Comparative transcriptomic analysis of rhizomes, stems, and leaves of Polygonatum odoratum (Mill.) Druce reveals candidate genes associated with polysaccharide synthesis

Gene 744 (2020) 144626

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Research paper

Comparative transcriptomic analysis of rhizomes, stems, and leaves of Polygonatum odoratum (Mill.) Druce reveals candidate genes associated with polysaccharide synthesis

T

Shengxiang Zhanga,b, Yuanyuan Shia,b, Luqi Huanga,e, Chenkai Wanga,b, Derui Zhaoa,b, ⁎ ⁎ Kelong Maa,c, Jiawen Wua,b,d, , Daiyin Penga,d, a

Anhui University of Chinese Medicine and Anhui Academy of Chinese Medicine, Hefei 230038, China Key Laboratory of Xin'an Medicine, Ministry of Education, Anhui University of Chinese Medicine, Hefei 230038 Clinical College of Integrated Traditional Chinese and Western Medicine, Anhui University of Chinese Medicine, China d Synergetic Innovation Center of Anhui Authentic Chinese Medicine Quality Improvement, Hefei 230012, China e State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Polygonatum odoratum Transcriptome Polysaccharide synthesis Key enzyme genes Transcription factors

Polygonatum odoratum (Mill.) Druce is a well-known traditional Chinese herb. Polysaccharides are major bioactive components of Polygonatum odoratum, which can improve immunity, and are used to treat rheumatic heart disease, cardiovascular disease, and diabetes. This study identified potential genes and transcription factors (TFs) that regulate polysaccharide synthesis in Polygonatum odoratum (Mill.) Druce using RNA sequencing data from leaf, stem, and rhizome tissues. 76,714 unigenes were annotated in public databases. Analysis of KEGG annotations identified 18 key enzymes responsible for polysaccharide biosynthesis and the most of the upregulated expressed unigenes were enriched in rhizome tissue compared with leaf or stem tissue. 73 TFs involved in polysaccharide synthesis were predicted. In addition, key enzyme genes were verified by quantitative realtime PCR. This study substantially enlarged the public transcriptome datasets of this species, and provided insight into detection of novel genes involved in synthesis of polysaccharides and other secondary metabolites.

1. Introduction Polygonatum odoratum (Mill.) Druce (P. odoratum), a typical representative of the Liliaceae family, is a perennial herbaceous plant that is widely distributed in East Asia and Europe (Zhao et al., 2017). Resources of this herb are diminishing due to uncontrolled harvesting. P. odoratum rhizomes are regarded as the medicinal parts of the plant, and have been used extensively to treat diseases such as hypoimmunity, rheumatic heart disease, cardiovascular diseases, and diabetes (Lin et al., 1994; Deng et al., 2012). P. odoratum has been found to contain several components with bioactive effects, including polysaccharides, steroidal glycosides, dipeptides, flavonoids, amino acids, and trace mineral elements (Haiming et al., 2010; Quan et al., 2015). Polysaccharides are significant bioactive components of P. odoratum that exhibit immunomodulatory, antidiabetic, antiaging, antitumor, and

antioxidant properties (Jiang et al., 2013). Polysaccharides are long-chain polymers consisting of > 20 monosaccharide molecules linked by glycosidic bonds, and can be categorized as homopolysaccharides or heteropolysaccharides (Guo et al., 2011; Shi, 2016). Homopolysaccharides contain repeating units of the same monosaccharide, such as starch and β-glucan, and heteropolysaccharides are comprised of two or more monosaccharides, such as glucomannan and pectin. P. odoratum polysaccharides are heteropolysaccharides comprised of mannose, galactose, glucose, fructose, rhamnose, arabinose, and galacturonic acid (Zhang et al., 2005; Wang et al., 2010). Previous studies have shown that polysaccharides in P. odoratum can be used to treat hyperthyroidism and osteoporosis, and to ameliorate immunological disequilibria, thereby enhancing cell immunity and slowing general loss of cognitive function (Shan et al., 2006; Ying et al., 2007).

Abbreviations: P. odoratum, Polygonatum odoratum (Mill.) Druceis; TF, transcription factor; qRT-PCR, quantitative real-time polymerase chain reaction; DEG, differentially expressed gene; sacA, β-fructofuranosidase; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology; KOG, clusters of euKaryotic Orthologous Groups; NR, NCBI non-redundant protein sequences; NT, NCBI nucleotide sequences ⁎ Corresponding authors at: Anhui University of Chinese Medicine and Anhui Academy of Chinese Medicine, Hefei 230038, China. E-mail addresses: [email protected] (J. Wu), [email protected] (D. Peng). https://doi.org/10.1016/j.gene.2020.144626 Received 18 November 2019; Received in revised form 19 February 2020; Accepted 24 March 2020 Available online 26 March 2020 0378-1119/ © 2020 Published by Elsevier B.V.

