Next Article in Journal
Population Dynamics and Feeding Preferences of Three Bacterial-Feeding Nematodes on Different Bacteria Species
Previous Article in Journal
Soil Organic Carbon Prediction Based on Different Combinations of Hyperspectral Feature Selection and Regression Algorithms
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 13
Issue 7
10.3390/agronomy13071807
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome-Wide Identification and Expression of the GRAS Gene Family in Oat (Avena sativa L.)

by
Rui Wu
,
Wenhui Liu
*,
Kaiqiang Liu
,
Guoling Liang
and
Yue Wang
Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai Academy of Animal Husbandry and Veterinary Sciences, Qinghai University, Xining 810016, China
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(7), 1807; https://doi.org/10.3390/agronomy13071807
Submission received: 5 June 2023 / Revised: 1 July 2023 / Accepted: 5 July 2023 / Published: 7 July 2023
(This article belongs to the Special Issue Dissecting Genetic Basis of Crop Agronomic Traits through Bioinformatics)
Browse Figures
Versions Notes

Abstract

:
The GRAS protein family is involved in plant growth and development, plant disease resistance, and abiotic stress response. Although the GRAS protein family has been systematically studied and reported in many plants, it has not been reported in oat, an excellent foodstuff crop of Gramineae. We identified 90 AsGRAS genes and all of the AsGRAS genes were randomly distributed on 21 chromosomes with 6 tandem duplicated genes and 49 pairs of segmental duplications, which may be the main reason for the expansion of the GRAS gene family. According to the phylogenetic tree, 90 AsGRASs were classified into 10 distinct subfamilies. Gene structure revealed introns varying from zero to seven, and all genes have conserved motifs and GRAS structure domain. Protein–protein interaction and miRNA prediction analysis showed that AsGRAS proteins mainly interacted with GA signalling, cell division, etc., and that the AsGRAS genes were targeted by miRNA171. RNA-seq and qRT–PCR data showed that GRAS genes were expressed at different growth and developmental stages and under different abiotic stresses in oat, indicating the potential role of GRAS genes in promoting growth and stress tolerance in oat. Overall, our evolutionary and expression analysis of AsGRAS genes contributes to the elucidation of a theoretical basis for the GRAS gene family. Moreover, it helped reveal gene function and laid the foundation for future agricultural improvement of oats based on functional properties.

1. Introduction

Transcription factors are a class of proteins that bind to specific upstream sites of gene sequences to regulate biological processes by altering gene expression and play an important role in plant growth and response to external stresses [1,2]. The GRAS gene family is a widespread transcriptional regulator family in plants; it is defined by nuclear localization, DNA binding, and transcriptional activation features and is named after three early identified functional genes, gibberellic acid insensitive (GAI), the repressor of GA1 (RGA), and scarecrow (SCR3) [3,4]. Interestingly, a study showed that this family first appeared in bacteria and that sequence homology exists between GRAS proteins and prokaryotic Rossmann-fold SAM-dependent methyltransferases [5]. GRAS proteins generally consist of at least 360–850 amino acids, including a highly conserved C-terminus and a variable N-terminus, with the C-terminus consisting of five conserved motifs, SAW, LHRI, LHRII, PFYRE, and VHIID, of which the most conserved is VHIID, which is the core sequence of GRAS proteins and is present in all subfamily members [6,7,8,9]. In contrast, the N-terminus includes a combination of several molecular recognition features that are required for protein–protein binding or molecular recognition, and this flexible and versatile N-terminal IDG extends the potential ligand binding sites of GRAS proteins. Thus, the N-terminal sequence is important for GRAS proteins to perform specific functions [10,11].
The early GRAS genes were divided into 8 subfamilies in Arabidopsis, LS, PAT1, SCL3, DELLA, LISCL, SCR, HAM and SHR, and then the DLT and SCL4/7 subfamilies were added based on more extensive protein sequence alignment, thus dividing the GRAS genes into 10 subfamilies [12,13]. Interestingly, subfamilies of the GRAS differ slightly among species. For example, GRAS proteins are identified and classified into 14 subfamilies in cotton (Gossypium hirsutum) [14] and cassava (Manihot esculenta) [15], 13 in tea plant (Camellia sinensis) [16], and 16 in alfalfa (Medicago truncatula) [17]. The different GRAS subfamilies have led to the functional diversity of this gene family and more subfamilies may be identified in the future. Whole gene identification and analysis of the GRAS gene family has been performed in a variety of plants, and 34, 153, 60, 106, 21, 48, and 52 GRAS genes were identified in Arabidopsis [18], wheat (Triticum aestivum) [9], rice (Oryza sativa) [19], Populus [20], tobacco (Nicotiana tabacum) [21], castor beans (Ricinus communis) [22], and grape (Vitis vinifera) [23], respectively. As whole genomes become available for more plants, more GRAS genes will be identified, as is the case for oat. GRAS transcription factors are involved in hormone signalling, regulation of tissue development, root and axillary shoot development, and response to external stress during plant growth and development [24,25,26,27,28,29]. For example, the SCR and SHR subfamilies regulate lateral root development in Arabidopsis and SHR/SCR/SCL3 may be involved in regulating gibberellins during mycorrhization in tomato [30]; AtPAT1, a member of the AtPAT1 subfamily, is involved in phytochrome A signalling in Arabidopsis [31]; overexpression of PeSCL7 in Populus euphratica (belonging to subfamily AtSCL4/7) enhances drought tolerance and salt tolerance in transgenic Arabidopsis plants [32]; and SHR and SCR are expressed in young leaf primordia, leaves, leaf vascular tissue, and vascular sheath cells [33]. It is worth noting that GAs regulate plant growth and senescence mainly by linking with hormonal pathways and this linkage is pivoted by DELLA proteins. When there is no GA in the plant, DELLA proteins inhibit plant growth and development; when GA is present, the GA signal sensing region of DELLA proteins receives GA signals, DELLA proteins are rapidly degraded, and the plant shows a normal GA response and growth [34]. Several studies have also confirmed that DELLA proteins participate in abiotic resistance in plants through their involvement in GA signalling [35] and AtGAI, a member of the DELLA subfamily, is involved in gibberellin signalling in Arabidopsis [36].
Oat is an annual grain and forage crop of Gramineae, with excellent characteristics related to cold, drought, and salinity stress [37,38]. Rich in vitamins, proteins and β-glucan, it is a whole grain with comprehensive nutritional value [39]. With the needs of livestock development, the continuous promotion of new varieties of oat, and nutritional healthcare needs, the development of the oat industry is becoming increasingly important. The release of the entire oat genome sequence in 2022 was a breakthrough in facilitating its molecular genetic analysis [40]. Based on published sequence data, comprehensive analyses of a given gene family can be performed to reveal its molecular function, evolution, and gene-expression profiles, and these analyses help reveal how genes in a gene family regulate traits at the genome-wide level. In this study, we identified GRAS gene family members from the oat genome and analysed their physicochemical properties, chromosomal localization, phylogenetic relationships, gene structure, covariance, promoters, and expression patterns to provide a theoretical basis for further studies on the functions of the GRAS gene family in environmental adaptation.

2. Materials and Methods

2.1. Identification of GRAS Genes in Oat

Three plant species with fully sequenced genomes were included in the analyses: Arabidopsis thaliana, Medicago truncatula, and Avena sativa. Arabidopsis genome files and genome annotation files were downloaded from Ensemble Plant (http://plants.ensembl.org/index.html) (accessed on 27 September 2022) [41,42], and the Arabidopsis GRAS sequences were downloaded from the TAIR database (https://www.arabidopsis.org/index.jsp) (accessed on 18 September 2022) [43]. Medicago truncatula GRAS sequences were downloaded from the PlantTFDB database (http://planttfdb.gao-lab.org/family.php?fam=GRAS) (accessed on 27 May 2023) [44]. The oat genome files and genome annotation files were downloaded from the GrainGenes website (http://wheat.pw.usda.gov) (accessed on 16 September 2022) [45]. Then, we used TBtools for blast sequence alignment of Arabidopsis GRAS genes with the oat genome to screen for GRAS family candidate genes in oat [46]. Candidate genes were further submitted to the NCBI online tool Batch CD-Search (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi) (accessed on 18 September 2022) to determine the conserved structural domains of GRAS proteins and preserved sequences with complete GRAS domains [47].

2.2. Physicochemical Property Analysis and Chromosomal Localization

Physicochemical properties such as amino acid number, molecular weight, and theoretical isoelectric point (pI) were analysed using the online analysis software ExPASy (http://web.expasy.org/compute_pi) (accessed on 25 September 2022) [48]. The software TBtools was used to extract GRAS gene location information from oat-genome files and gene-annotation files and to construct the GRAS gene physical map on the chromosomes. Sequence comparison of oat whole-genome data was performed using Blast and McscanX to screen for homologous genes.

