Transcriptional responses for biosynthesis of triterpenoids in exogenous inducers treated Inonotus hispidus using RNA-seq

doi:10.21203/rs.3.rs-1944681/v1

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Transcriptional responses for biosynthesis of triterpenoids in exogenous inducers treated Inonotus hispidus using RNA-seq

https://doi.org/10.21203/rs.3.rs-1944681/v1

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Inonotus hispidus is a traditional medicinal that grows in Northeast China and produces various economically important compounds, including polysaccharide compounds and terpenoids, triterpenoid saponins is the main bioactive component. Our research group has found that the accumulation of triterpenoids are affected by exogenous inducers. The experiment showed that the triterpenoid content of I.hispidus treated with 50µmol/LMethyl jasmonate(MeJA), 3%oleic acid and combination of 100µmol/L MeJA and 2% oleic acid inducers increased by 17.42%, 89.86% and 145.5% respectively. However, how exogenous inducers enhances production of secondary metabolites in I.hispidus is not well understood. In this study, the RNA-seq analysis was used to evaluate the effects of exogenous inducers on the expression of triterpenoid synthesis related genes in I.hispidus in liquid fermentation. This study is the first exploration to profile the transcriptome of I.hispidus after adding exogenous inducers, the generated data and gene will facilitate further molecular studies on the physiology and metabolism in this fungus. By comparative transcriptomic analysis, a series of candidate genes involved in the biosynthetic pathway of triterpenoids are identified, providing new insight into their biosynthesis at transcriptome level.

RNA-Seq

Inonotus hispidus

exogenous inducer

Differential expressed genes

Inonotus hispidus, also known as fusarosa, it belongs to Basidiomycetes, Hymenomycetes, Polyporales, which is a kind of rare medicinal fungus (Xin et al.2019). Every year from June to September, the subbody grows in large numbers, mainly parasitic on Manchurian Ash, elm, poplar, mulberry and so on. Distributed in Beijing, Hebei, Inner Mongolia, northeast China, Xinjiang and other places. Triterpenoids are considered as the main bioactive constituent of I.hispidus. Modern pharmacology researches have proved its extensive effects of pharmacological including anti-tumor, anti-oxidation, anti-inflammation, anti-virus, hypidemia, hypoglycemia and liver protection (Gründemann et al.2016; Renda et al.2021). Although as a traditional Chinese medicine, I.hispidus is playing its own unique medicinal value, the molecular mechanisms underlying accumulation of bioactive triterpenoids are poorly understood. With the vigorous development of health industry, it has become a trend to vigorously develop I.hispidus in the field of edible and medicinal to achieve industrialization development. With the increasing of the demand, it is important to take effective measures to increase the accumulation of triterpenoids in I.hispidus.

Progress has been achieved over the years in enhancing the triterpenoid content either by changing the medium composition, adjusting the fermentation parameters, or adding elicitors (Li et al.2017). Fungal inducers can act as a special chemical signal in liquid fermentation, which can effective selectively induce the expression of specific genes in plant metabolic pathway through the interaction between microorganisms and plants (Bilal et al.2020; Zhong et al.2021). Elicitors can be recognized by receptors located on the surface of plasma membrane or endomembrane. Receptors are activated and then activate their effectors, such as ion channels, GTP binding proteins, protein kinases and oxidative bursts (Kou et al.2022). MeJA has been widely used to stimulate plant stress responses, promote the expression of related genes in plant secondary metabolic pathways, and increase the production of plant secondary metabolites (phytoalexins, alkaloids, flavonoids, phenolic acids and terpenes) plant stress resistance.(Wasternack et al.2007; Peng et al.2017). Research shows that 150µmol/L MeJA was added to the submerged fermentation of Inonotus baumii, the triterpenoid content increased by 4.05 times compared with the control group (Sun et al.2017). Oleic acid is an unsaturated fatty acid existing in animals and plants (Xu et al.2017). Oleic acid has been used as a stimulatory agent to increase the production of triterpenes and promote the growth of mycelia (Lou et al.2021). Zhou .et al (2021) Showed that oleic acid as inducer increased the triterpenoid content of I.hispidus by 143.74%. Notwithstanding, the physiological processes and secondary metabolism of I.hispidus treated with exogenous inducer remains largely unknown.

