Evidence-Based Complementary and Alternative Medicine

Evidence-Based Complementary and Alternative Medicine / 2017 / Article

Review Article | Open Access

Volume 2017 |Article ID 7521363 | 9 pages | https://doi.org/10.1155/2017/7521363

Researches on Transcriptome Sequencing in the Study of Traditional Chinese Medicine

Academic Editor: Juntra Karbwang
Received04 Dec 2016
Revised21 Apr 2017
Accepted16 May 2017
Published16 Aug 2017

Abstract

Due to its incomparable advantages, the application of transcriptome sequencing in the study of traditional Chinese medicine attracts more and more attention of researchers, which greatly promote the development of traditional Chinese medicine. In this paper, the applications of transcriptome sequencing in traditional Chinese medicine were summarized by reviewing recent related papers.

1. Introduction

As an important part of human brilliant culture, Chinese medicine has made an important contribution to the survival and reproduction of mankind. In the modern disease prevention and health care model, the traditional Chinese medicine has great superiority for a thousand years of accumulation of precipitation. In recent years, the transcriptome studies developed rapidly. In animal studies, there are a lot of reports on the discovery of key genes, SNP, gene splicing, and complex disease research [1, 2]. The plant transcription study also showed great application potential. For example, Wang et al. (2010) using Solexa sequencing technology constructed the transcriptome and the expression profiling of fuzzless-lintless mutant and screened the key genes involved in control of cotton fiber development [3]. Zhou et al. (2011) obtained 7,155 sequences from the cauliflower and screened out 1,600 genes related to HYPOCOTYL5 (HY5) under the light [4]. He et al. (2012) got 1,244,501 transcripts from the reeds and selected 251 genes related to the plant allelopathy, development, and invasion, providing valuable information for stress regulation mechanism and the nonmodel plant development [5]. In addition, large scale studies on the medicinal plants have also been carried out [6, 7].

The transcriptome sequencing technology has experienced three generations change. At present, the second-generation sequencing technology still dominates; the third-generation sequencing technology shows a strong momentum of development. The characteristics comparison of three-generation sequencing technology is shown in Table 1. Now, the deep sequencing technology is able to identify all the transcripts, even lacking detailed genetic information or with no reference genome [8]. As a whole research on gene expression, transcriptome studies changed the single gene study pattern and brought gene expression regulation and genome research into a rapid development era [9]. This paper reviewed the main applications of transcriptome sequencing in the study of traditional Chinese medicine, which provided references for the further study and development of Chinese medicine.


Sequencing techniqueSequencing platformsCompanyMethods and enzymeSequencing length Output/cycleTime/cycleMain error

The first-generation sequencingSanger/ABI3730 DNA
Analyzer
Applied BiosystemsSanger sequencing/DNA polymerase600–1,000 bp56–96 Kb0.5–3 h

The second-generation sequencing454/GS FLX Titanium
Series
RochePyrosequencing/DNA polymerase400–700 bp400–700 Mb10–23 hInsertion/deletion
Solexa/Illumina Genome Analyzer/HiSeq 2000/HiSeq 2500/HiSeq 4000/HiSeq X10/NovoSeqIlluminaSequencing by synthesis (SBS)/DNA polymerase bp (high output)/ bp (rapid run)900 Gb–1 Tb (paired)/150–180 Gb (paired)6 d/40 hReplacement
SOLiD/SOLiD 3 systemApplied BiosystemsSequencing by ligation (SBL)/DNA ligase bp90–100 Gb6-7 dReplacement

The third-generation sequencingHeliscope/Helicos Genetic Analysis SystemHelicosSBS/DNA polymerase30–55 bp21–35 Gb8 dReplacement
Pacbio RS II/Pacbio SequelPacific BiosciencesSBS/DNA polymerase1.0– bp350 Gb-1 Tb0.5–4 h
Nanopore single moleculeOxford NanoporeSequencing by electrical signal/exonuclease2– bp20 Mb–200 Mb50 h

2. The Application of Transcriptome in Chinese Medicine

2.1. Construction of Gene Library (cDNA) and Transcription Database

Due to lack of genomic data, gene sequence information, and genetic background, the medical plants need a large amount of genetic information in order to analyze the gene function in the whole level. At present, the whole genome sequencing of most medicinal plants cannot be detected, so it is a quick way to compare the gene sequences, discover new genes, and identify the expressed genes by constructing the genomic library (cDNA) or the transcription database.

Large scale transcriptome studies have been carried out both in China and abroad on the medicinal plants such as American ginseng [7, 10, 11], liquorice [12], and Salvia miltiorrhiza [6]. Wildung and Croteau (1996) identified one key enzyme gene in the biosynthesis of taxol by using a homology probe to screen the cDNA library of Pacific ginseng combined with GC-MS method [13]. Ginseng (Panax ginseng C. A. Mey.) transcriptome (root, stem, leaf, and flower were sequenced, respectively) obtained 178,145 unique genes where 105,522 genes were discovered for the first time, and 65.6% of the newly independent genes were found in the stems, leaves, and flowers library [14]. Astragalus (Astragalus membranaceus (Fisch.) Bunge) transcriptome (root, stem, and leaf equivalent amount of RNA mixed sample) was successfully annotated with 9,732 Unigenes after de novo sequencing, and 2,877 of them were classified into 45 metabolic pathways by KEGG [15].

Up to March 2017, more than 50 species of traditional Chinese herbal medicine have been sequenced. Especially since 2014, the transcriptome study of traditional Chinese medicine developed rapidly. We have carried on the statistics to the common traditional Chinese medicine; specific sequence statistics are shown in Table 2.


