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Received: 19 December 2024
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Accepted: 24 January 2025
Published: 25 January 2025
Citation: Wang, X.; Dong, X.; Li, P.; Li,
M.; Wang, Z.; Zhou, Q.; Liu, Z.; Yan, L.
Genome-Wide Identification of the
GRAS Transcription Factor Family in
Medicago ruthenica and Expression
Analysis Under Drought Stress.
Agronomy 2025,15, 306. https://
doi.org/10.3390/agronomy15020306
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Article
Genome-Wide Identification of the GRAS Transcription Factor
Family in Medicago ruthenica and Expression Analysis Under
Drought Stress
Xingli Wang 1, Xueming Dong 1, Pengzhen Li 1, Mingyu Li 1, Zhaoming Wang 2, Qiang Zhou 1, Zhipeng Liu 1
and Longfeng Yan 3,*
1State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Pastoral
Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China;
wangxl2023@lzu.edu.cn (X.W.); dongxm20@lzu.edu.cn (X.D.); 220220901180@lzu.edu.cn (P.L.);
limy19@lzu.edu.cn (M.L.); zhouq2013@lzu.edu.cn (Q.Z.); lzp@lzu.edu.cn (Z.L.)
2National Center of Pratacultural Technology Innovation, Huhehaote 010051, China; nmmckh@163.com
3Ministry of Education Key Laboratory of Cell Activities and Stress Adaptations, School of Life Sciences,
Lanzhou University, Lanzhou 730000, China
*Correspondence: yanlf@lzu.edu.cn
Abstract: The GRAS gene family encodes a group of plant-specific transcription factors
essential for regulating plant growth, development and stress responses. While the GRAS
gene family has been extensively studied in various plant species, a comprehensive charac-
terization of the GRAS gene family in Medicago ruthenica has not yet been conducted. In this
study, a total of 62 MrGRAS gene family members were identified through a comprehen-
sive whole-genome analysis of M. ruthenica, and phylogenetic analysis categorized these
62 genes into 13 distinct groups. Gene structure and conserved domain analysis showed
that MrGRAS genes from the same evolutionary branch share similar exon–intron ar-
chitecture and conserved motifs. A large number of hormone-responsive, growth and
development and stress-responsive cis-regulatory elements were detected in the upstream
sequences of MrGRAS genes. RT-qPCR analysis showed that drought stress significantly
induced the expression of nine selected MrGRAS genes. Overall, this study analyzed the
phylogenetic relationships, conserved domains, cis-regulatory elements and expression
patterns of the GRAS gene family in M. ruthenica, filling the gap in the identification of the
MrGRAS gene family and laying the foundation for functional analysis of the MrGRAS
gene family.
Keywords: genome-wide analysis; GRAS gene family; Medicago ruthenica; drought stress;
expression analysis
1. Introduction
Transcription factors are a type of protein that interacts with DNA and regulate
the process transcription. By connecting to specific regions on DNA (cis-regulatory ele-
ments), they influence the transcription activity of nearby genes, thereby regulating gene
expression [
1
]. Transcription factor families like GRAS, NAC, WOX, WRKY, MADS, MYB,
and bZIP are known to play key roles in plant growth and development, hormone signaling
and stress responses [
2
–
6
]. GRAS family members contain a conserved domain, known
as the GRAS domain. GRAS is an acronym representing several representative members
namely: Gibberellic Acid Insensitive (GAI), Repressor of GAI (RGA) and Scarecrow (SCR),
respectively [
7
–
9
]. The GRAS domain consists mainly of five typical motif regions: LHR I,
Agronomy 2025,15, 306 https://doi.org/10.3390/agronomy15020306
Agronomy 2025,15, 306 2 of 19
VHIID, LHR II, PFYRE, and SAW [
10
]. The VHIID is considered the fundamental structure
of GRAS proteins, the PFYRE is associated with phosphorylation [
11
]. The SAW is situated
at the C-terminus and consists of three conserved amino acid groups: R-E, W-G, and
W-W [
12
]. The N-terminal amino acid sequence of GRAS proteins can fold into specific
structures, enabling them to connect to target proteins and participate in multiple signal
pathways [
13
]. Now, Arabidopsis GRAS transcription factors were further divided into ten
subfamilies in studies of molecular signal recognition: DELLA, DLT, HAM, SCL4/7, SCR,
PAT1, SCL3, LAS, LISCL, and SHR [
14
]. Liu and Widmer conducted a comparative analysis
and identification of GRAS proteins in multiple species including Oryza sativa,Arabidopsis
thaliana,Populus trichocarpa,Vitis vinifera, and Solanum lycopersicum. Their study categorized
the O. sativa GRAS proteins into 13 subfamilies: DELLA, SCR, LISCL, PAT1, DLT, SCL3,
Pt20, HAM, SCL4/7, LAS, SHR, Os19, and Os4 [15].
In Arabidopsis, the SHR and SCR subfamilies influence the establishment of the cor-
tex/endodermis. These subfamily members are preferentially expressed in Triticum aes-
tivum roots, exhibiting a similar pattern, indicating a conserved role in regulating radial
growth [
16
]. The DoSCL3-1, 3-2, and 3-3 genes identified from the Dioscorea genome are
homologous to SCL3, showing high transcripts in all tissues, suggesting their importance
in plant development and growth [
17
]. In O. sativa,OsGRAS23, a homolog of SCL14, seems
important for participating in the drought stress response [
18
]. GRAS genes exhibit tissue
specificity, evident from differences in the transcript levels of FtGRAS in different tissues
and fruit development stages in Fagopyrum tataricum, indicating their distinct functions
in different tissue types [
19
]. Furthermore, GRAS genes are involved in responses to
hormone signaling and stress responses. Some identified EgrGRAS genes in Eucalyptus
grandis exhibit differential responses to gibberellin, abscisic acid, salt, drought, and temper-
ature stresses. Additionally, there are expression differences among members of the same
subfamily [
20
]. In Setaria italica, treatment with the exogenous regulator paclobutrazol
alters the transcription levels of DELLA members, reducing plant height while increas-
ing grain weight, corroborating their relationship with fruit development [
21
]. Drought,
sodium chloride, and jasmonic acid induce the expression of the OsGRAS23 gene in
O. sativa, which enhances drought tolerance [
18
]. In Brachypodium distachyon,BdGRAS
genes show changes in expression levels after inoculation with O. sativa blast fungus [
22
].