An increasing number of studies have focused on the transcriptome and genome levels with an understanding of plant secondary metabolic pathways, including Salvia miltiorrhiza (Yang et al.2013), Panax ginseng (Chen et al.2017) and Panax notoginseng (Liu et al.2015), among others. However, Genome-wide expression study of I. hispidus is still a blank space. Therefore, the purpose of this study was to explore the effects of exogenous inducers on triterpenoid contents of I.hispidus, through comparative transcriptome analysis, differentially expressed genes (DEGs) related to triterpenoids accumulation in I.hispidus induced by MeJA, oleic acid and formulation. We further explored the transcriptomic data combined with triterpenoids accumulation and provided more possibilities for biotechnology to improve the medicinal value of I. hispidus.

2.1 Experimental materials and design

The strain of Inonotus hispidus (IH-69) was sourced from the Key Laboratory Forest Food Resources Utilization of Heilongjiang Province. The strain was maintained on potato-agar-dextrose slants and cultured at 28°C for 7 days. According to previous methods culture media containing the following components (g/L) were prepared: fructose (40), Beef paste (2), KH₂PO₄(1), MgSO₄.7H₂O (0.5). Three mycelial pieces with a diameter of 12 mm were intercepted and inoculated in liquid medium. Accurately weigh 50µmoL MeJA with Twean-20 (0.2%) as cosolvent, and prepare the solution with 0.0025mol/L concentration of sterile water at a constant volume of 100ml. Then filter the solution with a 0.2µm filter membrane for sterilization, so that the final concentration of MeJA added to the medium is 50µmol/L. On the sixth day of fermentation, it was added as the first experiment. 3% oleic acid was added on the 0 day of fermentation as the second experiment, 2% oleic acid was added on the 0 day of fermentation, and 100umol/L MeJA was added on the 6 Day of fermentation as the third group. The culture cycle of each group was 10 days. The group without inducer was used as the blank control. The samples were snap-frozen in liquid nitrogen after a quick rinse with sterile water and stored at − 80°C for subsequent analysis. All determinations were carried out in triplicate.

2.2 Measurement of triterpenoid content in I.hispidus

Triterpenoids were extracted and quantified according to previous reports (Chuluunbaatar et al.2019). To extract the triterpenoids of I.hispidus, 100 mg dried mycelia were solubilized with 2 mL of 72% ethanol (v/v), and then placed in an ultrasonic chamber for 30 min at 210 W of ultrasound(40 kHz). Afterwards, the mycelia were removed by centrifugation at 4000×g for 10 min, and the supernatant was dried at 100℃ in a thermostatic water bath. To quantify the amount of triterpenoid, the residues were resuspended in 5% vanillin-acetic acid and perchloric acid, incubated at 70℃ for 15 min and cooled rapidly. Then,4 mL of ethyl acetate was added, and the absorbance at 551 nm was measured with a spectrophotometer. The triterpenoid content was calculated as betulin equivalent from a standard curve using betulin.

2.3 Library Preparation for Transcriptome Sequencing

Total RNA was extracted using an RNA prep pure Plant Kit (Tiangen, China) in accordance with the manufacturer’s instructions. The degradation and impurities of RNA samples were tested using 1% agarose electrophoresis. The libraries were sequenced with an Illumina HiSeq 4000 high throughput sequencing platform (Biomarker Technologies, China) to obtain a large number of reads referred to as raw data. All the clean reads were pooled and assembled using the Trinity de novo assembly program. Before assembly, raw data were filtered to remove reads containing adapter, reads containing ploy-N, and low quality reads to generate high quality clean data.

