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Article

Using Isoform Sequencing for De Novo Transcriptome Sequencing and the Identification of Genes Related to Drought Tolerance and Agronomic Traits in Tall Fescue (Festuca arundinacea Schreb.)

by
Chunyan Yang
1,2,†,
Li Zhong
2,3,4,†,
Erling Ou
2,
Fang Tian
2,3,
Mei Yao
2,3,
Ming Chen
5,
Xu Yan
1,
Yingzheng Li
1,
Xiaofeng Li
1,
Ruyu He
1,
Jianmei He
1,
Qilin Tang
1,* and
Degang Zhao
4
1
Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
2
Guizhou Institute of Prataculture, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
3
Guizhou Qian-Da Institute of Eco-Environment & Health, Guiyang 550025, China
4
The Key Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region, Guizhou University, Guiyang 550025, China
5
National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2023, 13(6), 1484; https://doi.org/10.3390/agronomy13061484
Submission received: 28 February 2023 / Revised: 17 May 2023 / Accepted: 19 May 2023 / Published: 28 May 2023
(This article belongs to the Special Issue Recognition and Utilization of Natural Genetic Resources for Advances in Plant Biology through Genomics and Biotechnology)
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Abstract

:
Plant height and tillering are the key traits of tall fescue (Festuca arundinacea Schreb.), a perennial turf grass widely used for forage and turf worldwide. It exhibits excellent abiotic stress tolerance. However, the investigation of these traits at the genetic level is limited by the lack of a completely sequenced genome of tall fescue. Here, we generated genome-wide transcriptome data using PacBio isoform sequencing (Iso-Seq) technology. We obtained 73,628 transcripts with an average length of 2410 bp. Among these transcripts, 42,265 (60.09%) were predicted as complete full-length open reading frames. The dataset contained 11,520 simple sequence repeats; 737 bp long non-coding RNAs; and 1599 alternative splicing sites in unigenes. Sixty-three unigenes involved in abscisic acid biosynthesis, catabolism, and signaling pathways were identified. The Illumina-sequencing analysis results, further verified using qRT-PCR, revealed the significant upregulation of nine unigenes under drought stress. Ninety-three unigenes involved in controlling plant height and tillering were also identified, of which FaMAX1 was functionally verified to regulate plant tillering. Our results provide a valuable genetic resource about the complete transcriptome of tall fescue; the identified candidate genes can aid in improving the drought tolerance and agronomic traits in tall fescue and other related plants.