To date, the expression patterns and evolutionary relationships of GRAS genes have been
studied in various species, including Arabidopsis [
23
], Cucumis sativus [
24
], O. sativa [
14
],
Brassia campestris [
25
], Triticum aestivum [
26
], Vitis vinifera [
27
], Fagopyrum tataricum [
19
],
Secale cereal [
28
], Miscanthus sinensis [
29
], G. max [
30
], Musa nana [
31
], and Cymbidium [
32
].
However, there is currently no information on the characterization and functional analysis
of the GRAS gene family in M. ruthenica.
Medicago ruthenica (2n = 2x = 16), belonging to the legume family (Leguminosae) in
the subfamily Papilionoideae [
33
], is mainly distributed in northern China, Mongolia, and
eastern Siberia. M. ruthenica is rich in protein, minerals, and other nutritional elements,
making it palatable and easily digestible, and has been widely grown as a novel forage crop
in recent years [
34
]. Due to its strong tolerance to drought, saline–alkali conditions, and cold
snowy winters, it is considered a genetic resource for enhancing the abiotic stress tolerance
in Medicago sativa [
35
]. However, information regarding GRAS genes and their functions in
M. ruthenica remains unclear. Therefore, the identification and characterization of GRAS
genes is crucial for understanding their roles in M. ruthenica towards stress tolerance, and
plant growth and development. This study aims to identify members of the GRAS gene
family in M. ruthenica and to study their response to drought stress. In this research, we
first identified GRAS genes in M. ruthenica genome, followed by detailed bioinformatics
studies (phylogenetic analysis, gene structure domains, conserved domains, collinearity,
Agronomy 2025,15, 306 3 of 19
chromosome locations, and cis-regulatory elements). In addition, this study also explored
the expression patterns of GRAS genes under drought stress, providing a foundation for
further analysis of GRAS genes in M. ruthenica, to explore their potential applications in
enhancing abiotic stress tolerance in leguminous plants.
2. Materials and Methods
2.1. Identification and Analysis of the MrGRAS Gene Family
To identify members of the M. ruthenica GRAS gene family, the M. ruthenica
genome sequence data were downloaded from github (https://github.com/, accessed on
20 October 2024) [
36
]. Subsequently, 34 Arabidopsis GRAS protein sequences were used
as reference sequences. The TBtools-Blast Compare Two Seq tool was utilized for the
initial local blast analysis [
36
]. The HMM of the GRAS domain (PF03514) was acquired
from the Pfam database (http://pfam-legacy.xfam.org/, accessed on 24 October 2024).
First, the downloaded HMM files were used to search the M. ruthenica protein file us-
ing HMMER 3.4 (phmmer search|HMMER), with the E-value set to
≤
0.01 [
37
]. To re-
duce redundancy, duplicate sequences were filtered out by merging the outcomes ob-
tained from BLAST and HMM searches. Additionally, sequences lacking the PF03514
domain were also filtered out based on the analysis at NCBI conserved domain database
(https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi, accessed on 24 October
2024), Pfam database (http://pfam-legacy.xfam.org/, accessed on 24 October 2024) and
SMART database (https://smart.embl.de/smart/batch.pl, accessed on 24 October 2024).
Finally, all identified M. ruthenica GRAS genes were renamed as MrGRAS01-MrGRAS62.
Additionally, we analyzed the physicochemical properties of the MrGRAS proteins using
the TBtools-Proteion ProtParamCalc and predicted subcellular localization using Plant-
mPLoc (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi, accessed on 24 October 2024).
2.2. Evolutionary, Gene Structure, and Conserved Motif Analysis of MrGRAS Gene Family
For the evolutionary study of M. ruthenica and Arabidopsis members, all MrGRAS
proteins were first subjected to multiple sequence alignment using ClustalW (http://www.
clustal.org/clustal2/, accessed on 26 October 2024) [
38
]. Subsequently, an evolutionary tree
was constructed by MEGA 11 software (https://www.megasoftware.net/docs, accessed on
26 October 2024) using the neighbor-joining (NJ) method with 1000 bootstrap replicates [
38
].
All the MsGRAS genes were classified according to their evolutionary relationships with
GRAS genes in Arabidopsis. Additionally, the conserved motifs of all MrGRAS proteins were
identified and analyzed using the MEME online platform (https://meme-suite.org/meme/,
accessed on 26 October 2024) [
39
]. Using following parameters: length: 20 to 100, maximum
no. of motifs to be identified: 10, repeat number: 0 or 1.
2.3. Prediction of Protein Secondary Structure and Modeling of MrGRAS Proteins’ 3D Structures
We utilized the SWISS-MODEL platform (https://swissmodel.expasy.org/, accessed
on 27 October 2024) to predict the three-dimensional structures of MrGRAS proteins [
37
].
The quality of the predicted models was assessed using the Global Model Quality Estima-
tion (GMQE) metric. Additionally, the secondary structure of the proteins was analyzed us-
ing SOPMA (https://npsa.lyon.inserm.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_
server.html, accessed on 27 October 2024).
2.4. Promoter Cis-Regulatory Elements Analysis of MrGRAS Gene Family
The 2000 bp sequences of all MrGRAS gene promoters were analyzed for cis-regulatory
elements using the PlantCARE database (https://bioinformatics.psb.ugent.be/webtools/
plantcare/html/, accessed on 18 December 2024) [38].
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2.5. Chromosomal Distribution, Gene Duplication and Collinearity Analyses of MrGRAS Genes
The location information and chromosome length of the MrGRAS genes were acquired
from Ensembl Plants [
40
]. Next, visual analysis of the chromosome distribution of Mr-
GRAS genes was conducted using the MapGene2Chrom (http://mg2c.iask.in/mg2c_v2.0/,
accessed on 30 October 2024) [
37
]. Duplication events of GRAS genes in the M. ruthenica
genome were analyzed using TBtools (v2.147) software, along with the collinearity relation-
ships of GRAS genes within M. ruthenica species and between M. ruthenica and Arabidopsis,
Glycine max, and M. sativa.
2.6. Analysis of the Expression Patterns of MrGRAS Genes Under Different Abiotic Stresses Treatments
The raw transcriptome sequencing data [
41
] of M. ruthenica under different abiotic
stresses (ABA, Cold, Freezing, Osmotic, Salt, and Drought) were downloaded from Github.
