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Article

Comparative Transcriptome Analysis to Identify Candidate Genes Related to Chlorogenic Acid and Flavonoids Biosynthesis in Iridaceae

by
Guijun Han
1,
Guoqing Bai
1,
Yongpeng Wu
1,
Yafu Zhou
1,
Wenjing Yao
2,3,* and
Long Li
2,3,*
1
Shaanxi Engineering Research Centre for Conservation and Utilization of Botanical Resources, Xi’an Botanical Garden of Shaanxi Province (Institute of Botany of Shaanxi Province), Xi’an 710061, China
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
3
Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
*
Authors to whom correspondence should be addressed.
Forests 2022, 13(10), 1632; https://doi.org/10.3390/f13101632
Submission received: 17 September 2022 / Revised: 1 October 2022 / Accepted: 4 October 2022 / Published: 6 October 2022
(This article belongs to the Section Genetics and Molecular Biology)
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Abstract

:
Iris (Iridaceae) is one of the most widely admired ornamental plants. It has been used mainly in medicine due to the high concentration of chlorogenic acid (CGA), flavonoids, isoflavones, lignans, and other compounds in its rhizomes. In iris, the gene functions related to CGA and flavonoids biosynthesis are still unclear. In this study, we compared the I. germanica rhizome with a high accumulation level of CGA but a low accumulation level of flavonoids, and the I. pallida rhizome with a low accumulation level of CGA but a high accumulation level of flavonoids at the transcriptome and metabolome levels. A total of 761 metabolites were detected, including 202 flavonoids and 106 phenolic acids based on metabolome profiling. In total, 135 flavonoids were highly accumulated in I. pallida, including three flavanols, 51 flavonoids, 12 flavonoid carbonosides, 31 flavonols, and 21 isoflavones. Based on single-molecule long-read sequencing technology, 94,461 transcripts were identified in iris. Expression analysis indicated that the high accumulation level of C4H and 4CL in I. germanica were essential for CGA accumulation, while CHS, DFR, ANS, ANR, LAR, and 3GT were essential for flavonoids biosynthesis in I. pallida. Many transcription factors such as transcript_83288 (MYB), transcript_57970 (WRKY), and transcript_77465 (WRKY) act as regulators, playing important roles in these biological processes. Our findings provide new insights into the molecular mechanisms associated with the biosynthesis and regulation of flavonoids and CGA in the iris rhizome, and highlight the usefulness of an integrated approach for understanding this process.