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Polysaccharide biosynthesis occurs through three main processes. In the first step of the reaction, sucrose is converted to glucose 6-phosphate and fructose by β-fructofuranosidase, and fructose is converted to fructose 6-phosphate by hexokinase and fructokinase. (Kelker et al., 1970; Kono et al., 2006; Richez et al., 2007). Phosphoglucomutase catalyzes isomerization of glucose 6-phosphate to glucose 1-phosphate, and UDP-glucose and guanosine diphosphate mannose are produced from glucose 1-phosphate and fructose 6- phosphate precursors, respectively (Marchase et al., 1993; Decker et al., 2012). In the second step, several NDP-sugar interconversion enzymes catalyze conversion of either UDP-Glc or GDP-Man to other NDP sugars (Yanbin Yin et al., 2011). Finally, the resultant NDP-sugars are assembled into polysaccharides by various glycosyltransferases (Breton et al., 2006; Gille et al., 2013). To date, there have been no comprehensive reports on the genes involved in polysaccharide metabolism in P. odoratum, and no reports exist on their expression patterns in different tissues. RNA-sequencing can provide comprehensive gene expression information, allowing for understanding of gene regulation and metabolic pathways (Saito and Yonekura-Sakakibara, 2008). Some medicinal plant genomes have been sequenced, including Artemisia argyi (Liu et al., 2018), Dendrobium officinale (Chunmei et al., 2015), Pueraria lobata (Han et al., 2015), Gentiana rigescens (Zhang et al., 2015), and Arisaema heterophyllum Blume (Wang et al., 2018), and novel genes that encode key enzymes involved in specific metabolic pathways have been identified. However, genomic information for P. odoratum has not been reported. In this study, we performed deep de novo transcriptome assembly on different tissues of P. odoratum using RNA sequencing. The numbers of potential genes that participate in polysaccharide pathways were identified using our assembled transcriptome. The transcriptome data from P. odoratum will be an important resource to investigate polysaccharide biosynthesis and other metabolic pathways in plants.

Yield(%) =

Polysaccharide content from extract (g) × 100. Sample powder weight(g)

2.3. Complementary DNA library preparation and sequencing (mRNA-Seq) Extracted tissue RNA was detected using a NanoDrop 2000 (Thermo, CA, USA), and the RNA concentration was determined using an Agilent 2100 BioAnalyzer to confirm the integrity of the RNA. The mRNA from each sample was enriched from total RNA using oligo (dT) beads, and mRNA was fragmented to produce short fragments. First strand cDNA was synthesized using random primers, and second strand cDNA was synthesized using dNTPs, RNase H, and DNA polymerase I. The short cDNA fragments were subjected to end repair and ligated with adapters, and the intact fragments were selected for PCR amplification. Each cDNA library was sequenced using the BGISEQ-500 system, according to the manufacturer’s instructions, at the Beijing Genomics Institute (BGI) (Shenzhen, Guangdong province, China) (Zhu et al., 2018). The quality of the three cDNA libraries was evaluated using an ABI StepOnePlus Real-Time PCR System and an Agilent 2100 Bioanalyzer (Agilent RNA 6000 Nano Kit). 2.4. Transcript assembly and unigene functional annotation After sequencing, the raw data were filtered to remove low quality reads (above 50% of bases with Q-value 20) (Cock et al., 2009). The clean reads were used to assemble transcripts using Trinity (version 2.06), which efficiently formed contigs for reconstructing all-length transcripts across a wide range of expression levels using default parameters (Grabherr et al., 2011). These contigs were then further processed using the TGICL tool to remove redundant Trinity-generated contigs (Pertea et al., 2003). To determine the functions of the unigenes, all unigenes were annotated to five databases using BLAST (version: 2.2.23), including Nt (NCBI nucleotide sequences), Nr (NCBI non-redundant protein sequences), KEGG (Kyoto Encyclopedia of Genes and Genome), KOG (Clusters of euKaryotic Orthologous Groups), and SwissProt (A manually annotated and reviewed protein sequence database). Using nr annotation, GO (Gene Ontology) annotations of the unigenes were obtained using the Blast2GO program (Ana et al., 2005), and InterPro annotations were constructed using InterProScan5 (Jones et al., 2014). Using the KEGG database, we further evaluated complex biological behaviors associated with genes of interest, and determined pathway annotations (Minoru et al., 2004).

2. Materials and methods 2.1. Plant material and RNA extraction Three P. odoratum plants were harvested from the Anhui University of Chinese Medicine herb garden with permission on April 18, 2018 (identified by Professor Qingshan Yang, Anhui University of Chinese Medicine). Fresh plants were washed with sterile distilled water several times and wiped clean with filter paper. The stem, leaf, and rhizome samples were selected from three independent plants. The tissues were placed in 50 mL centrifuge tubes, flash-frozen in liquid nitrogen, and stored at −80 °C until RNA extraction. Extraction of RNA was performed using the RNA Plant Kit (Aidlab Biotech, Beijing, China) according to the manufacturer’s protocol (Wang et al., 2019).