1. Introduction

Tall fescue (Festuca arundinacea Schreb.) is extensively planted in warm temperate to subtropical regions worldwide. Tall fescue is widely used for forage and turf and contributes to soil conservation and environmental protection because of its exceptional resistance to abiotic stress, particularly drought [1,2,3,4,5,6,7]. The mechanism underlying the adaptation of tall fescue to abiotic stress has attracted widespread interest; however, its understanding at the genetic level is rudimentary [5,7]. Plants adapt to adverse abiotic stresses through several survival strategies, including hormone responses. Among them, abscisic acid (ABA), also called a “stress hormone”, is a central regulator of environmental stress response in plants [8,9]. Therefore, several efforts have been made to understand ABA biosynthesis, catabolism, and signaling.
ABA is biosynthesized de novo in plastids and cytoplasm of carotenoids [10,11]. The conversion of zeaxanthin to violaxanthin is catalyzed by zeaxanthin epoxidase (ZEP), after which 9-cis-epoxycarotenoids are formed by rearranging trans-violaxanthin and cleaved to produce xanthoxin by 9-cis-epoxycarotenoid dioxygenase (NCED) [12]. Then, xanthoxin conversion to ABA is catalyzed by two enzymes, ABA2 and AAO3 [12]. ABA is irreversibly catabolized by conversion to phaseic acid through the enzyme ABA-8′-hydroxylase [13,14]. To date, three core components were identified in ABA signaling: ABA receptor family PYR/PYL/RCAR (pyrabactin resistance/pyrabactin-like/regulatory component of ABA receptor) [15,16], group A protein phosphatase 2C (PP2C-A) [17,18], and sucrose nonfermenting-related protein kinase 2 (SnRK2) [19,20]. In the absence of ABA, PP2C-A blocks SnRK2 kinase activity through dephosphorylation. In the presence of ABA, ABA-bound PYR/PYL/RCAR binds to PP2C-A, releasing SnRK2 from PP2C-A inhibition. When SnRK2 is activated, it phosphorylates downstream substrates such as ABA-responsive element-binding transcription factor (AREB/ABF) for gene expression [21]. SnRK2 is the core positive regulator of ABA signaling; for instance, ten SnRK2 genes, designated as SAPK1-10, have been identified in the rice (Oryza sativa) genome [22]. However, how these genes affect adaptation to abiotic stress in tall fescue remains unknown.
Tall fescue is a perennial allohexaploid (2n = 6x = 42) with a large genome size (6 × 103 Mb), approximately 14-fold larger than that of O. sativa [23,24,25]. Next-generation sequencing has generated short, incomplete transcriptome assemblies and provided limited genomic information for this species [26,27,28,29,30]. Recently, isoform sequencing (Iso-Seq) technology developed by Pacific Biosciences has been used to analyze full-length transcriptomes in multiple plant species, such as Triticum aestivum, Morinda citrifolia, Salvia miltiorrhiza, Zea mays, Panax ginseng, and Astragalus membranaceus [31,32,33,34,35,36,37]. Unlike other methods, Iso-Seq produces full-length transcripts without assembly and is a much better system for genome annotation, the identification of novel genes and isoforms, the discovery of long non-coding RNA (lncRNA) sequences, and the detection of alternative splicing (AS) events. Therefore, we hypothesized that Iso-Seq would provide a new strategy for an in-depth overview of the tall fescue transcriptome and identify genes regulating drought tolerance and important agronomic traits in tall fescue.
In this study, we generated full-length transcriptome data of tall fescue using Iso-Seq and performed systematic functional annotation; unigenes, lncRNAs, and AS events were identified. Furthermore, we identified genes involved in ABA biosynthesis, catabolism, and signaling in tall fescue under drought stress. We also analyzed unigenes related to agronomic traits, including plant height and tillering.

2. Materials and Methods

2.1. Plant Sampling and RNA Isolation

A commercial-type tall fescue ‘Qiancao No.1’ (provided by Guizhou Institute of Prataculture, Guizhou Academy of Agricultural Sciences, China) was seeded in a plastic pot (7.5 cm in diameter and 9.0 cm deep) filled with pearl stone and vermiculite (1:1, v/v). After germination, the plants were transferred to a greenhouse with a daily maximum/minimum temperature of 24/20 °C for a 16 h photoperiod (300 μmol photons m−2 s−1 PAR) for 15 d, allowing the roots and shoots to establish. Then, plants were harvested and washed with distilled water prior to snap-freezing in liquid nitrogen. RNA was extracted using a Spectrum Plant Total RNA Kit (Sigma-Aldrich, Sydney, Australia) following the manufacturer’s instructions.

2.2. cDNA Synthesis and PacBio Iso-Seq

The quality of extracted RNAs was evaluated using an Agilent 2100 Bioanalyzer (SA Pathology, Adelaide, Australia). High-quality RNAs were used for cDNA synthesis and library construction using a SMARTer PCR cDNA Kit (Clontech, Mountain View, CA, USA). First-strand cDNA was synthesized from the total RNA using SMART Scribe Reverse Transcriptase (Clontech, Mountain View, CA, USA), SMARTer II A Oligonucleotide (Clontech, Mountain View, CA, USA), and 3′ SMART CDS Primer II A (Clontech, Mountain View, CA, USA). The second strand was synthesized and amplified using 5′ PCR Primer II A. Size selection was carried out on a BluePippin (Sage Science, Beverly, MA, USA) with three bin sizes: 1–2, 2–3, and 3–6 kb. Two and one SMRT cells were used for sequencing the three libraries, respectively. SMRTbell template libraries were prepared from these cDNAs and sequenced on a PacBio RS II system as recommended by Pacific Biosciences (Palo Alto, CA, USA).

2.3. Iso-Seq Data Processing

The standard RS Iso-Seq protocol (SMRT Analysis 2.3) was used to process raw sequencing data [38]. Raw reads were processed into error-corrected reads of inserts (ROIs) using the ToFu pipeline with default parameters. Full-length (FL), non-chimeric transcripts were selected by searching for poly (A) tail signals and 5′ and 3′ cDNA primers in the ROIs. Iterative clustering for error correction was used to obtain consensus isoforms, which were polished using Quiver. FL transcripts with post-correction accuracy above 99% were generated for further analysis. Redundancy was removed from these high-quality FL transcripts using CD-HIT (Identity > 0.99) [39].