Firstly, FASTP (v0.19.4) software was utilized to perform quality control and filtering on the
raw sequencing data to remove low-quality data. The quality-controlled data were aligned
to the reference genome using HISAT2, then featureCounts tool was used for quantitative
analysis of gene expression [
25
]. Subsequently, TBtools-BLAST alignment was performed
on this transcriptome dataset [
26
]. The expression levels of these genes were visualized
using TBtools-HeatMap. In addition, correlation analysis of MrGRAS gene expression
under the six stress conditions was conducted using the Corrplot plugin in Origin.
2.7. Plant Material, Growth Conditions, and Stress Treatment
The “Zhongke” M. ruthenica variety was used as the experimental material (We started
preparing the materials on 10 October 2024, and completed all experiments and analyses
by 17 November 2024). Two thousand M. ruthenica seeds were subjected to abrasion
treatment to break the hard coat. After disinfection with 5% sodium hypochlorite to
remove surface contaminants, the seeds were spread in square petri dishes for germination.
After inverted cultivation in a walk-in growth chamber for four days, healthy and robust
seedlings were selected and transferred to hydroponic boxes. The seedlings were then
grown hydroponically using MS nutrient solution for four days, with the solution replaced
every two days. Subsequently, the seedlings were subjected to the following treatments:
(A)
Control treatment: Seedlings were transferred to hydroponic boxes, and starting from
the 8th day, they were treated with MS solution daily until sampling on the 13th day.
(B)
Different concentrations of drought stress treatment: Seedlings were transferred to
hydroponic boxes, and starting from the 8th day, they were treated daily with different
concentrations of Mannitol (50 mM, 100 mM, 200 mM, 300 mM and 400 mM) and sampled.
(C)
Direct drought stress treatment: Seedlings were transferred to hydroponic boxes, and
on the 12th day (The treatments at different time points were ultimately sampled at
the same time), they were treated with 400 mM Mannitol for 1 h, 3 h, 6 h, 12 h, and
24 h, followed by sampling on the 13th day.
After every treatment, leaves were collected, rapidly frozen in liquid nitrogen, and
then kept at
−
80
◦
C to extract total RNA. Three technical and three biological duplicates
were employed.
2.8. RT-qPCR Analysis
The SPARKeasy Plant Extraction Kit (SparkJade, Jinan, China) was used to extract
total, which was reverse transcribed into complementary DNA (cDNA) according to the
instructions provided with the SPARKscript II All-in-one RT kit. The RT-qPCR reaction
was conducted using Taq SYBr
®
Green qPCR Premix (Universal) Yugong Biotech, Nanjing,
China with a reaction volume of 10
µ
L. Primers were designed using primer3plus (https:
//www.primer3plus.com/index.html, accessed on 1 November 2024). The qPCR reaction
Agronomy 2025,15, 306 5 of 19
conditions were conducted as per the manufacturer’s instructions. Information on primers
and the reference gene MrACTION [42] can be found in Supplementary Table S1.
3. Results
3.1. Identification of the MrGRAS Gene Family Members and Analysis of the Physicochemical Properties
In the M. ruthenica reference genome, overall, 62 MrGRAS genes were identified,
which were designated as MrGRAS01 to MrGRAS62. The detailed information on the
identified MrGRAS protein sequences is listed in Table S2. The physicochemical properties
of the MrGRAS proteins are listed in Table S3. The MrGRAS proteins range in length from
93 (MrGRAS19) to 817 (MrGRAS48) amino acids, with molecular weights ranging from
65,919.79 (MrGRAS01) to 90,193.44 (MrGRAS48) Da, and isoelectric points (pI) ranging
from 4.72 (MrGRAS52) to 9.33 (MrGRAS11). The instability index of all the MrGRAS
proteins falls between 27 and 61, with average grand average of hydropathy (GRAVY)
values below 0, indicating their instability, solubility, and hydrophilicity. Furthermore,
based on subcellular localization predictions, we found that, except for genes MrGRAS16,
MrGRAS 18 and MrGRAS19, which were predicted to be localized in the mitochondria, the
remaining MrGRAS genes were predicted to be localized in the nucleus (Table S3).
3.2. Evolutionary, Gene Structure and Conserved Motif Analysis of MrGRAS Gene Family
A Neighbor-Joining (NJ) method based on a phylogenetic tree (Figures 1and 2A)
classified all the GRAS proteins into 13 subgroups, including SHR, HAN, GRASM6,
GRASM7, SCL, PAT1, DELLA, SCR, GRASM5, GRAS8, LAS, and SCL26. The SCL sub-
group contained the highest number of MrGRAS proteins, while GRASM7, GRASM5,
and GRAS8 were newly identified families. The Gene Structure Display Server (GSDS)
(http://gsds.cbi.pku.edu.cn, accessed on 1 November 2024) was used to investigate the
gene structure features of MrGRAS genes. Most of the genes are primarily composed of
exons (Figure 2B). Conserved motifs within the MrGRAS proteins and their distribution,
discovered using the MEME tool, are listed in Table S4. GRAS proteins that gather within
the same subfamily displayed comparable motif numbers and types, indicating potential
functional similarities (Figure 2C).
3.3. Prediction of the Three-Dimensional Structure and Secondary Structure Analysis of MrGRAS Protein
Understanding the three-dimensional structure of proteins is vital for unraveling their
functions, and operational mechanisms in biological research. Protein three-dimensional
structures generated using the Swiss Model were of good quality based on the GMQE
score, which exceeded 0.7 (Figure 3). Upon delving into the prediction of secondary
structures for all the MrGRAS proteins (refer to Table S3), it was revealed that random
coil proteins comprised the largest proportion (ranging from 30.44% to 63.07%), trailed
by
α
-helix structures (27.97–60.11%) and extended strand proteins (0.70–33.05%). The
absence of
β
-turn protein structures was observed, aligning closely with the outcomes of
the three-dimensional structure predictions. Additionally, we observed that the protein
structures on the MrGRAS03, MrGRAS17, and MrGRAS37 branches exhibited similarities,
suggesting that these proteins may have potential functional similarities.
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Figure 1. The unrooted phylogenetic tree of GRAS proteins from M. ruthenica and Arabidopsis was
constructed using the NJ method in MEGA 11. The tree categorizes the GRAS proteins into 13 dis-
tinct groups, each represented by different clade colors.