2.5. Analysis of differentially expressed genes (DEGs) After assembly, clean reads were mapped to unigenes using Bowtie2 (version 2.2.5) (Langmead and Salzberg, 2012). The unigenes were divided into two categories: clusters and singletons. Clusters were denoted by CL followed by cluster ID. Singletons were identified using the prefix unigene. The expression levels of each unigene were estimated using RSEM (v1.2.8) (Bo and Dewey, 2011). Each unigene was quantified using FPKM (fragments per kb per million fragments) values. Differentially expressed genes were authenticated using the PossionDis method with the following parameters: |Fold Change| > = 2.0-fold (|log 2 FC| > 1) with a false discovery rate (FDR) < = 0.001 (Audic and Claverie, 1997). Differentially expressed genes were then enriched to GO terms and the KEGG database to determine their functions in various tissues.

2.2. Determination of total polysaccharide content Polysaccharide content in dried P. odoratum samples (rhizomes, stems, and leaves) was determined using the phenol-sulfuric acid method (Kushwaha and Kates, 1981). Dried powders (0.2 g) from each sample (rhizomes, stems, and leaves) were mixed with 100 mL of distilled water, then extracted twice for 1 h at 100 °C in boiling distilled water. Following extraction, the samples were precipitated by addition of 95% ethanol (10 mL). The samples were then centrifuged, and the precipitates were dissolved in distilled water (50 mL) with 4% phenol (1 mL) and sulfuric acid (7 mL). The absorbance of the samples was measured at 490 nm using a UV-spectrophotometer (JASCO company, Japan). Determination of polysaccharide content was performed using three biological and three technical replicates. A standard concentration-absorbance curve was generated using anhydrous glucose (Fig. S1). The yield (%) of total polysaccharides was calculated using the following equation:

2.6. Identification of transcription factors (TF) A transcription factor is a protein that binds to a specific DNA sequence and regulates the rate of transcription of genetic information from DNA to mRNA. To identify TFs of P. odoratum, we tested the open 2

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reading frames (ORFs) of unigenes, then aligned the ORFs to the transcription factor protein domain using hmmsearch (http://hmmer.org). Unigenes were annotated using PlantTFDB (Plant transcription factor database) (Rice et al., 2000). The unigenes that encoded the transcription factors were identified through comparison with Pfam23.0 using the hmmsearch program (Jaina et al., 2013).

Table 1 Summary statistics of annotations for P. odoratum unigenes in seven public databases.

2.7. Quantitative RT-PCR validation of key genes in polysaccharide biosynthesis Quantitative RT-PCR was performed using a real-time Thermal Cycler 5100 PCR System and GoTaq qPCR Master Mix PCR kit (Promega). Special primers were designed for different genes using Primer Premier 5.0 (Table S2). The RNA from the three tissue samples (leaves, stems, and rhizomes) was extracted reverse-transcribed into cDNA using TransScript All-in-One cDNA supermix for qPCR. Polymerase chain reaction conditions were as follows: 95 °C for 2 min, 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. All qRT-PCR analyses were repeated in three biological and three technical replicates. The actin gene (CL2254.Contig1) was used as a reference in P. odoratum. The relative expression levels of the selected genes were determined using the 2(−ΔΔCt) method (Livak and Schmittgen, 2001).

Database

Number Annotated

Percentage (%)

Nr Nt Swissprot KEGG KOG Pfam GO Overall

72,709 56,712 55,223 56,755 58,103 53,845 17,752 76,714

64.66 50.44 49.11 50.47 51.67 47.89 15.79 68.22

(9.67%) unigenes were annotated in five databases (Fig. 1A). The majority of mapped unigenes exhibited the closest homology with Asparagus officinalis (62.71%) in the NR database. The second highest homology was Elaeis guineensis (9.16%). Phoenix dactylifera (5.66%), Ananas comosus (2.13%), and Musa acuminata subsp. malaccensis (2.02%) were other highly homologous species (Fig. 1B). Gene ontology classification showed that 17,752 unigenes (15.79%) were divided into three categories: molecular function, cellular component, and biological processes. A detailed analysis of the biological processes group resulted in subclassification into ‘cellular process’ (5209 genes), ‘biological regulation’ (1765 genes), ‘localization’ (1260 genes), ‘metabolic process’ (1161 genes), and ‘cellular component organization or biogenesis’ (1158 genes). Further characterization of molecular function resulted in subclassification into ‘binding’ (8257 genes) and ‘catalytic activity’ (7963 genes). In the cellular component group, the top three GO terms were ‘cell’ (5313 genes), ‘membrane part’ (5259 genes), and ‘organelle part’ (2301 genes) (Fig. S4). Using KOG analysis, 58,103 unigenes (51.67%) were grouped into 25 functional categories. The top two categories were “general function prediction only” (12,145 genes) and “signal transduction mechanisms” (6994 genes).

2.8. Analysis of the structural characteristics of sacA Seven complete amino acid sequences were selected from 20 unigenes that encode sacA (β-fructofuranosidase). Alignment of 7 sacA amino acid sequences was performed using DNAMAN software. Three dimensional structural models of sacA proteins were simulated using the SWISS-MODEL and were depicted using PyMOL software (Biasini et al., 2014). 3. Results 3.1. Total polysaccharide content in P. odoratum samples

3.4. Overview of expression

Total polysaccharides were extracted from dried P. odoratum rhizomes, stems, and leaves. The results showed that among the three tissues, polysaccharide content was highest in rhizomes (3.11%), and lowest in leaves (1.15%). (Fig. S1).