Traditional Chinese medicine nameSequencing timeSequencing countrySequencing platforms

Artemisia annua [26]2009ChinaGS FLX™ System
Epimedium sagittatum [27]2010ChinaGS FLX System
Glycyrrhiza uralensis [12]2010ChinaGS FLX System
Panax quinquefolius [11]2010ChinaGS FLX Titanium System
Salvia miltiorrhiza [6]2010ChinaGS FLX Titanium System
Cervus nippon [28]2011ChinaIllumina HiSeq™ 2000
C. nippon [29]2011ChinaIllumina HiSeq 2000
Panax ginseng [30]2011ChinaGS FLX Titanium System
Siraitia grosvenorii [31]2011ChinaIllumina GA II platform
Lonicera japonica [32]2012ChinaIllumina GA II platform
Carthamus tinctorius L [17]2012ChinaIllumina HiSeq 2000
Picrorhiza kurroa [33]2012IndiaIllumina HiSeq 2000
Lilium regale [34]2012NetherlandsGS FLX Titanium System
Polygonum cuspidatum [35]2012ChinaIllumina HiSeq 2000
Eucommia ulmoides [36]2012ChinaIllumina HiSeq 2000
Cemw elaphus [37]2012ChinaIllumina HiSeq 2000
Nelumbo nucifera Gaertn. [38]2013USAIllumina HiSeq 2000
L. japonica [39]2013ChinaGS FLX System
Aquilaria sinensis [40]2013ChinaIllumina HiSeq 2000
Amomum villosum Lour. [41]2014ChinaIllumina HiSeq 2000
Fallopia multiflora [42]2014ChinaIllumina HiSeq 2000
Conyza blinii H.Lév. [43]2015ChinaIllumina HiSeq 2500
Glycyrrhiza uralensis Fisch. [44]2015ChinaIllumina HiSeq 2500
Gynostemma pentaphyllum (Thunb.) Makin [45]2015ChinaIllumina HiSeq 2000
Erigeron breviscapus. [46]2015ChinaIllumina HiSeq 2000
Polygala tenuifolia [47]2015ChinaIllumina HiSeq 2000
Xanthium strumarium L. [48]2015ChinaIllumina HiSeq platform
Lonicera macranthoides Hand.-Mazz. [49]2015ChinaIllumina HiSeq 2000
Lepidium apetalum Willd. [16]2016ChinaIllumina HiSeq 2000
Andrographis paniculata [50]2016IndiaIllumina HiSeq 2000
Platycodon grandiflorus [21]2016JapanIllumina HiSeq platform
Achyranthes bidentata Bl. [51]2016ChinaIllumina HiSeq 2500
Forsythia koreana [52]2016JapanIllumina HiSeq 1500
Picrorhiza kurroa [23]2016IndiaIllumina HiSeq platform
Ephedra sinica [53]2016JapanIllumina Genome Analyzer IIx
Pinellia ternata [54]2016ChinaIllumina HiSeq 2000
Swertia japonica [55]2016JapanIllumina HiSeq platform
Anemone flaccida [56]2016ChinaIllumina HiSeq 2000
Atractylodes lancea [57]2016ChinaIllumina HiSeq platform
Plantago ovata [58]2016IndiaIllumina Genome Analyzer II
Eleutherococcus senticosus Maxim. [59]2016ChinaIllumina HiSeq platform
Corydalis (C.) [60]2016ChinaIllumina HiSeq 2000
Dendrobium nobile Lindl. [19]2017ChinaIllumina HiSeq 4000
Dendrobium officinale [20]2017ChinaIllumina HiSeq 2500
Dracocephalum tanguticum [61]2017ChinaIllumina HiSeq 4000
Swertia mussotii [22]2017ChinaIllumina HiSeq 2000
Elettaria cardamomum (L.) Maton. [62]2017IndiaIon Proton sequencer
Physalis alkekengi [63]2017JapanIllumina HiSeq 2000
Physalis peruviana [63]2017JapanIllumina HiSeq 2000
Taxillusi chinensis (DC.) Danser [64]2017ChinaIllumina HiSeq 2000
Cassia angustifolia Vahl. [65]2017IndiaIllumina MiSeq platform

2.2. Identification of the Enzymes Coding Genes Involved in Biosynthetic Pathway of Secondary Metabolites

Secondary metabolites are usually effective constituents or regulatory substances in Chinese medicine. The secondary metabolites include glycosides, alkaloids, saponins, flavonoids, steroids, organic acids, and many key enzymes in metabolic process. The mechanism of “multicomponent and multitarget” has made the secondary metabolites and its regulation mechanism become one of the important contents in the modern Chinese medicine research. Secondary, not only do metabolites play an important role in plants adapting to the special ecological environment and resistance to biotic or abiotic stresses (especially some enzymes), but many secondary metabolites with special biological activity are important active components of medicinal plants. The description of transcriptome can provide new information about biology and biochemistry, which can be used to find synthesis genes and its expression pattern of secondary metabolites and finally to determine its biosynthetic pathway. Because most of transcriptome studies in medicinal plants focus on the biosynthesis of active compounds and the research about this part is so much, this part is summarized as chemical composition.

Study on flavonoids related genes and enzymes: Lepidium seed is commonly used in traditional Chinese medicine where a variety of medicinal components have been extracted, but the synthesis genetic basis of these substances is still not clear. Lepidium seed transcriptome sequencing found 534 genes involved in the synthesis and metabolism of secondary metabolites. The genes in the biosynthetic pathway of mustard glycosides, flavonoids, and glycosides compounds were, respectively, 4, 19, and 69 Unigenes and 92 Unigenes in the phenylalanine metabolic pathway [16]. Huang et al. (2012) used KEGG to predict the biosynthetic pathways of flavonoids and unsaturated fatty acids in safflower (Carthamus tinctorius L.) and showed that the genes related to the pathway were conserved [17]. Wang et al. (2017) studied C-glycosyltransferases (CGTs) effect to the synthesis of isoflavonoids and revealed that PlUGT43, a novel glucosyltransferase, possesses an activity for the C-glycosylation of daidzein to puerarin [18].

Study on alkaloids related genes and enzymes: Dendrobium officinale L. is an important traditional herb with high commercial value and excellent medicinal effect in China. Li et al. (2017) analyzed the genes involved in dendrobine biosynthesis in Dendrobium nobile Lindl., and they found 30 Unigenes encoding proteins were possibly related to the biosynthesis of dendrobine sesquiterpene backbone; MF23 might stimulate dendrobine biosynthesis by regulating the expressions of genes involved in the mevalonate (MVA) pathway and postmodification enzymes might play a major role in dendrobine biosynthesis [19]. Shen et al. (2017) also identified the genes associated with the synthesis of bioactive constituents in Dendrobium officinale, which got Unigenes related to the enzymes involved in fructose and mannose metabolism and Unigenes associated with putative upstream elements of the alkaloid biosynthetic pathway [20]. Iron Dendrobium transcription sequencing data found that 25 enzyme genes were involved in alkaloid synthesis [14].

