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Article

Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta)

by
Yun Jia
1,2,
Yong-Peng Wu
1,2,
Feng-Wei Wang
1,2,
Lei Zhang
1,2,
Gang Yu
1,2,
Ya-Ling Wang
1,2 and
Ying Zhang
1,2,*
1
Xi’an Botanical Garden of Shaanxi Province, Institute of Botany of Shaanxi Province, Xi’an 710061, China
2
Shaanxi Engineering Research Centre for Conservation and Utilization of Botanical Resources, Xi’an 710061, China
*
Author to whom correspondence should be addressed.
Diversity 2022, 14(6), 424; https://doi.org/10.3390/d14060424
Submission received: 12 April 2022 / Revised: 8 May 2022 / Accepted: 15 May 2022 / Published: 26 May 2022
Browse Figures
Versions Notes

Abstract

:
Kiwifruit an important horticultural crop that is widely cultivated and is known as the king of fruits. Recently, a new seedless kiwifruit cultivar, ‘Chengxiang’ (Actinidia arguta), was discovered by field transplantation. It exhibited distinguishable characteristics such as parthenocarpy, and a unique flavor and appearance when compared to other cultivated type. Flavonoids are known to play an important role in fertility and parthenocarpy in plants. However, the genes responsible for flavonoid biosynthesis in seedless kiwifruit remain largely unknown. Especially, chalcone synthase (CHS), as a key enzyme catalyzing the first committed step in the flavonoid pathway, remains a mystery. In this study, we combined a full-length transcriptome survey by PacBio single-molecule real-time (SMRT) sequencing, CHS gene family analysis, and analysis of the gene expression involved in flavonoid pathways to further enhance the understanding of parthenocarpy. Based on SMRT, we obtained 80,615 high-quality full-length consensus transcripts. In total, 52,406 (90.79%) transcripts were functionally annotated, and more than 80% of the transcripts were longer than 1Kb. Among them, 39,117 (74.64%) transcripts were assigned to GO terms, the majority of which were associated with the cell (19,089, 48.80%) and metabolic process (19,859, 50.77%). Furthermore, 25,289 (48.26%) transcripts were mapped into 129 KEGG pathways. We identified the majority of putative genes as being involved in the flavonoid biosynthesis pathway, including 14 key enzyme gene families, such as CHS, chalcone isomerase (CHI), flavonol synthase (FLS), and so on. Moreover, we also identified 13 CHS genes and characterized the CHS gene family in seedless kiwifruit. We further evaluated the expression pattern of 10 flavonoid-related key enzyme genes in flowers using quantitative real-time PCR. This is the first time that the full-length transcriptome have been studied in seedless kiwifruit, and the findings enhance our understanding the molecular mechanisms of parthenocarpy.

1. Introduction

Parthenocarpy, the formation of seedless fruits in the absence of pollination and/or functional fertilization, is a desirable trait for horticultural plants, including citrus, eggplant, tobacco, and tomato [1,2,3]. The primary advantage of parthenocarpy is that fruit set and growth are not impeded by adverse environmental conditions, so as to further ensure the stability of fruit productivity [2]. Therefore, the trait of parthenocarpy can be of great value to consumers, the processing industries, and breeding companies [1,2,4].
At present, parthenocarpy can be induced by natural mutation [3], chemically [5] and genetically [2,4,6]. In general, artificial parthenocarpy involves the exogenous application of auxin, cytokinin, or gibberellin, suggesting that many independent and possibly redundant hormone pathways directly lead to parthenocarpy [3,6,7]. Otherwise, the identification of parthenocarpy-related genes can induce seedlessness using gene knockout or over-expression, which may be potential targets for genetic engineering of seedless plants’ development [3]. For example, the suppression of the chalcone synthase (CHS) genes by RNA interference (RNAi)-mediated, the first enzymatic step in the flavonoid pathway, has been shown to result in parthenocarpic tomato (Solanum lycopersicum) with decreased levels of total flavonoids [1]. In addition, the alteration of flavonoid biosynthesis by stilbene synthase (StSy) over-expression also induced parthenocarpy and caused abnormal pollen development in tomato [2]. These suggested that fertility and plant reproduction are partially constrained by flavonoid biosynthesis, which is associated with numerous physiological and biological processes in plants [2,8,9]. Moverover, Ylstra et al.’s (1992) research has proven that flavonoids in the anther or pistil areessential for pollen tube growth, fertilization, and seed set by pollination experiments [10]. However, therelation between parthenocarpic fruit development and flavonoids has never been described, therefore, the molecular and genetic implications induced by flavonoid biosynthesis in terms of parthenocarpic plants need to be studied in more detail.
Kiwifruit is a perennial horticultural crop of the Actinidiaceae family with remarkably high nutritional and economic value [11]. It has been domesticated and cultivated successfully in the last century and it is becoming more and more popular around the world [12]. At present, Actinidia arguta (an all-red fleshed kiwifruit) is commercially cultivated in Korea and eastern Russia as well as many other regions, and has been introduced to the market due to its special desirable traits such as its appearance and high levels of anthocyanin [13,14,15]. Recently, the cultivation of A. arguta has gradually increased in China and its research and utilization in biology and agriculture are also rapidly developing [16]. Nowadays, a new seedless kiwifruit cultivar, ‘Chengxiang’ was discovered by field transplanting (Figure 1). It exhibited distinguishable characteristics such as parthenocarpy, a unique flavor, and appearance, different than other cultivated type. Parthenocarpy is one of the valuable traits found in kiwifruit, which is supposed to overcome the shortage of pollen that occurs from the kiwifruit industry market, and it is an essential pathway for producing seedless fruit, which can also be used as commercial feature for high-quality kiwifruit. Considering its significant economic contribution, it is necessary to improve the fruit quality and study the molecular mechanisms of parthenocarpy in seedless kiwifruit development. Up to now, many studies have focused on volatile compounds, pigment genes, pancreatic lipase inhibitor, and flavonols in A. arguta fruits [12,17], flowers [18], leaves [16] and roots [19].
However, genes responsible for flavonoid biosynthesis in the seedless kiwifruit remain largely unknown. It is instrumental in identifying its essential role in parthenocarpy and male sterility [1]. Moreover, the number of CHS members that catalyze the first committed step in the flavonoid pathway remains a mystery in seedless kiwifruit. In this study, we sequenced and analyzed the ‘Chengxiang’ transcriptome of the flowers, leaves, and stems using PacBio single-molecule real-time (SMRT) sequencing. We combined full-length transcriptome surveys, CHS gene family analysis, and key enzyme genes’ expression involved in flavonoid biosynthesis to further enhance the understanding of parthenocarpy in seedless kiwifruit. We also investigated CHS genes from the transcriptome and characterized the CHS gene family in seedless kiwifruit. Our findings are an essential resource for flavonoid-related genes, which provide significant foundations for molecular genetic studies in seedless kiwifruit. Moreover, our research improves our understanding of the molecular mechanisms of parthenocarpy.