1. Introduction

Iris (Iridaceae) is one of the most widely admired ornamental plants. It appeared in ancient Egyptian artifacts around the 20th century before Christ (Lyte et al., 1997). Iris is widely distributed in Eurasia, North America, and North Africa [1].
Iris rhizome is an excellent source of chlorogenic acid, flavonoids, ferulic acid, and (+)-catechin and other medicinal ingredients, and has the effects of topically healing sores, anti-spasmodics, diuretics, removing freckles, emmenagogues, stimulants, aperients, diuretics, laxatives, and carminatives [2,3,4,5]. Furthermore, iris also has important applications in landscaping. Due to its considerable economic and social benefits, iris is an important plant resource all over the word.
Flavonoids are characterized as defense compounds in the plant kingdom [6], and can be divided into seven subclasses, including flavones, flavandiols, flavonols, anthocyanins, condensed tannins, chalcones, and aurones [7,8]. Flavonoids are synthesized through a series of catalytic reactions that originate from the precursor phenylalanine, and forming quercetin, catechin, peonidin, delphinidin, anthocyanidin, and other flavonoids catalyzed by phenylalanine ammonia lyase (PAL), 4-coumarate CoA ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonoid 3′5′-hydroxylase (F3′5′H), flavonoid 3′-hydroxylase (F3′H), and other phenylpropanoid pathway enzymes. The activities of flavonoid biosynthesis associated genes are primarily regulated by a transcriptional activation complex formed by R2R3-MYB, bHLH, and WD40.
In the phenylpropanoid pathway, the synthetic substrate of both flavonoids and chlorogenic acid (CGA) are P-coumaryol-CoA. Thus, more flavonoids synthesis means less chlorogenic acid synthesis if the P-coumaryol-CoA content is kept at a relatively stable level. CGA is often used in medicines or foods due to the effect of increasing white blood cells, stimulating the central nervous system, anti-tumor, and scavenging free radicals [9]. The first steps of chlorogenic acid biosynthesis are the same as flavonoids. Previous studies have indicated that CGA was biosynthesized by three pathways, and the relative importance of each pathway varied dramatically among different species [10]. First, CGA is generated from caffeic acid coenzyme A and quinic acid via the mediation of hydroxycinnamoyl-CoA quinate hydroxycinnamoyl transferase (HQT) [11]. Second, the conversion of coumaroyl quinic acid and caffeoyl-D-glucose to CGA is catalyzed by hydrolyxycinnamoyl D-glucose: quinate hydroxycinnamoyl transferase (HCGQT) [12]. Third, CGA is synthesized from p-coumaroyl quinic acid mediated by hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase (HCT) [13]. Recently, many studies have focused on the synthesis of CGA. The rate-limiting role of HQT involved in CGA biosynthesis has been proven in many model plants [14,15,16]. The AtPAL2 overexpression line resulted in a much higher CGA accumulation level by comparing with WT, while silencing of HQT in AtPAL2 overexpressing Arabidopsis resulted in the content of CGA being reduced by half. In poplar, HCT2 activity was significantly associated with CGA biosynthesis [17]. In potatoes, the accumulation level of CGA was correlated with HCT, PAL, and CGA, due to development, or under the stimulation of the external environment [18,19]. It has been documented that many transcription factors participate in the CGA biosynthesis pathway. MYB1 acts as a transcriptional activator by regulating the expression of PAL1, and MYB3 and MYB5 are important transcriptional activators of PAL3 in carrots [20]. In poplar, WRKY38, 45, 60, 89, and 93 act as activators of the HCT2 promoter [17]. ERF1 acted as a positive regulator for PAL3 [20].
To date, although many medicinal ingredients have been identified in iris rhizomes, and the research of flavonoids and CGA in iris has mainly involved extraction methods and content determination, systematic studies on the identification of key genes related to flavonoids and CGA biosynthesis have not been fully described.
In the present study, the rhizome of I. pallida with a high accumulation level of total flavonoids, which used for spice and medicine, was selected as the experimental group. I. germanica, which is mainly used for admiring, was selected as the internal control. Metabolome profiling was carried out to identify categories of metabolites and their abundance in the iris rhizome. Single-molecule long-read sequencing (SLS) data were used to ensure a wide coverage of the transcripts in the iris rhizome. To compare the expression levels between the two species, and to explore potential genes and regulation factors involved in flavonoids and CGA biosynthesis in iris rhizome, SGS was carried out using isoform models identified through SLS. Our studies provide new insights into the molecular mechanisms associated with flavonoid and CGA biosynthesis in the iris rhizome, and our results highlight the usefulness of an integrated approach for understanding this process.

2. Materials and Methods

2.1. Plant Materials Collection

I. germanica and I. pallida were planted at the nursery of Xi’an Botanical Garden. I. pallida rhizome and I. germanica rhizome samples were sampled in mid-August. All collected samples were rapidly snap-frozen in liquid nitrogen and stored in an ultra low temperature freezer (−80 °C) until further processing (Figure 1). For metabolite profiling and transcriptome sequencing, three biological replicates were conducted, and the tissues from each biological replicates were mixed from tetrad independent individuals.