Study on terpenes and glycosides related genes and enzymes: the roots of Platycodon grandiflorus are widely used as a crude drug. The active components include a variety of triterpenoid saponins. Tamura et al. (2017) varied cytochrome P450 monooxygenases (P450s) function in triterpenoid saponin biosynthesis of Platycodon grandiflorus by the analysis of three different tissues (roots, leaves, and petals) using RNA sequencing (RNA-Seq) technology [21]. Ma et al. (2016) and Liu et al. (2017) analyzed the transcriptome of Swertia mussotii and screened 39 candidate transcripts involved in secoiridoid biosynthesis [22]. Transcriptional regulation of picrosides biosynthesis in Picrorhiza kurroa is completely unknown until Vashisht et al. (2016) investigated complete spectrum of different transcription factors and discerned their association with picrosides biosynthesis [23]. Wu et al. (2010) obtained the specific gene expression profiles and found 24 genes that might be involved in ginsenoside biosynthesis by analyzing the American ginseng transcription of 3 different tissues. And a number of transcription factors genes involved in the regulation of growth and response to environmental stress were obtained by sequence comparison and functional annotation [11]. Wu et al. (2012) obtained 23,532 transcripts from the foxglove, screened 140 key genes involved in the biosynthesis of cardiac glycosides, and identified 29 new miRNAs [24]. In addition, Camptotheca acuminata transcriptome acquired 20 genes involved in the synthesis of camptothecin skeleton, including 13 new genes [25].

Study on organic acids related genes and enzymes: Li et al. (2017) by analyzing 18 libraries from six organs, namely, roots, stems, leaves, sepals, flowers, and seeds of D. Tanguticum, found 22 predicted biosynthetic genes related to RA and two of these genes were identified as candidates by evaluating the correlation coefficient between the RA contents and the expression of the predicted biosynthetic genes in the six organs [61]. Li et al. (2010) by using high throughput sequencing technology and bioinformatics analysis obtained more than 27,000 Unigenes and 16 enzymes genes in the biosynthetic pathway of the glycyrrhizic acid [12]. Honeysuckle flower and leaf EST library found that almost all enzymes participate in the chlorogenic acid and luteolin biosynthetic and established the chlorogenic acid and luteolin biosynthetic pathway. The synthesis of Ganoderma triterpenoids is regulated by 11 upstream pathway key enzymes and 214 candidate cytochrome oxidase genes of downstream biosynthetic pathway [66]. Lonicera japonica is one of the most important medicinal plants. Chlorogenic acid, luteolin, other flavonoids, and secoiridoids are the most important effective ingredients. Rai et al. (2016) studied the potential candidate genes involved in chlorogenic acid, luteolosides, and secoiridoid biosynthesis pathways of nine tissues of Lonicera japonica and the results showed that different tissues of L. japonica are enriched with sets of Unigenes associated with specific pharmaceutically important metabolic pathways and possess unique medicinal properties [67]. Also, the candidate genes involved in the biosynthesis of benzoic acid and ephedrine in Pinellia ternata had been studied and identified by de novo sequencing and transcriptome analysis [54].

2.3. Cultivation and Breeding of Chinese Medicinal Herbs

Over a long period time, the cultivation of Chinese medicinal herbs is still along the traditional extensive management mode with low planting management: the seeds and seedlings are reproduction or retention by farmers themselves, so the phenomenon of gene isolation, degeneration, and poor disease resistance is very serious; due to the long time extensive planting, the phenomenon is more serious especially in some local varieties; these problems are often covered in the appearance that “Chinese medicinal herbs are difficult to grow” and not recognized. Therefore, using the modern transcriptional technology to study the metabolism pathway and regulation mechanism in the stage of seed germination is helpful for genetic breeding and making the key influencing factors clear in breeding traditional Chinese medicine. Ephedra as one traditional Chinese herbal medicine has a history of more than four thousand years. However, the problems of low germination rate, long breeding period, and low seedling survival rate always existed. Deng et al. (2015) studied the seed transcriptome of Ephedra przewalskii Stapf and found that a total of 16,748 coding genes were involved in 125 metabolic process during seed germination, where metabolic pathways (metabolic pathways) were involved in 3,768 genes, accounting for 22.5% of all encoding genes; then the biosynthesis of the secondary metabolites was involved in 1,888 encoding genes, accounting for 11.27% of all encoding genes; the plant hormone signal transduction accounted for 4.54% (761 encoding genes) [68]. In Andrographis paniculata as a large Chinese herbal medicine, there exist some limitations or barriers for crossability within AP accessions, and the problem is solved by using a combination of crossbreeding and genomic data method [69]. Wei et al. (2017) for the first time profiled transcriptome globally in Loranthus seeds and studied the genes regulations of Loranthus seeds in response to water loss, which make a new understanding of drought tolerance and germination of seeds [64]. The data above laid the foundation for further seedling research.

2.4. The Pharmacodynamic Mechanism of Traditional Chinese Medicine

In a large number of Chinese herbal medicines, different parts of the same plant can be classified as different Chinese herbal medicines or pieces, and their pharmacological effects are different. The basis of different parts with different efficacy should be caused by difference chemical composition. And the essence is the difference of gene regulatory network of plant metabolism. Therefore, it is of great significance to research the transcriptome and to reveal the different pharmacological mechanisms for the modernization of traditional Chinese medicine. Lotus plumule and lotus leaf are from the same plant, but the efficacies are significantly different. Lotus plumule is cold in property and can soothe nerves and clear away heart fire; lotus leaf is flat in property and can clear away summer-heat and eliminate dampness. Pharmacological aspects also showed that the lotus plumule can be anticardiac arrhythmia, and lotus leaf has obvious pharmacological activities in weight loss and blood fat. Shan studied the basic reason of different pharmacological effects between lotus plumule and lotus leaf. The study found that the different effects were caused by differences in the chemical composition. The bisbenzylisoquinoline and aporphine alkaloids were the major differences in the composition of the two parts. The different expression pattern of NnCYP80A and NnCYP80 in lotus was suggested to be an important factor that leads to the differentiation of components and finally affected the efficacy [70]. This study provided effective evidences for the elaboration of different pharmacological mechanisms of traditional Chinese medicine, as well as a breakthrough in the study of the mechanism of traditional Chinese medicine.