2.3. Phylogenetic Tree Construction, Gene Structure, and Conserved Motif

The GRAS protein sequences of oat, Medicago truncatula and Arabidopsis were sequenced using Muscle of MEGA11 [49]. Based on this result, we first analysed the best model for LG using the phylogenetic analysis function, and, then, the maximum likelihood (ML) phylogenetic tree of Arabidopsis, Medicago truncatula, and oat was generated according to the following parameters: 1000 bootstrap replicates, LG model, gamma distributed (G) rates among sites, and partial deletion with 95%. The evolutionary tree was visualized and modified to create a circle using the EvolView website (https://evolgenius.info//evolview-v2/#login) (accessed on 2 June 2023) [50]. Prediction of conserved motifs and gene structures of oat GRAS proteins was performed by the online software MEME (https://meme-suite.org/meme/tools/meme) (accessed on 22 September 2022) [51] and subfamily analysis was based on the results. The site distribution was zero or one occurrence per sequence (zoops), and 10 motifs were searched, with all other parameters at the default. Combined analysis of the phylogenetic tree, conserved structural domains, and gene structures was performed using TBtools. The promoter analysis was mainly performed by extracting upstream 2000 bp sequences, which were further submitted to PlantCARE (https://bioinformatics.psb.ugent.be/webtools/plantcare/html) (accessed on 21 December 2022) for prediction and screening [52].

2.4. Synteny Analyses

Synteny analyses were analyzed by McscanX software in TBtools. TBtools (simple Ka/Ks calculator) was used to calculate the nonsynonymous (Ka) and synonymous (Ks) of each duplication pair. It is generally accepted that Ka/Ks < 1 indicates purifying or negative selection (tendency to purify), Ka/Ks = 1 indicates neutral selection (pseudogene), and Ka/Ks > 1 indicates positive selection. The approximate timing of duplication events was analyzed by 2.6 × 10−9 substitution/synonymous site in oat [40]. To clarify the genetic homology of oat with other species, the whole genome data of oat with Arabidopsis, rice, maize, and wheat were compared using the blast function of TBtools software and a synteny analysis plot was constructed using dual synteny plotter in TBtools.

2.5. Protein–Protein Interaction and miRNA Prediction

TBtools (PPI Predict) was used to predict the interacting proteins with Arabidopsis as the reference species and psRNATarget (https://www.zhaolab.org/psRNATarget/analysis) (accessed on 22 February 2023)was used to predict the miRNA of AsGRAS proteins [53]. All results were visualized with Cytoscape 3.9.0 software.

2.6. Expression Analysis of AsGRAS Genes

Transcriptomic data for oat drought stress with silicon, salt stress, high-temperature stress, lemma development, and seed vigour were downloaded from the public database NCBI (https://www.ncbi.nlm.nih.gov/) (accessed on 19 February 2023) and their accession numbers were SRP237902, SRP094911, SRP420373, SRP294982, and SRP235083 [54,55,56,57]. In addition, we also analyzed the transcriptomic data under drought stress from the previous study. We analyzed the expressions under each treatment using the Kallisto and then plotted the heat maps in TBtools with transcripts per million (TPM) [58].

2.7. Plant Materials

Oat seeds were planted in plastic cups with nutritional soil and grown in an incubator under a 12/12 h light/dark photoperiod regime at 24 °C temperature. Two-week-old seedlings were treated with 20% PEG6000 and a 150 mM NaCl solution, respectively; leaves were collected at 0, 2, 4, 8, 12, and 24 h and were immediately frozen in liquid nitrogen and stored at −80 °C for RNA extraction.

2.8. Total RNA Extraction and Real-Time Quantitative PCR

Total RNAs were extracted with EasyPure® Plant RNA Kit (TAKARA, Dalian, China) following the manufacturer’s instructions and then reverse-transcribed using PrimeScriptTM RT reagent Kit (TAKARA, Dalian, China). Primer Premier 6 was used to design the particular 10 primers for the oat GRAS gene for quantitative real-time PCR (qRT-PCR) (Table S1). qRT-PCR was conducted on a Light Cycle96 using TB Green®Premix Ex Taq™II (TAKARA, Dalian, China). The reaction system was as follows: 10 s at 95 °C, 40 cycles of 95 °C for 5 s, and 60 °C for 30 s. The data were analysed by the 2−ΔΔCT method [59] with 3 replicates per sample set.

3. Results

3.1. Identification of GRAS Family Genes in Oat Genome

Ninety distinct GRAS genes were identified in the whole oat genome and designated as AsGRAS1 to AsGRAS90 based on their chromosome locations (Tables S2 and S3). Sequence analyses revealed that these GRAS proteins varied greatly in length, from 261 and 868 amino acids. The protein molecular weight of these GRAS proteins ranged from 30.03 kD (AsGRAS34) to 95.16 kD (AsGRAS33). Their isoelectric points (pI) ranged from 4.72 (AsGRAS41) to 9.55 (AsGRAS71). Among them, 85 GRAS proteins with isoelectric points less than seven were rich in acidic amino acids. Based on the instability index, the structure and stability of the AsGRAS proteins were determined, which provides an estimate of the protein stability. Only one AsGRAS protein was probably stable, with an instability index of 38.34 (AsGRAS63), and the other 89 AsGRAS proteins were unstable because they all had an instability index higher than 40. Subcellular locations showed that all AsGRAS were predicted to localize in the nucleus.

3.2. Protein Motif and Gene Structure Analysis of AsGRAS Family

The conserved motifs of oat GRAS family proteins were analysed by MEME, and the relationship between conserved motifs and phylogeny was further analysed (Figure 1 and Figure S1). The number of introns varied from zero to seven. Otherwise, 58.9% (53/90) of proteins were intronless. While 21.1% (19/90) of proteins contained one intron, other proteins had two or more introns. The phylogenetic results showed that GRAS proteins could be grouped into 10 distinct subclusters. Among the 90 AsGRAS proteins, a total of 10 different motifs were predicted.
These number of AsGRAS genes are somewhat different and the conserved structural domains are similar within the same subfamily, indicating that the same subfamily may have similar functions. The SCL3 subfamily contains six conserved motifs and the HAM and SCR subfamilies contain nine conserved motifs. The LS, DLT, DELLA, SCL4/7, LISCL, SHR, and PAT1 subfamilies contain 10 conserved motifs. All AsGRAS proteins contain motif3, indicating that this motif is highly conserved in AsGRAS and plays an important role. The majority of the encoded motifs in most of the GRAS-like proteins are in the order motif10, motif6, motif5, motif2, motif7, motif9, motif8, motif4, motif1, and motif3. Among them, motif1, motif4, motif5, motif6, and motif8 are prone to transposition. A gene-structure analysis showed that all oat GRAS genes contained one to nine untranslated regions (UTRs); The AsGRAS genes all contain the coding regions (CDS), and all GRAS proteins contain GRAS structural domain; The DELLA subfamily contains five genes, of which the DELLA structural domain was not found in the structure analysis of AsGRAS32 and AsGRAS27.

3.3. Phylogenetic Relationship of GRAS Family Proteins in Plants

To evaluate the evolutionary history of the GRAS family, the evolutionary tree was conducted based on GRAS domains of 32 Arabidopsis, 75 Medicago truncatula, and 90 AsGRAS by using the maximum likelihood method (ML) (Figure 2). The results showed that Arabidopsis, Medicago truncatula, and oat GRAS proteins were clustered into 10 subfamilies, including HAM, LS, DLT, SCR, DELLA, SCL4/7, SCL3, LISCL, SHR, and PAT1. Members of the GRAS gene family are unevenly distributed in different subfamilies with LISCL being the largest subfamily, comprising 47 members (26 AsGRAS, 15 MtGRAS, and 6 AtGRAS), followed by the PAT1 subfamily, which contains a total of 41 GRAS genes (19 AsGRAS, 16 MtGRAS, and 6 AtGRAS). While LS, DLT, and SCL4/7 are smaller subfamilies, they contain only six GRAS genes. HAM, SCR, DELLA, SCL3, and SHR subfamilies contain 24, 12, 15, 18, and 22 members, respectively; AsGRAS74 is homologous to AT5G41920.1 and Medtr4g076020.1 in SCR subfamily; AT2G37650.1 and Medtr7g062120.1 are closely related in LISCL subfamily; AsGRAS25 and Medtr1g096030.1 are closely related in the HAM subfamily. As a whole, the AsGRAS gene family has a common ancestor with Arabidopsis and Medicago truncatula.