In each tissue, the expression values of all transcripts (FPKM > 1) were counted, and 41,811, 44,472, and 46,349 unigenes were expressed in leaf, rhizome, and stem tissues, respectively (Fig. 2A). The overall level of gene expression was higher in rhizome tissue than that in leaf or stem tissues (Fig. 2B).

3.2. RNA-seq and de novo transcriptome assembly The numbers of raw reads for P. odoratum in the leaf, stem, and rhizome samples were 120,415,666, 117,871,048, and 120,302,266, respectively. The raw reads were generated using a BGISEQ-500 highthroughput sequencing platform. The Q30 of each sample was > 89.33%, and the GC content of each sample was approximately 43.57%. After thorough quality control and filtering, transcriptomes were generated and 112,443 unigenes were assembled and clustered using Trinity software. The average unigene length was 1240 bp and the N50 was 1937 bp. Of these unigenes, 47.35% (53,237) were longer than 1000 bp, and 66.81% (75,126) were longer than 500 bp (Fig. S2). The quality of the assembled transcripts was assessed using a single copy orthologous database (BUSCO), and 97% of the unigenes were perfectly matched (Fig. S3).

3.5. Characterization of functional genes involved in polysaccharide biosynthesis using KEGG pathway analysis KEGG classification resulted in mapping of 56,755 unigenes (50.47%) to 20 pathways. The most represented KEGG function class was global and overview maps (12,994 genes), followed by carbohydrate metabolism (4829 genes), translation (4537 genes), folding, sorting, and degradation (3572 genes), and transcription (3238 genes) (Fig. S5). The “carbohydrate metabolism” subcategory contained 15 pathways, including starch and sucrose metabolism (ko00500), amino sugar and nucleotide sugar metabolism (ko00520), glycolysis/gluconeogenesis (ko00010), citrate cycle (ko00020), pentose phosphate pathway (ko00030), pentose and glucuronate interconversions (ko00040), fructose and mannose metabolism (ko00051), galactose metabolism (ko00052), ascorbate and aldarate metabolism (ko00053), inositol phosphate metabolism (ko00562), pyruvate metabolism (ko00620), glyoxylate and dicarboxylate metabolism (ko00630), propanoate metabolism (ko00640), butanoate metabolism (ko00650), and c5-branched dibasic acid metabolism (ko00660) (Fig. 3). Among these pathways, we annotated 1108 unigenes involved in starch and sucrose metabolism, and 942 unigenes involved in amino sugar and nucleotide sugar metabolism. Bioinformatics analysis

3.3. Functional annotation of unigenes To predict and classify possible functions of unigenes, 112,443 unigenes were annotated using NR, NT, Swissprot, KEGG, Pfam, KOG, and GO databases. In total, 76,714 (68.22%) unigenes were mapped to least one public database, with the following annotation distribution: 72,709 (NR: 64.66%), 56,712 (NT: 50.44%), 55,223 (Swissprot: 49.11%), 56,755 (KEGG: 50.47%), 17,752 (GO: 15.79%), 58,103 (KOG: 51.67%), and 53,845 (Pfam: 47.89%) (Table 1). A total of 10,877 3

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Fig. 1. Unigene functional annotation. (A) Venn diagram of annotated unigenes from five different databases. (B) Species distribution of annotations in the NR database for P. odoratum.

unique expression in leaf, rhizome, and stem tissues, respectively (Fig. 5A). Among these unigenes, 128, 82, and 79 unigenes in leaf, rhizome, and stem tissues were involved in carbohydrate metabolism, respectively (Fig. S6). Enrichment analysis of DEGs using KEGG pathway analysis resulted in identification of 38,085 unigenes (22,825 up-regulated unigenes and 15,260 down-regulated unigenes) significantly different in rhizome tissue compared to those in leaf tissue. These DEGs included 810 unigenes involved in phenylpropanoid biosynthesis, 566 unigenes involved in starch and sucrose metabolism, 147 unigenes involved in carotenoid biosynthesis, and 133 unigenes involved in flavonoid biosynthesis. Comparison of rhizome tissue and stem tissue resulted in identification of 23,016 DEGs (9701 up-regulated unigenes and 13,315 down-regulated unigenes), including 557 unigenes involved in phenylpropanoid biosynthesis, 380 unigenes involved in starch and sucrose metabolism, 107 unigenes involved in flavonoid biosynthesis, and 100 unigenes involved in carotenoid biosynthesis (Fig. S7). Comparison of rhizome tissue with stem and leaf tissues resulted in identification of 16,655 DEGs, including 7647 co-upregulated unigenes and 7797 co-downregulated unigenes (Fig. 5B). Up-regulated unigenes involved in biosynthesis were examined further. Seven thousand six hundred ten specific up-regulated unigenes were identified in rhizome tissue compared to stem and leaf tissues, with log2 (fold changes) > 1. These unigenes were further subjected to KEGG classification and GO enrichment. Among these up-regulated unigenes, 394 unigenes were involved in carbohydrate metabolism, as determined using KEGG classification, and 42 unigenes were enriched to DNA binding transcription