2.4. Coding Sequences (CDS) Detection and Functional Annotation

Protein CDs were identified using a TransDecoder set to the following criteria [40]: (1) a minimum-length open reading frame (ORF) is found in a transcript sequence; (2) a log-likelihood score of >0 is similar to that computed using the GeneID software [41]; (3) the coding score for ORF is greatest when the ORF is scored in the first reading frame as compared to scores in the other two forward reading frames; (4) if the coordinates of another candidate ORF fully encapsulate a candidate ORF, the longer one is reported; however, a single transcript could report multiple ORFs (allowing for operons and chimeras); and (5) optional putative peptides with a match to a Pfam domain above the noise cutoff score. For functional annotation, unigenes were searched against the UniProt, NCBI non-redundant (NR), TAIR, and PlantTFDB databases using BLASTX [42]. Protein domains were also searched using InterProScan [43]. Gene ontology (GO) and pathway annotations, using the Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed using Blast2GO [44].

2.5. Simple Sequence Repeat (SSR) and lncRNA Analysis

Simple sequence repeats (SSRs) were searched using the Gramene SSR Finder [45]. Four computational approaches, the coding potential calculator (CPC), coding–non-coding index (CNCI), coding potential assessment tool (CPAT), and protein families database (Pfam), were combined to sort non-protein coding RNA candidates from putative protein-coding RNAs in the unknown transcripts. Putative protein-coding RNAs were filtered using a minimum length and exon number threshold. Transcripts longer than 200 nt and with more than two exons were selected as lncRNA candidates and further screened using CPC, CNCI, CPAT, and Pfam, which have the power to distinguish protein-coding genes from non-coding genes.

2.6. Identification of AS Isoforms

AS isoforms were analyzed as reported previously [37]. In brief, error-corrected non-redundant transcripts (transcripts before Cogent reconstruction) were mapped to UniTransModels. Transcripts with the same splicing junctions were collapsed, whereas those with different splicing junctions were identified as transcription isoforms of UniTransModels. AS events were detected using the computational tool SUPPA on default settings.

2.7. Drought Treatment, TIS108 Treatment, and Illumina Sequencing

The tall fescue plants used in this study were obtained from turfgrass fields in Guiyang City (Guizhou Province, China). Seedlings were established in Petri dishes for 3 d and then transferred to a growth chamber, where they were grown in hydroponic culture with half-strength Hoagland’s nutrient solution. Three treatment protocols were employed. Polyethylene glycol 6000 (PEG, Guangdong Guanghua Sci-tech Co., Ltd., Guanghua, Guangdong, China) was added to the hydroponic solution at a concentration of 20% (w/v) to simulate drought stress for 7 d. In the final treatment assay, 6-phenoxy-1-phenyl-2-(1H-1,2,4-triazol-1-yl) hexan-1-one (TIS108) (StrigoLab, Turin, Italy), which inhibits strigolactone biosynthesis by suppressing the expression of MAX1, one of the key genes involved in strigolactone synthesis, was added to the hydroponic solution at a concentration of 5 μM for 14 d [46].
Total RNA was isolated from samples subjected to the PEG treatment and control and purified using an RNeasy plant mini kit (Qiagen, Valencia, CA, USA). Biotin-oligo (dT) magnetic beads were used to isolate mRNA from each total RNA sample (Illumina, San Diego, CA, USA). The isolated mRNAs were randomly cleaved into small fragments using a fragmentation buffer, which were then used to synthesize first-strand cDNA with random hexamer primers and M-MuLV reverse transcriptase (RNase H). Sample libraries were sequenced using the Illumina HiSeq 2000 platform (Illumina).