Figure 2. Gene architecture, conserved motifs, and phylogenetic linkages: (A) MrGRAS gene phy-
logenetic relationships. The NJ method was used to generate the phylogenetic tree; (B) MrGRAS
gene structures. Exon and intron are shown by the green boxes and black lines, respectively; (C)
MrGRAS protein motif paerns. Colored boxes stand for various motifs.
Figure 1. The unrooted phylogenetic tree of GRAS proteins from M. ruthenica and Arabidopsis was
constructed using the NJ method in MEGA 11. The tree categorizes the GRAS proteins into 13 distinct
groups, each represented by different clade colors.
Agronomy 2025, 15, x FOR PEER REVIEW 6 of 19
Figure 1. The unrooted phylogenetic tree of GRAS proteins from M. ruthenica and Arabidopsis was
constructed using the NJ method in MEGA 11. The tree categorizes the GRAS proteins into 13 dis-
tinct groups, each represented by different clade colors.
Figure 2. Gene architecture, conserved motifs, and phylogenetic linkages: (A) MrGRAS gene phy-
logenetic relationships. The NJ method was used to generate the phylogenetic tree; (B) MrGRAS
gene structures. Exon and intron are shown by the green boxes and black lines, respectively; (C)
MrGRAS protein motif paerns. Colored boxes stand for various motifs.
Figure 2. Gene architecture, conserved motifs, and phylogenetic linkages: (A)MrGRAS gene phylo-
genetic relationships. The NJ method was used to generate the phylogenetic tree; (B)MrGRAS gene
structures. Exon and intron are shown by the green boxes and black lines, respectively; (C) MrGRAS
protein motif patterns. Colored boxes stand for various motifs.
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3.3. Prediction of the Three-Dimensional Structure and Secondary Structure Analysis of
MrGRAS Protein
Understanding the three-dimensional structure of proteins is vital for unraveling
their functions, and operational mechanisms in biological research. Protein three-dimen-
sional structures generated using the Swiss Model were of good quality based on the
GMQE score, which exceeded 0.7 (Figure 3). Upon delving into the prediction of second-
ary structures for all the MrGRAS proteins (refer to Table S3), it was revealed that random
coil proteins comprised the largest proportion (ranging from 30.44% to 63.07%), trailed by
α-helix structures (27.97%–60.11%) and extended strand proteins (0.70%–33.05%). The ab-
sence of β-turn protein structures was observed, aligning closely with the outcomes of the
three-dimensional structure predictions. Additionally, we observed that the protein struc-
tures on the MrGRAS03, MrGRAS17, and MrGRAS37 branches exhibited similarities, sug-
gesting that these proteins may have potential functional similarities.
Figure 3. The three-dimensional structure of the MrGRAS protein was predicted using homology
modeling, and the model quality was evaluated using Global Model Quality Estimation (GMQE).
The GMQE value ranges from 0 to 1, with values closer to 1 indicating a higher quality of the pre-
dicted model.
Figure 3. The three-dimensional structure of the MrGRAS protein was predicted using homology
modeling, and the model quality was evaluated using Global Model Quality Estimation (GMQE). The
GMQE value ranges from 0 to 1, with values closer to 1 indicating a higher quality of the predicted model.
3.4. Promoter Cis-Regulatory Elements Analysis
To investigate whether the MrGRAS genes participate in plant growth and devel-
opment, hormone, and stress responses, we performed an analysis of the cis-regulatory
elements within the 2000 bp upstream regions of the MrGRAS genes using PlantCARE
(Figure 4). Several cis-regulatory elements were identified through these sequences, which
were classified into three main categories based on their functional annotations: plant
growth and development, phytohormone responsive, and abiotic/biotic stress response.
Notably, regulatory elements, such as MBS, ABRE, and LRE, are involved in drought
induction, stress responses and cold tolerance. Analysis revealed that 28 MrGRAS genes
contain MBS elements, indicating their potential for drought response. Furthermore, the
majority of MrGRAS genes contain multiple G-box, and Box-4, suggesting their significance
in the regulation of gene transcription.
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3.4. Promoter Cis-Regulatory Elements Analysis
To investigate whether the MrGRAS genes participate in plant growth and develop-
ment, hormone, and stress responses, we performed an analysis of the cis-regulatory ele-
ments within the 2000 bp upstream regions of the MrGRAS genes using PlantCARE (Fig-
ure 4). Several cis-regulatory elements were identified through these sequences, which
were classified into three main categories based on their functional annotations: plant
growth and development, phytohormone responsive, and abiotic/biotic stress response.
Notably, regulatory elements, such as MBS, ABRE, and LRE, are involved in drought in-
duction, stress responses and cold tolerance. Analysis revealed that 28 MrGRAS genes
contain MBS elements, indicating their potential for drought response. Furthermore, the
majority of MrGRAS genes contain multiple G-box, and Box-4, suggesting their signifi-
cance in the regulation of gene transcription.
Figure 4. Prediction of cis-acting elements in MrGRAS gene promoters: (A) the number of cis-regu-
latory elements in the 2000-bp upstream promoter region; (B) the number of plant hormone, plant
growth, and stress response elements for each MrGRAS.
3.5. Chromosomal Distribution, Gene Duplication and Collinearity Analyses of MrGRAS Genes
An analysis of gene distribution on the chromosomes revealed that 59 MrGRAS genes
are distributed irregularly on the eight chromosomes of M. ruthenica (Figure 5), with 12,
9, 10 and 3 MrGRAS genes located on chromosomes Chr2, Chr4, Chr3, and Chr1, respec-
tively. Additionally, seven MrGRAS genes are situated on chromosomes Chr5 and Chr7,
while only one MrGRAS gene is found on chromosome Chr6. Tandem genes were identi-
fied on chromosomes Chr2, Chr3, Chr4, and Chr8.
Figure 4. Prediction of cis-acting elements in MrGRAS gene promoters: (A) the number of cis-
regulatory elements in the 2000-bp upstream promoter region; (B) the number of plant hormone,
plant growth, and stress response elements for each MrGRAS.
3.5. Chromosomal Distribution, Gene Duplication and Collinearity Analyses of MrGRAS Genes
An analysis of gene distribution on the chromosomes revealed that 59 MrGRAS genes
are distributed irregularly on the eight chromosomes of M. ruthenica (Figure 5), with 12, 9,
10 and 3 MrGRAS genes located on chromosomes Chr2, Chr4, Chr3, and Chr1, respectively.