2. Materials and Methods

2.1. Plant Material and RNA Extraction

The kiwifruit cultivar ‘Chengxiang’ (female plant) was transplanted from the middle range of Qinling Mountains (34.50 N, 109.78 E), Shaanxi, China in 2017. Young stem, leaves, and flowers were collected, immediately frozen in liquid nitrogen, and were stored at −80 °C until RNA extraction. Total RNA was isolated using the Tiangen RNA preparation kits (Tiangen Biotech, Beijing, China) according to the manufacturer’s recommendations. RNA quality and integrity were determined using electrophoresis (Junyi, Beijin, China), Nanodrop 2000 (Implen, Westlake Village, CA, USA), and further by the Agilent 2100 (Agilent Technologies, Inc., Santa Clara, CA, USA). RNA integrity number > 8.0 was utilized for SMRT sequencing.

2.2. PacBio SMRT Library Construction and Sequencing

The total RNA of the three individual samples (flowers, leaves and stem) was pooled together at an equal ratio to provide total ‘Chengxiang’ RNA. Full-length cDNAs of mRNAs were synthesized using SMARTer cDNA Synthesis Kit (Clontech, San Jose, CA, USA). Full-length cDNA fragments were selected using the BluePippin® (SageScience, Beverly, MA, USA) and then amplified again by PCR. Subsequently, full-length cDNA was repaired at the end, and the dumbbell-shaped SMRT adapter were subjected to the construction of cDNA using the SMRTBell Template Prep Kit. BluePippin was used for secondary screening to obtain a cDNA library. Qubit 2.0 and the Agilent 2100 (Agilent Technologies, Inc., Santa Clara, CA, USA) was used to measure the concentration and quality of the library, respectively. Finally, full-length transcriptome sequencing was achieved via the PacBio RSII platform (Pacific Biosciences, Menlo Park, CA, USA). Quality filtering and error correction was performed by CD-HIT (-c 0.95 -T 6 -G 0 -aL 0.00 -aS 0.99) to obtain final transcripts for the subsequent analysis [20]. The PacBio-seq raw reads (Biomarker Technologies, Beijing, China) of this study have been deposited into NCBI with the following accession number: SRR19075498 (Sequence Read Archive number; https://www.ncbi.nlm.nih.gov/sra/, accessed on 9 May 2022).

2.3. Functional Annotation and Classification

In order to predict putative gene function, all obtained non-redundant transcripts were assigned to the protein databases NCBI non-redundant (NR) [21], Clusters of Orthologous Groups of proteins (COG) [22], Clusters of enKaryotic Orthologous Groups of proteins (KOG) [23], Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups database (eggNOG) [24], Protein families (Pfam) [25], the Swiss-Prot protein database (Swiss-Prot) [26] utilizing BLASTX with an E-value threshold of 10−5. Gene Ontology (GO) [27] and Kyoto Encyclopedia of Genes and Genomes (KEGG) [28] analyses were also performed utilizing Blast2GO [29] and Kobas v3.0 [30] to against with their respective databases for functional classification and biosynthetic metabolic pathway.

2.4. Prediction of Long Non-Coding RNAs (LncRNAs), Transcription Factors (TFs), and Simple Sequence Repeats (SSR)

LncRNAs are a class of poly-A non-coding RNAs, which play roles in plant growth and development. Herein, four computational methods were utilized for screening lncRNAs, including CNCI v2 (https://github.com/www-bioinfo-org/CNCI, accessed on 20 June 2021) [31], CPC vcpc-0.9-r2 (http://cpc.cbi.pku.edu.cn/, accessed on 20 June 2021) with an E-value threshold of 10−10 [32], Pfam-scan with default parameters of -E 0.001 --domE 0.001 [33], and CPAT (http://lilab.research.bcm.edu/cpat/, accessed on 20 June 2021) with default parameters of -minlength 200 [34]. TFs were identified using iTAK v1.7a (https://github.com/kentnf/iTAK/, accessed on 18 June 2021) [35]. SSRs were predicted using MISA v1.0 (http://pgrc.ipk-gatersleben.de/misa/, accessed on 18 June 2021) [36] with default parameters.

2.5. Gene Expression Analysis of Flavonoid Biosynthesis

Ten enzyme-encoding genes that are involved in flavonoid biosynthesis were selected for qRT-PCR with specific primers designed by Primer Premier 5 software (Table S1). The fresh flowers were utilized for RNA extraction by Tiangen RNA preparation kits (Tiangen Biotech, Beijing, China). The cDNA was synthesized via SMART PCRcDNA synthesis kit (Clontech, CA, USA). The reaction mixture of qRT-PCR was 10 µL with the following components: 5 µL SYBR green, 3.4 µL ddH2O, 0.3 µL primers, and 1.0 µL cDNA. The reaction was set at 95 °C for 30 s, 40 cycles of 95 °C for 10 s, and 60 °C for 30 s. The reaction was implemented in three biological replicates for each genes and the data are presented as means ± SDs (n = 3) [37].

2.6. Prediction of the CHS Family Members in the Seedless Kiwifruit Cultivar ‘Chengxiang’

The Hidden Markov Model (HMM) file corresponding to the CHS domain was generated from Pfam database (https://pfam.xfam.org/, accessed on 26 December 2021) [25]. The candidate AaCHS proteins containing the CHS domain (PF00195 and PF02797) were searched for from the A. arguta transcriptome using HMMER v3.0 (http://hmmer.janelia.org/, accessed on 26 December 2021). The default parameters were performed, and the threshold value was set at 0.01. Subsequently, these CHS proteins were further verified as to whether they were all members of CHS family, utilizing BLASTP in NCBI. Furthermore, the basic characteristics of the CHS proteins, such as the coding sequence length (CDS) and isoelectric point (pI), were determined using EXPASY (http://web.expasy.org/protparam/, accessed on 27 December 2021).

2.7. Phylogenetic Analysis and Conserved Motif Analysis

All identified CHSs were used for multiple amino acid sequence alignments by ClustalW2 (http://ftp.ebi.ac.uk/pub/software/clustalw2/, accessed on 27 December 2021) [38]. The phylogenetic relationship of CHSs among themselves was performed with MEGA v6.0 based on the Neighbor-Joining (NJ) method, involving 1000 bootstrap replicates [39]. To compare the differences in CHSs, the conserved motif of the CHS proteins were analyzed using MEME (http://memesuite.org/tools/meme/, accessed on 27 December 2021) [40]. The maximum motif search value was set at 20.