resulted in identification of 211 unigenes involved in polysaccharide biosynthesis, including beta-fructofuranosidase (sacA), hexokinase (HK), fructokinase (scrK), mannose 6-phosphate isomerase (MPI), phosphomannomutase (PMM), mannose 1-phosphate guanylyltransferase (GMPP), GDP-mannose 4,6-dehydratase (GMDS), GDP-Lfucose synthase (TSTA3), glucose 6-phosphate isomerase (GPI), phosphoglucomutase (pgm), UTP-glucose 1-phosphate uridylyltransferase (UGP2), UDP-glucose 4-epimerase (GALE), UDP-glucose 6-dehydrogenase (UGDH), UDP-apiose/xylose synthase (AXS), UDP-arabinose 4-epimerase (UXE), UDP-glucose 4,6-dehydratase (RHM), and 3,5-epimerase/4-reductase (UER1) (Table 2). In the P. odoratum transcriptome, 7 subclasses of NDP-sugar interconversion enzymes (NSEs) were identified, including RHM (17 unigenes), UER1 (2 unigenes), GMDS (6 unigenes), GALE (34 unigenes), UGDH (12 unigenes), UGE (1 unigenes), and UXE (5 unigenes). Using our transcriptome data that identified key enzymes in carbohydrate metabolism, we outlined potential biosynthetic pathways for polysaccharide formation in P. odoratum (Fig. 4). The unigenes predicted to be key enzymes in this pathway were sacA, HK, scrK, MPI, PMM, GMPP, GMDS, TSTA3, GPI, pgm, UGP2, GALE, UGDH, AXS, UXE, UGE, RHM, and UER1. 3.6. Validation and analysis of differentially expressed genes (DEGs) and specific gene expression in P. odoratum tissues In P. odoratum tissues, 78,288 shared unigenes were identified, of which 3760 were involved in polysaccharide biosynthesis. Based on the FPKM values of all unigenes, 4374, 3343, and 3109 unigenes showed

Fig. 2. Overall expression profiles in P. odoratum leaf, rhizome, and stem tissues. (A) The distributions of expressed unigene number in the three tissues. (B) Boxplot of unigenes expressed among the three tissues. The x-axis represents the three tissues, and the y-axis represents log10 (FPKM + 1) values. 4

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Fig. 3. Pathway classifications for carbohydrate metabolism.

unigenes), C3H (143 unigenes), FAR (135 unigenes), C2H2 (76 unigenes), and Trihelix (69 unigenes) (Fig. 6A). Pathway classifications of all TF families resulted in identification of 73 unigenes involved in carbohydrate metabolism, including MYB (6 unigenes), C2H2 (41 unigenes), Trihelix (7 unigenes), bHLH (4 unigenes), FAR1 (2 unigenes), and GeBD (2 unigenes) (Fig. 6B). Furthermore, 49 unigenes involved in biosynthesis of other secondary metabolites were identified, including MYB (15 unigenes), Trihelix (8 unigenes), C2C2-Dof (5 unigenes), LoB (4 unigenes), C2H2 (3 unigenes), and BES1 (2 unigenes) (Fig. 6C). These unigenes were associated with regulation of polysaccharide biosynthesis pathways (Table S1). As shown in the hierarchical clustering heat map (Fig. S8), the expression levels of 73 transcription factors involved in carbohydrate metabolism were higher in rhizome tissue than those in leaf or stem tissues, including 47 upregulated unigenes in rhizome tissue compared to leaf tissue and 42 up-regulated unigenes in rhizome tissue compared to stem tissue. The expression levels of 49 transcription factors involved in biosynthesis of other secondary metabolites were higher in rhizome tissue compared with those in leaf or stem tissues, of which 37 unigenes were up-regulated in rhizome tissue compared with leaf tissue and 27 unigenes were up-regulated in rhizome tissue compared with stem tissue.

Table 2 Number of unigenes that encoded key enzymes involved in the biosynthesis or metabolism of polysaccharides in P. odoratum. Abbreviation

EC number

Unigene Number

Enzyme Name

sacA HK scrK MPI PMM GMPP

3.2.1.26 2.7.1.1 2.7.1.4 5.3.1.8 5.4.2.8 2.7.7.13

20 18 22 1 6 21

GMDS TSTA3 GPI pgm UGP2

4.2.1.47 1.1.1.271 5.3.1.9 5.4.2.2 2.7.7.9

6 1 21 4 17

GALE UGDH AXS UXE RHM UER1 UGE

5.1.3.2 1.1.1.22 AXS 5.1.3.5 4.2.1.76 5.1.3.-, 1.1.1 5.1.3.6

34 12 4 5 17 2 1

beta-fructofuranosidase hexokinase fructokinase mannose-6-phosphate isomerase phosphomannomutase mannose-1-phosphate guanylyltransferase GDP-mannose 4,6-dehydratase GDP-L-fucose synthase glucose-6-phosphate isomerase phosphoglucomutase UTP-glucose-1-phosphate uridylyltransferase UDP-glucose 4-epimerase UDP-glucose 6-dehydrogenase UDP-apiose/xylose synthase UDP-arabinose 4-epimerase UDP-glucose 4,6-dehydratase 3,5-epimerase/4-reductase UDP-glucuronate 4-epimerase