2.2. Metabolomic Analysis

Rhizome samples were freeze-dried and further crushed using a vacuum freeze-dryer (Scientz-100F, Scientz, Ningbo, China) and mixer mill (Retsch, Haan, Germany), respectively. Extraction buffer was used to dissolve the freeze-dried tissue (0.1 g), and the mixture was placed in a refrigerator at 4 °C for 12 h. Next, the extracts were centrifuged at 14,000 rpm for 8 min. Finally, the sample extracts were analyzed using an UPLC-ESI-MS/MS (ultra performance liquid chromatography-electrospray ionization-tandem mass spectrometry) system [21]. Samples were injected onto an Agilent SB-C18 column (1.8 µm, 2.1 mm × 100 mm). The mobile phase consisted of phase A (pure water with 0.1% formic acid) and phase B (acetonitrile with 0.1% formic acid). The gradient program was run as follows: (1) 5% B at 10 min; (2) a linear gradient to 95% B, and 95% B was kept for 1 min; (3) 5% B was adjusted within 1.1 min and kept for 2.9 min. The flow velocity was 0.35 mL/min. The detection of metabolites eluted from the column was executed via ESI-triple quadrupole-linear ion trap (QTRAP)-MS (ABI, Waltham, MA, USA), in both positive and negative polarity mode. The ESI source operating parameters, instrument tuning, and mass calibration were performed with reference to a previous study [22,23]. Based on the optimized collision energy and declustering, a triple quadrupole scan (QQQ) was used to scanning each ion pair [21]. ANOVA was used to quantify absolute metabolites, and Tukey’s honest significance difference test was used in PAST v.3.x for a paired comparison [24].

2.3. RNA Extraction and RNA Quality Assessment

A plant RNA extraction kit (TaKaRa MiniBEST, Kyoto, Japan) was used to extract the total RNA of I. pallida rhizome and I. germanica rhizome. DNA contamination remaining in the RNA was removed using RNase-free DNase I (Thermo Fisher Scientific, Waltham, MA, USA). Then, the concentration, purity, and integrity of the RNA were determined using 2.0% agarose gel electrophoresis, NanoDrop One (Thermo Fisher Scientific, Waltham, MA, USA), and an Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA).

2.4. Iso-Seq Library Preparation, Sequencing, and Bioinformatics Analysis

Two isoform sequencing libraries were established using the total RNA extracted from I. pallida rhizome and I. germanica rhizome. Total RNA was reversely transcribed into full-length cDNA using a Clontech SMARTer PCR cDNA Synthesis Kit (TaKaRa, Dalian, China), and then PCR was conducted to access sufficient total cDNA. The Pacific Biosciences DNA Template Prep Kit 2.0 (Pacific Biosciences, Menlo Park, CA, USA) was used to generate an SMRT bell library according to the technical manual. Finally, SMRT sequencing was executed on the PacBio RS II platform (Pacific Biosciences, Menlo Park, CA, USA).
The data obtained via isoform sequencing were further analyzed using SMRT Analysis software (Version 2.3.0). First, the pbtranscript.py script was run to identify the full-length read. The FLNC ROIs were identified based on their 5′ adapter, and 3′ adapter observed with the Clontech kit, as well as a poly(A) tail preceding the 3′ adapter. Next, the 5′ and 3′ adapters and poly(A) tails were removed. Only full-length non-chimeric ROIs were applied for further research.

2.5. Illumina Transcriptome Library Preparation, Sequencing, and Bioinformatics Analysis

Illumina transcriptome sequencing [24,25] was used to explore differentially expressed genes (transcripts) between I. pallida rhizome and I. germanica rhizome using isoform models identified via SLS. For each sample, the transcriptome sequencing libraries was constructed based on 1 μg RNA using the NEBNext Ultra II RNA Library Preparation Kit for Illumina (NEB, Ipswich, MA, USA) according to the user’s manual.
The transcriptome sequencing libraries were sequenced on an Illumina HiSeq X Ten platform at Biomaker (Biomaker, Beijing, China).
Raw RNA-seq reads were filtered using in-house Perl scripts with the default parameters to remove reads containing adapters or poly-N sequences, as well as reads of low quality. These high-quality reads were further aligned to the gene sets obtained via SLS mentioned above, using Hisat2 [26]. The expression levels of gene or transcript were calculated as fragments per kilobase of exon model per million mapped fragments (FPKM).
The DESeq R package was executed to identify differentially expressed genes or transcripts between I. pallida rhizome and I. germanica rhizome [27]. Genes or transcripts were defined as being differentially expressed with FDR ≤ 0.05 and fold change ≥2 using the Benjamini and Hochberg method.
All the identified transcripts were annotated using the database list as follows (p-value ≤ 10−7): Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, National Center for Biotechnology Information (NCBI), non-redundant protein (Nr), NCBI non-redundant nucleotide (Nt), Swiss-Prot, and Protein Family (Pfam).