2.4 Functional Annotation and Metabolic Pathway Analysis

The unigenes sequences were compared with those in the National Center for Biotechnology Information non − redundant database (Nr) by using BLAST software with the E value set to ≤ 10^− 5, the functional annotations of the proteins were obtained (Wang et al.2020). Moreover, the unigenes searched against different databases, including NCBI non redundant protein sequences (Nr), NCBI non-redundant nucleotide sequences (Nt), Protein primogenomic cluster (KOG/COG), Artificial annotated and reviewed protein sequence database (Swiss-Prot), Kyoto Encyclopedia of Genes and Genomes(KEGG), Gene Ontology (GO), and Pfam to classify the function and analyze the biological metabolic pathway of unigenes (Conesa et al.2005).

2.5 Analysis of differential genes

Fragments per kilobase of transcript per million mapped reads (FPKM)is the number of reads per thousand base length of a gene compared in each million reads, it is a common method to estimate gene expression level in transcriptome sequencing data analysis. The FPKM value were used to evaluate the gene expression levels (Zhao et al.2021). Taking the blank sample as a control, differentially expressed genes (DEGs) analysis in pair-wise comparisons was conducted using the DESeq2_EBSeq software, and the input data of the DEGs was based on the read counts (Shilpashree et al.2022). The significant p-value was corrected. The corrected p-value were used as key indicators for DEG screening to obtain independent statistical parameters related to the expression of a large number of genes. In the screening process, the p-value was < 0.05 and the fold change (FC) difference > 1.5 was used as a screening criterion. Furthermore, the DEGs were then analyzed through GO and KEGG pathway enrichment analyses.

2.6 Statistical Analysis

Experimental data are given as the mean ± standard deviation with three replications. Charts were processed using Origin 9.0 software, and significance analyses were performed with SPSS 21.0 software. Different letters in the figures indicate a significant difference (p < 0.05). The differences between the amounts of mycelia are represented by A, B, C, and D, and the differences between the amounts of triterpenoids are represented by a, b, c, and d.

3.1 Effect of inducer on triterpenoid content of I.hispidus

The triterpenoid content in I.hispidus treated with 50 µmol/L MeJA, 3% oleic acid ,formulation(2% oleic acid and100umol/L MeJA)increased significantly compared with that in the CK. Among them, the triterpenoid content in I.hispidus treated with formulation was the highest.

3.2 RNA‑seq and De Novo Assembly of I. hispidus Reference Transcriptome

RNA-seq on I.hispidus with different treatments was performed using the Illumina HiSeq 4000 sequencing platform, which resulted into four samples named CK and MeJA(S₁),Oleic acid(S₂),formulation(S₃) with a total of 12 sequencing libraries. After filtering out the low-quality reads, the results in Table 1 showed that a total of 82,680,165 clean reads in CK、82,271,188 clean reads in the S₁、91,676,834clean reads in the S₂ and 96,148,730 clean reads in S₃ were obtained. A total clean base number of 24.64G (CK) ,24.51G(S₁),27.33G(S₂) and 28.62G(S₃), was obtained respectively. The percentage of Q30 was 92.98% or higher, and the percentage of GC was approximately 52%.

Table 1

Summary of Illumina HiSeq 4000 sequencing data
sample	Clean reads	Clean bases	Q30	GC
CK-1	28,043,969	8.35G	94.15	52.01
CK-2	27,100,025	8.07G	94.32	51.96
CK-3	27,536,171	8.22G	94.21	51.87
S₁-1	30,910,974	9.21G	94.21	51.92
S₁-2	25,327,950	7.55G	94.07	51.78
S₁-3	26,032,264	7.75G	94.31	51.91
S₂-1	34,705,547	10.36G	94.29	51.82
S₂-2	27,883,532	8.30G	94.60	51.87
S₂-3	29,087,755	8.67G	94.14	51.85
S₃-1	32,483,363	9.66G	94.09	51.81
S₃-2	30,986,102	9.22G	92.98	51.94
S₃-3	32,679,265	9.74G	94.17	51.91