2.5. The Syndrome Differentiation and Treatment of Chinese Medicine

Syndrome differentiation and treatment as the main method of clinical diagnosis and treatment of traditional Chinese medicine is the essence of traditional Chinese medicine. Because determining the TCM symptoms often lacks an objective standard in a deep level, it is difficult to achieve the objective quantitatively in real sense. Both traditional Chinese medicine and the transcription group focus on integrity, so the introduction of transcriptional group is conducive to the comprehensive treatment of TCM diagnosis and treatment. The transcriptome of kidney deficiency syndrome based on the 3 kinds of diseases (impotence, chronic nephritis, and diabetic nephropathy) was analyzed, it was found that there were 332 different expressed genes, and the common signaling pathways associated with kidney yang deficiency syndrome were 37 [71]. Comparing the leukocyte gene expression difference of liver kidney yin deficiency, blood stagnation, and spleen deficiency syndrome through the analysis of chronic hepatitis B caused by liver and kidney yin deficiency syndrome and liver-stagnation and spleen deficiency syndrome by gene chip technology, Guan and Su found that these two syndromes have significant differences between gene expressions. The study of these differences provides a theoretical basis for the view of “the same syndrome for different disease” in traditional Chinese medicine [72].

In TCM syndrome differentiation and treatment system, syndrome differentiation is very important, but to understand Chinese patent medicine mechanism of action is more important. Huang et al. by gene chip combined with RT-PCR method discovered that Jinlong capsule plays anti-brain-tumor effect maybe through upregulating VNN1 [73]. In the study of tumor metastasis related gene expression resulting from Xiaoliu Baofei Pill, Duan et al. found that more than 30 genes were upregulated more than 1.5 times, suggesting that the regulation of traditional Chinese medicine on lung cancer metastasis is multilevel and multitarget [74]. Xie et al. studied the effect of Bu-Shen-Yi-Gan-Huo-Xue decoction on gene expression of mouse bone marrow stromal cells into cartilage differentiation and found that the two important related genes Eefmp1 and Mmp3 had significant differences in expression of cartilage metabolism, indicating that the mechanism of Bu-Shen-Yi-Gan-Huo-Xue decoction in the treatment of osteoarthritis may be related to the pathway mediated by EFEMP1 and MMP3 [75].

2.6. Other Researches

The transcriptome research combined with biochemical experimental data can clarify the mechanism of the active components and better explain the profound connotation of the theory of traditional Chinese medicine from the level of gene expression. For example, American ginseng transcriptome studies combined with experiment induced by methyl jasmonate and real-time PCR experiment identified 5 candidate genes involved in the synthesis of ginsenoside [7]. The study of Lonicera Japonica transcriptome combined with GC-MS and HPLC technology established the relationship between gene expression amount and the content of active substances [32]. Graham et al. found 3 QTLs loci by analyzing the genotype data and the phenotypic artemisinin concentration [76].

3. Conclusion

The transcription group can provide the information of gene expression regulation system (noncoding RNA), all functional protein sequence, and protein interaction [77]. The establishment of transcriptome constitutes a large gene expression information platform, which can be used to study the molecular mechanism of gene expression and regulation of almost all the organisms in the phenomenon of life. Because the transcriptome only determines the expression sequence, there are no large numbers of redundant and repetitive sequences in the genome. Therefore, the study of transcription group sequencing is more simple and practical than the genome sequencing, showing the incomparable superiority [38, 78, 79]. In addition, PacBio has a huge advantage without interruption and assembling, so the Iso-seq (the full-length transcriptome) technology, as a new technology, has been widely used in the traditional Chinese medicine [80, 81]. Synthesizing all the above, transcriptome sequencing encompasses a wide variety of applications from simple mRNA profiling to discovery and analysis of the entire transcriptome, including both coding mRNA and noncoding RNA. Furthermore, transcriptome sequencing can be utilized to analyze transcriptome profiles and deliver unbiased information. Subsequently, transcriptome analysis can identify genetic function in cells and tissues and is important for understanding the development of diseases.

Although the research of Chinese medicine transcription has made great progress, at the same time, we should also be aware of some problems. First, the action mechanism of traditional Chinese medicine is multicomponents and multitargets; the pharmacological interaction cross constitutes a complex pharmacology network. Therefore, only studying some chemical composition or certain types of ingredients to elucidate the pharmacology of traditional Chinese medicine is still one-sided. Second, there are many secondary metabolites in traditional Chinese medicine, and the genome is relatively large, which leads to the lack of genome sequencing or complete genome data and brings some difficulties for the data splicing and annotation. Third, the harvest of Chinese traditional medicine pays attention to the right place and right time and one false step in time will make a great difference in efficacy, such as capillary wormwood herb in traditional Chinese medicine, as the saying goes “Herba Artemisia scoparia in March, wormwood in April, cut as firewood in May”; namely, in the 3rd lunar month, the capillary wormwood herb has excellent efficacy, with the effect of clearing heat and removing dampness, benefiting gallbladder jaundice, and being diuretic and detoxifying; in April, capillary wormwood herb lost medicinal value and slowly grew into the white Artemisia; this is the best time to eat; and in May, the medicinal and edible values have been lost, only “cut as firewood.” Transcriptome sequencing is an immediate expression of plants, so it has a strict requirement for sampling time.

The concept of “omics” in the transcriptome is consistent with the idea of “whole” in Chinese medicine. Along with the continuous progress of sequencing technology, new technology and new method of proteomics, metabolomics, and network pharmacology, the modernization of traditional Chinese medicine will be developed rapidly.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Acknowledgments

This work was supported by the Foundation of Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-Year Plan Period of China (2011BAI06B06).