3.4. Analysis of Chromosome Distribution, Tandem Duplications, and Segmental Duplications of AsGRAS Genes

A map of the chromosomal distributions of AsGRAS genes constructed based on their physical position information illustrates that they were unevenly distributed on 21 chromosomes (Figure 3). Among them, nine AsGRAS genes localize on Chr4D (10%), eight AsGRAS genes on Chr7C (8.9%), and only one AsGRAS gene (1.1%) on Chr3A and Chr6D (Figure S2).
Tandem duplications and segmental duplications play an important role in gene-duplication events. The tandem duplication of genes is on chromosomes chr4D and chr5C (red lines connecting the genes on the same chromosome indicate that the related genes are tandem duplications). Tandem duplication genes accounted for 6.59% of all GRAS genes, indicating the occurrence of tandem duplication events in the oat GRAS family and the role of tandem duplication events in the expansion of the oat GRAS family (Figure 4). In addition, we identified 49 pairs of segmental duplications (Figure 4, Table S4). The number of segmental duplications was much greater than that of tandem duplications. Afterwards, we calculated the nonsynonymous substitution (Ka) to synonymous substitution (Ks) ratio of all AsGRAS gene pairs to determine the nature and extent of evolutionary selection pressure (Table S5). The results showed that all duplicate gene pairs had Ka/Ks < 1, indicating that these genes underwent purifying selection. Meanwhile, we analyzed the approximate timing of duplication events and the results showed that AsGRAS gene-duplication events occurred between 0.22 Mya and 52.76 Mya, with a mean value of 8.06 Mya.

3.5. Synteny Analyses of GRAS Gene Family

To further understand the evolutionary mechanism of the GRAS family in oat, we constructed a covariance map of the AsGRAS family with four other species, including Arabidopsis (dicot), rice, wheat, and maize (monocote) (Figure 5, Table S6). A total of 15 GRAS genes showed a syntenic relationship with those in Arabidopsis and 65 corresponding orthologs were identified in rice, 175 homologous genes were identified in wheat, and 93 GRAS genes showed syntenic relationships with those in maize.

3.6. Protein–Protein Interaction Network and miRNA Prediction for AsGRAS Genes

The construction of an unknown protein interaction network relationship map is helpful for functional prediction in nonmodel plants. In this study, the model plant Arabidopsis was used as the background for the study of oat AsGRAS protein and its potential functionally associated proteins were predicted and analyzed by TBtools software (Figure 6, Table S7). The results showed that 13 AsGRAS proteins interacted with other proteins, with a higher number of proteins interacting with AsGRAS35, AsGRAS50, AsGRAS60, and AsGRAS65. The main proteins that interact with AsGRAS proteins are IDD, SHR1, WOX5, GID, PIL, etc. Functional annotation shows that they are mainly zinc finger proteins, transcription factors, etc. Further analysis revealed that these proteins are mainly involved in GA signalling, the cell division process, and the light-signal transduction process.
miRNAs are highly conserved regulatory elements of gene expression commonly found in plants and animals. Most of the known miRNAs target different types of transcription factors and the prediction of miRNAs can clarify the roles played by related genes in plant growth and development [60,61]. During the prediction of targeting miRNAs for the AsGRAS genes using the psRNAtarget tool, a total of 14 AsGRAS were found to be targeted by 215 miRNAs by parameter prediction; all miRNAs were miR171 at expectation values from zero to two, indicating that miR171 may have important regulatory functions in the AsGRAS gene family (Figure 7, Table S8).

3.7. Expression Profiling of AsGRAS Genes

To analyse the expression of the GRAS family in oat, we downloaded transcriptome data from public databases and analyzed the expression patterns of all AsGRAS genes under treatments of silicon drought stress, salt stress, high-temperature and drought, or associated with lemma development and seed vigour (Figure 8, Table S9). The results showed that each AsGRAS gene was differentially expressed under different treatments, with most genes being expressed during oat stress and growth and a few genes not being expressed. Under silica-induced drought stress, AsGRAS3, AsGRAS8, and AsGRAS33 were not expressed, while other genes were upregulated or downregulated (Figure 8A). With an increasing duration of drought stress, the expression of the MW variety was more significantly upregulated under drought stress (Figure 8D). Under salt stress, the expression of most AsGRAS genes was upregulated with increasing stress duration, especially at 12 h and 24 h (Figure 8B). Under high-temperature treatment, the expression of 23 AsGRAS genes was downregulated and 53 AsGRAS genes’ expressions were upregulated (Figure 8C). In addition, AsGRAS genes are differentially expressed in oat growth and development. For example, the gene expression of the OA1613 variety was higher than that of BY685 in terms of lemma development (Figure 8E). Most of the AsGRAS genes were downregulated at 16 d of seed ageing and about one-third of the genes were upregulated at 32 d of seed ageing (Figure 8F).

3.8. Expression Analysis of AsGRAS Genes in Response to Abiotic Treatments

Based on the transcriptome data results, it was found that the expression of AsGRAS genes was mostly induced by different stress treatments (drought, high temperature, salt stress, and other treatments). To verify the reliability of RNA-seq results of GRAS family genes under abiotic stress, we selected 10 of these AsGRAS genes and used qRT-PCR to validate their expression patterns under drought and salt stress (Figure 9). The results showed that the expression of some AsGRAS genes increased and then decreased with an increasing stress duration, and that of some genes increased with an increasing stress duration. Under drought stress, the expression of AsGRAS6/13/20/37/51/84 was highest at 24 h of stress. Under salt stress, the expression of AsGRAS6/13/16/19/20/40/41 was highest at 24 h. Other genes were higher at 4–8 h of stress. The AsGRAS gene-expression patterns were consistent with the RNA-seq results, and all 10 AsGRAS genes were induced to different degrees by abiotic stresses.