Additionally, seven MrGRAS genes are situated on chromosomes Chr5 and Chr7, while
only one MrGRAS gene is found on chromosome Chr6. Tandem genes were identified on
chromosomes Chr2, Chr3, Chr4, and Chr8.
To identify gene duplication events, we performed collinearity analysis among these
59 MrGRAS genes. In our study, 10 pairs of segmental duplications in MrGRAS genes
(MrGRAS1/MrGRAS24,MrGRAS10/MrGRAS26,MrGRAS10/MrGRAS46,MrGRAS4/MrGRAS59,
MrGRAS10/MrGRAS62,MrGRAS20/MrGRAS40,MrGRAS25/MrGRAS44,MrGRAS26/MrGRAS46,
MrGRAS36/MrGRAS56, and MrGRAS37/MrGRAS53) were identified. The results show that
the MrGRAS gene family expansion in the M. ruthenica genome is primarily driven by seg-
mental duplication events. To explore the potential evolutionary mechanisms underlying
the MrGRAS gene family, we analyzed the collinearity relationships within the M. ruthenica
species (Figure 6) and between M. ruthenica and other plants, including Arabidopsis,G. max,
and M. sativa (Figure 7). The inter-species collinearity analysis reveals that the number
of homologous events between MrGRAS and GmGRAS is significantly higher than those
between MrGRAS and AtGRAS,MrGRAS and MsGRAS. This suggests a closer evolutionary
relationship between M. ruthenica and G. max compared to M. ruthenica and the other three
plant species (Arabidopsis and M. sativa).
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Figure 5. The positions and distribution of the 59 members of the MrGRAS gene family across the
eight chromosomes of M. ruthenica are shown. The chromosomes are depicted by the green bars,
with the left scale indicating the chromosome lengths. Black lines mark the locations of each
MrGRAS gene on the chromosomes.
To identify gene duplication events, we performed collinearity analysis among these
59 MrGRAS genes. In our study, 10 pairs of segmental duplications in MrGRAS genes
(MrGRAS1/MrGRAS24, MrGRAS10/MrGRAS26, MrGRAS10/MrGRAS46,
MrGRAS4/MrGRAS59, MrGRAS10/MrGRAS62, MrGRAS20/MrGRAS40,
MrGRAS25/MrGRAS44, MrGRAS26/MrGRAS46, MrGRAS36/MrGRAS56, and
MrGRAS37/MrGRAS53) were identified. The results show that the MrGRAS gene family
expansion in the M. ruthenica genome is primarily driven by segmental duplication events.
To explore the potential evolutionary mechanisms underlying the MrGRAS gene family,
we analyzed the collinearity relationships within the M. ruthenica species (Figure 6) and
between M. ruthenica and other plants, including Arabidopsis, G. max, and M. sativa (Figure
7). The inter-species collinearity analysis reveals that the number of homologous events
between MrGRAS and GmGRAS is significantly higher than those between MrGRAS and
AtGRAS, MrGRAS and MsGRAS. This suggests a closer evolutionary relationship be-
tween M. ruthenica and G. max compared to M. ruthenica and the other three plant species
(Arabidopsis and M. sativa).
Figure 5. The positions and distribution of the 59 members of the MrGRAS gene family across the
eight chromosomes of M. ruthenica are shown. The chromosomes are depicted by the green bars, with
the left scale indicating the chromosome lengths. Black lines mark the locations of each MrGRAS
gene on the chromosomes.
Agronomy 2025, 15, x FOR PEER REVIEW 10 of 19
Figure 6. The syntenic relationships of genes within the M. ruthenica. The grey lines in the back-
ground indicate all gene duplication events across the M. ruthenica genome, while the turquoise
lines highlight segmental duplication events specific to GRAS genes. The outer circles, distinguished
by different colors, illustrate the gene density distribution across the genome.
Figure 7. Synteny analysis of GRAS genes between M. truncatula and three plant species, M. sativa,
G. max and M. sativa. The gray lines in the background indicate all synteny blocks within the M.
truncatula genome and the other genomes, and red lines indicate the duplicated GRAS gene pairs.
Figure 6. The syntenic relationships of genes within the M. ruthenica. The grey lines in the background
indicate all gene duplication events across the M. ruthenica genome, while the turquoise lines highlight
segmental duplication events specific to GRAS genes. The outer circles, distinguished by different
colors, illustrate the gene density distribution across the genome.
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Figure 6. The syntenic relationships of genes within the M. ruthenica. The grey lines in the back-
ground indicate all gene duplication events across the M. ruthenica genome, while the turquoise
lines highlight segmental duplication events specific to GRAS genes. The outer circles, distinguished
by different colors, illustrate the gene density distribution across the genome.
Figure 7. Synteny analysis of GRAS genes between M. truncatula and three plant species, M. sativa,
G. max and M. sativa. The gray lines in the background indicate all synteny blocks within the M.
truncatula genome and the other genomes, and red lines indicate the duplicated GRAS gene pairs.
Figure 7. Synteny analysis of GRAS genes between M. truncatula and three plant species, M. sativa,
G. max and M. sativa. The gray lines in the background indicate all synteny blocks within the
M. truncatula genome and the other genomes, and red lines indicate the duplicated GRAS gene pairs.
3.6. Expression Analysis of MrGRAS Genes Under Different Stress Conditions
The GRAS gene family members possess the cis-elements associated with abiotic
stresses. To understand the expression patterns of the MrGRAS gene family under different
abiotic stress treatments, RNA-seq data [
41
] from six different treatments, including ABA
phytohormone treatment, cold, freezing, osmotic, salt, and drought stress. The FPKM
method was used to compare the expression levels of each gene. Among the 62 GRAS genes
in M. ruthenica, the transcript levels of 59 genes could be determined in each tissue sample
whereas expression of the other three genes (MrGRAS60,MrGRAS61,MrGRAS62) was
not detected in the RNA-seq data, possibly due to lack of expression or temporal-spatial
patterns. It was observed that under low temperature, ABA, and cold stress treatments, the
expression level of most genes decreased, while under salt and osmotic stress treatments, the
expression pattern of most genes increased. Except for MrGRAS17,MrGRAS38,MrGRAS39,
and MrGRAS43, the remaining MrGRAS genes were induced to varying extent under
these five abiotic stresses analyzed (Figure 8A). The correlation analysis of gene expression
patterns under five different stress conditions indicating approximately 35% of MrGRAS
genes exhibited a positive correlation in their expression patterns, while 8% showed a
negative correlation, most of MrGRAS genes show no correlation (Figure 8B).