2.6. Reverse Transcription and qRT-PCR Analysis

The Plant RNA Extraction Kit (TaKaRa, Kyoto, Japan) was used to extract the total RNA of I. pallida rhizome and I. germanica rhizome. A total of 1 μg RNA was reverse-transcribed into First-strand cDNA using a PrimeScriptTM RT Reagent Kit (TaKaRa, Kyoto, Japan) according to the product operation manual. The gene-specific primers were designed using an online program—Primer 3, and listed in Table S1. SYBR Green chemistry (Roche, Mannheim, Germany) and a Light Cycler 480 II instrument (Roche, Rotreuz, Switzerland) were used to conduct real-time quantification. The expression levels of each target genes were normalized to the Actin11 expression level and calibrated to the expression level in the I. germanica rhizome using the 2−ΔΔ Ct method [28].

3. Results

3.1. Metabolome Analysis

A total of 761 metabolites, including 202 flavonoids, 106 phenolic acids, 77 amino acid derivatives, 55 organic acids, 43 flavonols, and 37 free fatty acids were identified from two iris species using UPLC-MS (Figure 2 and Table S2). Most of the flavonoids were highly accumulated in I. pallida. Of all 202 identified flavonoids in iris, 135 flavonoids were highly accumulated in I. pallida, including three flavanols, 51 flavonoids, 12 flavonoid carbonosides, 31 flavonols, and 21 isoflavones. A total of 106 phenolic acids were identified, and 48 of them were highly accumulated in I. germanica. Chlorogenic acid, neochlorogenic acid, and ferulic acid showed a high concentration in I. germanica, while protocatechuic acid-4-O-glucoside and caffeic acid showed a high concentration in I. pallida.

3.2. Overview of SLS and SGS Results

SLS and SGS were performed in order to obtain comprehensive annotations of iris genes and to identify key genes and regulation factors involved in CGA and flavonoids biosynthesis in the iris rhizome. A total of 207,120 and 229,121 circular consensus sequencing (CCS) reads were obtained from I. germanica rhizome and I. pallida rhizome, respectively (Table S3). Among these CCS reads, 193,390 and 213,005 sequences containing the poly(A) tail and the entire transcript region were identified as FLNC reads (Figures S1 and S2). A total of 7,152,084,894 consensus isoforms, including 7,151,184,884 high-quality consensus transcript sequences, were obtained based on the ICE clustering algorithm using SMRT Analysis (v2.3.0) software. After the elimination of redundancy, executed using Cogent software, 94,461 transcripts were finally obtained.
Six Illumina transcriptome sequencing libraries covered 45.88 Gb clean read data with high Q30 (>94%) (Table S4). A total of 88,575 transcripts were annotated using the seven major databases mentioned in the Methods section. Among them, 88,287 transcripts were annotated in the NR database, accounting for 93.46% of the total transcripts. This was followed by the eggNOG and Pfam databases, with 86,826 and 73,950 unigenes, accounting for 91.97% and 78.28% of the total transcripts, respectively. There were 39,084, 43,230, 56,256, 58,990, and 66,912 transcripts annotated in the COG, KEGG, GO, KOG, and Swiss-Prot databases, respectively. Transcript comparisons indicated that iris had the most homologous sequences, with Asparagus officinalis (37.44%), followed by Elaeis guineensis (18.30%), Phoenix dactylifera (14.02%), and Musa acuminata (4.12%) (Figure 3A). A total of 39,084 transcripts were annotated based on homology search against the COG database, and further classified into 25 different functional classes (Figure 3B). The most dominant group, ‘‘Signal transduction mechanisms’’, contained 4107 all-transcripts (10.50%), followed by ‘‘Translation, ribosomal structure and biogenesis’’ (9.90%), and ‘‘General function predicted only (8.74%)’. Based on GO analysis, iris transcripts were categorized into three main GO ontologies: molecular function, cellular component, and biological process. Under the cellular component category, ‘‘cell’’, ‘‘cell part’’, and ‘‘membrane’’ were the most frequent terms. In the molecular function category, ‘‘catalytic activity’’, ‘binding’’, and ‘‘transporter activity’’ were predominant. In the biological process category, the dominant groups were ‘‘metabolic process’’, ‘‘cellular process’’, and ‘‘single-organism process’’ (Figure 3C).
A total of 9638 transcription factors were identified, including 559 MYBs, 190 WRKYs, 77 bHLH, nine GRF, six E2F, etc. A total of 3560 lncRNAs were identified from the 94,461 PacBio Iso-Seq isoforms based on four computational approaches, including CPC/CNCI/CPAT/Pfam.