References

  1. L.-X. Xiang, D. He, W.-R. Dong, Y.-W. Zhang, and J.-Z. Shao, “Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish,” BMC Genomics, vol. 11, no. 1, article no. 472, 2010. View at: Publisher Site | Google Scholar
  2. J. R. Prensner, M. K. Iyer, O. A. Balbin et al., “Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression,” Nature Biotechnology, vol. 29, no. 8, pp. 742–749, 2011. View at: Publisher Site | Google Scholar
  3. Q. Q. Wang, F. Liu, X. S. Chen, X. J. Ma, H. Q. Zeng, and Z. M. Yang, “Transcriptome profiling of early developing cotton fiber by deep-sequencing reveals significantly differential expression of genes in a fuzzless/lintless mutant,” Genomics, vol. 96, no. 6, pp. 369–376, 2010. View at: Publisher Site | Google Scholar
  4. X. Zhou, Z. Fei, T. W. Thannhauser, and L. Li, “Transcriptome analysis of ectopic chloroplast development in green curd cauliflower (Brassica oleracea L. var. botrytis),” BMC Plant Biology, vol. 11, article 169, 2011. View at: Publisher Site | Google Scholar
  5. R. He, M.-J. Kim, W. Nelson et al., “Next-generation sequencing-based transcriptomic and proteomic analysis of the common reed, Phragmites australis (Poaceae), reveals genes involved in invasiveness and rhizome specificity,” American Journal of Botany, vol. 99, no. 2, pp. 232–247, 2012. View at: Publisher Site | Google Scholar
  6. Y. Li, C. Sun, H.-M. Luo, X.-W. Li, Y.-Y. Niu, and S.-L. Chen, “Transcriptome characterization for Salvia miltiorrhiza using 454 GS FLX,” Acta Pharmaceutica Sinica, vol. 45, no. 4, pp. 524–529, 2010. View at: Google Scholar
  7. C. Sun, Y. Li, Q. Wu et al., “De novo Sequencing and analysis of the American ginseng root transcriptome using a GS FLX Titanium platform to discover putative genes involved in ginsenoside biosynthesis,” BMC Genomics, vol. 11, article 262, 2010. View at: Publisher Site | Google Scholar
  8. M. G. Grabherr, B. J. Haas, M. Yassour et al., “Full-length transcriptome assembly from RNA-Seq data without a reference genome,” Nature Biotechnology, vol. 29, no. 7, pp. 644–652, 2011. View at: Publisher Site | Google Scholar
  9. H. Chen, S. Yu, K. Li, and P. Yang, “Biomarkers and transcriptome profiling of lung cancer,” Respirology, vol. 17, no. 4, pp. 620–626, 2012. View at: Publisher Site | Google Scholar
  10. Y. Li, H. Luo, X. Li et al., “P-117 analysis of expressed sequence tags from glycyrrhiza uralensis shed a light on genes related to glycyrrhizin biosynthesis,” Planta Medica, vol. 76, no. 05, 2010. View at: Publisher Site | Google Scholar
  11. Q. Wu, J. Song, Y. Sun et al., “Transcript profiles of Panax quinquefolius from flower, leaf and root bring new insights into genes related to ginsenosides biosynthesis and transcriptional regulation,” Physiologia Plantarum, vol. 138, no. 2, pp. 134–149, 2010. View at: Publisher Site | Google Scholar
  12. Y. Li, H.-M. Luo, C. Sun et al., “EST analysis reveals putative genes involved in glycyrrhizin biosynthesis,” BMC Genomics, vol. 11, no. 1, article no. 268, 2010. View at: Publisher Site | Google Scholar
  13. M. R. Wildung and R. Croteau, “A cDNA clone for taxadiene synthase, the diterpene cyclase that catalyzes the committed step of taxol biosynthesis,” Journal of Biological Chemistry, vol. 271, no. 16, pp. 9201–9204, 1996. View at: Publisher Site | Google Scholar
  14. S. Guo, “Mining and identification of genes involved in dendrobivun alkaloid and ginsenoslde biosynthesis based on transcriptome analysis,” Peking Union Medical College, CAMS, 2013. View at: Google Scholar
  15. X. B. Liu, “Screening for regulation elicitor of secondary metabolism pathways and transcriptome studies of Astragalus membranaceus (Fisch.) Bge,” Northeast Forestry University, 2013. View at: Google Scholar
  16. Q. Z. Zhou, X. Hui, P. P. Li et al., “De novo characterization of the seed transcriptome of Lepidium apetalum Willd,” China Biotechnology, vol. 36, no. 1, pp. 38–46, 2016. View at: Google Scholar
  17. L. Huang, X. Yang, P. Sun et al., “The first Illumina-based de novo transcriptome sequencing and analysis of safflower flowers,” PLoS ONE, vol. 7, no. 6, Article ID e38653, 2012. View at: Publisher Site | Google Scholar
  18. X. Wang, C. Li, C. Zhou et al., “Molecular characterization of the C-glucosylation for puerarin biosynthesis in Pueraria lobata,” The Plant Journal, 2017. View at: Google Scholar
  19. Q. Li, G. Ding, B. Li, and S. Guo, “Transcriptome Analysis of genes involved in dendrobine biosynthesis in Dendrobium nobile Lindl. infected with mycorrhizal fungus MF23 (Mycena sp.),” Scientific Reports, vol. 7, no. 1, article 316, 2017. View at: Publisher Site | Google Scholar
  20. C. Shen, H. Guo, H. Chen et al., “Identification and analysis of genes associated with the synthesis of bioactive constituents in Dendrobium officinale using RNA-Seq,” Scientific Reports, vol. 7, no. 1, 2017. View at: Publisher Site | Google Scholar
  21. K. Tamura, Y. Teranishi, and S. Ueda, “Cytochrome P450 monooxygenase CYP716A141 is a unique β-amyrin C-16β oxidase involved in triterpenoid saponin biosynthesis in Platycodon grandiflorus,” Plant & Cell Physiology, 2017. View at: Google Scholar
  22. Y. Liu, Y. Wang, F. Guo et al., “Deep sequencing and transcriptome analyses to identify genes involved in secoiridoid biosynthesis in the Tibetan medicinal plant Swertia mussotii,” Scientific Reports, vol. 7, p. 43108, 2017. View at: Publisher Site | Google Scholar