2.8. Identification and Validation of Differentially Expressed Isoforms

The clean paired-end reads obtained via Illumina sequencing were mapped to the newly generated transcriptome to identify all differentially expressed isoforms. The software package RSEM was used to count the read numbers mapped to each isoform [43]. Based on the length of the isoforms and the read counts, the fragments per kilobase of transcript per million fragments mapped (FPKM) of each isoform were calculated. Finally, differential expression analysis was performed for the PEG and control treatments using the DESeq R package (version 1.10.1) (Anders S and Huber W, Heidelberg, Germany). Isoforms with an adjusted p-value < 0.05 were identified as differentially expressed.
Reverse transcription–quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate differentially expressed isoforms. Total RNA was isolated from the samples subjected to the drought and TIS108 treatments and the control. First-strand cDNA was synthesized using the one-step SYBR1 prime Script1 RT-PCR kit (Takara Bio Inc., Dalian, China). Using a CFX96™ Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA, USA) and SYBR Premix Ex Taq (Takara Bio Inc.), the cycle threshold (CT) values of triplicate samples were recorded and then further calculated using the 2−∆∆Ct method. The FaTublin gene was used as the reference gene; the primers used are provided in Supplementary Table S1.

2.9. Statistical Analysis

Each experiment was repeated at least three times. Statistical analyses were performed using analysis of variance (ANOVA) followed by Duncan’s multiple range tests. Means were considered significantly different at a p-value of <0.05.

3. Results

3.1. Transcriptome Sequencing of Tall Fescue Using Iso-Seq

PacBio RS II sequencing of three Iso-Seq libraries and five cells generated 4.02 million sequencing subreads (Supplementary Table S2) and 120,746; 112,281; and 69,425 ROIs from the three libraries (Supplementary Table S3). ROIs from different libraries were classified into 43,204; 50,050; and 37,692 FL non-chimeric transcripts, depending on whether 5′ and 3′ primer sequences or poly (A) tails were detected. FL non-chimeric transcripts accounted for 35.8% of ROI (Supplementary Table S4). After clustering and polishing the non-chimeric transcripts, 79,577 high-quality consensus isoforms were generated (Figure 1A, Supplementary Table S5), which were merged into 73,628 unigenes with an average length of 2410 bp and N50 of 2725 bp, accounting for approximately 173.3 Mb in cumulative length (Supplementary Table S6). ORFs were found in 70,339 unigenes (95.53%), and 42,265 of these (60.09%) were predicted to be complete full-length ORFs. The lengths of the encoded proteins mostly ranged from 100 to 400 aa (49.02%; Figure 1B).
To further verify the completeness and accuracy of the transcript sequences generated by Iso-Seq, one mycorrhizal symbiosis-related gene, NUP133, which has long coding sequences, was cloned and sequenced. NUP133 contained a 3882 bp ORF encoding a 1293 aa and shared 81.7% of this amino acid sequence with the homologous gene LOC_Os03g12450 in O. sativa (Supplementary Figure S1). These results are consistent with the sequences generated by Iso-Seq, suggesting that a complete FL transcriptome of tall fescue was generated in this study.

3.2. Functional Annotation and Categorization of the Tall Fescue Transcriptome

BLAST and InterProScan showed that 68,806 (93.45%) unigenes called Iso-seq aligned with existing protein sequence databases such as KOG, NR, Swissprot, and Pfam, demonstrating very high hit scores (Figure 2A), whereas 33,143 unigenes (45.01%) had high scores with proteins in all four databases (Figure 2B). Approximately 61,511 unigenes (83.54%) of tall fescue were predicted to be homologous to three model plant genomes: 62,054 of these annotated unigenes showed homology to genes in Arabidopsis, 66,383 unigenes to those in O. sativa, and 66,708 to those in Brachypodium distachyon (Figure 2C). NR annotation showed that B. distachyon had the highest transcriptome similarity to tall fescue (Figure 2D). A total of 1790 unigenes were predicted as transcription factor (TF)-related sequences, and MYB-related (10.67%), bHLH (6.2%), C2H2 (6.2%), WRKY (5.2%), and FAR1 (5.14%) families were the most abundant (Figure 2E).
To classify transcript functions, 57,276 unigenes were assigned GO terms and categorized as molecular functions, cellular components, and biological processes (Figure 3A). Unigenes involved in “cell”, “cell part”, and “organelle” were highly represented in the cellular component category; those involved in “catalytic activity” and “binding” were heavily represented in the molecular functions category; and those involved in “metabolic processes” and “cellular processes” were major subgroups in the biological processes category. To explore the biological functions and interactions of genes in tall fescue, 17,782 unigenes were annotated and assigned to the KEGG database. “Carbon metabolism” and “Spliceosome” were the largest categories (Figure 3B).