3.3. Annotation Analysis of DEG

A comparative analysis between I. germanica rhizome (experimental group) and I. pallida rhizome (internal control) was performed to identify CGA and flavonoids biosynthesis associated genes. A total of 36,324 genes were differentially expressed, including 19,865 up-regulated and 16,549 down-regulated genes. These DEGs were categorized into 128 pathways using KEGG pathways. Of these, Ribosome biogenesis in eukaryotes, RNA transport, Non-homologous end-joining, and spliceosome were the four most enriched pathways in the group of up-regulated genes (Figure 4A), while cysteine and methionine metabolism, terpenoid backbone biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; and valine, leucine and isoleucine degradation were the four most enriched pathways in the group of down-regulated genes (Figure 4B).

3.4. Genes Related to Flavonoid Biosynthesis

A total of 131 functional genes were associated with flavonoid biosynthesis, including 38 PAL, 11 4CL, three C4H, 15 CHS, and 10 CHI; four F3H, 10 F3′H, six FLS, 21 UFGT, five 3GT, two AOMT, two LAR, and four ANR genes, based on public database annotation. About one half of the PAL and 4CL genes showed higher expression levels in the I. pallida rhizome (Figure 5A). Among these, transcript_6820 (PAL), and transcript_12844 (PAL) were expressed more than 10-fold higher in I. germanica, while transcript_7603 (PAL) and transcript_46598 (PAL) were expressed more than 10-fold higher in I. pallida. Nearly two-thirds of CHSs and CHIs were highly accumulated in I. pallida. Among these, transcript_47083 (CHS), transcript_51781 (CHS), and transcript_47227 (CHI) exhibited the most significantly increased expression (Figure 5B). Mostly, 3GT and all DFR, ANR, and LAR performed with much higher expression levels in I. pallida (Figure 5A). Their high expression level was essential for flavonoids, especially flavonols and anthocyanins accumulation in I. pallida.

3.5. Genes Related to CGA Biosynthesis

A total of 29 HCT and two C3H genes were identified in iris. However, two specific enzymes encoded by UGCT and HCGQT in the second pathway were not found in the transcriptome sequencing data (Figure 5A). transcript_11480 and transcript_30818 encoding C4H, and transcript_27273 encoding C3H were expressed much more highly in I. germanica rhizome (Figure 5B). It was found that 19 of 29 HCT genes were preferentially expressed in I. germanica rhizome. The predominant expression of HCTs in I. germanica might be associated with its high abundance of CGA.

3.6. Transcriptional Regulation Involved in Flavonoid and CGA Biosynthesis

In terms of transcription factor coding genes, nearly half of the bHLH and bZIP genes were much more highly expressed in I. germanica. Most of the WRKYs, Dofs and MYBs were highly expressed in I. pallida rhizome (Figure 6A). Amongst all, transcript_83288 (MYB), transcript_57970 (WRKY), transcript_77465 (WRKY), and transcript_58948 (Dof), which were up-regulated more than 10-fold, were essential for flavonoids biosynthesis. By contrast, transcript_13409 (bHLH), transcript_30127 (bHLH), transcript_17702 (MYB), and transcript_71528 (WRKY) which showed the highest -fold differential expression, were highly expressed in I. germanica (Figure 6B), and their accumulation level might be essential for CGA biosynthesis.