3. Results

3.1. SMRT Sequencing of Kiwifruit Cultivar ‘Chengxiang’

We sequenced the transcriptome of ‘Chengxiang’ (Figure 1) and, after removing adaptor sequences and low-quality sequences, screened out 161,390 circular consensus (CCS) reads with an average length of 1907 bp (Figure S1A). Among the total CCS reads, 89.97% (145,210) of reads were identified as the full length non-chimeric (FLNC) reads with an average length of 2808 bp (Figure S1B). Subsequently, 80,615 high-quality full-length consensus transcripts were obtained from FLNC sequences clustering by the IsoSeq algorithm (Figure S1C) [41]. Finally, a final set of 57,721 non-redundant transcripts were obtained using CD-HIT, and were further processed for gene annotation (Table 1).

3.2. Functional Annotation of Transcripts

Function annotation of the unique transcripts was conducted by searching against the protein databases NCBI non-redundant (NR), Clusters of Orthologous Groups of proteins (COG), Clusters of enKaryotic Orthologous Groups of proteins (KOG), Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups database (eggNOG), Protein families (Pfam), the Swiss-Prot protein database (Swiss-Prot), Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In total, 90.79% (52,406) transcripts were functionally annotated, and more than 80% of the transcripts were longer than 1Kb (Figure 2A, Table S2). In detail, a total of 99.77% (52,287) of the transcripts were annotated in NR, 21,390 transcripts in COG, 33,494 transcripts in KOG, 51,491 transcripts in eggNOG, 42,535 transcripts in Pfam, and 38,985 transcripts in Swiss-Prot (Figure 2A). The top-hit species in the annotated distribution was Vitis vinifera (10118, 19.38%), followed by Quercus suber (2387, 4.57%), and Coffea canephora (1927, 3.69%) (Figure 2B). The remaining 27,295 (52.29%) potential transcripts showed no homology to known sequences that are deposited in these databases.
Meanwhile, GO functional annotation indicated that most of the transcripts (39,117, 74.64%) were associated with the cellular component, followed by biological processes, and were least associated with the molecular functions. The ‘cell’ (19,089, 48.80%), ‘metabolic process’ (19,859, 50.77%), and ‘catalytic activity’ (19,947, 50.99%) were the largest and most highly represented in these three main terms, respectively (Figure 2C). The KOG annotation allocated 29,986 transcripts into 25 KOG categories (Figure S2); the general functional cluster prediction (4903, 16.35%) was the largest group, followed by posttranslational modification, protein turnover, chaperones (3792, 12.65%), and signal transduction mechanisms (2867, 9.56%). Additionally, a total of 25,289 (48.26%) transcripts were mapped into 129 KEGG functional pathways. The first three transcript-related pathways were carbon metabolism (ko01200, 1033, 4.08%), protein processing in the endoplasmic reticulum (ko04141, 934, 3.69%) and the biosynthesis of amino acids (ko01230, 889, 3.52%).

3.3. Identification of LncRNAs, TFs and SSRs

A total of 12,056, 11,062, 57,721, and 7289 lncRNAs were recognized in the Coding Potential Assessment Tool (CPAT), Coding-Non-Coding-Index (CNCI), Coding Potential Calculator (CPC), and Pfam databases, respectively. 7289 transcripts were predicted as lncRNAs by all methods by screening transcripts of less than 300 bp (Figure S3). In addition, 2671 putative TFs were identified and classified into 64 families in the ‘Chengxiang’ transcriptome, which mainly belong to the bHLH (210, 7.86%), AP2/ERF-ERF (168, 6.29%), NAC (145, 5.43%), MYB-related (141, 5.28%), C3H (140, 5.24%), bZIP (135, 5.05%), WRKY (123, 4.61%), C2H2(123, 4.61%), GRAS (109, 4.08%), and MYB (88, 3.29%) families (Figure 3).
All unique transcripts were subjected to SSR analysis. A total of 37,686 SSRs were recognized in 44,153 transcripts, of which 8937 sequences contained more than one SSR repeat (Table S3). The most abundant repeat types were dinucleotides (23,023), followed by mononucleotides (9333) and trinucleotides (4109). The dominant classes of the sequence repeat were AG/CT (19,839) in the dinucleotides A/T (8504) in the mononucleotides, and AAG/CTT (1007) in the trinucleotides.

3.4. Candidate Genes Involved in Flavonoid Biosynthesis

To understand the mechanisms regulating the biosynthesis of flavonoids in seedless kiwifruits, based on the KEGG database, a comprehensive search was carried out in the annotated results of ‘Chengxiang’. We sketched the proposed pathways for flavonoid biosynthesis in ‘Chengxiang’ (Figure 4). A total of 98 transcripts coding for 14 key enzymes were found, which are known to be involved in the flavonoid biosynthesis pathway (Table 2, Table S4). CHS (EC:2.3.1.74, 15 transcripts) converted 4-coumaryl-CoA to naringenin chalcone, which led to the formation of naringenin by the action of chalcone isomerase (CHI, EC:5.5.1.6, 2 transcripts). CHS controls the first committed step of flavonoid biosynthesis and regulates the production of total flavonoids by genes’ overall expression [42]. For flavanone 3-hydroxylase (F3H, EC:1.14.11.23), 8 transcripts were involved in the catalysis of conversion of dihydroflavonols from flavanones. We also found 12 transcripts and 3 transcripts annotated as flavonol synthase (FLS, EC:1.14.11.23) and flavanone 3′ hydroxylase (F3′H, EC:1.14.13.21), respectively. Leucoanthocyanidins are the direct precursors of flavan-3-ols produced by leucoanthocyanidin reductase (LAR, EC:1.17.1.3). There were seven LAR genes in our database. Besides these genes, we also detected genes that encode enzymes that are indirectly involved in flavonoid biosynthesis, including anthocyanidin reductase (ANR, EC:1.3.1.112), trans-cinnamate 4-monooxygenase (C4H, EC:1.14.13.11), bifunctional dihydroflavonol 4-reductase/flavanone 4-reductase (DFR, EC:1.1.1.219 /1.1.1.234), and shikimate O-hydroxycinnamoyltransferase (HCT, EC:2.3.1.133) (Table 2, Figure 4). Among them, 16 transcripts (most represent) were annotated as encoding anthocyanidin synthase (ANS, EC:1.14.11.19). Moreover, to confirm the accuracy and reproducibility of the SMRT-Seq results, qRT-PCR was performed on ten key enzyme-encoding genes that are associated with flavonoid biosynthesis, including C4H (WZCX_transcript_28878), CHS10 (WZCX_transcript_66409), CHS11 (WZCX_transcript_69406), CoAOMT (WZCX_transcript_13803), DFR (WZCX_transcript_10695), FLS (WZCX_transcript_11905), F3H (WZCX_transcript_59962), F3′5′H (WZCX_transcript_6942), HCT (WZCX_transcript_8458), and LAR (WZCX_transcript_10801) (Table S1, Figure 5).