4. Discussion

The GRAS gene family is a candidate factor that is widely involved in the growth process of various plants and is thought to be critical for plants under many conditions. Our study led to the identification of 90 AsGRAS genes in the oat genome. Different plants possess different numbers of GRAS genes. The number of AsGRAS genes is approximately 1.5 times that in rice (60 OsGRAS) [19] and approximately 1.7 times that in tomato (Solanum lycopersicum) (53 SlGRASs) [62]; however, compared with that in wheat (183 TaGRAS) [63], the number of AsGRAS was only half. This result may be attributed to the genome size or maybe the result of gene-duplication events [64]. Ninety AsGRAS genes are randomly distributed on 21 chromosomes; the three chromosomes chr4D, chr5A, and chr5C have many genes that appear to have been added via tandem duplications. The LISCL subfamily has been reported to have expanded due to tandem and segmental duplications [27]. Interestingly, the LISCL subfamily of oat has the largest number of genes and three tandem duplication events occurred in this subfamily. We found 49 pairs of segmental duplications, indicating the dominance of segmental duplication in oat-gene duplication events. Gene duplication due to polyploidization plays an important role in the expansion of the GRAS gene family in plants [65]. Oat, as a hexaploid crop, are similar to other flowering plants. Therefore, chromosome polyploidization may have an important influence on oat evolution and has resulted in a large oat genome. Many gene functions have evolved through gene duplication and play an important role in the development of plants [66], so studying gene duplication events can be useful for understanding gene function, the evolutionary consequences of gene duplication and their contribution to evolution.
An interesting phenomenon suggests that intronless genes are typical of prokaryotes genes but they also occupy a certain proportion in eukaryotes, for example, 21.7% in Arabidopsis and 19.9% in rice. The plant GRAS family contains a high proportion of intronless genes, suggesting an evolutionary relationship of GRAS proteins, for example, 67.6% of Arabidopsis [19] and 83.3% of Chinese cabbage (Brassica pekinensis) [64]. Interestingly, we found that 52.5% of oat GRAS genes were intronless, indicating that the structure of GRAS genes is highly conserved in oat. It is hypothesized that a large number of intronless genes in plants originate from prokaryotes and are replicated in the plant genome to produce [67,68]. Another study reported that the GRAS gene originated in the bacterial genome [69], which may be the reason why the GRAS family contains a large number of intronless genes. Phylogenetic analysis clustered the AsGRAS into 10 subfamilies: HAM, LS, DLT, SCR, DELLA, SCL4/7, SCL3, LISCL, SHR, and PAT1. This subfamily classification is similar to that of other plants, indicating the high diversity of GRAS genes in plants [22]. The same subfamily shares a similar structure and specific structural domains and motifs of GRAS proteins determine their ability to recognize and interact with different DNA, thus participating in different regulatory pathways and performing different biological functions [70]. For example, the SCR and SHR subfamilies are involved in root radial patterning [71], and the SCL subfamily is involved in abiotic stress [72]. In our study, GRAS genes of the same subfamily showed similar protein motifs and structural domains, which means the same subfamily genes may have the same function.
We know GRAS genes were found to possess five conserved structural domains: VHIID, LHRI, LHRII, PFYRE, and SAW [5]. With research progress, an increasing number of experiments have demonstrated that the LRI–VHIID–LRII structure of the GRAS protein is involved in protein–DNA and protein–protein interactions and these pieces of evidence also indirectly indicate that the C-terminal structure of the GRAS protein mainly plays a major role in its transcription and translation processes [71]. The PFYRE motif is divided into three conserved regions, P (proline), FY (phenylalanine and tyrosine), and RE (arginine and glutamate acid), which may be related to phosphorylation [73]. Although the function of the SAW motif is unknown, it may play an important role in maintaining the structural integrity of the GRAS protein [74]. In addition, the N-terminal of GRAS includes DELLA and TVHYNP proteins, whose high variability determines the diversity of GRAS protein functions [29].
Since the 1960s, the green revolution (GR), marked by semidwarf breeding, has dramatically increased the yields of major crops worldwide. Semidwarf plants have the advantage of being lodging resistant and have a high harvest index, which greatly increases plant yield [75]. Research shows that the DELLA proteins are green-revolution genes; they are negative regulators of the GAs metabolic pathway and belong to the plant-specific GRAS family; they act as blocking proteins of the GA signal to regulate vertical growth and plants overexpressing the DELLA gene showed dwarfism [76]. Our protein–protein interaction studies revealed that AsGRAS genes are also involved in GA signalling. So, this property of DELLA protein helps to clarify the important mechanism of the green-revolution gene DELLA; it also provides a strategy for cultivating high-yielding crops and reducing nitrogen fertilization. DELLA proteins regulate plant growth and development, but their structural domains are relatively complex [20,77,78]. There are five DELLA proteins in the Arabidopsis GRAS family, all of which contain the typical structural domains of DELLA and TVHYNP at their N terminus [79]. In oat, we identified five DELLA genes but not all of them contained the DELLA structural domain; this phenomenon is similar to that in rice [80]. This may be due to deletions caused during chromosome replication or fragment insertions during gene replication. Whether the presence or absence of the DELLA structural domain affects the function of oat DELLA protein remains to be further investigated.
MicroRNAs (miRNAs), as extremely important endogenous noncoding small RNA molecules in plants, play an important role in the regulation of endogenous gene expression in plants [81]. The main target genes of miRNAs are transcription factors, stress-responsive genes, important protein-coding genes, etc. [82]. They play important roles in leaf development and formation (miR165/166) [83], flowering time repression (miR824) [84], drought resistance (miR164) [85], transition from nutritional to reproductive growth (miR172) [86], and developmental timing (miR172/156) [87]. miR171, a conserved miRNA in plants, can mediate gibberellin-regulated chlorophyll biosynthesis through binding of the miR171-targeted SCL gene to GT cis-elements [88]. Downregulation of sly-miR171 expression in tomato was found to be associated with irregular compound leaf development and increased axillary branch number [89]. Our study showed that GRAS family genes were targeted by miRNA171 and AsGRAS genes possess a complex network relationship with miRNAs, where one miRNA can target multiple genes and one gene can be targeted by multiple miRNAs. The prediction of so many miRNAs can laterally prove that the GRAS family or its binding sites are conserved and we know that miRNA171 plays an important role in the GRAS family through prediction; so, further studies are needed on its specific regulatory function.
Plants generally respond to external abiotic stresses by modulating the expression of transcription factors to alter their metabolism [90]. Analysis of the 2000 bp promoter region upstream of oat revealed that a total of 38 cis-acting protagonists were identified to be involved in plant growth and stress responses and 97.8% of genes contained at least one element involved in defence and stress responsiveness (Figure S3, Table S10). Several studies have confirmed the response of GRAS genes to abiotic stresses, such as OsGRAS23 in rice [91], BkGRAS2 in Betula kirghisorum [92], Ct-SCL1 in Cyamopsis tetragonoloba [93], and SCL7 in Arabidopsis [32]. According to public transcriptome data, GRAS genes were clearly classified into three categories: upregulated, downregulated, and unchanged under high temperatures. Meanwhile, they were clearly classified into five categories under salt and drought stress, including upregulated, downregulated, unchanged, up and down, and down and up. It is worth noting that the number of genes that were not expressed was 3, 9, 14, 5, 3, and 5 in drought with silicon, salt stress, high temperature, drought stress, lemma development and seed vigour, respectively. Furthermore, public transcriptome data analysis and qRT-PCR analysis indicated that some genes of the PAT1, SCL4/7, DELLA, and LISCL subfamilies were found to be highly expressed under abiotic stresses such as drought and salt stress, specifically AsGRAS6/16/37/40/51/84. Further review of the functions of the above subfamilies revealed that they all play important roles in plant stress resistance. For example, the DELLA subfamily promotes ABA accumulation and improves plant stress resistance by positively regulating GA; the genes of SCL and PAT1 subfamilies are upregulated in response to stresses such as drought and low temperature. Therefore, we can focus on the response of these subfamilies to stress in the future and provide insight for revealing the mechanism of the GRAS family in stress resistance in oat.

5. Conclusions

In conclusion, we performed a genome-wide analysis of the GRAS family in oat, culminating in the identification of 90 AsGRAS genes, and biochemical characterization was performed. AsGRAS genes were distributed on 21 oat chromosomes, and gene duplication plays an important role in the expansion of the AsGRAS family. Based on the phylogenetic tree, AsGRAS proteins were classified into 10 subfamilies: HAM, LS, DLT, SCR, DELLA, SCL4/7, SCL3, LISCL, SHR, and PAT1. Gene structure and motif analysis indicated that the GRAS proteins of the same subfamily have similar protein motifs and that all genes contain the GRAS structural domain. miRNA prediction showed that the AsGRAS genes were targeted by miRNA171. Transcript-expression analysis showed that most GRAS genes are involved in plant growth and are also responsive to abiotic stresses such as drought and salt, which provides important resources for future functional research in molecular breeding and genetic improvement.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13071807/s1, Figure S1. The motif composition structure of oat GRAS protein. Figure S2. The number of AsGRAS genes on chromosomal. Figure S3. The cis-element in the promoter regions of the GRAS gene family. Table S1. qRT-PCR primers of AsGRAS genes. Table S2. Information of 90 AsGRAS genes. Table S3. The basic information of GRAS family genes in oats. Table S4. Segmental-duplicated gene pairs of GRAS genes in oats. Table S5. Segmental and tandem duplications of AsGRAS gene pairs in oat. Table S6. Synteny analysis between A. sativa with A. thaliana, O. sativa, T. aestivum and Z. mays. Table S7. Information on protein interactions of AsGRAS genes. Table S8. miRNA-AsGRAS prediction. Table S9. Expression pattern of 90 AsGRAS genes under various stress treatments. Table S10. The cis-element in the promoter regions of the GRAS gene family.

Author Contributions

Conceptualization, R.W. and W.L.; methodology, K.L.; data collation and curation, R.W. and K.L.; writing—original draft preparation, R.W.; writing—review and editing, G.L. and Y.W.; supervision, K.L.; project administration, W.L.; funding acquisition, W.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Qinghai Natural Science Foundation Program-Innovation Team (2022-ZJ-902); China Agriculture Research System (CARS-34).

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank Chengjie Chen for providing the TBtools software.

Conflicts of Interest

The authors declare they have no conflict of interest.