4. Discussion

The recently developed single-molecule long-read sequencing (SLS) technology can produce full-length isoforms and omits transcriptome assembly, which is essential for second-generation sequencing (SGS) [29]. Recently, SLS has been used to identify novel genes and isoforms, and improve genome annotation in many model plants, such as Populus, Sorghum bicolor, and Gossypium hirsutum [25,30,31]. However it still absent in iris. Recently, many genetic and genomic studies have been reported in iris using SGS technology, such as the identification of genes in lead-stress response [32], flower development [33], and reblooming mechanisms [34]. In order to ensure the wide coverage of iris transcripts, SLS was conducted in this study. SGS was carried out to explore the potential factors involved in the metabolite biosynthesis of CGA in iris rhizome.
It reported in many model plants that the PAL gene family has been demonstrated to be the key enzyme for flavonoids and CGA biosynthesis. The quantity of PAL genes varies dramatically in different species, with two PALs in poplar, three PALs in kidney bean, four PALs in parsley, one PAL in tea tree, and more than 40 PALs in potato [35,36,37,38]. The genetic diversity of the PAL gene family in iris is much higher than in the other plant species mentioned above except potato, which may be related to the rich active components of flavonoids and CGA.
In this study, we identified four ANR genes using single-molecule long-read sequencing, which was much higher than in many reported plants. The greater number of ANR genes identified in the iris genome may be caused by a much larger genome size. In our study, a total of 94,461 transcripts were identified using single molecular long-read sequencing, including four ANR transcripts. Excluding the influence of multiple transcripts (isoforms) produced by one gene that was caused by the effect of selective promoters and alternative splicing, all four ANR transcripts were produced by four different gene sets. It is reported that the genome size of iris is 4494.1 Mb, which is much larger than those of apple (742.3 Mb) and Glycine max (941 to 1374 Mb), which harbored two ANRs, respectively. It is also larger than those of Arabidopsis (135 MB) and rice (389 MB), which both harbor only one ANR. Thus, a larger genome size harboring more gene sets results in more ANR genes [39,40,41,42,43,44,45].
There were two main branches in the phenylpropanoid pathway from the node of P-coumaryol-CoA: one branch leading to CGA biosynthesis under the regulation of HQT and HCT, and the other one leading to flavonoid biosynthesis under the regulation of CHS. Flavonoids are a large and structurally diverse group of polyphenolic compounds in plant [46]. A total of 202 flavonoids were identified in iris, and most of them were preferentially accumulated in the I. pallida rhizome. Consistent with the differences in flavonoid content between I. pallida and I. germanica, flavonoid biosynthetic related isoforms such as CHS, DFR, ANS, ANR, LAR, and 3GT also demonstrated high expression levels in I. pallida. In the biological process of flavonoid biosynthesis, CHS act as the first enzyme. Most CHS members, especially transcript_47083, transcript_51781 showed trends of up-regulation in I. pallida rhizome, indicating the importance of CHS involvement in flavonoid biosynthesis. In addition, CHI (transcript_47227) and F3H (transcript_18844) are able to convert tetrahydroxy-chalcone to dihydrokaempferol, which serves as the common substrate for F3′H and FLS, resulting in the production of different flavonoids and anthocyanins [47]. FLS is the main enzyme that is responsible for the formation of flavonols, including quercetin and gossypetin; therefore, FLSs were expressed at much higher levels in I. pallida, which caused more flavonols to accumulate in I. pallida. MYB TFs regulate flavonoid and phenylpropanoid accumulation by binding to the promoters of target genes, including CHS, CHI, and DFR, and regulate their expression [48,49,50]. As one of the largest and most functionally diverse TF families in the plant kingdom [51], MYBs or the MBW complex formed by MYB, bHLH, and WD40 play important roles in regulating flavonoid and phenylpropanoid biosynthesis [7]. transcript_83288 (MYB) and transcript_38645 (MYB), which were up-regulated more than 10 times in I. pallida, were essential for flavonoid accumulation in I. pallida. The WRKYs, ERFs, and Dofs involved in flavonoid biosynthesis were also reported in many model plants [52,53,54,55]. MdWRKY72 promotes anthocyanins synthesis in apple by regulating the expression of MdMYB1 under UV-B stimulation [52].
FhDof4, 9, 15, and 16 is involved in flavonoid biosynthesis through binding to the flavonoid C-glycosyltransferase (FhCGT) promoter in ‘Hongkong’ kumquat [55]. In our study, a large amount of WRKY, ERF, and Dof TFs were differentially expressed and showed a high accumulation level in I. pallida. These TFs and functional genes formed a complex regulatory network and participated in flavonoid biosynthesis in the I. pallida rhizome.
Phenolic acids are characterized as defense compounds due to their effects against oxidative damage diseases such as stroke, coronary heart disease, and cancers [56,57,58]. In this study, a total of 106 phenolic acids, including CGA, were identified in iris rhizome. Previous studies have suggested that CGA is one of the most important medicinal components in all phenolic acids, and that the content of CGA directly determines its utilization value in plants [59,60,61]. It has been reported that there are roughly three CGA biosynthetic pathways in plants [12]. However, only route 2 and route 3 were identified in iris, and iris lacks the UGCT and HCGQT that are necessary for the synthesis of chlorogenic acid in route 1. C4H and 4CL act as key enzymes the upstream of quinic acid and CGA biosynthesis; their enzymatic activity directly determines the accumulation level of these two components. Expression analysis showed that most C4H and 4CL were highly abundance in I. germanica, which caused a high accumulation level of CGA in I. germanica.
In the phenylpropanoid biosynthetic pathway, HQT and HCT are homologous genes with different catalytic functions. HQT can only use quinate as a substrate, whereas HCT can use both shikimate and quinate as substrates. The roles of HCT and HQT participating in CGA biosynthesis have been well documented in tobacco, tomato [13], and artichoke [62,63]. In this study, 28 HQT/HCT transcripts were identified in iris, of which 19 transcripts showed high accumulation levels in I. germanica and were positive correlated with CGA content, suggesting their key roles in CGA biosynthesis in I. germanica. transcript_13817, which was expressed more than 10-fold higher in I. germanica, shared the highest similarity with AtHCT (Locus: AT5G48930) in Arabidopsis, which synthesizes and catabolizes hydroxycinnamoylesters (coumaroyl/caffeoyl shikimate and quinate) involved in the phenylpropanoid pathway [64]. However, many studies have indicated that some HQTs such as LjHQTs did not show significant organ preferential expression and may not be the critical genes regulating CGA content [65]. Our results are consistent with this result. For example, transcript_29593 and transcript_17936 displayed no significant differential expression level between the two sample groups.