  23. I. Vashisht, T. Pal, H. Sood, and R. S. Chauhan, “Comparative transcriptome analysis in different tissues of a medicinal herb, Picrorhiza kurroa pinpoints transcription factors regulating picrosides biosynthesis,” Molecular Biology Reports, vol. 43, no. 12, pp. 1395–1409, 2016. View at: Publisher Site | Google Scholar
  24. B. Wu, Y. Li, H. Yan et al., “Comprehensive transcriptome analysis reveals novel genes involved in cardiac glycoside biosynthesis and mlncRNAs associated with secondary metabolism and stress response in Digitalis purpurea,” BMC Genomics, vol. 13, no. 1, article no. 15, 2012. View at: Publisher Site | Google Scholar
  25. Y. Sun, H. Luo, Y. Li et al., “Pyrosequencing of the Camptotheca acuminata transcriptome reveals putative genes involved in camptothecin biosynthesis and transport,” BMC Genomics, vol. 12, article 533, 2011. View at: Publisher Site | Google Scholar
  26. W. Wang, Y. Wang, Q. Zhang, Y. Qi, and D. Guo, “Global characterization of Artemisia annua glandular trichome transcriptome using 454 pyrosequencing,” BMC Genomics, vol. 10, article 465, 2009. View at: Publisher Site | Google Scholar
  27. S. Zeng, G. Xiao, J. Guo et al., “Development of a EST dataset and characterization of EST-SSRs in a traditional Chinese medicinal plant, Epimedium sagittatum (Sieb. Et Zucc.) Maxim,” BMC Genomics, vol. 11, no. 1, article 94, 2010. View at: Publisher Site | Google Scholar
  28. B. Yao, Y. Zhao, Q. Wang et al., “De novo characterization of the antler tip of Chinese Sika deer transcriptome and analysis of gene expression related to rapid growth,” Molecular and Cellular Biochemistry, vol. 364, no. 1-2, pp. 93–100, 2012. View at: Publisher Site | Google Scholar
  29. B. Yao, Y. Zhao, H. Zhang et al., “Sequencing and de novo analysis of the Chinese Sika deer antler-tip transcriptome during the ossification stage using Illumina RNA-Seq technology,” Biotechnology Letters, vol. 34, no. 5, pp. 813–822, 2012. View at: Publisher Site | Google Scholar
  30. S. Chen, H. Luo, Y. Li et al., “454 EST analysis detects genes putatively involved in ginsenoside biosynthesis in Panax ginseng,” Plant Cell Reports, vol. 30, no. 9, pp. 1593–1601, 2011. View at: Publisher Site | Google Scholar
  31. Q. Tang, X. J. Ma, C. M. Mo et al., “An efficient approach to finding Siraitia grosvenorii triterpene biosynthetic genes by RNA-seq and digital gene expression analysis,” BMC Genomics, vol. 12, article 343, 2011. View at: Publisher Site | Google Scholar
  32. Y. Yuan, L. Song, M. Li et al., “Genetic variation and metabolic pathway intricacy govern the active compound content and quality of the Chinese medicinal plant Lonicera japonica thunb,” BMC Genomics, vol. 13, no. 1, article 195, 2012. View at: Publisher Site | Google Scholar
  33. P. Gahlan, H. R. Singh, R. Shankar et al., “De novo sequencing and characterization of Picrorhiza kurrooa transcriptome at two temperatures showed major transcriptome adjustments,” BMC Genomics, vol. 13, no. 1, article 126, 2012. View at: Publisher Site | Google Scholar
  34. A. Shahin, M. van Kaauwen, D. Esselink et al., “Generation and analysis of expressed sequence tags in the extreme large genomes Lilium and Tulipa,” BMC Genomics, vol. 13, no. 1, article no. 640, 2012. View at: Publisher Site | Google Scholar
  35. D. Hao, P. Ma, J. Mu et al., “De novo characterization of the root transcriptome of a traditional Chinese medicinal plant Polygonum cuspidatum,” Science China Life Sciences, vol. 55, no. 5, pp. 452–466, 2012. View at: Publisher Site | Google Scholar
  36. T. Z. Li, Y. H. Du, H. M. Liu, Y. T. N. Wu, L. Wang, and S. J. Ye, “Transcriptome data assembly and gene function annotation of Eucommia fruits and leaves,” Journal of Central South University of Forestry and Technology, vol. 32, no. 11, article 122, 2012. View at: Google Scholar
  37. R. Shi, “Analysis of SNP and DIP from transcriptional expression profiling of cartilage tissue in antler of the red deer (Cervus elaphus),” Northeast Forestry University, 2012. View at: Google Scholar
  38. M.-J. Kim, W. Nelson, C. A. Soderlund, and D. R. Gang, “Next-generation sequencing-based transcriptional profiling of sacred lotus ‘china antique’,” Tropical Plant Biology, vol. 6, no. 2-3, pp. 161–179, 2013. View at: Publisher Site | Google Scholar
  39. L. He, X. Xu, Y. Li et al., “Transcriptome analysis of buds and leaves using 454 pyrosequencing to discover genes associated with the biosynthesis of active ingredients in lonicera japonica thunb,” PLoS ONE, vol. 8, no. 4, Article ID e62922, 2013. View at: Publisher Site | Google Scholar
  40. H. Q. Wu, L. Wang, M. H. Tao, X. X. Gao, L. Bai, and W. M. Zhang, “Transcriptome library construction and sequencing from chemically induced Aquilaria sinensis,” Biotechnology Bulletin, vol. 8, article 63, 2013. View at: Google Scholar
  41. A. M. Yu, “Research on the sugar and terpenoid metabolism during the Amomum villosum Lour, fruit development using RNA-Seq,” Guangzhou University of Chinese Medicine, 2014. View at: Google Scholar
  42. W. Zhao, W. Xia, J. Li, S. Sheng, L. Lei, and S. Zhao, “Transcriptome profiling and digital gene expression analysis of Fallopia multiflora to discover putative genes involved in the biosynthesis of 2,3,5,4'-tetrahydroxy stilbene-2-O-β-d-glucoside,” Gene, vol. 547, no. 1, pp. 126–135, 2014. View at: Publisher Site | Google Scholar