I.hispidus clean reads were assembled from 12 libraries using Trinity software to obtain 300,423 transcripts. The average read length and N50 length were 3407.04 and 4385 bp, respectively. (Table 2) By continuing to assemble these transcripts using Trinity, a total of 24306 unigenes were spliced, with an average read length and N50 length of 1096.06 and 2687 bp, respectively. Among them, 9520 (39.17%) were 200–300 bp, 4738 (19.49%) were 300–500 bp, 3067 (12.62%) were 500-1 kb, and 2784 (11.45%) were 1–2 k bp. 4197 (17.27%) are longer than 2 k bps.

Table 2

Summary of splicing transcripts
Length_interval	200–300 bp		300–500 bp		500 bp–1 kbp	1 kb–2 kbp	> 2 k bp	Total
Number of transcripts		10947		7551	12949	56309	212667	300423
Number of unigenes		9520		4738	3067	2784	4197	24306

3.3 Functional annotation and classification

In order to obtain comprehensive gene function information, all the assembled unigenes were successfully annotated using eight public databases. (Nr, Nt, Pfam, KOG, COG, Swiss-prot, KEGG, GO). As shown in Table 3, out of 19429 unigenes. The annotation success rate of unigenes was 6537 in COG (33.65%), 6884 in GO (35.76%), 6640 in KEGG (33.5%), 11968 in KOG (62.17%), 12430 in Pfam (63.98%), 8355 in Swiss-prot (43%), 17914 in eggNOG (92.2%), and 12754 in NR (65.60%). The functions of the predicted unigenes were classified in KOG, GO and KEGG.

Table 3

Function annotation of unigene
Database	Number of unigenes	Percentage
Annotated in COG	6537	33.65%
Annotated in GO	6884	35.76%
Annotated in KEGG	6640	33.5%
Annotated in KOG	11968	62.17%
Annotated in Pfam	12430	63.98%
Annotated in Swiss-prot	8355	43%
Annotated in eggNOG	17914	92.2%
Annotated in NR	12754	65.60%
Total unigenes	19429	100%

The species distribution of the Nr annotation showed that 36.22% (4606) of the unigenes had the highest homology to genes from Sanghuangporus baumii,13.72% (1744) to Fomitporia mediterranea, 2.62% (333) to Basidiobolus meristosporus, and 2.56% (325) to Spizellomyces punctatus. (Fig. 2)

KOG results show a total of 13,272 unigenes divided into 25 categories (Fig. 3a). Among these genes, the cluster “General function prediction only” cluster represented the largest group (R) (1797, 15.02%), followed by Posttranslational modification, protein turnover, chaperones (O) (1670, 13.95%), Translation, ribosomal structure and biogenesis (J) (1080, 9.02%), and Signal transduction mechanisms(T) (1077,9%). In addition, 418 (3.49%) unigenes were associated with secondary metabolites biosynthesis, transport and catabolism, and 105 were associated with defense mechanism unigenes (V).

According to sequence homology, 39274 unigenes were classified into three GO categories: biological process (14511,36.95%), cellular component (16952,43.16%), and molecular function (7811,19.89%) (Fig. 3b). The most popular terms in the biological process category were “metabolic processes (3868)”, “cellular processes (3778)” and “single-organism process (2406)”. In the cellular component category, the most common terms were “cell (3831)”, “cell parts (3811)”. and “organelle (2758)”. In the molecular function category, the main terms were “catalytic activity (3505)” and “binding (3124)”, suggesting that this study may provide clues to understanding genes involved in secondary metabolite synthesis pathways. Transcripts associated with binding GO terms were more common in the molecular functional category.