3.8. Validation of key enzyme genes using qRT-PCR factor activity, as determined using GO enrichment analysis (Fig. 5C,D). Many DEGs were classified under “carbohydrate metabolism”. Of these DEGs, 2367 unigenes were up-regulated in rhizome tissue compared to leaf tissue, and 1821 unigenes were up-regulated in rhizome tissue compared to stem tissue (Table 3). The “Biosynthesis of other secondary metabolites” classification was enriched in DEGs, of which 1031 unigenes were up-regulated in rhizome tissue compared to leaf tissue, and 809 unigenes were up-regulated in rhizome tissue compared to stem tissue (Table 4). In this study, unigenes up-regulated in rhizomes may potentially improve the effectiveness of biosynthetic polysaccharide precursors in P. odoratum, and have the potential to increase polysaccharide yield.

The expression levels of UGE, UGP2, GMPP, and sacA genes were evaluated using qRT-PCR. The relative expression levels of UGE, UGP2, and sacA were higher in rhizome tissue than those in stem or leaf tissues. The relative expression of the GMPP gene was greater in leaf tissue than that in stem or rhizome tissue, which was consistent with our transcription data (Fig. 7). 3.9. The structural characteristics of sacA involved in polysaccharide biosynthesis β-fructofuranosidase (sacA), the first key enzyme in the polysaccharide synthesis pathway, catalyzes conversion of sucrose to glucose 6-phosphate (Glc-6P) and fructose. Alignment of 7 sacA amino acid sequences showed that the sequence identity was not high (59.57%), but the 7 sacA sequences showed similar spatial structures, and each had three well-conserved motifs. A 3D structural model of sacA (CL7969. Contig2) was constructed based on the crystal structure of 6SST/6-SFT from Pachysandra terminalis (PDB ID: 3UGF) using SWISSMODEL and PyMOL software. The spatial structure model contained one β-propeller domain and one β-sheet domain connected by an αhelix. The β-propeller domain had five radially oriented blades (Fig. 8A,

3.7. Analysis of transcription factors involved in biosynthesis of polysaccharides and other secondary metabolites Transcription factors (TFs) are involved in various developmental and physiological functions of plants. From our P. odoratum database, 2865 unigenes were annotated in the PlantTFDB, and assigned to 58 TF families. Among these TF families, the most abundant was the MYB family (343 unigenes), followed by bHLH (223 unigenes), WRKY (188 unigenes), AP2-EREBP (180 unigenes), NAC (149 unigenes), bHLH (150 5

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Fig. 4. Proposed polysaccharide biosynthesis pathways in P. odoratum. Activated monosaccharide units are marked in red. The expression levels of each unigene that encoded the enzymes in each step are shown as heatmaps. The columns L, Rh, and S correspond to leaf, rhizome, and stem samples, respectively. Red and green represent high and low expression levels, respectively. Non-dashed line arrows represent identified enzymatic reactions, and dashed line arrows represent multiple enzymatic reactions through multiple steps. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

et al., 2016), and the average unigene length (1937 bp) was longer than those of Polygonatum sibiricum (900 bp), Pinellia ternata (750 bp) (Zhang et al., 2016), and Platycodon grandiflorum (1102 bp). These results strongly indicated high quality and reliable transcriptome assembly. Analysis of DEGs by KEGG pathway analysis indicated that 38,085 DEGs were mapped to metabolic pathways in rhizome tissue compared to leaf or stem tissues. These DEGs were primarily enriched in “starch and sucrose metabolism”, “plant hormone signal transduction”, and “phenylpropanoid biosynthesis”. Two hundred seventy-six DEGs were up-regulated in starch and sucrose metabolism in rhizome tissue compared to leaf tissue, and 123 DEGs were up-regulated in starch and sucrose metabolism in rhizome tissue compared to stem tissue. These results suggested that P. odoratum rhizomes may be effective as a Chinese medicinal material at the genetic level. Analysis of KEGG annotations identified 18 key enzymes responsible for polysaccharide biosynthesis including sacA, HK, scrK, MPI, PMM, GMPP, GMDS, TSTA3, GPI, pgm, UGP2, GALE, UGDH, AXS, UXE, UGE, RHM and UER1. The unigenes that encode sacA, UGE, and UGP2 were expressed at higher levels in rhizome tissue than in leaf or stem tissues. Furthermore, the higher expression levels of unigenes that encoded (CL6184.Contig2), UGE (Unigene7572), and sacA UGP2 (CL7969.Contig2) in rhizomes were verified by qRT-PCR data, which was consistent with accumulation of total polysaccharide content in P.