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3.6. Expression Analysis of MrGRAS Genes Under Different Stress Conditions
The GRAS gene family members possess the cis-elements associated with abiotic
stresses. To understand the expression paerns of the MrGRAS gene family under differ-
ent abiotic stress treatments, RNA-seq data [41] from six different treatments, including
ABA phytohormone treatment, cold, freezing, osmotic, salt, and drought stress. The
FPKM method was used to compare the expression levels of each gene. Among the 62
GRAS genes in M. ruthenica, the transcript levels of 59 genes could be determined in each
tissue sample whereas expression of the other three genes (MrGRAS60, MrGRAS61,
MrGRAS62) was not detected in the RNA-seq data, possibly due to lack of expression or
temporal-spatial paerns. It was observed that under low temperature, ABA, and cold
stress treatments, the expression level of most genes decreased, while under salt and os-
motic stress treatments, the expression paern of most genes increased. Except for
MrGRAS17, MrGRAS38, MrGRAS39, and MrGRAS43, the remaining MrGRAS genes were
induced to varying extent under these five abiotic stresses analyzed (Figure 8A). The cor-
relation analysis of gene expression paerns under five different stress conditions indicat-
ing approximately 35% of MrGRAS genes exhibited a positive correlation in their expres-
sion paerns, while 8% showed a negative correlation, most of MrGRAS genes show no
correlation (Figure 8B).
Figure 8. Expression analysis of M. ruthenica GRAS genes in six different treatments, including ABA
phytohormone treatment, cold, freezing, osmotic, and salt stress: (A) heatmap illustrating the dif-
ferential expression of MrGRAS genes under these five abiotic stresses. The values are depicted after
Figure 8. Expression analysis of M. ruthenica GRAS genes in six different treatments, including
ABA phytohormone treatment, cold, freezing, osmotic, and salt stress: (A) heatmap illustrating the
differential expression of MrGRAS genes under these five abiotic stresses. The values are depicted
after logarithmic conversions. Shades of red and blue indicate high and low expressions of MrGRAS
genes, respectively; (B) Correlation analysis of the average gene expression levels under five different
stress conditions. The correlations are visualized with red and blue colors, representing positive and
negative correlations.
3.7. Expression Analysis of GRAS Genes Under Increasing Drought Stress
The expression patterns of MrGRAS genes were also investigated in depth, under
mannitol treatment. The expression patterns of the 62 MrGRAS genes varied under drought
stress and can be broadly categorized into two types; half of the genes showed a decreasing
trend in expression levels with increased duration of stress, implying their roles as potential
negative regulators of drought stress response. In particular, MrGRAS05,MrGRAS22,
MrGRAS30,MrGRAS33, and MrGRAS36 exhibited the most significant down-regulation.
In contrast, 10 MrGRAS genes exhibited a significant up-regulation under drought stress,
implying their roles as positive regulators. The most prominent up-regulation was ob-
served in MrGRAS08,MrGRAS29,MrGRAS38, and MrGRAS46 (Figure 9A). The correlation
analysis of gene expression patterns under four different drought conditions indicated that
approximately 76.9% of MrGRAS genes exhibited a positive correlation in their expression
patterns, while 19.5% showed a negative correlation (Figure 9B).
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logarithmic conversions. Shades of red and blue indicate high and low expressions of MrGRAS
genes, respectively; (B) Correlation analysis of the average gene expression levels under five differ-
ent stress conditions. The correlations are visualized with red and blue colors, representing positive
and negative correlations.
3.7. Expression Analysis of GRAS Genes Under Increasing Drought Stress
The expression paerns of MrGRAS genes were also investigated in depth, under
mannitol treatment. The expression paerns of the 62 MrGRAS genes varied under
drought stress and can be broadly categorized into two types; half of the genes showed a
decreasing trend in expression levels with increased duration of stress, implying their
roles as potential negative regulators of drought stress response. In particular, MrGRAS05,
MrGRAS22, MrGRAS30, MrGRAS33, and MrGRAS36 exhibited the most significant
down-regulation. In contrast, 10 MrGRAS genes exhibited a significant up-regulation un-
der drought stress, implying their roles as positive regulators. The most prominent up-
regulation was observed in MrGRAS08, MrGRAS29, MrGRAS38, and MrGRAS46 (Figure
9A). The correlation analysis of gene expression paerns under four different drought
conditions indicated that approximately 76.9% of MrGRAS genes exhibited a positive cor-
relation in their expression paerns, while 19.5% showed a negative correlation (Figure
9B).
Figure 9. Expression analysis of M. ruthenica GRAS genes under under 0, 5, 7, 9 d continuous
mannitol treatment: (A) heatmap illustrating the differential expression of MrGRAS genes under
these different mannitol treatments. The values are depicted after logarithmic conversions. Shades of
red and blue indicate high and low expressions of MrGRAS genes, respectively; (B) the correlation
heatmaps illustrate the expression patterns of the genes under four different drought stresses, positive
correlations are represented in red, while negative correlations are shown in blue.
3.8. RT-qPCR Validation
Nine selected genes (MrGRAS05,MrGRAS06, MrGRAS09, MrGRAS11, MrGRAS22,
MrGRAS24, MrGRAS29, MrGRAS40, and MrGRAS53) were further subjected to RT-qPCR
assay to understand their expression level of under different drought stress. Under short-
term treatment (1 day) with different concentrations of mannitol, the expression levels of
MrGRAS06 and MrGRAS09 decreased compared to the control group. The expression levels
of MrGRAS11,MrGRAS22,MrGRAS24 and MrGRAS40 showed an initial increase followed
by a subsequent decrease, while MrGRAS29 and MrGRAS53 exhibited an upward trend in
expression levels in comparison to the control (Figure 10). Under treatment with 400 mM
mannitol for different durations, only the expression levels of MrGRAS06, MrGRAS05,
MrGRAS22, and MrGRAS53 decreased. The expression levels of the other genes showed
an up-regulation trend, with MrGRAS11,MrGRAS24, and MrGRAS29 exhibiting the most
significant changes in expression levels (Figure 11).