  43. R. Sun, S. Lin, Z. Z. Tang, H. J. Jin, C. L. Li, and H. Chen, “Study on transcriptome characteristic of genuine traditional Chinese medicine Conyzablinii H. Lév Leaves of Sichuan,” Molecular Plant Breeding, vol. 13, no. 12, pp. 2754–2760, 2015. View at: Google Scholar
  44. Y. Liu, P. Zhang, M. Song et al., “Transcriptome analysis and development of SSR molecular markers in Glycyrrhiza uralensis fisch,” PLoS ONE, vol. 10, no. 11, Article ID e0143017, 2015. View at: Publisher Site | Google Scholar
  45. Y.-M. Zhao, T. Zhou, Z.-H. Li, and G.-F. Zhao, “Characterization of global transcriptome using illumina paired-end sequencing and development of EST-SSR markers in two species of Gynostemma (Cucurbitaceae),” Molecules, vol. 20, no. 12, pp. 21214–21231, 2015. View at: Publisher Site | Google Scholar
  46. R.-B. Chen, J.-H. Liu, Y. Xiao et al., “Deep sequencing reveals the effect of MeJA on scutellarin biosynthesis in Erigeron breviscapus,” PLoS ONE, vol. 10, no. 12, 2015. View at: Publisher Site | Google Scholar
  47. H. Tian, X. Xu, F. Zhang et al., “Analysis of Polygala tenuifolia transcriptome and description of secondary metabolite biosynthetic pathways by illumina sequencing,” International Journal of Genomics, vol. 2015, Article ID 782635, 11 pages, 2015. View at: Publisher Site | Google Scholar
  48. R. Fan, Y. Li, C. Li, and Y. Zhang, “Differential microRNA analysis of glandular trichomes and young leaves in Xanthium strumarium L. reveals their putative roles in regulating terpenoid biosynthesis,” PLoS ONE, vol. 10, no. 9, Article ID e0139002, 2015. View at: Publisher Site | Google Scholar
  49. Z. Chen, N. Tang, Y. You, J. Lan, Y. Liu, and Z. Li, “Transcriptome analysis reveals the mechanism underlying the production of a high quantity of chlorogenic acid in young leaves of Lonicera macranthoides Hand.-Mazz,” PLoS ONE, vol. 10, no. 9, Article ID e0137212, 2015. View at: Publisher Site | Google Scholar
  50. N. Cherukupalli, M. Divate, S. R. Mittapelli, V. R. Khareedu, and D. R. Vudem, “De novo assembly of leaf transcriptome in the medicinal plant Andrographis paniculata,” Frontiers in Plant Science, vol. 7, no. 2016, article 1203, 2016. View at: Publisher Site | Google Scholar
  51. J. Li, C. Wang, X. Han et al., “Transcriptome analysis to identify the putative biosynthesis and transport genes associated with the medicinal components of Achyranthes bidentata Bl,” Frontiers in Plant Science, vol. 7, no. 2016, article 1860, 2016. View at: Publisher Site | Google Scholar
  52. A. Shiraishi, J. Murata, E. Matsumoto, S. Matsubara, E. Ono, and H. Satake, “De novo transcriptomes of Forsythia koreana using a novel assembly method: insight into tissue- and species-specific expression of lignan biosynthesis-related gene,” PLoS ONE, vol. 11, no. 10, Article ID e0164805, 2016. View at: Publisher Site | Google Scholar
  53. T. Okada, H. Takahashi, Y. Suzuki et al., “Comparative analysis of transcriptomes in aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing,” Genomics Data, vol. 10, pp. 4–11, 2016. View at: Publisher Site | Google Scholar
  54. G.-H. Zhang, N.-H. Jiang, W.-L. Song, C.-H. Ma, S.-C. Yang, and J.-W. Chen, “De novo sequencing and transcriptome analysis of Pinellia ternata identify the candidate genes involved in the biosynthesis of benzoic acid and ephedrine,” Frontiers in Plant Science, vol. 7, no. 2016, article no. 1209, 2016. View at: Publisher Site | Google Scholar
  55. A. Rai, M. Nakamura, H. Takahashi, H. Suzuki, K. Saito, and M. Yamazaki, “High-throughput sequencing and de novo transcriptome assembly of Swertia japonica to identify genes involved in the biosynthesis of therapeutic metabolites,” Plant Cell Reports, vol. 35, no. 10, pp. 2091–2111, 2016. View at: Publisher Site | Google Scholar
  56. C. Zhan, X. Li, Z. Zhao et al., “Comprehensive analysis of the triterpenoid saponins biosynthetic pathway in Anemone flaccida by transcriptome and proteome profiling,” Frontiers in Plant Science, vol. 7, no. 2016, article 1094, 2016. View at: Publisher Site | Google Scholar
  57. S. Ahmed, C. Zhan, Y. Yang et al., “The transcript profile of a traditional chinese medicine, Atractylodes lancea, revealing its sesquiterpenoid biosynthesis of the major active components,” PLOS ONE, vol. 11, no. 3, Article ID e0151975, 2016. View at: Publisher Site | Google Scholar
  58. S. Kotwal, S. Kaul, P. Sharma et al., “De novo transcriptome analysis of medicinally important Plantago ovata using RNA-seq,” PLoS ONE, vol. 11, no. 3, Article ID e0150273, 2016. View at: Publisher Site | Google Scholar
  59. L. Tao, Y. Zhao, Y. Wu et al., “Transcriptome profiling and digital gene expression by deep sequencing in early somatic embryogenesis of endangered medicinal Eleutherococcus senticosus Maxim,” Gene, vol. 578, no. 1, pp. 17–24, 2016. View at: Publisher Site | Google Scholar
  60. D. Liao, P. Wang, C. Jia et al., “Identification and developmental expression profiling of putative alkaloid biosynthetic genes in Corydalis yanhusuo bulbs,” Scientific Reports, vol. 6, Article ID 19460, 2016. View at: Publisher Site | Google Scholar