References

  1. Zheng, X.W.; Yi, D.X.; Shao, L.H.; Li, C. In silico genome-wide identification, phylogeny and expression analysis of the R2R3-MYB gene family in Medicago truncatula. J. Integr. Agric. 2017, 16, 1576–1591. [Google Scholar] [CrossRef] [Green Version]
  2. Jin, J.F.; Wang, Z.Q.; He, Q.Y.; Wang, J.Y.; Li, P.F.; Xu, J.M.; Zheng, S.J.; Fan, W.; Yang, J.L. Genome-wide identification and expression analysis of the NAC transcription factor family in tomato (Solanum lycopersicum) during aluminum stress. BMC Genom. 2020, 21, 288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Itoh, H.; Ueguchi-Tanaka, M.; Sato, Y.; Ashikari, M.; Matsuoka, M. The gibberellin signaling pathway is regulated by the appearance and disappearance of SLENDER RICE1 in nuclei. Plant Cell 2002, 14, 57–70. Available online: https://www.jstor.org/stable/3871482 (accessed on 20 December 2022). [CrossRef] [PubMed] [Green Version]
  4. Morohashi, K.; Minami, M.; Takase, H.; Hotta, Y.; Hiratsuka, K. Isolation and characterization of a novel GRAS gene that regulates meiosis-associated gene expression. J. Biol. Chem. 2003, 278, 20865–20873. [Google Scholar] [CrossRef] [Green Version]
  5. Bolle, C. Chapter 10—Structure and evolution of plant GRAS family proteins. In Plant Transcription Factors; Gonzalez, D.H., Ed.; Academic Press: Boston, MA, USA, 2016; pp. 153–161. [Google Scholar] [CrossRef]
  6. Ro, D.K.; Ehlting, J.; Douglas, C.J. Cloning, functional expression, and subcellular localization of multiple NADPH-cytochrome P450 reductases from hybrid poplar. Plant Physiol. 2002, 130, 1837–1851. [Google Scholar] [CrossRef] [Green Version]
  7. Zhang, H.; Mi, L.M.; Xu, L.; Yu, C.X.; Li, C.; Chen, C.L. Genome-wide identification, characterization, interaction network and expression profile of GRAS gene family in sweet orange (Citrus sinensis). Sci. Rep. 2019, 9, 2156. [Google Scholar] [CrossRef]
  8. Li, S.P.; Zhao, Y.H.; Zhao, Z.; Wu, X.L.; Sun, L.F.; Liu, Q.S.; Wu, Y.K. Crystal structure of the GRAS domain of SCARECROW-LIKE7 in Oryza sativa. Plant Cell 2016, 28, 1025–1034. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Chen, K.M.; Li, H.W.; Chen, Y.F.; Zheng, Q.; Li, B.; Li, Z.S. TaSCL14, a novel wheat (Triticum aestivum L.) GRAS gene, regulates plant growth, photosynthesis, tolerance to photooxidative stress, and senescence. J. Genet. Genom. 2015, 42, 21–32. [Google Scholar] [CrossRef] [PubMed]
  10. Sun, X.L.; Xue, B.; Jones, W.T.; Rikkerink, E.; Dunker, A.K.; Uversky, V.N. A functionally required unfoldome from the plant kingdom: Intrinsically disordered N-terminal domains of GRAS proteins are involved in molecular recognition during plant development. Plant Mol. Biol. 2011, 77, 205–223. [Google Scholar] [CrossRef]
  11. Sun, X.L.; Jones, W.T.; Harvey, D.; Edwards, P.J.B.; Pascal, S.M.; Kirk, C.; Considine, T.; Sheerin, D.J.; Rakonjac, J.; Oldfield, C.J.; et al. N-terminal domains of DELLA proteins are intrinsically unstructured in the absence of interaction with GID1/gibberellic acid receptors. J. Biol. Chem. 2010, 285, 11557–11571. [Google Scholar] [CrossRef] [Green Version]
  12. Lee, M.H.; Kim, B.; Song, S.K.; Heo, J.O.; Yu, N.I.; Lee, S.A.; Kim, M.; Kim, D.G.; Sohn, S.O.; Lim, C.E.; et al. Large-scale analysis of the GRAS gene family in Arabidopsis thaliana. Plant Mol. Biol. 2008, 67, 659–670. [Google Scholar] [CrossRef] [Green Version]
  13. Liu, M.; Huang, L.; Ma, Z.; Sun, W.J.; Wu, Q.; Tang, Z.Z.; Bu, T.L.; Li, C.L.; Chen, H. Genome-wide identification, expression analysis and functional study of the GRAS gene family in Tartary buckwheat (Fagopyrum tataricum). BMC Plant Biol. 2019, 19, 342. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Zhang, B.; Liu, J.; Yang, Z.E.; Chen, E.Y.; Zhang, C.J.; Zhang, X.Y.; Li, F.G. Genome-wide analysis of GRAS transcription factor gene family in Gossypium hirsutum L. BMC Genom. 2018, 19, 348. [Google Scholar] [CrossRef] [PubMed]
  15. Shan, Z.Y.; Luo, X.L.; Wu, M.Y.; Wei, L.M.; Zhu, Y.M. Genome-wide identification and expression of GRAS gene family members in cassava. BMC Plant Biol. 2020, 20, 46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Wang, Y.X.; Liu, Z.W.; Wu, Z.J.; Li, H.; Wang, W.L.; Cui, X.; Zhuang, J. Genome-wide identification and expression analysis of GRAS family transcription factors in tea plant (Camellia sinensis). Sci. Rep. 2018, 8, 3949. [Google Scholar] [CrossRef] [Green Version]
  17. Zhang, H.L.; Cao, Y.P.; Shang, C.; Li, J.K.; Wang, J.L.; Wu, Z.Y.; Ma, L.C.; Qi, T.X.; Fu, C.X.; Bai, Z.T.; et al. Genome-wide characterization of GRAS family genes in Medicago truncatula reveals their evolutionary dynamics and functional diversification. PLoS ONE 2017, 12, e0185439. [Google Scholar] [CrossRef] [Green Version]
  18. Yuan, Y.Y.; Fang, L.C.; Karungo, S.K.; Zhang, L.L.; Gao, Y.Y.; Li, S.H.; Xin, H.P. Overexpression of VaPAT1, a GRAS transcription factor from Vitis amurensis, confers abiotic stress tolerance in Arabidopsis. Plant Cell Rep. 2016, 35, 655–666. [Google Scholar] [CrossRef]
  19. Tian, C.G.; Wan, P.; Sun, S.H.; Li, J.Y.; Chen, M.S. Genome-wide analysis of the GRAS gene family in rice and Arabidopsis. Plant Mol. Biol. 2004, 54, 519–532. [Google Scholar] [CrossRef]
  20. Liu, X.Y.; Widmer, A. Genome-wide comparative analysis of the GRAS gene family in Populus, Arabidopsis and rice. Plant Mol. Biol. Rep. 2014, 32, 1129–1145. [Google Scholar] [CrossRef]
  21. Chen, Y.Q.; Tai, S.S.; Wang, D.W.; Ding, A.M.; Sun, T.T.; Wang, W.F.; Sun, Y.H. Homology-based analysis of the GRAS gene family in tobacco. Genet. Mol. Res. 2015, 14, 15188–15200. [Google Scholar] [CrossRef]
  22. Xu, W.; Chen, Z.X.; Ahmed, N.; Han, B.; Cui, Q.H.; Liu, A.Z. Genome-wide identification, evolutionary analysis, and stress responses of the GRAS gene family in castor beans. Int. J. Mol. Sci. 2016, 17, 1004. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Grimplet, J.; Agudelo-Romero, P.; Teixeira, R.T.; Martinez-Zapater, J.M.; Fortes, A.M. Structural and functional analysis of the GRAS gene family in grapevine indicates a role of GRAS proteins in the control of development and stress responses. Front. Plant Sci. 2016, 7, 353. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Lu, J.X.; Wang, T.; Xu, Z.D.; Sun, L.D.; Zhang, Q.X. Genome-wide analysis of the GRAS gene family in Prunus mume. Mol. Genet. Genom. 2015, 290, 303–317. [Google Scholar] [CrossRef] [PubMed]
  25. Zeng, X.; Ling, H.; Chen, X.M.; Guo, S. Genome-wide identification, phylogeny and function analysis of GRAS gene family in Dendrobium catenatum (Orchidaceae). Gene 2019, 705, 5–15. [Google Scholar] [CrossRef]
  26. Li, W.J.; Wu, J.G.; Weng, S.L.; Zhang, Y.J.; Zhang, D.P.; Shi, C.H. Identification and characterization of dwarf 62, a loss-of-function mutation in DLT/OsGRAS-32 affecting gibberellin metabolism in rice. Planta 2010, 232, 1383–1396. [Google Scholar] [CrossRef]
  27. Cenci, A.; Rouard, M. Evolutionary analyses of GRAS transcription factors in angiosperms. Front. Plant Sci. 2017, 8, 273. [Google Scholar] [CrossRef] [Green Version]
  28. Cui, H.C.; Levesque, M.P.; Vernoux, T.; Jung, J.W.; Paquette, A.J.; Gallagher, K.L.; Wang, J.Y.; Blilou, I.; Scheres, B.; Benfey, P.N. An evolutionarily conserved mechanism delimiting SHR movement defines a single layer of endodermis in plants. Science 2007, 316, 421–425. [Google Scholar] [CrossRef] [Green Version]
  29. Bolle, C. The role of GRAS proteins in plant signal transduction and development. Planta 2004, 218, 683–692. [Google Scholar] [CrossRef]