3.3. Identification of SSRs, lncRNA, and AS Isoform in the Tall Fescue Transcriptome

A total of 11,520 SSRs were identified for unigenes (Figure 4A). The SSR motifs in di- and tri-nucleotide repeats were primarily CT (accounting for 19.84% of di-nucleotide repeats) and CCG (7.03% of tri-nucleotide repeats) sequences. Di- and trinucleotide repeats also predominated the untranslated regions and ORFs, indicating that transcribed regions in tall fescue can be characterized by SSRs. We also identified 737 transcripts as lncRNAs in the Iso datasets (Supplementary Figure S2), with transcripts ranging mostly from 1000 to 3000 bp (Figure 4B). The functions of these lncRNAs need to be further characterized. A total of 1599 UniTransModel-based AS events were identified; retained introns were identified as the most abundant AS event. Together with alternative 5′- or 3′-end AS events, these three types of AS events accounted for >90% of all detected events (Figure 4C). Moreover, we verified an exon skipping event with a 72 bp deletion in the DKE-like protein, homologous by gene cloning and sequencing, which was consistent with the sequences generated by Iso-Seq (Genes: F01.PB39480, F01.PB49961, and F01.PB44588; Figure 4D).

3.4. Identification and Analysis of Unigenes Related to Drought Response

The screening of the DEGs revealed significant changes in the transcriptome of the treated plants compared to that of the controls (Figure 5A). With the threshold of log2 fold-change ≥ 2 and p-value ≤ 0.01, thousands of genes with changes in their expression were identified (Figure 5B). After the DEGs were annotated and assigned to the KEGG database, we identified 186 differently expressed unigenes related to plant hormone signal transduction (Figure 5C), whereas 709 unigenes related to plant hormone signal transduction were identified previously (Figure 3B).
We identified 63 unigenes related to ABA synthesis, catabolism, and signaling (Supplementary Table S7). qRT-PCR analysis identified nine unigenes that were significantly upregulated under drought stress compared to that under control conditions (Figure 6). These results were consistent with the RNA-seq results, suggesting that these nine unigenes related to ABA synthesis, catabolism, and signaling were involved in drought response in tall fescue.

3.5. Identification and Functional Analysis of Unigenes Involved in Control of Plant Height and Tillering

Tall fescue is one of the most widely used grasses for forage and turf, with plant height and tillering capacity being important traits affecting its use. We identified 93 unigenes putatively affecting tall fescue height and tillering or both, of which 52 were predicted to be complete ORFs (Supplementary Table S8). The TIS108 treatment assay revealed 60% more tillers in the TIS108-treated tall fescue than that in the control-treated tall fescue (Figure 7A,B). In addition, the expression of FaMAX1 was significantly inhibited by TIS108 treatment (Figure 7C), indicating that the suppression of FaMAX1 increased the lateral branching in tall fescue.

4. Discussion

4.1. Iso-Seq Provides a More Comprehensive View of the Tall Fescue Transcriptome

High-throughput sequencing using Illumina HiSeq has facilitated large-scale transcriptome sequencing and opened a new phase of transcriptome-wide research on tall fescue, enabling differential gene expression analysis. In tall fescue, transcriptomes from different tissues such as late floral meristem (SRX3802799), ovary (SRX3802788), and various tissues following a range of stress treatments, including heat (SRX1056958), drought (SRX963535), and heavy metals were obtained using Illumina HiSeq [26,27,28,29,30]. This provided genomic resources to identify candidate genes associated with different traits. However, previous de novo transcriptome assembly using short reads generated structural errors, incomplete assemblies, and base errors, resulting in high mis-assembly rates and unreliable gene annotation. Moreover, obtaining full-length ORFs is highly time-consuming and costly. Additionally, this problem is exacerbated in species without a reference genome sequence for the prediction of gene models.
The PacBio Iso-Seq method is superior to next-generation sequencing, which is typically used by gene discovery studies. In our study, we generated 73,628 unigenes with an average length of 2410 bp and N50 of 2725 bp, which are greater than those in other databases generated using Illumina HiSeq (average length of 596.18 bp and N50 of 821 bp) [26]. The transcriptome data generated in this study are more comprehensive than those reported in previous studies with a higher number of predicted FL transcripts (with completed ORFs); 42,265 unigenes (60.09%) were predicted to be complete FL ORFs. This dataset provides a resource that can be directly used for downstream functional gene studies without additional PCR amplification to obtain a complete transcript. We also detected 1599 UniTransModel-based AS events. The high proportion of transcripts with multiple splicing isoforms suggests high transcriptome complexity in tall fescue.