  61. H. Li, Y. Fu, H. Sun, Y. Zhang, and X. Lan, “Transcriptomic analyses reveal biosynthetic genes related to rosmarinic acid in Dracocephalum tanguticum,” Scientific Reports, vol. 7, no. 1, 2017. View at: Publisher Site | Google Scholar
  62. F. Nadiya, N. Anjali, J. Thomas, A. Gangaprasad, and K. Sabu, “Transcriptome profiling of Elettaria cardamomum (L.) Maton (small cardamom),” Genomics Data, vol. 11, pp. 102-103, 2017. View at: Publisher Site | Google Scholar
  63. A. Fukushima, M. Nakamura, H. Suzuki et al., “Comparative characterization of the leaf tissue of physalis alkekengi and physalis peruviana using RNA-seq and metabolite profiling,” Frontiers in Plant Science, vol. 7, no. 2016, article no. 1883, 2016. View at: Publisher Site | Google Scholar
  64. S. Wei, X. Ma, L. Pan et al., “Transcriptome analysis of Taxillusi chinensis (DC.) danser seeds in response to water loss,” PLOS ONE, vol. 12, no. 1, Article ID e0169177, 2017. View at: Publisher Site | Google Scholar
  65. R. H. Mehta, M. Ponnuchamy, and J. Kumar, “Exploring drought stress-regulated genes in senna (Cassia angustifolia Vahl.): a transcriptomic approach,” Functional & Integrative Genomics, vol. 17, no. 1, pp. 1–25, 2017. View at: Google Scholar
  66. X. L. Xu, “Excavation and analysis of key enzymes in the biosynthesis of chlorogenic acid and ganoderma triterpene,” Peking Union Medical College, CAMS, 2013. View at: Google Scholar
  67. A. Rai, H. Kamochi, H. Suzuki et al., “De novo transcriptome assembly and characterization of nine tissues of Lonicera japonica to identify potential candidate genes involved in chlorogenic acid, luteolosides, and secoiridoid biosynthesis pathways,” Journal of Natural Medicines, vol. 71, no. 1, 2016. View at: Publisher Site | Google Scholar
  68. N. Deng, S. Q. Shi, E. M. Chang, J. F. Liu, Q. Lan, and Z. P. Jiang, “Transcriptomic analysis of germinated seeds of Ephedra przewalskii,” Journal of Northeast Forestry University, vol. 43, no. 2, pp. 28–32, 2015. View at: Google Scholar
  69. A. Valdiani, D. Talei, S. K. Lattoo et al., “Genoproteomics-assisted improvement of Andrographis paniculata: toward a promising molecular and conventional breeding platform for autogamous plants affecting the pharmaceutical industry,” Critical Reviews in Biotechnology, pp. 1–14, 2016. View at: Publisher Site | Google Scholar
  70. F. Shan, “Molecular mechanism study on efficacy difference of Lotus leaf and lotus plumule,” Cheng Du University of TCM, 2015. View at: Google Scholar
  71. S. L. Yan, H. C. Shen, H. Z. Wang et al., “Research to three kinds of disease kidney yang syndrome 'treating same pattern with different method' at signal transduction pathways,” Journal of Yunnan University of Traditional Chinese Medicine, vol. 35, no. 1, pp. 5–9, 2012. View at: Google Scholar
  72. Y. Guan and S. B. Su, “Analysis of differential gene expression profile in chronic hepatitis B,” Journal of New Chinese Medicine, vol. 9, pp. 58–60, 2014. View at: Google Scholar
  73. H. Huang, X. W. Cui, G. J. Yue et al., “Inhibitory effect of Jinlong capsules on gliomatosis cerebri and mechanisms,” Pharmaceutical Journal of Chinese People’s Liberation Army, vol. 30, no. 3, pp. 188–191, 2014. View at: Google Scholar
  74. Z. Duan, L. Chen, and Y. L. Jiang, “Effect of Xiaoliu Baofei pill on tumor metastasis-associated gene expression based on gene-chip technology,” Chinese Journal of Experimental Traditional Medical Formulae, vol. 20, no. 19, pp. 186–190, 2013. View at: Google Scholar
  75. L. Xie, W. Q. Xu, G. Q. Wang et al., “The impact of related gene expression of the chondrogenic differentiation of rat bone marrow stromal cells by Bu-Shen-Yi-Gan-Huo-Xue decotion,” Chinese Journal of Traditional Medical Traumatology & Orthopedics, vol. 21, no. 5, pp. 4–8, 2013. View at: Google Scholar
  76. L. A. Graham, K. Besser, S. Blumer et al., “The genetic map of Artemisia annua L identifies loci affecting yield of the antimalarial drug artemisinin,” Science, vol. 327, no. 5963, pp. 328–331, 2010. View at: Publisher Site | Google Scholar
  77. V. E. Velculescu, L. Zhang, W. Zhou et al., “Characterization of the yeast transcriptome,” Cell, vol. 88, no. 2, pp. 243–251, 1997. View at: Publisher Site | Google Scholar
  78. Z. Wang, B. Fang, J. Chen et al., “De novo assembly and characterization of root transcriptome using Illumina paired-end sequencing and development of cSSR markers in sweet potato (Ipomoea batatas),” BMC Genomics, vol. 11, no. 1, article 726, 2010. View at: Publisher Site | Google Scholar
  79. Y.-X. Qi, Y.-B. Liu, and W.-H. Rong, “RNA-Seq and its applications: a new technology for transcriptomics,” Hereditas, vol. 33, no. 11, pp. 1191–1202, 2011. View at: Publisher Site | Google Scholar
  80. Z. Xu, H. Luo, A. Ji, X. Zhang, J. Song, and S. Chen, “Global identification of the full-length transcripts and alternative splicing related to phenolic acid biosynthetic genes in Salvia miltiorrhiza,” Frontiers in Plant Science, vol. 7, no. 2016, article 100, 2016. View at: Publisher Site | Google Scholar
  81. J. Chin, P. Peluso, and D. Rank, “SMRT Sequencing Solutions for Large Genomes and Transcriptomes,” Journal of Biomolecular Techniques: JBT, vol. 25, supplement S15, 2014. View at: Google Scholar

Copyright © 2017 Jie Xin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

1487 Views | 573 Downloads | 3 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.