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Figure 9. Expression analysis of M. ruthenica GRAS genes under under 0, 5, 7, 9 d continuous man-
nitol treatment: (A) heatmap illustrating the differential expression of MrGRAS genes under these
different mannitol treatments. The values are depicted after logarithmic conversions. Shades of red
and blue indicate high and low expressions of MrGRAS genes, respectively; (B) the correlation
heatmaps illustrate the expression paerns of the genes under four different drought stresses, pos-
itive correlations are represented in red, while negative correlations are shown in blue.
3.8. RT-qPCR validation
Nine selected genes (MrGRAS05, MrGRAS06, MrGRAS09, MrGRAS11, MrGRAS22,
MrGRAS24, MrGRAS29, MrGRAS40, and MrGRAS53) were further subjected to RT-qPCR
assay to understand their expression level of under different drought stress. Under short-
term treatment (1 day) with different concentrations of mannitol, the expression levels of
MrGRAS06 and MrGRAS09 decreased compared to the control group. The expression lev-
els of MrGRAS11, MrGRAS22, MrGRAS24 and MrGRAS40 showed an initial increase fol-
lowed by a subsequent decrease, while MrGRAS29 and MrGRAS53 exhibited an upward
trend in expression levels in comparison to the control (Figure 10). Under treatment with
400 mM mannitol for different durations, only the expression levels of MrGRAS06,
MrGRAS05, MrGRAS22, and MrGRAS53 decreased. The expression levels of the other
genes showed an up-regulation trend, with MrGRAS11, MrGRAS24, and MrGRAS29 ex-
hibiting the most significant changes in expression levels (Figure 11).
Figure 10. Expression analysis of f MrGRAS gene under 0 (CK), 50 mM, 100 mM, 200 mM, 300 mM
and 400 mM mannitol treatment for 1 d, respectively. Note: * represents the significant difference in
the relative expression levels at different times of drought stress compared with CK (p< 0.05).
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Figure 10. Expression analysis of f MrGRAS gene under 0 (CK), 50 mM, 100 mM, 200 mM, 300 mM
and 400 mM mannitol treatment for 1 d, respectively. Note: * represents the significant difference in
the relative expression levels at different times of drought stress compared with CK (p < 0.05).
Figure 11. Expression analysis of MrGRAS gene under 400 mM mannitol treatment for 0 (CK), 1, 3,
6, 12, and 24 h. Note: * represents the significant difference in the relative expression levels at differ-
ent times of drought stress compared with CK (p < 0.05).
4. Discussion
GRAS transcription factors are now widely found in plants and can not only phyto-
hormone signal transduction during plant growth and development but also play im-
portant roles in biotic and abiotic stresses [43]. In this study, we identified 62 MrGRAS
genes from the M. ruthenica genome and analyzed their characteristics. Despite similar
instability, MrGRAS proteins exhibit differences in protein length, molecular weight, and
theoretical isoelectric point. Subcellular localization studies showed that most MrGRAS
proteins are located in the nucleus, as seen in other species [3]. The 62 M. ruthenica GRAS
genes and Arabidopsis GRAS genes were divided into 13 subfamilies. As genes within the
same evolutionary clade are likely to have similar functions, we can infer the potential
functions of MrGRAS genes based on their homology with other species [44]. For instance,
overexpression of the PtSCL7 gene from poplar in Arabidopsis improved its resistance to
salt and drought stress [45]. The OsGRAS23 gene, a homolog of the SCL14 subfamily, is
involved in regulating the drought stress response in O. sativa. This suggests that the 13
M. ruthenica genes identified in the SCL subfamily may also play a role in drought re-
sistance [46]. The intron–exon structure analysis revealed that approximately 88.7% of the
Figure 11. Expression analysis of MrGRAS gene under 400 mM mannitol treatment for 0 (CK), 1, 3, 6,
12, and 24 h. Note: * represents the significant difference in the relative expression levels at different
times of drought stress compared with CK (p< 0.05).
4. Discussion
GRAS transcription factors are now widely found in plants and can not only phytohor-
mone signal transduction during plant growth and development but also play important
roles in biotic and abiotic stresses [
43
]. In this study, we identified 62 MrGRAS genes from
the M. ruthenica genome and analyzed their characteristics. Despite similar instability,
MrGRAS proteins exhibit differences in protein length, molecular weight, and theoretical
isoelectric point. Subcellular localization studies showed that most MrGRAS proteins
are located in the nucleus, as seen in other species [
3
]. The 62 M. ruthenica GRAS genes
and Arabidopsis GRAS genes were divided into 13 subfamilies. As genes within the same
evolutionary clade are likely to have similar functions, we can infer the potential functions
of MrGRAS genes based on their homology with other species [
44
]. For instance, overex-
pression of the PtSCL7 gene from poplar in Arabidopsis improved its resistance to salt and
drought stress [
45
]. The OsGRAS23 gene, a homolog of the SCL14 subfamily, is involved in
regulating the drought stress response in O. sativa. This suggests that the 13 M. ruthenica
genes identified in the SCL subfamily may also play a role in drought resistance [
46
]. The
intron–exon structure analysis revealed that approximately 88.7% of the MrGRAS genes
(55 out 62) are primarily composed of exons, the diversity in intron deletions in these species
showed that the GRAS gene is species-specific and has a high proportion of intron-free
genes, indicating a close evolutionary relationship between GRAS proteins [47].
Agronomy 2025,15, 306 15 of 19
Gene replication plays a very important role in the evolutionary expansion of all gene
families in plants [
48
]. In our study, except for chromosomes Chr1 and 6, the members of the
M. ruthenica gene family cluster together on the remaining chromosomes, indicating gene
duplication events within the MrGRAS genes. Similar situations have been observed in
O. sativa and Arabidopsis [
14
], suggesting that segmental repeats are the main mechanism of
gene amplification for the MrGRAS genes during their evolution and expansion. Moreover,
the identification of homologous genes across species helps in elucidating gene and plant
evolution through phylogenetic analysis [
49
]. We conducted a comparative analysis of
orthologous genes among M. ruthenica,Arabidopsis, and G. max. Structural analysis data
revealed that M. ruthenica and G. max share the highest number of orthologous genes,
indicating a close evolutionary relationship. Similar characteristics were also reported in
Brassica rapa [25].