Comparing Unigenes with standard metabolic pathways in the KEGG database to better understand the biological pathways of I.hispidus leaves(Fig. 3c). The 6640 Unigenes are divided into 4 KEGG categories and 117 sub categories: “metabolism”, “genetic information processing”, “environmental information processing” and “cellular processes”. In the KEGG secondary metabolic pathways, most unigenes were classified into “Biosynthesis of antibiotics” (606 unigenes, ko01130), “Ribosome” (499 unigenes, ko03010), “Carbon metabolism” (364 unigenes, ko01200) and “Biosynthesis of amino acids” (324 unigenes, ko01230).

3.4 Identification and analysis of DEGs

241 up regulated DEGs and 112 down regulated DEGs were identified in the group ‘CK vs S₁’, 635 up regulated DEGs and 443 down regulated DEGs were identified in the group ‘CK vs S₂’, 529 up regulated DEGs and 364 down regulated DEGs were identified in the group ‘CK vs S₃’ (Fig. 4a.b.c). A total of 162 core DEGs (co-upregulated or co-downregulated in all three exogenous inducers treated samples) were obtained in the three comparison groups. Furthermore, overlapping studies found that there were 150, 296 and 126 unique genes in the S₁, S₂ and S₃ (Fig. 4d)

3.5 Enrichment analysis of DEGs

To compare the unigenes from different inducer treated I.hispidus, a Venn diagram was constructed. The results showed that 6777 unigenes were shared by four sample. A total of 54, 61,44 and 43 unigenes were specific to CK, MeJA, Oleic acid, formulation treated I. hispidus, respectively, with the MeJA treated samples having the highest number of unique unigenes. (Fig. 5a)

KEGG pathway analysis of all DEGs was performed to characterize the complex biological behaviors. The enriched pathways are presented in Fig. 5, and reflected the preferential biological functions of samples from different inducer treated samples. In ‘CK vs S₁’, genes involved in “Ribosome”, “DNA replication” and “Cell cycle – yeast” were overexpressed (Fig. 5b). Hierarchical clustering of all DEGs indicated that part unigenes enrichment characteristics were similar between the ‘CK vs S₂’ and ‘CK vs S₃’comparisons, with genes involved in “Ribosome”, “Peroxisome” and “ABC transporters” over-expressed (Fig. 5c.d). The major GO enrichment terms of the 162core DEGs were shown in Fig. 6a, including “translation”, “ribosome” and “structural constituent of ribosome” etc. The KEGG pathway enrichment analysis showed that the most of core DEGs were significantly enriched in Ribosome pathways (Fig. 6b).

3.6 Putative genes involved in triterpenoid biosynthesis

Triterpenoids are widely found in nature (Da et al. 2015). In plants, sesquiterpenoids are typically synthesized via mevalonate(MVA)and 2-methyl-d-erythritol 4-phosphate (MEP) biosynthetic pathways(Biswas et al. 2019). Although the MVA and MEP pathways are located in different intracellular regions, the two pathways are not separated. Additionally, there may be unknown interference between certain devices. It is generally believed that triterpenes and sesquiterpenes are synthesized through the MVA pathway, while monoterpenes and diterpenes are synthesized through the MEP pathway (Li et al.2020). IPP and DMAPP are catalyzed by the sequential conversion of geranyl diphosphate synthase (GPPS), clopyridine diphosphate synthase (FPPS), squalene synthase (SS) and squalene epodase (SE). It is an important intermediate for the oxidation of 2,3 squalene (Hyeonbae et al.2020; Pu et al.2021).

After annotating 117 pathways using the KEGG database, 29,13and 7 unigenes were found to be associated with the Terpenoid backbone biosynthesis(ko00900), Ubiquinone and other terpenoid-quinone biosynthesis(ko00130) and Sesquiterpenoid and triterpenoid biosynthesis(ko00909) pathways respectively. Comparing the NR database, a total of 29 unigenes that may be involved in the triterpene synthesis pathway of I.hispiduswere found (Table.4).