3.5. Identification of the CHS Proteins in Seedless Kiwifruit Cultivar ‘Chengxiang’

A total of 22 candidate gene models corresponding to the Pfam CHS family were originally generated in the seedless kiwifruit cultivar ‘Chengxiang’. The annotation of these gene models were further confirmed using available seedless kiwifruit transcriptome data. Finally, 13 gene models were selected and annotated as being seedless kiwifruit AaCHS genes, based on the presence of apparently complete CHS domains (Table 3). Gene characteristics, including the length of the CDS, the length of the protein sequence, the protein molecular weight (MW), and isoelectric point (pI) were analyzed (Table 3). Among the 13 AaCHS proteins, AaCHS7 was identified to be the smallest protein with 136 amino acids (aa), whereas the largest one was AaCHS9 with 418 aa. The MW of the proteins ranged from 2.79 to 45.56 kDa, and the pI ranged from 4.88 (AaCHS7) to 6.96 (AaCHS11).

3.6. Phylogenetic Analyses and Motif Composition of CHS Gene Family in the Seedless Kiwifruit Cultivar ‘Chengxiang’ ,

The AaCHS proteins were divided into two clades by the phylogenetic tree (Figure 6A). AaCHS members within the same cluster were usually found to share a similar motif composition. A total of 15 distinct conserved motifs were found; motifs four and nine were widely distributed in the AaCHS domains (Figure 6B). For example, motif 11 is special to AaCHS 9,11,13, which may be important to the functions of the unique AaCHS protein. The clustered AaCHS pairs, i.e., AaCHS 1/3 and AaCHS 2/12, showed highly similar motif distribution, indicating potential functional similarities among AaCHS proteins. Motif five and the adjacent motif fifteen only co-existed in AaCHS 4,8,5. These specific motifs may contribute to the functional divergence of AaCHS genes.

4. Discussion

Seedlessness is a significant trait in relation to fruits’ quality, and consumers are increasingly interested in seedless fruits such as citrus, grape, and watermelon [3]. Commercially seedless cultivars require the inability to produce seeds under specific growth conditions, or by application of exogenous hormones, which affect the formation of seedless fruit [3]. However, the seedless kiwifruit used in this study occurs naturally, suggesting an expression of specific genes and resulting in changes in metabolites that permit the occurrence of parthenocarpy in kiwifruit. Up to date, most of the kiwifruit transcriptome studies were generated short-reads using second-generation sequencing technology on the Illumina platform, hindering the accurate assembly of full-length transcripts [12,16,43]. In this study, using PacBio SMRT-Seq platform (Pacific Biosciences, Menlo Park, CA, USA), 161,390 CCS with an average 1907bp were obtained, the total number of transcripts were 80,615, and total genes were 52,406 in the seedless kiwifruit cultivar ‘Chengxiang’ (Table 1). As was the same with other reports [44,45], our results have also suggested that PacBio SMRT-Seq was efficient for full-length cDNA sequencing and provided an abundant resource for further functional genomics analysis in seedless kiwifruit.
The BLAST searches against the eight databases (NR, COG, EggNOG, KOG, Pfam, Swiss-prot, GO, and KEGG) allowed the successful annotation of 90.79% (52,406) transcripts with high E-values (Table S2, Figure 2A). With GO terms, transcripts were associated with the cell in cellular component, metabolic processes in biological processes, and catalytic activity in molecular functions, which were enriched in subcategories (Figure 2C). Based on similarity hits against the KEGG database, 48.26% of transcripts were found to be involved in 129 functional pathway, confirming the advantage of full-length transcripts for discovering candidate genes involved in various biosynthesis pathways, especially for carbon metabolism, protein processing in the endoplasmic reticulum, and the biosynthesis of amino acids. Overall, the results might provide a foundation to identify genetic networks and gene expression and regulation for desirable traits in seedless kiwifruit. Additionally, lncRNAs are regulated with gene expression, transcriptional and post-transcriptional levels during plant growth, development, and biological stress [46,47,48]. A total of 7289 lncRNA transcripts were identified, utilizing four analytical methods in ‘Chengxiang’ (Figure S3). Their function in seedless kiwifruit need to be further investigated in more detail. Furthermore, some important transcription factors were determined in ‘Chengxiang’. TFs play crucial roles in many biological and developmental processes in plants by their regulation of spatiotemporal gene expression, e.g., NAC, ERF, and MYB, etc. [49]. In this study, a total of 145 transcripts were identified in the NAC gene networks. Li et al. found that NAC plays a positive role in the salt tolerance regulation mechanism in kiwifruit [49]. In addition, we identified 168 ERF TFs, which may regulate soluble sugar accumulation in kiwifruit [50]. In total, 141 transcripts were annotated as being MYB transcription factors, which modulate chlorophyll and carotenoid accumulation, via regulation of key metabolic genes [51]. TFs regulate diverse plant developmental processes and understanding their roles is important for developing new cultivars.
The flavonoid biosynthesis pathway is responsible for the synthesis of important compounds involved in various biological functions in plants [52], including flower pigmentation, pollen fertility, antioxidant functions [53], and protection from UV radiation [54]. However, a relation between parthenocarpic fruit development and flavonoids has never been described, it is a truism that flavonoids play a significant role in plant reproduction [1,2]. The flavonoid biosynthetic pathway is well-characterized in other parthenocarpic plants such as tomato [1,2], citrus [3], and litchi [5], however, no such studies were conducted in seedless kiwifruit. In this study, we examined in detail the enzymes associated with flavonoid biosynthesis pathway (Figure 4). A large number of flavonoid-related genes were identified in our full-length transcriptome data (Table 2 and Table S4). When compared with other plant species, the types of key enzymes involved in flavonoid biosynthesis found in this transcriptome study are not much different, including CHS (WZCX_transcript_66409, WZCX_transcript_69406), C4H (WZCX_transcript_28878), FLS (WZCX_transcript_11905), F3H (WZCX_transcript_59962), DFR (WZCX_transcript_10695), LAR (WZCX_transcript_10801), and HCT (WZCX_transcript_8458) (Table 2, Figure 5). This is consistent with most of the candidate genes involved in flavonoid synthesis found in the A. arguta transcriptome [12]. These genes are likely candidates, by genetic manipulation, for improving or modifying the content of flavonoids compounds in seedless kiwifruit. In addition to known candidate genes, further research should be performed t better understand the role of flavonoids in hormone-related processes such as the growth and development of parthenocarpic fruits.
According to a previous study, genomic and cDNA sequences encoding for CHS have been characterized, and the expression of endogenous CHS genes has been studied in detail [1,3]. Further evidence of silencing of CHS genes has been indicated to result in parthenocarpic processes, with decreased levels of total flavonoids [1,2]. In the seedless kiwifruit cultivar ‘Chengxiang’, we identified 13 CHS genes and characterized the CHS gene family. The CHS gene is a typical gene family, with a gene coding region that is very conserved [55]. Our study also confirmed that CHS genes was highly conserved by alignment with the amino acid sequences and motif structure (Figure 6). Moreover, regarding the function of genes, the CHS gene plays an essential role in plant stress resistance, secondary metabolite synthesis, and physiological development [56]. However, the specific mechanism needs further study to prove in seedless kiwifruit.
In summary, the fruit set of parthenocarpy is a complicated process, and we know little about it in seedless kiwifruit. The genes identified in our data will facilitate the dissection of the molecular and genetic basis of flavonoid biosynthesis in seedless kiwifruit. The findings also contribute to our understanding the molecular mechanisms of parthenocarpy.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d14060424/s1, Figure S1: (A) Numbers and length distributions of 161,390 circular consensus (CCS) reads, (B) 145,210 full-length nonchimeric (FLNC) sequences, and (C) 80,615 high-quality full-length consensus transcripts with PacBio single-molecule realtime sequencing in seedless kiwifruit, Figure S2: Clusters of enKaryotic Ortholog Groups (KOG) classification, Figure S3: Venn diagram of long non-coding RNAs (lncRNAs). CPC: coding potential calculator; CNCI: cod-ing-noncoding index; CPAT: coding potential assessment tool; Pfam: protein families, Table S1: qRT-PCR primers for key enzyme genes of flavonoid metabolism pathway, Table S2: Summary of transcriptome data and functional annotation of seedless kiwifruit, Table S3: Summary of SSR results of seedless kiwifruit, Table S4: Annotated transcripts in the flavonoid biosynthesis pathway.