By identifying the cis-regulatory elements in genes and combining them with existing
transcription factor and expression profile data, the regulatory roles of genes in response to
abiotic stresses can be inferred [
50
]. Many regulatory elements, such as ABRE, DRE, TC-
rich repeat, and LRE play a role in the plant’s response to abiotic stresses such as drought,
low temperature, and salinity [
19
]. These elements were identified in the GRAS family in
Arabidopsis [
51
], Cicer arietinum [
52
], and M. sativa [
3
]. The ABRE cis-regulatory elements,
associated with ABA response, are typically found in genes that react to drought or salt
stress [
53
]. On the other hand, cis-regulatory elements such as DER, LRE, and TC-rich
repeats are located in the promoter regions of genes and serve as key regulatory factors in
plant responses to drought, low temperature, and other abiotic stresses [
19
]. The existence
of these cis-regulatory elements in MrGRAS genes suggests that they may be crucial in the
plant’s stress tolerance mechanisms [
54
]. The GRAS genes in the PAT1 family contain the
highest number of these cis-regulatory elements, which indirectly suggests their potential
for stress tolerance. For example, in cotton, two genes, Gh_D01G0564 and Gh_A04G0196,
were identified from the PAT1 subfamily, which was up-regulated under abiotic stress
conditions, including cold, salt, drought, and heat [
55
]. In Avena sativa, members of the
PAT1 subfamily, such as AsGRAS16, can regulate the plant’s response to low (8
◦
C) and
freezing (4 ◦C) temperatures, while AsGRAS14 is induced under salt and alkali stress [56].
This suggests that the PAT1 subfamily proteins in the GRAS gene family play essential
roles and potentially exert key functions in abiotic stress through complex regulatory
networks [
51
]. Analyzing the transcriptional patterns of the MrGRAS gene family under
different stress conditions revealed that several genes belonging to the PAT subfamily in
M. ruthenica, such as MrGRAS01,MrGRAS04,MrGRAS20,MrGRAS24,MrGRAS40,
MrGRAS41,MrGRAS42,MrGRAS50, and MrGRAS59, showed altered expression pat-
terns under cold, ABA, freezing, osmotic a, salt stress, and mannitol treatments, suggesting
their ability to respond to abiotic stresses.
Numerous studies indicate that GRAS genes play a crucial role in conferring drought
resistance in plants [
52
]. Such expression analysis of C. arietinum GRAS genes revealed that
members of the PAT1, SCR, SCL3, and SHR GRAS subfamilies have the potential to respond
to drought. CaGRAS12 (SCR) is considered a drought-responsive GRAS transcription factor
gene and a candidate gene for developing drought-tolerant C. arietinum varieties [
56
]. GRAS
genes identified in white-flowered wax mallow showed an up-regulation trend under ABA,
drought, and salt stress, indicating their significant role in responding to abiotic stress.
Furthermore, MaGRAS12,MaGRAS34, and MaGRAS33 were also found to enhance yeast
cell drought or salt tolerance [
57
]. In a study involving GRAS genes identified from roses,
most genes were significantly down-regulated after exogenous GA application, the SCR,
RAM1, and PAT1 subfamilies exhibited significant down-regulation under drought stress
conditions, suggesting their important roles in GA and drought stress signal regulation [
58
].
Agronomy 2025,15, 306 16 of 19
In Arabidopsis, overexpressing the SCL14 gene from the GRAS family resulted in enhanced
drought tolerance under stress, demonstrating the potential application of GRAS genes in
drought resistance [
59
]. Sami et al. utilized CRISPR/Cas9 technology to target multiple
GRAS genes in Arabidopsis and analyzed their responses to drought stress. The results
showed that the knockout of specific GRAS genes significantly improved drought tolerance,
highlighting the potential of gene editing to regulate GRAS genes and enhance crop water
retention ability [60]. Currently, precise regulation of the GRAS gene family through gene
editing technologies has not been extensively studied. Moving forward, research should
focus on this direction to enhance crop stress tolerance, accelerate plant growth, increase
yields, or improve other agricultural traits. In this study, a total of 62 MrGRAS genes were
identified, of which most genes showed significant expression differences under drought
stress, suggesting their crucial roles in drought stress responses and these genes can serve
as candidates for future research. Additionally, we validated using RT-qPCR experiments
the significant induction of nine genes by drought stress (identified through RNA-Seq
analysis). While some expression patterns were consistent with those observed in the
RNA-Seq analysis, the fold changes in gene expression levels differed. This variation could
be due to the biological diversity observed among different genotypes of M. ruthenica [
61
].
5. Conclusions
In this study, a total of 62 members of the M. ruthenica GRAS gene family were iden-
tified, which were analyzed for physicochemical properties, evolutionary relationships,
gene structures, protein motif compositions, three-dimensional protein structures, gene
duplication events, chromosomal distributions, cis-regulatory elements, and expression
patterns under abiotic stress conditions. RT-qPCR experiments revealed that the relative
expression levels of three genes—MrGRAS11,MrGRAS24 and MrGRAS29—showed signifi-
cant changes under various drought stress treatments. Overall, this study compiles the first
thorough identification and analysis of the GRAS gene family in M. ruthenica, providing a
solid foundation for further investigation into the functions and molecular mechanisms of
GRAS genes in response to drought stress in this species.
Supplementary Materials: The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/agronomy15020306/s1, Supplementary Table S1: qRT-PCR primers;
Supplementary Table S2: The protein sequence of 62 MrGRAS genes; Supplementary Table S3: The
physicochemical properties of 62 MrGRAS genes; Supplementary Table S4: Sequence and logo of motif1-10.
Author Contributions: Conceptualization: L.Y. and Z.L.; methodology: P.L. and Q.Z.; software: X.D.;
validation: X.D. and M.L.; formal analysis: M.L.; investigation: P.L. and Q.Z.; resources: P.L.; data
curation: M.L. and X.D.; writing—original draft preparation: X.W.; writing—review and editing:
X.W.; visualization: Z.W.; supervision: L.Y. and Z.L.; project administration: L.Y.; funding acquisition:
Z.W. All authors have read and agreed to the published version of the manuscript.
Funding: Inner Mongolia Seed Industry Science and Technology Innovation Major Demonstration
Project: 2022JBGS0040; National Center of Pratacultural Technology Innovation (under preparation)
Special fund for innovation platform construction: CCPTZX2023N04; Leading Scientist Project of
Gansu Province: 23ZDKA013; the earmarked fund for CARS (CARS-34).
Data Availability Statement: The data supporting the findings of this study are available from the
corresponding author upon reasonable request.
Conflicts of Interest: The authors declare no conflicts of interest.
Agronomy 2025,15, 306 17 of 19
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