blades I–V, colored in orange, cyan, magenta, green, and yellow, respectively), each with one α-helix at the N-terminus and the C-terminus. The β-sheet domain consisted of two six-stranded antiparallel beta-sheets (Fig. 8A, colored in blue), which formed a sandwich-like fold. A well-conserved catalytic triad was located in the deep central pocket of the β -propeller domain (D95, D224 and E282) (Fig. 8C) 4. Discussion Although polysaccharides are the major bioactive components of P. odoratum, and they have significant medicinal value, the molecular mechanisms that contribute to their synthesis are unknown. To further identify the genes that encode key enzymes and TFs that modulate polysaccharide synthesis, we constructed a comprehensive genomic library of P. odoratum leaf, stem, and rhizome tissues. This study was the first to report the transcriptome of P. odoratum, which may serve as a reference for study of other plants with close relationships to P. odoratum. A total of 112,443 unigenes were assembled in our datasets, of which 47.35% (53,237) were longer than 1000 bp, and 66.81% (75,126) were longer than 500 bp. The N50 of all unigenes was 1937 bp. Compared with transcript datasets reported for other medicinal plants, P. odoratum had more unigenes than Polygonatum sibiricum (76,717) (Wang et al., 2017) and Platycodon grandiflorum (34,053) (Ma 6

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Fig. 5. Unigenes expressed in P. odoratum tissues. (A) Venn diagram of unigenes expressed in leaf, stem, and rhizome tissues. (B) Number of DEGs in P. odoratum leaf, stem, and rhizome tissues. A summary up-regulated and down-regulated unigenes between sets of two specified samples. Differentially expressed genes expressed at higher levels in rhizome tissue compared with leaf or stem tissues were defined as “up-regulated,” while those with lower expression levels in rhizome tissue were defined as “down-regulated.” (C) Up-regulated KEGG enrichment pathways in rhizome tissue compared with those in stem and leaf tissues. (D) Gene ontology enrichment of up-regulated genes in rhizome tissue compared to stem and leaf tissues.

motifs. The active site of sacA is located in the deep central pocket of the β-propeller domain. A catalytic triad was identified as D95, D224, and E282 (part of the FMSDPSG motif, FRDP motif, and WECTD motif, respectively) by superposition and comparison with the active site of a plant fructan biosynthesis enzyme from Pachysandra terminalis (Lammens et al., 2012) (Fig. 8B, shown as red spheres). These results indicated that the gene cluster of sacA may play a role in regulating

odoratum, as determined using UV-spectrophotometry. Previous studies have indicated that UGP2, UGE, and sacA are key regulators of polysaccharide biosynthesis, and expression levels of these enzymes may be a rate-limiting factor for accumulation of polysaccharide (Weissborn et al., 1994; Luesink et al., 1999; Mølhøj et al., 2004). The seven sacAs with different amino acid sequences (identity 59.57%) showed similar spatial structures and had well-conserved

Table 3 The numbers of up-regulated genes in rhizome tissue compared with those in the other two tissues in the carbohydrate metabolic pathway. Carbohydrate metabolism pathway

Glycolysis/Glucon Citrate cycle (TCA cycle) eogenesis Pentose phosphate pathway Pentose and glucuronate interconversions Fructose and mannose metabolism Galactose metabolism Ascorbate and aldarate metabolism Starch and sucrose metabolism Amino sugar and nucleotide sugar metabolism Inositol phosphate metabolism Pyruvate metabolism Glyoxylate and dicarboxylate metabolism Propanoate metabolism Butanoate metabolism C5-Branched dibasic acid metabolism

Unigene number

Pathway ID

587 338 360 726 373 555 357 1108 942 419 491 446 191 104 56

ko00010 ko00020 ko00030 ko00040 ko00051 ko00052 ko00053 ko00500 ko00520 ko00562 ko00620 ko00630 ko00640 ko00650 ko00660

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Number of up-regulated genes Rhizome vs Leaf

Rhizome vs Stem

300 181 195 352 179 316 184 529 410 235 243 197 87 57 20

226 100 136 256 143 226 135 433 324 168 182 159 81 44 17

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Table 4 The numbers of up-regulated genes in rhizome tissue compared with those in the other two tissues in the biosynthesis of other secondary metabolism pathway. Biosynthesis of other secondary metabolites pathway

Caffeine metabolism Monobactam biosynthesis Benzoxazinoid biosynthesis Indole alkaloid biosynthesis Phenylpropanoid biosynthesis Flavonoid biosynthesis Anthocyanin biosynthesis Isoflavonoid biosynthesis Flavone and flavonol biosynthesis Stilbenoid, diarylheptanoid and gingerol biosynthesis Isoquinoline alkaloid biosynthesis Tropane, piperidine and pyridine alkaloid biosynthesis Betalain biosynthesis Glucosinolate biosynthesis

Unigene number

Pathway ID

17 62 16 104 1605 192 38 30 26 112 115 103 31 11

ko00232 ko00261 ko00402 ko00901 ko00940 ko00941 ko00942 ko00943 ko00944 ko00945 ko00950 ko00960 ko00965 ko00966