4.2. Unigenes in ABA Pathways under Drought Stress

ABA is a plant stress hormone and one of the important signaling molecules in plants, which plays versatile functions in regulating adaptive stress processes [47]. Therefore, we analyzed the main components of the ABA pathways in tall fescue, including NCEDs, ABA-8′-hydroxylase, PYR/PYL/RCAR, SnRKs, and PP2Cs. Five NCED genes likely to be involved in ABA biosynthesis have been identified in Arabidopsis [47,48] and rice [49,50]. Previous studies have shown abundant transcript levels of OsNCED2 in seed [50] and OsNCED1 in leaves of rice [51]. Here, we identified four NCED genes in tall fescue, of which two genes, FaNCED1 and FaNCED4, are significantly induced by drought stress, indicating their involvement in increasing the ABA level in tall fescue in response to drought stress. ABA concentration in plants under stress conditions depends on ABA synthesis and catabolism. In rice, three ABA-8-hydroxylases have been identified (Saika et al., 2007). Among these, OsABA8ox2 and OsABA8ox3 are induced significantly early in seed germination [50], while OsABA8ox1 is dramatically induced by rehydration [51]. Our study revealed that the expression of FaABA8OX1 was highly induced by drought stress, which may contribute to balancing the ABA concentration in tall fescue under stress conditions. Moreover, three PYR/PYL/RCAR genes have been identified in tall fescue; however, our data revealed an alteration in the expression of only one member of these genes under drought stress (Figure 6). Overexpression of OsPYL11 (OsPYL/RCAR5) shows its hypersensitivity to ABA during seed germination and early seedling growth, whereas overexpression of OsPYL3 and OsPYL9 substantially improves drought and cold stress tolerance in rice [40]. These results indicate that specific genes are involved in ABA biosynthesis, catabolism, and signaling, which function in different tissues and various development processes. Therefore, investigating the specific functions of these genes under drought stress is necessary to gain in-depth insights.

4.3. Unigenes Involved in Regulation of Plant Tillering

Tillering is an important component of plant development, regulated by a highly complex network of hormonal signals, including auxin, cytokinins, gibberellins, abscisic acid (ABA), and sucrose [52]. Here, we identified 30 unigenes putatively affecting tall fescue tillering. All the identified unigenes related to strigolactone (SL) pathways. Recent reports have revealed that SLs repress tillering by inhibiting axillary bud growth [53,54]. The biosynthesis and signal transport of SLs rely on a series of key genes, including (1) the β-carotene biosynthesis genes, particularly those encoding phytoene synthase (CrtB) and phytoene desaturase (PDS); (2) the SL biosynthesis genes DWARF27 (D27), More Axillary Growth 1 (MAX1), MAX3 (also known as carotenoid cleavage dioxygenase 7 (CCD7)), and MAX4 (also known as CCD8); and (3) the SL signaling genes α/β-hydrolase receptor DWARF14 (D14) and MAX2 [55]. In this study, FaD14, FaMAX1, and FaMAX2 were identified; the suppression of FaMAX1 increased the lateral branching in tall fescue, consistent with previous reports that mutating the key genes involved in the synthesis of SLs leads to the formation of plants with increased lateral branch tillers [56,57,58]. These results suggest that the SL pathway, which is common and conserved in plants, can be used to improve agronomic traits for tall fescue and other plants.