Author Contributions

Y.Z. designed the study; Y.J., Y.-P.W., F.-W.W., L.Z., G.Y., Y.-L.W. and Y.Z. undertook field research and sampling; Y.J. and Y.-P.W. conducted the data analysis; Y.Z. and Y.J. wrote and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Shaanxi Academy of Sciences (NO. 2019k-01 (2021)); the Science and Technology Department of Shaanxi Province (NO. 2020NY-044, 2019TG-005, 2021NY-058); and the Xi’an Science and Technology Bureau (NO. 20193028YF016NS016, 20NYYF0003).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The PacBio SMRT-seq raw reads of this study was deposited NCBI under the following accession number SRR19075498 (Sequence Read Archive number; https://www.ncbi.nlm.nih.gov/sra/, accessed on 9 May 2022).

Acknowledgments

We are grateful to Jun-Ying Qian for helpful suggestions and comments to our text.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Schijlen, E.G.W.M.; Ric de Vos, C.H.; Martens, S.; Jonker, H.H.; Rosin, F.M.; Molthoff, J.W.; Tikunov, Y.M.; Angenent, G.C.; van Tunen, A.J.; Bovy, A.G. RNA interference silencing of chalcone synthase, the first step in the flavonoid biosynthesis pathway, leads to parthenocarpic tomato fruits. Plant Physiol. 2007, 144, 1520–1530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Ingrosso, I.; Bonsegna, S.; Domenico, S.D.; Laddomada, B.; Blando, F.; Santino, A.; Giovinazzo, G. Over-expression of a grape stilbene synthase gene in tomato induces parthenocarpy and causes abnormal pollen development. Plant Physiol. Biochem. 2011, 49, 1092–1099. [Google Scholar] [CrossRef] [PubMed]
  3. Zhang, S.J.; Shi, Q.C.; Albrecht, U.; Shatters Jr, R.G.; Stange, R.; McCollum, G.; Zhang, S.; Fan, C.M.; Stover, E. Comparative transcriptome analysis during early fruit development between three seedy citrus genotypes and their seedless mutants. Hortic. Res. 2017, 4, 17041. [Google Scholar] [CrossRef] [PubMed]
  4. Rotino, G.L.; Perri, E.; Zottini, M.; Sommer, H. Genetic engineering of parthenocarpic plants. Nat. Biotechnol. 1997, 15, 1398–1401. [Google Scholar] [CrossRef]
  5. Liu, W.; Chen, M.S.; Bai, L.J.; Zhuang, Z.H.; Fan, C.; Jiang, N.H.; Zhao, J.S.; Ma, S.P.; Xiang, X. Comprehensive transcriptomics and proteomics analyses of pollinated and parthenocarpic litchi (Litchi chinensis sonn.) fruits during early development. Sci. Rep. 2017, 7, 5401. [Google Scholar] [CrossRef]
  6. Varoquaux, F.; Blanvillain, R.; Delseny, M.; Gallois, P. Less is better: New approaches for seedless fruit production. Trends Biotechnol. 2000, 18, 233–242. [Google Scholar] [CrossRef]
  7. Gillaspy, G.; Ben-David, H.; Gruissem, W. Fruits: A developmental perspective. Plant Cell 1993, 5, 1439–1451. [Google Scholar] [CrossRef] [Green Version]
  8. Vivian-Smith, A.; Koltunow, A.M. Genetic analysis of growth-regulator-induced parthenocarpy in Arabidopsis. Plant Physiol. 1999, 121, 437–451. [Google Scholar] [CrossRef] [Green Version]
  9. Koes, R.; Verweij, W.; Quattrocchio, F. Flavonoids: A colourful model for the regulation and evolution of biochemical pathways. Trends Plant Sci. 2005, 10, 236–242. [Google Scholar] [CrossRef]
  10. Ylstra, B.; Touraev, A.; Benito Moreno, R.M.; Stoger, E.; van Tunen, A.J.; Vicente, O.; Mol, J.N.M.; Heberle-Bors, E. Flavonols stimulate development, germination and tube growth of tobacco pollen. Plant Physiol. 1992, 100, 902–907. [Google Scholar] [CrossRef] [Green Version]
  11. Wu, H.L.; Ma, T.; Kang, M.H.; Ai, F.D.; Zhang, J.L.; Dong, G.Y.; Liu, J.Q. A high-quality Actinidia chinensis (kiwifruit) genome. Hortic. Res. 2019, 6, 117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Li, Y.; Fang, J.; Qi, X.; Lin, M.; Zhong, Y.; Sun, L.; Cui, W. Combined analysis of the fruit metabolome and transcriptome reveals candidate genes involved in flavonoid biosynthesis in Actinidia arguta. Int. J. Mol. Sci. 2018, 19, 1471. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Almeida, D.; Pinto, D.; Santos, J.; Vinha, A.F.; Palmeira, J.; Ferreira, H.N.; Rodrigues, F.; Oliveira, M.B.P. Hardy kiwifruit leaves (Actinidia arguta): An extraordinary source of value-added compounds for food industry. Food Chem. 2018, 259, 113–121. [Google Scholar] [CrossRef] [PubMed]
  14. Li, Y.; Fang, J.; Qi, X.; Lin, M.; Zhong, Y.; Sun, L. A key structural gene, AaLDOX, is involved in anthocyanin biosynthesis in all red-fleshed kiwifruit (Actinidia arguta) based on transcriptome analysis. Gene 2018, 648, 31–41. [Google Scholar] [CrossRef] [PubMed]
  15. Li, Y.; Cui, W.; Wang, R.; Lin, M.; Fang, J. Microrna858-mediated regulation of anthocyanin biosynthesis in kiwifruit (Actinidia arguta) based on small RNA sequencing. PLoS ONE 2019, 14, e0217480. [Google Scholar] [CrossRef] [PubMed]
  16. Tan, C.H.; Wang, Z.G.; Feng, X.L.; Pan, B.T.; Irfan, M.; Liu, C.J. Transcriptomic and metabolomics of flavonoid compounds in Actinidia arguta var. Arguta. J. King Saud Univ. Sci. 2021, 33, 101605. [Google Scholar] [CrossRef]
  17. Wojdyło, A.; Nowicka, P. Anticholinergic effects of Actinidia arguta fruits and their polyphenol content determined by liquid chromatography-photodiode array detector-quadrupole/time off light-mass spectrometry (LC-MS-PDA-Q/TOF). Food Chem. 2019, 271, 216–223. [Google Scholar] [CrossRef]