Table 4

Unigenes involved in Biosynthesis of Triterpenoid.
Gene		Gene ID
SS SE AACT HMGR	2 6 4 3	c7497.graph_c0、c14961.graph_c0 c16422.graph_c0、c15729.graph_c0、 c24729.graph_c0、c20215.graph_c0 c61.graph_c0、c19680.graph_c0 c8971.graph_c0、c16837.graph_c0 c7417.graph_c0、c18532.graph_c0 c12846.graph_c0、c17445.graph_c0 c18037.graph_c0、
FPPS	2	c3736.graph_c0、c67.graph_c0
FPS	2	c67.graph_c1、c10924.graph_c0
PMK	2	c13594.graph_c0、c22627.graph_c0
SM	1	c25144.graph_c0
HMGS	5	c10205.graph_c0、c16013.graph_c0
		c26810.graph_c0、c20761.graph_c0
		c27696.graph_c0
DMD	1	c9873.graph_c0
FT	1	c15553.graph_c0

^{SS: squalene synthase ,SE: squalene epoxidase, AACT: Acetyl−CoA acetyltransferase, HMGR: 3−hydroxy−3−methylglutaryl coenzyme A reductase, FPPS: Farnesyl pyrophosphate synthase, FPS: farnesyl−diphosphate synthase, PMK: Phospho mevalonate kinase, SM: squalene monooxygenase ,HMGS: hydroxymethylglutaryl−CoA synthase, DMD༚Diphospho mevalonate decarboxylase, FT༚farnesyl transferase}

3.7 Analysis of CYP450 defense genes

CYP450 play important roles in plant defense through their involvement in phytoalexin biosynthesis, hormone metabolism and the biosynthesis of some other secondary metabolites (Qiu et al.2021; Zhang et al.2020). However, the systematic identification of CYP450 has not been reported in I.hispidus. By searching the annotation results of the transcriptome database of I.hispidus, we found that a total of 90 unigenes were annotated as CYP450, of which 66 CYP450 unigenes were annotated into the ‘defense mechanisms’. We speculate that due to the addition of exogenous inducers, I.hispidus causes defense response and promotes the synthesis of triterpenes. Most CYP450 annotated to the “defense mechanisms” also illustrate this view. After the addition of inducer, 1, 10 and 9 CYP450 genes were up-regulated in S₁, S₂ and S₃ groups, respectively. Therefore, in this study, it can be speculated that the up regulation of CYP450 promotes the synthesis of triterpenoids, which will help to reveal its regulatory mechanism in the terpenoid synthesis pathway of I.hispidus.

In transcriptome sequencing data of I.hispidus, we found 2 SS, 6 se, 2 FPPS and other terpene related genes. Cytochrome P450 plays an important role in the terpene biosynthesis. Monoterpenes, sesquiterpenes, and diterpenes can be substrates of P450(Yu et al.2021). For example, Guo (2016) showed that CYP76AH3 and CYP76AK1 are involved in the tanshinone biosynthesis. In this study, 66 CYP450 genes were found in the defense pathway,among them, 1, 10 and 9 up-regulated genes were in MeJA, oleic acid and formulation groups respectively. Therefore, the accumulation of the triterpenoid content in I.hispidus might be due to exogenous inducer treatment, which activated and improved the CYP450 expression.

3.8 Analysis of defensive Enzymatic defense genes

As a traditional Chinese medicinal fungus, I.hispidus has been studied for its antitumor(Yang et al.2019) ,bacteriostatic(Angelini et al.2019) and other efficacy in the past. Elicitation is one of the most effective ways to increase the activity of plant compounds such as triterpenes (Tan et al.2021). The SOD, CAT and POD are important cytoprotective enzymes that eliminate reactive oxygen species in plants. Its activity may reflect plant adaptation to abiotic stress. (Xu et al.2014; Nguyen et al.2012). Exogenous inducers can affect the secondary metabolism of plants by altering the metabolism of reactive oxygen species (ROS), resulting in an increase in secondary metabolites (Ye et al.2013). Naeem.et al (2021) showed that salicylic acid can induce reactive oxygen species burst, up-regulate artemisinin gene expression, and increase artemisinin production. In transcriptome sequencing data of I.hispidus, 34 genes annotated as POD, 7 genes annotated as CAT and 5 genes annotated as SOD. However, we found that only three POD genes were up-regulated in the ‘CK vs S₁’, others are normal genes. MeJA elicits rapid defense responses changes metabolic processes dramatically toward energy supply (Benevenuto et al.2018). Therefore, under the MeJA treatment of I. hispidus, the increase in the antioxidant enzyme activity was promoted through POD upregulation to regulate the biosynthesis of secondary metabolites, such as triterpenoid. However, how oleic acid stimulates metabolism needs further exploration.