5. Conclusions

We identified numerous long-read isoforms specific to tall fescue and characterized FL transcripts and AS events related to stress adaptation. The availability of FL isoforms will help improve transcriptome characterization and further gene annotation. The data on related unigenes involved in ABA biosynthesis, catabolism, and signaling pathways paved the foundation for further investigation to understand the mechanism underlying the abiotic stress tolerance in tall fescue. Furthermore, the unigenes controlling important agronomic traits were identified and functionally verified in the present study. Hence, this study contributes valuable genetic resource information for future research in the gene discovery and molecular breeding of tall fescue. Our results also suggest that long-read, full-length unigene data with high-quality assemblies are invaluable as transcriptomic references in tall fescue and can be used for comparative analyses in closely related plants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13061484/s1. Supplementary Table S1, Primers used in this study; Table S2, Summary of sequencing data for tall fescue; Table S3, Reads of interest (ROI) summary fortall fescue; Table S4, Summary of classified reads of interest (ROI) numbers intall fescue; Table S5, Summary of consensus isoforms; Table S6, Summary of final consensus isoforms; Table S7, Unigenes involved in abscisic acid (ABA) synthesis and signaling components; Table S8, Unigenes involved in height and tillering; Supplementary Figure S1, Amino acid sequence comparison of NUP133 of tall fescue (Festuca arundinacea) with the homologous protein of Oryza sativa. Black letters mean the same amino acid sequences, whereas the blue letters mean different parts; Figure S2, Venn diagram of lncRNA analyzed by coding potential calculator (CPC), coding non-coding index (CNCI), coding potential assessment tool (CPAT), and Protein families (Pfam).

Author Contributions

Conceptualization, Q.T. and C.Y.; methodology, C.Y., L.Z., E.O. and D.Z.; validation, Q.T., C.Y., L.Z. and D.Z.; data curation and writing—original draft preparation, C.Y. and L.Z.; writing—review and editing, C.Y.; visualization, C.Y.; supervision, Q.T.; project administration, C.Y., L.Z., E.O., F.T., M.Y., M.C., X.Y., Y.L., X.L., R.H. and J.H.; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (grant numbers: 31701950 and 31960609), Innovation Project (grant number: Qian Ke Fu Qi [2022]004), Guizhou Scientific Research Innovation Team (grant number: [2019] 5618), Science and Technology Program of Guizhou (grant number: [2019]2856), and Program of Guizhou Academy of Agricultural Sciences (grant number: [2015]021, [2017]17, [2021]13 and [2021]47).