  18. Matich, A.J.; Young, H.; Allen, J.M.; Wang, M.Y.; Fielder, S.; McNeilage, M.A.; MacRae, E.A. Actinidia arguta: Volatile compounds in fruit and flowers. Phytochemistry 2003, 63, 285–301. [Google Scholar] [CrossRef]
  19. Jang, D.S.; Lee, G.Y.; Lee, Y.M.; Kim, Y.S.; Sun, H.; Kim, D.H.; Kim, J.S. Flavan-3-ols having a g-Lactam from the roots of Actinidia arguta inhibit the formation of advanced glycation end products in Vitro. Chem. Pharm. Bull. 2009, 57, 397–400. [Google Scholar] [CrossRef] [Green Version]
  20. Song, H.; Yang, M.; Yu, Z.; Zhang, T. Characterization of the whole transcriptome of whelk Rapana venosa by single-molecule mRNA sequencing. Mar. Genom. 2019, 44, 74–77. [Google Scholar] [CrossRef]
  21. Li, W.; Jaroszewski, L.; Godzik, A. Tolerating some redundancy significantly speeds up clustering of large protein databases. Bioinformatics 2002, 18, 77–82. [Google Scholar] [CrossRef] [PubMed]
  22. Tatusov, R.L.; Galperin, M.Y.; Natale, D.A.; Koonin, E.V. The COG database: A tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000, 28, 33–36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Tatusov, R.L.; Fedorova, N.D.; Jackson, J.D.; Jacobs, A.R.; Kiryutin, B.; Koonin, E.V.; Krylov, D.M.; Mazumder, R.; Mekhedov, S.L.; Nikolskaya, A.N. The COG database: An updated version includes eukaryotes. BMC Bioinform. 2003, 4, 41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Huerta-Cepas, J.; Szklarczyk, D.; Heller, D.; Hernández-Plaza, A.; Forslund, S.K.; Cook, H.; Mende, D.R.; Letunic, I.; Rattei, T.; Jensen, L.J.; et al. eggNOG 5.0: A hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019, 47, D309–D314. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Mistry, J.; Chuguransky, S.; Williams, L.; Qureshi, M.; Salazar, G.A.; Sonnhammer, E.L.L.; Tosatto, S.C.E.; Paladin, L.; Raj, S.; Richardson, L.J.; et al. Pfam: The protein families database in 2021. Nucleic Acids Res. 2021, D412–D419. [Google Scholar] [CrossRef]
  26. Bairoch, A.; Apweiler, R. The SWISS-PROT protein sequence database and its supplement TrEMBL. Nucleic Acids Res. 2000, 28, 45–48. [Google Scholar] [CrossRef]
  27. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Harris, M.A. Gene ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef] [Green Version]
  28. Kanehisa, M.; Goto, S.; Kawashima, S.; Okuno, Y.; Hattori, M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004, 32, D277–D280. [Google Scholar] [CrossRef] [Green Version]
  29. Conesa, A.; Götz, S.; García-Gómez, J.M.; Terol, J.; Talon, M.; Robles, M. Blast2GO: A universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21, 3674–3676. [Google Scholar] [CrossRef] [Green Version]
  30. Mao, X.; Cai, T.; Olyarchuk, J.G.; Wei, L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 2005, 21, 3787–3793. [Google Scholar] [CrossRef]
  31. Sun, L.; Luo, H.; Bu, D.; Zhao, G.; Yu, K.; Zhang, C.; Zhao, Y. Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic Acids Res. 2013, 41, e166. [Google Scholar] [CrossRef] [PubMed]
  32. Kong, L.; Zhang, Y.; Ye, Z.Q.; Liu, X.Q.; Zhao, S.Q.; Wei, L.; Gao, G. CPC: Assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res. 2007, 35, W345–W349. [Google Scholar] [CrossRef] [PubMed]
  33. Finn, R.D.; Coggill, P.; Eberhardt, R.Y.; Eddy, S.R.; Mistry, J.; Mitchell, A.L.; Salazar, G.A. The Pfam protein family’s database: Towards a more sustainable future. Nucleic Acids Res. 2016, 44, D279–D285. [Google Scholar] [CrossRef] [PubMed]
  34. Wang, L.G.; Park, H.J.; Dasari, S.; Wang, S.Q.; Kocher, J.P.; Li, W. CPAT: Coding-potential assessment tool using an alignment-free logistic regression model. Nucleic Acids Res. 2013, 41, e74. [Google Scholar] [CrossRef] [PubMed]
  35. Zheng, L.; Jiao, W.; Song, H.; Qu, H.; Li, D.; Mei, H.; Tong, Q. miRNA-558 promotes gastric cancer progression through attenuating Smad4-mediated repression of heparanase expression. Cell Death Dis. 2016, 7, e2382. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Beier, S.; Thiel, T.; Münch, T.; Scholz, U.; Mascher, M. MISA-web: A web server for microsatellite prediction. Bioinformatics 2017, 33, 2583–2585. [Google Scholar] [CrossRef] [Green Version]
  37. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2DDCt method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  38. Rédei, G.P. CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting, Position-Specific Gap Penalties and Weight Matrix Choice. Nucleic Acids Res. 1994, 22, 4673–4680. [Google Scholar]
  39. Tamura, K.; Stecher, G.; Peterson, D.; Filipski, A.; Kumar, S. MEGA6: Molecular evolutionary genetics analysis version 6. Mol. Biol. Evol. 2013, 30, 2725–2729. [Google Scholar] [CrossRef] [Green Version]
  40. Bailey, T.L.; Boden, M.; Buske, F.A.; Frith, M.; Grant, C.E.; Clementi, L.; Ren, J.; Li, W.W.; Noble, W.S. MEME Suite: Tools for motif discovery and searching. Nucleic Acids Res. 2009, 37, 202–208. [Google Scholar] [CrossRef]
  41. Nvh, A.; Rjh, B. Iso-Seq Long Read Transcriptome Sequencing. In Comprehensive Foodomics; Cifuentes, A., Ed.; Elsevier: Amsterdam, The Netherlands, 2021; pp. 486–500. [Google Scholar]