  30. Ho-Plágaro, T.; Molinero-Rosales, N.; Flores, D.F.; Diaz, M.V.; Garcia-Garrido, J.M. Identification and expression analysis of GRAS transcription factor genes involved in the control of arbuscular mycorrhizal development in tomato. Front. Plant Sci. 2019, 10, 268. [Google Scholar] [CrossRef]
  31. Bolle, C.; Koncz, C.; Chua, N.H. PAT1, a new member of the GRAS family, is involved in phytochrome A signal transduction. Genes Dev. 2000, 14, 1269–1278. [Google Scholar] [CrossRef]
  32. Ma, H.S.; Liang, D.; Shuai, P.; Xia, X.L.; Yin, W.L. The salt-and drought-inducible poplar GRAS protein SCL7 confers salt and drought tolerance in Arabidopsis thaliana. J. Exp. Bot. 2010, 61, 4011–4019. [Google Scholar] [CrossRef] [Green Version]
  33. Wysocka-Diller, J.W.; Helariutta, Y.; Fukaki, H.; Malamy, J.E.; Benfey, P.N. Molecular analysis of SCARECROW function reveals a radial patterning mechanism common to root and shoot. Development 2000, 127, 595–603. [Google Scholar] [CrossRef]
  34. Davière, J.M.; Achard, P. A pivotal role of DELLAs in regulating multiple hormone signals. Mol. Plant 2016, 9, 10–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Achard, P.; Renou, J.P.; Berthomé, R.; Harberd, N.P.; Genschik, P. Plant DELLAs restrain growth and promote survival of adversity by reducing the levels of reactive oxygen species. Curr. Biol. 2008, 18, 656–660. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Peng, J.R.; Carol, P.; Richards, D.E.; King, K.E.; Cowling, R.J.; Murphy, G.P.; Harberd, N.P. The Arabidopsis GAI gene defines a signaling pathway that negatively regulates gibberellin responses. Genes Dev. 1997, 11, 3194–3205. [Google Scholar] [CrossRef] [Green Version]
  37. Ju, Z.L.; Liu, K.Q.; Zhao, G.Q.; Ma, X.; Jia, Z.F. Nitrogen fertilizer and sowing density affect flag leaf photosynthetic characteristics, grain yield, and yield components of oat in a semiarid region of northwest China. Agronomy 2022, 12, 2108. [Google Scholar] [CrossRef]
  38. Liu, K.Q.; Ju, Z.L.; Jia, Z.F.; Liang, G.L.; Ma, X.; Liu, W.H. Genome-wide identification and characterization of the Oat (Avena sativa L.) WRKY transcription factor family. Genes 2022, 13, 1918. [Google Scholar] [CrossRef] [PubMed]
  39. Yin, H.; Zhao, X.; Tong, L.L.; Wang, Z. In vitro and in vivo anti-hyperglycemic effects of polysaccharides from Auricularia auricular. Food Chem. 2015, 36, 221–226. [Google Scholar]
  40. Peng, Y.Y.; Yan, H.H.; Guo, L.C.; Deng, C.; Wang, C.L.; Wang, Y.B.; Kang, L.P.; Zhou, P.P.; Yu, K.Q. Reference genome assemblies reveal the origin and evolution of allohexaploid oat. Nat. Genet. 2022, 54, 1248–1258. [Google Scholar] [CrossRef]
  41. Jin, J.P.; He, K.; Tang, X.; Li, Z.; Lv, L.; Zhao, Y.; Luo, J.C.; Gao, G. An Arabidopsis transcriptional regulatory map reveals distinct functional and evolutionary features of novel transcription factors. Mol. Biol. Evol. 2015, 32, 1767–1773. [Google Scholar] [CrossRef] [Green Version]
  42. Jin, J.P.; Tian, F.; Yang, D.C.; Meng, Y.Q.; Kong, L.; Luo, J.C.; Gao, G. PlantTFDB 4.0: Toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Res. 2016, 45, 1040–1045. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Garcia-Hernandez, M.; Berardini, T.; Chen, G.H.; Crist, D.; Doyle, A.; Huala, E.; Knee, E.; Lambrecht, M.; Miller, N.; Mueller, L.A.; et al. TAIR: A resource for integrated Arabidopsis data. Funct. Integr. Genom. 2002, 2, 239–253. [Google Scholar] [CrossRef] [PubMed]
  44. Guo, A.Y.; Chen, X.; Gao, G.; Zhang, H.; Zhu, Q.H.; Liu, X.C.; Zhong, Y.F.; Gu, X.C.; He, K.; Luo, J.C. PlantTFDB: A comprehensive plant transcription factor database. Nucleic Acids Res. 2007, 36, 966–969. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Matthews, D.E.; Carollo, V.L.; Lazo, G.R.; Anderson, O.D. GrainGenes, the genome database for small-grain crops. Nucleic Acids Res. 2003, 31, 183–186. [Google Scholar] [CrossRef] [Green Version]
  46. Chen, C.J.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.H.; Xia, R. TBtools: An integrative toolkit developed for interactive analyses of big biological data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  47. Yang, M.; Derbyshire, M.K.; Yamashita, R.A.; Marchler-Bauer, A. NCBI’s conserved domain database and tools for protein domain analysis. Curr. Protoc. Bioinform. 2020, 69, e90. [Google Scholar] [CrossRef] [Green Version]
  48. Artimo, P.; Jonnalagedda, M.; Arnold, K.; Baratin, D.; Csardi, G.; De Castro, E.; Duvaud, S.; Flegel, V.; Fortier, A.; Gasteiger, E. ExPASy: SIB bioinformatics resource portal. Nucleic Acids Res. 2012, 40, W597–W603. [Google Scholar] [CrossRef]
  49. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef]
  50. Subramanian, B.; Gao, S.; Lercher, M.J.; Hu, S.; Chen, W.H. Evolview v3: A webserver for visualization, annotation, and management of phylogenetic trees. Nucleic Acids Res. 2019, 47, W270–W275. [Google Scholar] [CrossRef]
  51. Bailey, T.L.; Johnson, J.; Grant, C.E.; Noble, W.S. The MEME suite. Nucleic Acids Res. 2015, 43, W39–W49. [Google Scholar] [CrossRef] [Green Version]
  52. Lescot, M.; Déhais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouzé, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef] [PubMed]
  53. Dai, X.B.; Zhuang, Z.H.; Zhao, P.X. psRNATarget: A plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018, 46, W49–W54. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Zhang, J.; Yin, Q.; Yan, Z.J.; Wan, Y.Q.; Wang, Y.Q. Molecular mechanism of silicon response to oat root under drought stress. Triticeae Genom. Genet. 2022, 13, 1–11. [Google Scholar] [CrossRef]
  55. Wu, B.; Hu, Y.; Huo, P.; Zhang, Q.; Chen, X.; Zhang, Z. Transcriptome analysis of hexaploid hulless oat in response to salinity stress. PLoS ONE 2017, 12, e0171451. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Ko, C.S.; Lee, J.S.; Seo, Y.W. Various temperature effects on spikelet growth in hulless oat during grain-filling stage. Agric. Food Sci. 2022, 31, 282–296. [Google Scholar] [CrossRef]
  57. Cheng, H.; Ma, X.Q.; Jia, S.G.; Li, M.L.; Mao, P.S. Transcriptomic analysis reveals the changes of energy production and AsA-GSH cycle in oat embryos during seed ageing. Plant Physiol. Bioch. 2020, 153, 40–52. [Google Scholar] [CrossRef]
  58. Bray, N.L.; Pimentel, H.; Melsted, P.; Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 2016, 34, 525–527. [Google Scholar] [CrossRef]
  59. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  60. Axtell, M.J.; Bowman, J.L. Evolution of plant microRNAs and their targets. Trends Plant Sci. 2008, 13, 343–349. [Google Scholar] [CrossRef]
  61. Jones-Rhoades, M.W.; Bartel, D.P.; Bartel, B. MicroRNAs and their regulatory roles in plants. Annu. Rev. Plant Biol. 2006, 57, 19–53. [Google Scholar] [CrossRef]
  62. Huang, W.; Xian, Z.Q.; Kang, X.; Tang, N.; Li, Z.G. Genome-wide identification, phylogeny and expression analysis of GRAS gene family in tomato. BMC Plant Biol. 2015, 15, 209. [Google Scholar] [CrossRef] [Green Version]
  63. Kumar, B.; Bhalothia, P. Evolutionary analysis of GRAS gene family for functional and structural insights into hexaploid bread wheat (Triticum aestivum). J. Biosci. 2021, 46, 45. [Google Scholar] [CrossRef]
  64. Song, X.M.; Liu, T.K.; Duan, W.K.; Ma, Q.H.; Ren, J.; Wang, Z.; Li, Y.; Hou, X.L. Genome-wide analysis of the GRAS gene family in Chinese cabbage (Brassica rapa ssp. pekinensis). Genomics 2014, 103, 135–146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Moghe, G.D.; Hufnagel, D.E.; Tang, H.; Xiao, Y.L.; Dworkin, L.; Town, C.D.; Conner, J.K.; Shiu, S.H. Consequences of whole-genome triplication as revealed by comparative genomic analyses of the wild radish Raphanus raphanistrum and three other Brassicaceae species. Plant Cell 2014, 26, 1925–1937. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Magadum, S.; Banerjee, U.; Murugan, P.; Gangapur, D.; Ravikesavan, R. Gene duplication as a major force in evolution. J. Genet. 2013, 92, 155–161. [Google Scholar] [CrossRef]