Data Availability Statement

The sequence data generated for this work are accessible via the NCBI Sequence Read Archive under accession numbers (SRA: SRR8202096, SRR8202097, SRR8202098, SRR8202099, SRR8202100).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Length distribution of tall fescue transcripts and encoded proteins. (A) Histograms of isoform length. (B) Length distribution of proteins encoded by transcripts, which were predicted to be complete FL ORFs.
Figure 1. Length distribution of tall fescue transcripts and encoded proteins. (A) Histograms of isoform length. (B) Length distribution of proteins encoded by transcripts, which were predicted to be complete FL ORFs.
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Figure 2. Functional annotation of unigenes from tall fescue. (A) Number of unigene hits to known sequences. (B) Overlaps of hits among known homologous genes searched against KOG, Pfam, Swissprot, and NR databases. (C) Overlaps of hits among known homologous genes searched against model plant genomes: Arabidopsis, Oryza sativa, and Brachypodium distachyon. (D) Transcriptome similarity of Festuca arundinacea to other plant species. (E) Transcription factor (TF) families identified among unigenes.
Figure 2. Functional annotation of unigenes from tall fescue. (A) Number of unigene hits to known sequences. (B) Overlaps of hits among known homologous genes searched against KOG, Pfam, Swissprot, and NR databases. (C) Overlaps of hits among known homologous genes searched against model plant genomes: Arabidopsis, Oryza sativa, and Brachypodium distachyon. (D) Transcriptome similarity of Festuca arundinacea to other plant species. (E) Transcription factor (TF) families identified among unigenes.
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Figure 3. Functional classification of unigenes by GO (A) and KEGG (B) annotation. The x-axis represents the percentage and number of transcripts, and the Y-axis represents the KEGG function category.
Figure 3. Functional classification of unigenes by GO (A) and KEGG (B) annotation. The x-axis represents the percentage and number of transcripts, and the Y-axis represents the KEGG function category.
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Figure 4. Analysis of SSR, lncRNA, and AS isoforms of tall fescue transcripts. (A) Frequency of SSR motifs in unigenes based on representation in various motif-repeat types. (B) Length distribution of identified lncRNAs in F. arundinacea. (C) Numbers of different AS events detected in full-length transcriptomes. SE, skipped exon; RI, retained intron; A5, alternative 5′ splice-site; A3, alternative 3′ splice-site; AF, alternative first exon. (D) Identification of AS isoforms of DKE-like homologues.
Figure 4. Analysis of SSR, lncRNA, and AS isoforms of tall fescue transcripts. (A) Frequency of SSR motifs in unigenes based on representation in various motif-repeat types. (B) Length distribution of identified lncRNAs in F. arundinacea. (C) Numbers of different AS events detected in full-length transcriptomes. SE, skipped exon; RI, retained intron; A5, alternative 5′ splice-site; A3, alternative 3′ splice-site; AF, alternative first exon. (D) Identification of AS isoforms of DKE-like homologues.
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Figure 5. Analysis of differently expressed genes under drought stress (PEG treatment) and the control. (A) Patterns of DEGs in the PEG-treated and control samples. (B) Volcano plots of DEGs from the PEG-treated and control samples. (C) KEGG pathway classification of the annotated DEGs. X-axis represents the percentage and number of transcripts. Y-axis represents the KEGG function category.
Figure 5. Analysis of differently expressed genes under drought stress (PEG treatment) and the control. (A) Patterns of DEGs in the PEG-treated and control samples. (B) Volcano plots of DEGs from the PEG-treated and control samples. (C) KEGG pathway classification of the annotated DEGs. X-axis represents the percentage and number of transcripts. Y-axis represents the KEGG function category.
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Figure 6. qRT-PCR analysis of expression level of genes in ABA pathways under drought stress (PEG treatment). Mean relative expression level (±SEM) of different genes; the relative expression was detected 14 d after PEG6000 treatment. Asterisks indicate significant differences as determined by t-tests (** p < 0.01).
Figure 6. qRT-PCR analysis of expression level of genes in ABA pathways under drought stress (PEG treatment). Mean relative expression level (±SEM) of different genes; the relative expression was detected 14 d after PEG6000 treatment. Asterisks indicate significant differences as determined by t-tests (** p < 0.01).
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Figure 7. Phenotypical differences in tillering between TIS108-induced FaMAX1 deficiency and wild-type (WT) plants. (A) Three-week-old WT and TIS108-treated tall fescues (Red triangles refer to tillering). (B) Mean tiller number (± SEM) of three-week-old control and TIS108-treated tall fescues. (C) Mean relative expression level (± SEM) of FaMAX1. Asterisks indicate significant differences as determined by t-tests (** p < 0.01).
Figure 7. Phenotypical differences in tillering between TIS108-induced FaMAX1 deficiency and wild-type (WT) plants. (A) Three-week-old WT and TIS108-treated tall fescues (Red triangles refer to tillering). (B) Mean tiller number (± SEM) of three-week-old control and TIS108-treated tall fescues. (C) Mean relative expression level (± SEM) of FaMAX1. Asterisks indicate significant differences as determined by t-tests (** p < 0.01).
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Yang, C.; Zhong, L.; Ou, E.; Tian, F.; Yao, M.; Chen, M.; Yan, X.; Li, Y.; Li, X.; He, R.; et al. Using Isoform Sequencing for De Novo Transcriptome Sequencing and the Identification of Genes Related to Drought Tolerance and Agronomic Traits in Tall Fescue (Festuca arundinacea Schreb.). Agronomy 2023, 13, 1484. https://doi.org/10.3390/agronomy13061484

AMA Style

Yang C, Zhong L, Ou E, Tian F, Yao M, Chen M, Yan X, Li Y, Li X, He R, et al. Using Isoform Sequencing for De Novo Transcriptome Sequencing and the Identification of Genes Related to Drought Tolerance and Agronomic Traits in Tall Fescue (Festuca arundinacea Schreb.). Agronomy. 2023; 13(6):1484. https://doi.org/10.3390/agronomy13061484

Chicago/Turabian Style

Yang, Chunyan, Li Zhong, Erling Ou, Fang Tian, Mei Yao, Ming Chen, Xu Yan, Yingzheng Li, Xiaofeng Li, Ruyu He, and et al. 2023. "Using Isoform Sequencing for De Novo Transcriptome Sequencing and the Identification of Genes Related to Drought Tolerance and Agronomic Traits in Tall Fescue (Festuca arundinacea Schreb.)" Agronomy 13, no. 6: 1484. https://doi.org/10.3390/agronomy13061484

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