  42. Wang, Z.B.; Yu, Q.B.; Shen, W.X.; El Mohtar, C.A.; Zhao, X.C.; Gmitter, F.G., Jr. Functional study of CHS gene family members in citrus revealed a novel chs gene affecting the production of flavonoids. BMC Plant Biol. 2018, 18, 189. [Google Scholar] [CrossRef] [PubMed]
  43. Li, W.B.; Liu, Y.F.; Zeng, S.H.; Xiao, G.; Wang, G.; Wang, Y.; Peng, M.; Huang, H.W. Gene expression profiling of development and anthocyanin accumulation in kiwifruit (Actinidia chinensis) based on transcriptome sequencing. PLoS ONE 2015, 10, e0136439. [Google Scholar]
  44. Zuo, C.; Matthew, B.; Avinash, S.; Kuo, R.C.; Kunde, R.G.; Torres-Jerez, I.; Li, G.F.; Wang, M.; Dilworth, D.; Barry, K.; et al. Revealing the transcriptomic complexity of switchgrass by pacbio long-read sequencing. Biotechnol. Biofuels 2018, 11, 170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Chen, S.; Qiu, G.; Yang, M. SMRT sequencing of full-length transcriptome of seagrasses. Sci. Rep. 2019, 9, 14537. [Google Scholar] [CrossRef] [PubMed]
  46. Wang, B.; Tseng, E.; Regulski, M.; Clark, T.A.; Hon, T.; Jiao, Y.; Lu, Z.; Olson, A.; Stein, J.C.; Ware, D. Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing. Nat. Commun. 2016, 7, 11708. [Google Scholar] [CrossRef] [Green Version]
  47. Karlik, E.; Marakli, S.; Gozukirmizi, N. Two lncRNAs expression profiles in salt stressed barley (Hordeum vulgare L.) roots. Cytologia 2018, 83, 37–43. [Google Scholar] [CrossRef] [Green Version]
  48. Wang, J.; Lin, J.; Kan, J.; Wang, H.; Li, X.; Yang, Q.; Li, H.; Chang, Y. Genome-wide identification and functional prediction of novel drought-responsive LncRNAs in Pyrus betulifolia. Genes 2018, 9, 311. [Google Scholar] [CrossRef] [Green Version]
  49. Li, M.; Wu, Z.; Gu, H.; Cheng, D.; Guo, X.; Li, L.; Shi, C.; Xu, G.; Gu, S.; Abid, M.; et al. AvNAC030, a NAC Domain Transcription Factor, Enhances Salt Stress Tolerance in Kiwifruit. Int. J. Mol. Sci. 2021, 22, 11897. [Google Scholar] [CrossRef]
  50. Wang, R.C.; Shu, P.; Zhang, C.; Zhang, J.L.; Chen, Y.; Zhang, Y.X.; Du, K.; Xie, Y.; Li, M.Z.; Ma, T.; et al. Integrative analyses of metabolome and genome-widetranscriptome reveal the regulatory network governing flavor formation in kiwifruit (Actinidia chinensis). New Phytol. 2022, 233, 373–389. [Google Scholar] [CrossRef]
  51. Ampomah-Dwamena, C.; Thrimawithana, A.H.; Dejnoprat, S.; Lewis, D.; Espley, R.V.; Allan, A.C. A kiwifruit (Actinidia deliciosa) R2R3-MYB transcription factor modulates chlorophyll and carotenoid accumulation. New Phytol. 2019, 221, 309–325. [Google Scholar] [CrossRef] [Green Version]
  52. Liu, Y.Y.; Chen, X.R.; Wang, J.P.; Cui, W.Q.; Xing, X.X.; Chen, X.Y.; Ding, W.Y.; God’spower, B.O.; Eliphaz, N.; Sun, M.Q.; et al. Transcriptomic analysis reveals flavonoid biosynthesis of Syringa oblata Lindl. in response to different light intensity. BMC Plant Biol. 2019, 19, 487. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Agati, G.; Azzarello, E.; Pollastri, S.; Tattini, M. Flavonoids as antioxidants in plants: Location and functional significance. Plant Sci. 2012, 196, 67–76. [Google Scholar] [CrossRef] [PubMed]
  54. Nakatsuka, T.; Saito, M.; Yamada, E.; Fujita, K.; Kakizaki, Y.; Nishihara, M. Isolation and characterization of GtMYBP3 and GtMYBP4, orthologues of R2R3-MYB transcription factors that regulate early flavonoid biosynthesis, in gentian flowers. J. Exp. Bot. 2012, 63, 6505–6517. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Wani, T.A.; Pandith, S.A.; Gupta, A.P.; Chandra, S.; Sharma, N.; Lattoo, S. Molecular and functional characterization of two isoforms of chalcone synthase and their expression analysis in relation to flavonoid constituents in Grewia asiatica L. PLoS ONE 2017, 12, e0179155. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Campos, É.; Hamdan, F.F. Cloning of the chaperonin t-complex polypeptide 1 gene from Schistosoma mansoni and studies of its expression levels under heat shock and oxidative stress. Parasitol. Res. 2000, 86, 253–258. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Varying colors of fruits of seedless kiwifruit cultivar ‘Chengxiang’ (Actinidia arguta).
Figure 1. Varying colors of fruits of seedless kiwifruit cultivar ‘Chengxiang’ (Actinidia arguta).
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Figure 2. (A) Function annotation of unique transcripts in NR, COG, EggNOG, KOG, Pfam, Swiss-prot, GO, and KEGG databases. (B) Homologous species distribution diagram of transcripts in NCBI nonredundant protein sequences. (C) Gene Ontology (GO) classification of unique transcripts of seedless kiwifruits.
Figure 2. (A) Function annotation of unique transcripts in NR, COG, EggNOG, KOG, Pfam, Swiss-prot, GO, and KEGG databases. (B) Homologous species distribution diagram of transcripts in NCBI nonredundant protein sequences. (C) Gene Ontology (GO) classification of unique transcripts of seedless kiwifruits.
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Figure 3. Distribution of transcription factor types in seedless kiwifruits.
Figure 3. Distribution of transcription factor types in seedless kiwifruits.