Number of up-regulated genes Rhizome vs Leaf

Rhizome vs Stem

15 27 15 49 759 102 12 6 6 49 65 57 19 5

10 26 8 41 594 78 12 7 4 28 57 45 11 5

Fig. 6. Analysis of transcription factors. (A) Classification of transcription factor families. (B) Classification of transcription factors involved in carbohydrate metabolism. (C) Classification of transcription factors involved in biosynthesis of secondary metabolites.

rhizome tissue compared with leaf tissue, and 42 up-regulated unigenes in rhizome tissue compared with stem tissue. The expression levels of unigenes related to carbohydrate metabolism were higher in rhizomes than those in either leaves or stems. Previous studies showed that overexpression of MYB transcription factors resulted in significantly increased mannan content in Arabidopsis (Kim et al., 2014), and C2H2 zinc finger transcription factors play an important role in plant tolerance to various environmental stresses such as drought, cold, osmotic stress, damage, and mechanical load. (Ling, 2012; Xuan et al., 2012).

polysaccharide biosynthesis in P. odoratum rhizomes. Characterization of these unigenes may contribute to understanding of the molecular mechanisms underlying polysaccharide biosynthesis. In future studies, we will identify the function of sacA and other candidate genes. Analysis of TFs using the PlantTFDB database resulted in prediction of 2865 candidate genes representing 58 TF families, including MYB, C2H2, GeBP, bHLH, WRKY, AP2-EREBP, NAC, bHLH, C3H, FAR, and Trihelix. Seventy-three transcription factors related to carbohydrate metabolism were identified, including 47 up-regulated unigenes in

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Fig. 7. Quantitative RT-PCR analysis of four unigenes that encoded enzymes involved in polysaccharide biosynthesis. Relative expression of CL6184.Contig2 (UGP2), Unigene7572 (UGE), CL7969. Contig2 (sacA), and Unigene7862 (GMPP) was analyzed using the actin gene (CL2254.Contig1) as the internal reference. Technical triplicates were analyzed.

Fig. 8. Structural model and active site of sacA. (A) Structural models of sacA. β-propeller domain (blades I–V, colored in orange, cyan, magenta, green, and yellow, respectively) and one β-sheet domain (colored in blue). (B) The active site of sacA. The catalytic triad (D95, D224 and E282) is depicted as spheres in red. (C) Alignment of seven amino acid sequences of sacAs. Black and red show identical and similar amino acids, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 9

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Three hundred forty-three genes related to the MYB family and 76 genes related to the C2H2 family were examined in our transcriptional data. The results indicated that these genes may play an important role in regulation of polysaccharide content. This was the first large-scale transcriptome sequencing and analysis of P. odoratum. These data will provide a comprehensive genetic resource that will enable improvements in understanding of regulation of polysaccharide biosynthesis and accumulation at the molecular level.

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5. Conclusions In this study, transcriptome data for the leaf, stem, and rhizome tissues of P. odoratum were generated, and gene function annotations and gene expression profiles were evaluated. Eighteen key enzyme involved in biosynthesis of polysaccharides were identified, and differentially expressed genes were analyzed. A number of key enzyme genes were verified using qRT-PCR, and the results were consistent with the results of our RNA-Seq analysis. In this study, we elucidated the molecular mechanisms of polysaccharide biosynthesis, and identified polysaccharide biosynthetic pathways in P. odoratum. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments We thank the Beijing Genomics Institute for assistance with experiments, and Prof. Qingshan Yang (Anhui University of Chinese Medicine) for identification of plant materials. Financial support for the development and completion of this project was provided by startup funds through the National Key Research and Development Plan (2017YFC1701600) and the Natural Science Research Grant of Higher Education of Anhui Province (KJ2018ZD028). The Project of Sustainable Utilization of Famous Traditional Chinese Medicine Resources (2060302), the Open Fund of State Key Laboratory of Tea Plant Biology and Utilization (SKLTOF20190125) and National project cultivation fund of Anhui University of Chinese Medicine (2020py02) provided experimental support. Availability of data and material The RNA-seq datasets from three P. odoratum tissues were deposited in the NCBI Sequence Read Archive (SRA) database (Accession: SRP187533). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.gene.2020.144626. References Ana, C., Stefan, G.T., Juan Miguel, G.G., Javier, T., Manuel, T., Montserrat, R., 2005. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21, 3674–3676. Audic, S., Claverie, J.M., 1997. The significance of digital gene expression profiles. Genome Res. 7, 986–995. Biasini, M., Bienert, S., Waterhouse, A., Arnold, K., Studer, G., Schmidt, T., Kiefer, F., Cassarino, T.G., Bertoni, M., Bordoli, L., 2014. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucl. Acids Res. 42, W252. Bo, L., Dewey, C.N., 2011. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinf. 12, 323. Breton, C., Šnajdrová, L., Jeanneau, C., Koča, J., Imberty, A., 2006. Structures and mechanisms of glycosyltransferases. Glycobiology 16, 29R.

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