5. Conclusions

In summary, a total of 761 metabolites, including 202 flavonoids and 106 phenolic acids based on the metabolome, were identified in the iris rhizome. Based on single-molecule long-read sequencing technology, 94,461 transcripts were identified. Expression analysis based on transcriptome sequencing and qRT-PCR indicated that the high accumulation levels of C4H and 4CL in I. germanica were essential for CGA accumulation, while CHS, DFR, ANS, ANR, LAR, and 3GT were essential for flavonoids biosynthesis in I. pallida. WRKY, MYB, bHLH, bZIP, etc. act as regulators, playing important roles in these biological processes. These results characterize a potential molecular regulatory mechanism for CGA and flavonoids biosynthesis, and provide a wealth of candidate genes for future studies to engineer the improvement of iris.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13101632/s1, Figure S1: Distribution of read length in the IgFL (A) and IpFL (B) library; Figure S2: Distribution of read length of full-length non-chimeric (FLNC) reads in the single-molecule long-read sequencing library. (A) IgFL and (B) IpFL; Table S1: Primers used for qRT-PCR; Table S2: The identified metabolites and their expression profiles in iris rhizome; Table S3: The identified CCS reads in the IgFL and IpFL library; Table S4: Overview of the second-generation sequencing reads.

Author Contributions

G.H. conceived and designed the research. G.B. conducted experiments, and analyzed data. Y.Z. and W.Y. conducted experiments and analyzed data. Y.W. revised the manuscript. L.L. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the key research and development project of Shaanxi Province (grant numbers 2022NY-152), and National Science Foundation of China (32201643).

Data Availability Statement

The data are available on request from the corresponding author.

Conflicts of Interest

The authors have no relevant financial or non-financial interests to disclose.