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Figure 4. The flavonoid biosynthetic pathways (Ko00491) were adapted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, available online (http://www.genome.jp/kegg/pathway.html). A total of 98 transcripts were identified by KEGG as encoding for 14 key enzymes (green color) and many metabolites (orange color) were found in seedless kiwifruits ‘Chengxiang’.
Figure 4. The flavonoid biosynthetic pathways (Ko00491) were adapted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, available online (http://www.genome.jp/kegg/pathway.html). A total of 98 transcripts were identified by KEGG as encoding for 14 key enzymes (green color) and many metabolites (orange color) were found in seedless kiwifruits ‘Chengxiang’.
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Figure 5. Gene expression involved in flavonoid biosynthesis by qRT-PCR in kiwifruit flowers. Bar represents means ± SDs (n = 3).
Figure 5. Gene expression involved in flavonoid biosynthesis by qRT-PCR in kiwifruit flowers. Bar represents means ± SDs (n = 3).
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Figure 6. (A) The phylogenetic tree was constructed among seedless kiwifruits CHS proteins based on MEGA 6.0 software (Mega Limited, Auckland, New Zealand). (B) The motif composition of seedless kiwifruits CHS proteins. The motifs, numbers 1–15, are displayed in different colored boxes.
Figure 6. (A) The phylogenetic tree was constructed among seedless kiwifruits CHS proteins based on MEGA 6.0 software (Mega Limited, Auckland, New Zealand). (B) The motif composition of seedless kiwifruits CHS proteins. The motifs, numbers 1–15, are displayed in different colored boxes.
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Table
Table 1. Summary of platforms used to establish gene sets in the seedless kiwifruit cultivar ‘Chengxiang’.
Table 1. Summary of platforms used to establish gene sets in the seedless kiwifruit cultivar ‘Chengxiang’.
DataPlatformNumber of Sequence
Circular Consensus (CCS) readsSMRT161,390
Number of full-length non-chimeric readsSMRT145,210
High quality consensus sequenceIsoSeq80,615
Nonredundant transcriptsCD-HIT57,721
Table
Table 2. List of candidate genes comprising flavonoid biosynthesis pathways involved in the seedless kiwifruit cultivar ‘Chengxiang’.
Table 2. List of candidate genes comprising flavonoid biosynthesis pathways involved in the seedless kiwifruit cultivar ‘Chengxiang’.
GeneEnzymeEnzyme CodeKEGG IDTranscripts
CHSchalcone synthase EC:2.3.1.74K0066015
CHIchalcone isomerase EC:5.5.1.6K018592
FLSflavonol synthase EC:1.14.11.23K0527812
F3′5′Hflavonoid 3′,5′-hydroxylaseEC:1.14.13.88K130832
DFRbifunctional dihydroflavonol 4-reductase/flavanone 4-reductase EC:1.1.1.219 1.1.1.234K130825
ANSanthocyanidin synthase EC:1.14.11.19K0527716
F3Hnaringenin 3-dioxygenase EC:1.14.11.9K004758
C4Htrans-cinnamate 4-monooxygenase EC:1.14.13.11K004874
F3′Hflavonoid 3′-monooxygenase EC:1.14.13.21K052803
F3′H1coumaroylquinate(coumaroylshikimate) 3′-monooxygenase EC:1.14.13.36K097541
LARleucoanthocyanidin reductase EC:1.17.1.3K130817
ANRanthocyanidin reductase EC:1.3.1.112K211023
CoAOMTcaffeoyl-CoA O-methyltransferase EC:2.1.1.104K005887
HCTshikimate O-hydroxycinnamoyltransferase EC:2.3.1.133K1306513
Table
Table 3. Basic characteristic of CHS genes in the seedless kiwifruit cultivar ‘Chengxiang’.
Table 3. Basic characteristic of CHS genes in the seedless kiwifruit cultivar ‘Chengxiang’.
Gene NameAccession NumberAmino AcidMolecular Weight (Da)Isoelectric PointsInstability IndexAliphatic Index
AaCHS1 WZCX_transcript_1009939042,660.456.2335.5991
AaCHS2 WZCX_transcript_1024439042,604.356.1835.8692.49
AaCHS3 WZCX_transcript_1937839042,660.456.2335.5991
AaCHS4 WZCX_transcript_3602325327,030.285.8129.58103.69
AaCHS5 WZCX_transcript_4352725027,236.335.4235.7793.61
AaCHS6 WZCX_transcript_4835725827,916.15.0549.896.07
AaCHS7 WZCX_transcript_4879513614,672.814.8826.48101.85
AaCHS8 WZCX_transcript_5090919921,321.536.2133.1897.07
AaCHS9 WZCX_transcript_6536541845,562.476.7236.5388.37
AaCHS10 WZCX_transcript_6640938942,499.246.7336.8191.21
AaCHS11 WZCX_transcript_6940641645,498.496.9635.7288.1
AaCHS12 WZCX_transcript_952939042,662.396.0436.0892.49
AaCHS13 WZCX_transcript_997541645,480.436.6736.1888.1
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Jia, Y.; Wu, Y.-P.; Wang, F.-W.; Zhang, L.; Yu, G.; Wang, Y.-L.; Zhang, Y. Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta). Diversity 2022, 14, 424. https://doi.org/10.3390/d14060424

AMA Style

Jia Y, Wu Y-P, Wang F-W, Zhang L, Yu G, Wang Y-L, Zhang Y. Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta). Diversity. 2022; 14(6):424. https://doi.org/10.3390/d14060424

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Jia, Yun, Yong-Peng Wu, Feng-Wei Wang, Lei Zhang, Gang Yu, Ya-Ling Wang, and Ying Zhang. 2022. "Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta)" Diversity 14, no. 6: 424. https://doi.org/10.3390/d14060424

APA Style

Jia, Y., Wu, Y. -P., Wang, F. -W., Zhang, L., Yu, G., Wang, Y. -L., & Zhang, Y. (2022). Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta). Diversity, 14(6), 424. https://doi.org/10.3390/d14060424

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