  67. Zou, M.; Guo, B.C.; He, S.P. The roles and evolutionary patterns of intronless genes in deuterostomes. Comp. Funct. Genom. 2011, 2011, 680673. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Jain, M.; Khurana, P.; Tyagi, A.K.; Khurana, J.P. Genome-wide analysis of intronless genes in rice and Arabidopsis. Funct. Integr. Genom. 2008, 8, 69–78. [Google Scholar] [CrossRef]
  69. Zhang, D.P.; Iyer, L.M.; Aravind, L. Bacterial GRAS domain proteins throw new light on gibberellic acid response mechanisms. Bioinformatics 2012, 28, 2407–2411. [Google Scholar] [CrossRef] [Green Version]
  70. Liu, L.S.; White, M.J.; MacRae, T.H. Transcription factors and their genes in higher plants: Functional domains, evolution and regulation. Eur. J. Biochem. 1999, 262, 247–257. [Google Scholar] [CrossRef]
  71. Hirsch, S.; Oldroyd, G.E.D. GRAS-domain transcription factors that regulate plant development. Plant Signal. Behav. 2009, 4, 698–700. [Google Scholar] [CrossRef] [Green Version]
  72. Torres-Galea, P.; Huang, L.F.; Chua, N.H.; Bolle, C. The GRAS protein SCL13 is a positive regulator of phytochrome-dependent red light signaling, but can also modulate phytochrome A responses. Mol. Genet. Genom. 2006, 276, 13–30. [Google Scholar] [CrossRef] [PubMed]
  73. Gao, M.J.; Parkin, I.; Lydiate, D.; Hannoufa, A. An auxin-responsive SCARECROW-like transcriptional activator interacts with histone deacetylase. Plant Mol. Biol. 2004, 55, 417–431. [Google Scholar] [CrossRef] [PubMed]
  74. Hirsch, S.; Kim, J.; Munoz, A.; Heckmann, A.B.; Downie, J.A.; Oldroyd, G.E.D. GRAS proteins form a DNA binding complex to induce gene expression during nodulation signaling in Medicago truncatula. Plant Cell 2009, 21, 545–557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Peng, J.; Richards, D.E.; Hartley, N.M.; Murphy, G.P.; Devos, K.M.; Flintham, J.E.; Beales, J.; Fish, L.J. ‘Green revolution’genes encode mutant gibberellin response modulators. Nature 1999, 400, 256–261. [Google Scholar] [CrossRef]
  76. Liu, Q.; Wu, K.; Harberd, N.P.; Fu, X.D. Green Revolution DELLAs: From translational reinitiation to future sustainable agriculture. Mol. Plant 2021, 14, 547–549. [Google Scholar] [CrossRef]
  77. Murase, K.; Hirano, Y.; Sun, T.P.; Hakoshima, T. Gibberellin-induced DELLA recognition by the gibberellin receptor GID1. Nature 2008, 456, 459–463. [Google Scholar] [CrossRef] [PubMed]
  78. Wang, L.; Ding, X.L.; Gao, Y.Q.; Yang, S.P. Genome-wide identification and characterization of GRAS genes in soybean (Glycine max). BMC Plant Biol. 2020, 20, 415. [Google Scholar] [CrossRef]
  79. Sun, X.L.; Jones, W.T.; Rikkerink, E.H.A. GRAS proteins: The versatile roles of intrinsically disordered proteins in plant signalling. Biochem. J. 2012, 442, 1–12. [Google Scholar] [CrossRef] [Green Version]
  80. Itoh, H.; Shimada, A.; Ueguchi-Tanaka, M.; Kamiya, N.; Hasegawa, Y.; Ashikari, M.; Matsuoka, M. Overexpression of a GRAS protein lacking the DELLA domain confers altered gibberellin responses in rice. Plant J. 2005, 44, 669–679. [Google Scholar] [CrossRef]
  81. Bartel, D.P. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004, 116, 281–297. [Google Scholar] [CrossRef] [Green Version]
  82. Rogers, K.; Chen, X.M. Biogenesis, turnover, and mode of action of plant microRNAs. Plant Cell 2013, 25, 2383–2399. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Merelo, P.; Ram, H.; Pia Caggiano, M.; Ohno, C.; Ott, F.; Straub, D.; Graeff, M.; Cho, S.K.; Yang, S.W.; Wenkel, S.; et al. Regulation of MIR165/166 by class II and class III homeodomain leucine zipper proteins establishes leaf polarity. Proc. Natl. Acad. Sci. USA 2016, 113, 11973–11978. [Google Scholar] [CrossRef] [PubMed]
  84. Hu, J.Y.; Zhou, Y.; He, F.; Dong, X.; Liu, L.Y.; Coupland, G.; Turck, F.; Meaux, J.D. miR824-regulated AGAMOUS-LIKE16 contributes to flowering time repression in Arabidopsis. Plant Cell 2014, 26, 2024–2037. [Google Scholar] [CrossRef] [Green Version]
  85. Fang, Y.J.; Xie, K.B.; Xiong, L.Z. Conserved miR164-targeted NAC genes negatively regulate drought resistance in rice. J. Exp. Bot. 2014, 65, 2119–2135. [Google Scholar] [CrossRef] [Green Version]
  86. Wang, J.W.; Park, M.Y.; Wang, L.J.; Koo, Y.; Chen, X.Y.; Weigel, D.; Poethig, R.S. miRNA control of vegetative phase change in trees. PLoS Genet. 2011, 7, e1002012. [Google Scholar] [CrossRef] [Green Version]
  87. Wu, G.; Park, M.Y.; Conway, S.R.; Wang, J.W.; Weijel, D.; Poethig, R.S. The sequential action of miR156 and miR172 regulates developmental timing in Arabidopsis. Cell 2009, 138, 750–759. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Ma, Z.X.; Hu, X.P.; Cai, W.J.; Huang, W.H.; Zhou, X.; Luo, Q.; Yang, H.Q.; Wang, J.W.; Huang, J.R. Arabidopsis miR171-targeted scarecrow-like proteins bind to GT cis-elements and mediate gibberellin-regulated chlorophyll biosynthesis under light conditions. PLoS Genet. 2014, 10, e1004519. [Google Scholar] [CrossRef] [Green Version]
  89. Kravchik, M.; Stav, R.; Belausov, E.; Arazi, T. Functional characterization of microRNA171 family in tomato. Plants 2019, 8, 10. [Google Scholar] [CrossRef] [Green Version]
  90. Guo, J.R.; Sun, B.X.; He, H.; Zhang, Y.F.; Tian, H.Y.; Wang, B.S. Current understanding of bHLH transcription factors in plant abiotic stress tolerance. Int. J. Mol. Sci. 2021, 22, 4921. [Google Scholar] [CrossRef]
  91. Xu, K.; Chen, S.J.; Li, T.F.; Ma, X.S.; Liang, X.H.; Ding, X.F.; Liu, H.Y.; Luo, L.J. OsGRAS23, a rice GRAS transcription factor gene, is involved in drought stress response through regulating expression of stress-responsive genes. BMC Plant Biol. 2015, 15, 141. [Google Scholar] [CrossRef] [Green Version]
  92. Li, G.Y.; Yang, C.J.; Liu, G.J. Cloning and expression pattern analysis of BkGRAS2 from Betula kirghisorum. Genet. Mol. Res. 2015, 14, 11335–11347. [Google Scholar] [CrossRef] [PubMed]
  93. Reddy, B.M.; Kumari, N.V.; Johnson, A.M.A.; Kumar, N.J.; Venkatesh, B.; Jayamma, N.; Sudhakar, C. Scarecrow like Protein 1, (Ct-SCL1) involved in drought stress tolerance by interacting with SWI3B component of Chromatin modelling complex in Cluster bean, Cyamopsistetragonaloba (L.) Taub. Int. J. Res. Anal. Rev. 2018, 5, j304–j312. [Google Scholar]
Agronomy 13 01807 g001 550
Figure 1. Phylogenetic tree, conserved motifs, and gene structures of AsGRAS proteins. (A) Phylogenetic tree of 90 AsGRAS protein sequences. Phylogenetic trees were constructed using maximum likelihood in MEGA11 software. (B) Alignment of conserved motifs in AsGRAS proteins. Ten motifs are represented by differently coloured boxes and numbers. The scale bar showing the motif size is at the bottom. (C) Exon–intron structure of AsGRAS genes. Black lines indicate introns and pink, yellow, and green boxes indicate exons. The size is indicated by the scale at the bottom. UTR: untranslated regions; CDS: coding regions.
Figure 1. Phylogenetic tree, conserved motifs, and gene structures of AsGRAS proteins. (A) Phylogenetic tree of 90 AsGRAS protein sequences. Phylogenetic trees were constructed using maximum likelihood in MEGA11 software. (B) Alignment of conserved motifs in AsGRAS proteins. Ten motifs are represented by differently coloured boxes and numbers. The scale bar showing the motif size is at the bottom. (C) Exon–intron structure of AsGRAS genes. Black lines indicate introns and pink, yellow, and green boxes indicate exons. The size is indicated by the scale at the bottom. UTR: untranslated regions; CDS: coding regions.