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Figure 1. Morphological characterization of Iris germanica and Iris pallida. (A) I. germanica flower, (B) I. pallida flower, (C) I. germanica rhizome, and (D) I. pallida rhizome.
Figure 1. Morphological characterization of Iris germanica and Iris pallida. (A) I. germanica flower, (B) I. pallida flower, (C) I. germanica rhizome, and (D) I. pallida rhizome.
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Figure 2. The identified metabolites in iris.
Figure 2. The identified metabolites in iris.
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Figure 3. The annotation results of all identified transcripts in iris rhizome. (A) Species distribution of iris transcripts in NR. (B) The classification of the clusters of orthologous groups (COG) annotation results for the iris transcripts. (C) The classification of Gene Ontology (GO) annotation results for the iris transcripts.
Figure 3. The annotation results of all identified transcripts in iris rhizome. (A) Species distribution of iris transcripts in NR. (B) The classification of the clusters of orthologous groups (COG) annotation results for the iris transcripts. (C) The classification of Gene Ontology (GO) annotation results for the iris transcripts.
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Figure 4. Scatter diagram of KEGG pathway enrichment of differentially expressed transcripts. (A) down-regulated genes, (B) up-regulated genes. The color scale represents the significance of the FDR value, and lower FDR value indicates greater enrichment. Rich factor = Amount of DEG annotated in a given pathway term/amount of all genes in the pathway term, and greater richness factor values indicate greater intensiveness. The circle size represents the quantity of DEGs.
Figure 4. Scatter diagram of KEGG pathway enrichment of differentially expressed transcripts. (A) down-regulated genes, (B) up-regulated genes. The color scale represents the significance of the FDR value, and lower FDR value indicates greater enrichment. Rich factor = Amount of DEG annotated in a given pathway term/amount of all genes in the pathway term, and greater richness factor values indicate greater intensiveness. The circle size represents the quantity of DEGs.
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Figure 5. (A) The purposed chlorogenic acid and flavonoids biosynthesis pathways for iris rhizome. The three CGA biosynthesis routes are labeled ①, ②, ③ in chart. The enzyme names, as well as their expression patterns, are displayed in each step. Heatmaps next to enzyme names indicate expression profiles of genes. Blue and yellow indicates low expression level and high expression level, respectively. (B) qRT-PCR verified the expression profiles of selected CGA and flavonoids associated genes.
Figure 5. (A) The purposed chlorogenic acid and flavonoids biosynthesis pathways for iris rhizome. The three CGA biosynthesis routes are labeled ①, ②, ③ in chart. The enzyme names, as well as their expression patterns, are displayed in each step. Heatmaps next to enzyme names indicate expression profiles of genes. Blue and yellow indicates low expression level and high expression level, respectively. (B) qRT-PCR verified the expression profiles of selected CGA and flavonoids associated genes.
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Figure 6. Expression profiles of transcription factors related to chlorogenic acid and flavonoids biosynthesis. (A) Expression profiles of WRKY, AP2/ERF, bZIP, MYB, Dof, and bHLH from transcriptome data. Blue and yellow indicates low expression level and high expression level, respectively. (B) qRT-PCR verified the expression profiles of selected TF genes.
Figure 6. Expression profiles of transcription factors related to chlorogenic acid and flavonoids biosynthesis. (A) Expression profiles of WRKY, AP2/ERF, bZIP, MYB, Dof, and bHLH from transcriptome data. Blue and yellow indicates low expression level and high expression level, respectively. (B) qRT-PCR verified the expression profiles of selected TF genes.
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Han, G.; Bai, G.; Wu, Y.; Zhou, Y.; Yao, W.; Li, L. Comparative Transcriptome Analysis to Identify Candidate Genes Related to Chlorogenic Acid and Flavonoids Biosynthesis in Iridaceae. Forests 2022, 13, 1632. https://doi.org/10.3390/f13101632

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Han G, Bai G, Wu Y, Zhou Y, Yao W, Li L. Comparative Transcriptome Analysis to Identify Candidate Genes Related to Chlorogenic Acid and Flavonoids Biosynthesis in Iridaceae. Forests. 2022; 13(10):1632. https://doi.org/10.3390/f13101632

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Han, Guijun, Guoqing Bai, Yongpeng Wu, Yafu Zhou, Wenjing Yao, and Long Li. 2022. "Comparative Transcriptome Analysis to Identify Candidate Genes Related to Chlorogenic Acid and Flavonoids Biosynthesis in Iridaceae" Forests 13, no. 10: 1632. https://doi.org/10.3390/f13101632

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