development of the maize brace root via Solexa sequencing. FEBS J. 2011, 278: 156-166. 10.1111/j.1742-4658.2010.07941.x.PubMedView ArticleGoogle Scholar
- Libault M, Farmer A, Joshi T, Takahashi K, Langley RJ, Franklin LD, He J, Xu D, May G, Stacey G: An integrated transcriptome atlas of the crop model Glycine max, and its use in comparative analyses in plants. Plant J. 2010, 63: 86-99.PubMedGoogle Scholar
- Li R, Fan W, Tian G, Zhu H, He L, Cai J, Huang Q, Cai Q, Li B, Bai Y: The sequence and de novo assembly of the giant panda genome. Nature. 2010, 463: 311-317. 10.1038/nature08696.PubMed CentralPubMedView ArticleGoogle Scholar
- Iorizzo M, Senalik DA, Grzebelus D, Bowman M, Cavagnaro PF, Matvienko M, Ashrafi H, Van Deynze A, Simon PW: De novo assembly and characterization of the carrot transcriptome reveals novel genes, new markers, and genetic diversity. BMC Genomics. 2011, 12 (1): 389-10.1186/1471-2164-12-389.PubMed CentralPubMedView ArticleGoogle Scholar
- Li D, Deng Z, Qin B, Liu X, Men Z: De novo assembly and characterization of bark transcriptome using Illumina sequencing and development of EST-SSR markers in rubber tree (Hevea brasiliensis Muell. Arg.). BMC Genomics. 2012, 13: 192-10.1186/1471-2164-13-192.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhang J, Liang S, Duan J, Wang J, Chen S, Cheng Z, Zhang Q, Liang X, Li Y: De novo assembly and characterisation of the transcriptome during seed development, and generation of genic-SSR markers in Peanut (L.). BMC Genomics. 2012, 13: 90-10.1186/1471-2164-13-90.PubMed CentralPubMedView ArticleGoogle Scholar
- Lulin H, Xiao Y, Pei S, Wen T, Shangqin H: The first Illumina based de novo transcriptome sequencing and analysis of Safflower flowers. PLoS One. 2012, 7: e38653-10.1371/journal.pone.0038653.PubMed CentralPubMedView ArticleGoogle Scholar
- Xie F, Burklew CE, Yang Y, Liu M, Xiao P, Zhang B, Qiu D: De novo sequencing and a comprehensive analysis of purple sweet potato (Impomoea batatas L.) transcriptome. Planta. 2012, 236: 101-113. 10.1007/s00425-012-1591-4.PubMedView ArticleGoogle Scholar
- Wang B, Guo G, Wang C, Lin Y, Wang X, Zhao M, Guo Y, He M, Zhang Y, Pan L: Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing. Nucleic Acids Res. 2010, 38 (15): 5075-5087. 10.1093/nar/gkq256.PubMed CentralPubMedView ArticleGoogle Scholar
- Wong MM, Cannon CH, Wickneswari R: Identification of lignin genes and regulatory sequences involved in secondary cell wall formation in Acacia auriculiformis and Acacia mangium via de novo transcriptome sequencing. BMC Genomics. 2011, 12: 342-10.1186/1471-2164-12-342.PubMed CentralPubMedView ArticleGoogle Scholar
- Mahato SB, Nandy AK, Roy G: Triterpenoids. Phytochemistry. 1992, 31: 2199-2249. 10.1016/0031-9422(92)83257-Y.PubMedView ArticleGoogle Scholar
- Kumar S, Kalra S, Kumar S, Kaur J, Singh K: Differentially expressed transcripts from leaf and root tissue of Chlorophytum borivilianum: A plant with high medicinal value. Gene. 2012, 511: 79-87. 10.1016/j.gene.2012.09.046.PubMedView ArticleGoogle Scholar
- Namdeo AG: Plant cell elicitation for production of secondary metabolites: a review. Pharmacognosy Rev. 2007, 1: 69-79.Google Scholar
- Suzuki H, Reddy MSS, Naoumkina MA, Aziz N, May GD, Huhman DV, Sumner LW, Blount JW, Mendes P, Dixon RA: Methyl jasmonate and yeast elicitor induce differential transcriptional and metabolic re-programming in cell suspension cultures of the model legume Medicago truncatula. Planta. 2005, 220: 696-707. 10.1007/s00425-004-1387-2.PubMedView ArticleGoogle Scholar
- Mert Turk F: Saponins versus plant fungal pathogens. J Cell Mol Biol. 2006, 5: 13-17.Google Scholar
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