Even though I.hispidus has great economic and pharmacological utility, there have been no transcriptomic databases for this plant constructed to date, and no studies have systematically identified genes involved triterpenoid biosynthesis. Our Illumina HiSeq 4000 sequencing provides the first transcriptome dataset, which, provides novel insights into the mechanism of abiotic stress responses in I.hispidus. This study would be helpful to understand the mechanism of triterpenoid biosynthesis in I,hispidus at the molecular level. Creating a cDNA library from the I.hispidus and performing RNA-seq and DEGs provided a very efficient means for identifying the genes associated with known enzymes involved in the biosynthesis of secondary metabolites and for providing candidate genes that could be associated with currently unknown steps in the pathway. Based on the bioinformatics analysis, all possible enzymes involved in the triterpenoid biosynthetic pathway of I.hispidus were identified. Among the 117 pathways, including 3 pathways related to triterpenoid biosynthesis. These unigenes were matched to the function genes which involved in the metabolic pathway of triterpenoid biosynthesis. Additionally, a total of 66 putative cytochrome P450(CYP450) were selected as the candidates of triterpenoid saponins modifiers. Our study shall greatly help further molecular cloning and functional identification of triterpenoid biosynthesis genes in I.hispidus. Based on assumption, CYP450 with unknown functions are highlighted in our analysis because it is most likely the committed enzymes for those unclear steps in the triterpenoid biosynthesis pathway. Given a very low growth and biomass accumulation of the plant, it is expected that triterpenoid pathway may be engineered in model species such as yeast to product rare triterpenoid saponins from I.hispidus in a large-scale.

Author contributions

DH L designed the experiments; YH H supervised Methodology, Formal analysis, Writing – original draft, Writing – review & editing. DC L carried out Methodology, Software, Formal analysis. CY S revised the manuscript. ZB W supervised Software, Investigation. All authors read and approved the final article.

Funding

This work was supported by the Hundred Million Science and Technology Major Special Project of Heilongjiang Province (2020ZX07B01-3), Harbin Science and Technology Bureau Science and Technology Innovation Talent Research Fund [2017RAQXJ091], the Natural Science Foundation of Heilongjiang Province [C2015062], and the China Scholarship Commission.

Data availability

The raw data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study. Enquiries about data availability should be directed to the authors

Conflict of interest: The authors have not disclosed any competing interests.

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Transcriptional responses for biosynthesis of triterpenoids in exogenous inducers treated Inonotus hispidus using RNA-seq

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Abstract

Figures

1 Introduction

2 Materials And Methods

2.1 Experimental materials and design

2.2 Measurement of triterpenoid content in I.hispidus

2.3 Library Preparation for Transcriptome Sequencing

2.4 Functional Annotation and Metabolic Pathway Analysis

2.5 Analysis of differential genes

2.6 Statistical Analysis

3 Result

3.1 Effect of inducer on triterpenoid content of I.hispidus

3.2 RNA‑seq and De Novo Assembly of I. hispidus Reference Transcriptome

3.3 Functional annotation and classification

3.4 Identification and analysis of DEGs

3.5 Enrichment analysis of DEGs

3.6 Putative genes involved in triterpenoid biosynthesis

3.7 Analysis of CYP450 defense genes

3.8 Analysis of defensive Enzymatic defense genes

4. Conclusion

Declarations

References

Supplementary Files

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