Agronomy 13 01807 g001
Agronomy 13 01807 g002 550
Figure 2. Phylogenetic tree of Arabidopsis, Avena sativa and Medicago truncatula GRAS proteins. The phylogenetic tree was constructed using the maximum likelihood (ML) method with 1000 bootstrap replicates. The 10 subfamilies are marked with different colours and labeled with their names, such as SHR, DELLA, LS, etc. The red circles represent Arabidopsis GRAS proteins, the green circles represent Medicago truncatula GRAS proteins, and the blue stars represent oat GRAS proteins. The value at the node indicates the bootstrap value, which is used to evaluate the confidence of the branch.
Figure 2. Phylogenetic tree of Arabidopsis, Avena sativa and Medicago truncatula GRAS proteins. The phylogenetic tree was constructed using the maximum likelihood (ML) method with 1000 bootstrap replicates. The 10 subfamilies are marked with different colours and labeled with their names, such as SHR, DELLA, LS, etc. The red circles represent Arabidopsis GRAS proteins, the green circles represent Medicago truncatula GRAS proteins, and the blue stars represent oat GRAS proteins. The value at the node indicates the bootstrap value, which is used to evaluate the confidence of the branch.
Agronomy 13 01807 g002
Agronomy 13 01807 g003 550
Figure 3. Chromosomal distribution and duplications of AsGRAS genes. The tandemly duplicated genes are represented by the red lines. The scale bar on the left indicates the length (Mb) of oat chromosomes.
Figure 3. Chromosomal distribution and duplications of AsGRAS genes. The tandemly duplicated genes are represented by the red lines. The scale bar on the left indicates the length (Mb) of oat chromosomes.
Agronomy 13 01807 g003
Agronomy 13 01807 g004 550
Figure 4. Synteny analysis of AsGRAS genes in oat. The red lines represent gene pairs with segmental duplication.
Figure 4. Synteny analysis of AsGRAS genes in oat. The red lines represent gene pairs with segmental duplication.
Agronomy 13 01807 g004
Agronomy 13 01807 g005 550
Figure 5. Collinearity analysis of GRAS gene family in oat with Arabidopsis, rice, wheat, and maize. Orange boxes indicate oat chromosomes and red lines indicate homologous genes. The species name with the prefixes ‘A. sativa’, ‘A. thaliana’, ‘O. sativa’,‘T. aestivum’ and ‘Z. mays’ indicate Avena sativa, Arabidopsis thaliana, Oryza sativa, Triticum Aestivum and Zea mays, respectively. Other numbers and letters in the figure indicate the chromosomes of the species.
Figure 5. Collinearity analysis of GRAS gene family in oat with Arabidopsis, rice, wheat, and maize. Orange boxes indicate oat chromosomes and red lines indicate homologous genes. The species name with the prefixes ‘A. sativa’, ‘A. thaliana’, ‘O. sativa’,‘T. aestivum’ and ‘Z. mays’ indicate Avena sativa, Arabidopsis thaliana, Oryza sativa, Triticum Aestivum and Zea mays, respectively. Other numbers and letters in the figure indicate the chromosomes of the species.
Agronomy 13 01807 g005
Agronomy 13 01807 g006 550
Figure 6. Protein–protein interaction network for AsGRAS proteins based on their orthologs in Arabidopsis. IDD3, Zinc finger protein MAGPIE; IDD8, Zinc finger protein NUTCRACKER; WOX5, WUSCHEL-related homeobox 5; RBR1, Retinoblastoma-related protein 1; RBR2, Retinoblastoma-related protein 2; BBM1, AP2-like ethylene-responsive transcription factor BBM1; BBM2, AP2-like ethylene-responsive transcription factor BBM2; SCR2, Protein SCARECROW 2; SHR1, Protein SHORT-ROOT 1; SCL3, Scarecrow-like protein 3; GID1, Gibberellin receptor GID1; PIL13, Transcription factor PHYTOCHROME INTERACTING FACTOR-LIKE 13; PIL15, Transcription factor PHYTOCHROME INTERACTING FACTOR-LIKE 15; CXE18, probable carboxylesterase 18; GAI, DELLA protein GAI; RHT1, DELLA protein RHT-1.
Figure 6. Protein–protein interaction network for AsGRAS proteins based on their orthologs in Arabidopsis. IDD3, Zinc finger protein MAGPIE; IDD8, Zinc finger protein NUTCRACKER; WOX5, WUSCHEL-related homeobox 5; RBR1, Retinoblastoma-related protein 1; RBR2, Retinoblastoma-related protein 2; BBM1, AP2-like ethylene-responsive transcription factor BBM1; BBM2, AP2-like ethylene-responsive transcription factor BBM2; SCR2, Protein SCARECROW 2; SHR1, Protein SHORT-ROOT 1; SCL3, Scarecrow-like protein 3; GID1, Gibberellin receptor GID1; PIL13, Transcription factor PHYTOCHROME INTERACTING FACTOR-LIKE 13; PIL15, Transcription factor PHYTOCHROME INTERACTING FACTOR-LIKE 15; CXE18, probable carboxylesterase 18; GAI, DELLA protein GAI; RHT1, DELLA protein RHT-1.
Agronomy 13 01807 g006
Agronomy 13 01807 g007 550
Figure 7. Relationships between oat GRAS gene family members and miRNAs.
Figure 7. Relationships between oat GRAS gene family members and miRNAs.
Agronomy 13 01807 g007
Agronomy 13 01807 g008a 550Agronomy 13 01807 g008b 550
Figure 8. Expression patterns of 90 AsGRAS genes based on different adversity stresses or growth and development based on RNA-seq data. (A) Expression patterns of 90 AsGRAS genes after exogenous silicon addition under drought stress. (B) Expression patterns of 90 AsGRAS genes under salt stress at 0 h (A1), 2 h (A2), 4 h (A3), 8 h (A4), 12 h (A5), and 24 h (A6). (C) Expression patterns of 90 AsGRAS genes under high temperature. (D) Expression patterns of 90 AsGRAS genes under drought stress between DY2 and MW varieties at 0 h, 6 h, and 24 h. (E) Expression patterns of 90 AsGRAS genes during lemma development between BY685 and OA1613 varieties at the P1, P2, and P3 stages. (F) Expression patterns of 90 AsGRAS genes during seed ageing.
Figure 8. Expression patterns of 90 AsGRAS genes based on different adversity stresses or growth and development based on RNA-seq data. (A) Expression patterns of 90 AsGRAS genes after exogenous silicon addition under drought stress. (B) Expression patterns of 90 AsGRAS genes under salt stress at 0 h (A1), 2 h (A2), 4 h (A3), 8 h (A4), 12 h (A5), and 24 h (A6). (C) Expression patterns of 90 AsGRAS genes under high temperature. (D) Expression patterns of 90 AsGRAS genes under drought stress between DY2 and MW varieties at 0 h, 6 h, and 24 h. (E) Expression patterns of 90 AsGRAS genes during lemma development between BY685 and OA1613 varieties at the P1, P2, and P3 stages. (F) Expression patterns of 90 AsGRAS genes during seed ageing.
Agronomy 13 01807 g008aAgronomy 13 01807 g008b
Agronomy 13 01807 g009 550
Figure 9. Expression patterns of 10 AsGRAS genes in response to drought and salt stress. * indicates significant correlation at the 0.05 level, ** indicates highly significant correlation at the 0.01 level.
Figure 9. Expression patterns of 10 AsGRAS genes in response to drought and salt stress. * indicates significant correlation at the 0.05 level, ** indicates highly significant correlation at the 0.01 level.
Agronomy 13 01807 g009
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Wu, R.; Liu, W.; Liu, K.; Liang, G.; Wang, Y. Genome-Wide Identification and Expression of the GRAS Gene Family in Oat (Avena sativa L.). Agronomy 2023, 13, 1807. https://doi.org/10.3390/agronomy13071807

AMA Style

Wu R, Liu W, Liu K, Liang G, Wang Y. Genome-Wide Identification and Expression of the GRAS Gene Family in Oat (Avena sativa L.). Agronomy. 2023; 13(7):1807. https://doi.org/10.3390/agronomy13071807

Chicago/Turabian Style

Wu, Rui, Wenhui Liu, Kaiqiang Liu, Guoling Liang, and Yue Wang. 2023. "Genome-Wide Identification and Expression of the GRAS Gene Family in Oat (Avena sativa L.)" Agronomy 13, no. 7: 1807. https://doi.org/10.3390/agronomy13071807

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop