Next Article in Journal
Phylogenomic Analysis of Cytochrome P450 Gene Superfamily and Their Association with Flavonoids Biosynthesis in Peanut (Arachis hypogaea L.)
Next Article in Special Issue
Identification of Genomic Regions Associated with Seedling Frost Tolerance in Sorghum
Previous Article in Journal
Recent Progress on Genetically Modified Animal Models for Membrane Skeletal Proteins: The 4.1 and MPP Families
Previous Article in Special Issue
Mulberry MnGolS2 Mediates Resistance to Botrytis cinerea on Transgenic Plants
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 14
Issue 10
10.3390/genes14101943
genes-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

Comparative Analysis of the GATA Transcription Factors in Five Solanaceae Species and Their Responses to Salt Stress in Wolfberry (Lycium barbarum L.)

by
Fengfeng Zhang
1,
Yan Wu
1,
Xin Shi
1,
Xiaojing Wang
1,* and
Yue Yin
2,*
1
Institute of Quality Standards and Testing Technology for Agricultural Products, Ningxia Academy of Agricultural and Forestry Sciences, Yinchuan 750002, China
2
National Wolfberry Engineering Research Center, Ningxia Academy of Agricultural and Forestry Sciences, Yinchuan 750002, China
*
Authors to whom correspondence should be addressed.
Genes 2023, 14(10), 1943; https://doi.org/10.3390/genes14101943
Submission received: 14 September 2023 / Revised: 9 October 2023 / Accepted: 13 October 2023 / Published: 15 October 2023
(This article belongs to the Special Issue Molecular Mechanisms of Plant Stress Responses)
Browse Figures
Review Reports Versions Notes

Abstract

:
GATA proteins are a class of zinc-finger DNA-binding proteins that participate in diverse regulatory processes in plants, including the development processes and responses to environmental stresses. However, a comprehensive analysis of the GATA gene family has not been performed in a wolfberry (Lycium barbarum L.) or other Solanaceae species. There are 156 GATA genes identified in five Solanaceae species (Lycium barbarum L., Solanum lycopersicum L., Capsicum annuum L., Solanum tuberosum L., and Solanum melongena L.) in this study. Based on their phylogeny, they can be categorized into four subfamilies (I-IV). Noticeably, synteny analysis revealed that dispersed- and whole-genome duplication contributed to the expansion of the GATA gene family. Purifying selection was a major force driving the evolution of GATA genes. Moreover, the predicted cis-elements revealed the potential roles of wolfberry GATA genes in phytohormone, development, and stress responses. Furthermore, the RNA-seq analysis identified 31 LbaGATA genes with different transcript profiling under salt stress. Nine candidate genes were then selected for further verification using quantitative real-time PCR. The results revealed that four candidate LbaGATA genes (LbaGATA8, LbaGATA19, LbaGATA20, and LbaGATA24) are potentially involved in salt-stress responses. In conclusion, this study contributes significantly to our understanding of the evolution and function of GATA genes among the Solanaceae species, including wolfberry.

1. Introduction

There are several adaptive mechanisms that plants have developed to cope with these abiotic stresses, including drought, salinity, and extreme temperatures during their growth and development [1]. To adapt to these extreme environmental stresses, complex and efficient regulatory networks, including changes in gene expression and transcription factors (TFs), are critical regulators of the plant’s adaptation to abiotic stresses [2]. Several families of TFs have been identified and reported in response to abiotic stresses, such as GATA-binding factor (GATA), V-myb avian myeloblastosis viral oncogene homolog (MYB), WRKY, Basic region leucine zipper (bZIP), GRAS (GAI, RGA, and SCR), NAC (NAM, ATAF1/ATAF2, and CUC2), Dehydration-responsive element-binding protein (DREB), and Basic helix–loop–helix (bHLH) [3,4,5,6,7,8,9,10]. However, only a few TFs have been identified and analyzed in Lycium barbarum L. and Lycium ruthenicum M., including R2R3-MYB, BBX, and WRKY [11,12,13]. Thus, the role of other crucial TFs, such as GATA, and the function of these proteins in L. barbarum are unclear.
GATA TFs are DNA-binding proteins widely distributed in eukaryotes, including fungi, metazoans, and plants [14]. They are a type IV zinc finger TF family member, with the conserved motif sequence C-X2C-X17–20-C-X2−C followed by a basic region. The GATA TFs recognize and bind the WGATAR (W = T or A; R = G or A) sequences regulating the transcription levels of their downstream genes [15]. In plants, most GATA proteins contain a single zinc-finger domain, C-X2-C-X18-C-X2-C, with a few proteins containing two zinc-finger domains, C-X2-C-X20-C-X2-C [16]. Based on the phylogenetic analysis, DNA-binding domains, and gene structures of Arabidopsis thaliana, the GATA family was divided into subfamilies I, II, III, and IV.
The GATA TFs have been found to play a critical role in regulating plant growth, development, and response to abiotic stresses in previous studies. For instance, in Arabidopsis thaliana, ectopic overexpression of either AtGNC or AtCGA1 promotes chloroplast biogenesis in the hypocotyl cortex and root pericycle cells [17]. In soybean, the overexpression of the GmGATA58 increases the chlorophyll content in the leaves but suppresses plant growth and yield in transgenic Arabidopsis [17]. In Brachypodium distachyon, the overexpression of the BdGATA13 in Arabidopsis results in darker green leaves, late flowering, and increased drought tolerance compared to the wild type [18]. In tomato, the overexpression of the SlGATA17 improves drought resistance by regulating the activity of the phenylpropanoid biosynthesis pathway [19]. Additionally, under salt stress, rice OsGATA8-overexpressing lines have higher light efficiency and biomass than wild-type and mutant plants [20]. More importantly, OsGATA16 is responsive to cold stress [21]. In sweet potato, the overexpression of the IbGATA24, a member of the subfamily III, significantly increases resistance to drought and salt stresses by interacting with the COP9-5a protein [22]. Additionally, the overexpression of TaGATA1 significantly enhances wheat resistance to Rhizoctonia cerealis, whereas silencing TaGATA1 suppresses the resistance [23]. The GATA transcription factors play an important role in nitrogen metabolism as well. For example, the overexpression of PdGNC, an ortholog of AtGNC in Arabidopsis, increases starch accumulation and promotes plant growth under nitrogen deficiency [24]. In general, GATA genes play an important role in many biological processes.
The GATA gene has been identified in several plant species, including 29 in Arabidopsis [3], 79 in wheat [25], 49 in potato [26], 28 in foxtail millet [27], 28 in buckwheat [28], 26 in cucumber [29], and 32 in Chinese pear [30]. To date, five species from the Solanaceae family have their whole genome sequenced and deposited in the Sol Genomics Network (SGN) database [31] and Spud DB [32]. Recently, the genome sequencing of wolfberry (Lycium barbarum cv. ‘Ningqi 1′) has been completed [33]. These genomic resources are informative for comparative analyses of the GATA gene family among the Solanaceae family.
Therefore, this study aimed to explore the potential regulatory roles of LbaGATA genes in response to salt stress. A genome-wide identification and comparative analysis of the GATA gene family was performed in five species, including wolfberry (Lycium barbarum L.), tomato (Solanum lycopersicum L.), pepper (Capsicum annuum L.), potato (Solanum tuberosum L.), and eggplant (Solanum melongena L.) from the Solanaceae family. In addition, a comprehensive phylogenetic analysis, exon–intron structure, motif composition, gene duplication, and cis-acting element analysis were performed. Moreover, the responses of GATA family members to salt stress in wolfberry were determined by combining transcriptome and qRT-PCR analyses. Based on these analyses, 156 GATA genes were identified. As a result of this study, we will gain a better understanding of the evolutionary relationship among the GATA genes in the family Solanaceae. Moreover, they will be useful to further characterize the functions of GATA genes in wolfberry and other Solanaceae plants.

2. Materials and Methods

2.1. Plant Materials and Salt Stress

Wolfberry (L. barbarum cv Ningqi 1) seeds were sown on moist filter papers on Petri plates for germination. Next, the seedlings were transplanted into a plastic box containing 1/2 Hoagland solution and maintained for four weeks. Subsequently, the seedlings were subjected to salt treatments. Briefly, the seedlings were transferred into a hydroponic culture consisting of a Hoagland solution under a 300 mM NaCl treatment and incubated at 22/18 °C (day/night), 65% relative humidity, and a 16 h photoperiod. Subsequently, the leaves’ tissues were collected at 0 h (samples without treatment, CK), 1 h, 3 h, 6 h, 12 h, and 24 h after salt application, grounded, frozen in liquid nitrogen, and stored at −80 °C awaiting RNA-seq and qRT-PCR analyses. There were at least six seedlings and three biological replicates in each treatment.

2.2. Identification and Characterization of the GATA Genes in Five Solanaceae Family Members

Annotations and genome sequences of Arabidopsis and five members of the Solanaceae family, including L. barbarum, S. lycopersicum, C. annuum, S. tuberosum, and S. melongena, were obtained from online databases. Precisely, the wolfberry genome data (accession number PRJNA640228) were downloaded from the NCBI [33]. The genome sequences of the other four species were downloaded from the SGN (https://solgenomics.net/, accessed on 10 October 2022) and Spud DB (http://spuddb.uga.edu/index.shtml, accessed on 10 October 2022). The A. thaliana genome data were retrieved from the Arabidopsis Information Resource (https://www.arabidopsis.org/, accessed on 10 October 2022).
The GATA genes in the five Solanaceae family members were identified using two methods as previously described [12]. First, the 29 Arabidopsis AtGATA protein sequences were used as queries for the genome data of the five species in the Solanaceae family using the BLASTP Program (E-value < 10−5). Second, the Pfam database (http://pfam.xfam.org/, accessed on 10 October 2022) was used to retrieve the genome data of the five species using the Hidden Markov Model (HMM) of the GATA zinc finger (PF00032). Subsequently, the potential GATA genes in the five species genomes were further screened for the GATA domain against the Pfam (http://pfam.xfam.org/, accessed on 10 October 2022), SMART (http://smart.embl.de/, accessed on 10 October 2022), and batch Conserved Domain Search (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 10 October 2022) databases [34,35,36]. In addition, the ExPASy server (https://web.expasy.org/protparam/, accessed on 10 October 2022) predicted the physical and chemical parameters of the GATA proteins in the five species [37], including molecular weights (MW), isoelectric point (pI), and grand average of hydropathicity (GRAVY). Finally, GATA protein subcellular locations were predicted using WOLF-PSORT (https://wolfpsort.hgc.jp/, accessed on 12 October 2022) [38].

2.3. Phylogenetic Analysis of GATA Proteins in Five Species of Solanaceae Family and Arabidopsis

Multiple sequence alignment of the full-length GATA proteins was performed using Muscle v5 software with default parameters [39]. Next, the Maximum Likelihood (ML) tree was constructed using the IQ-TREE v2 software with the JTT + G substitution model [40]. The bootstrap test was carried out with 1000 iterations, using pairwise deletion of gaps. Finally, we visualized the phylogenetic tree using iTOL v5 (https://itol.embl.de/, accessed on 12 November 2022) [41].

2.4. Gene Features and Conserved Motifs of the GATA Gene Family

The GATA exons and introns were identified using the five Solanaceae genome annotation files. First, the Gene Structure Display Server (http://gsds.gao-lab.org/index.php, on 18 November 2022) [42] was used to visualize the exon–intron. Second, the full-length sequence of GATA proteins was submitted to the MEME suite (https://meme-suite.org/meme/, on 18 November 2022), and the conserved motifs were analyzed with a maximum of 20 different motifs and an optimal width of 6–50 bp [43].

2.5. Analysis of GATA Chromosomal Location, Gene Duplication Events, and Gene Synteny

The information on the chromosomal locations of the GATA genes in L. barbarum, S. lycopersicum, S. melongena, S. tuberosum, and C. annuum was obtained from their genome annotation files. Next, their chromosomal locations were mapped using the TBtools v1.12 [44]. Subsequently, the gene duplication events in genes derived from dispersed duplicates (DSD), proximal duplicates (PD), whole-genome duplicates (WGD), transposed duplicates (TRD), and tandem duplicates (TD) were investigated using the DupGen_finder pipeline, with Arabidopsis as the outgroup. [45]. Finally, the TBtools v1.12 [44] performed syntenic analysis to reveal the syntenic relationships between LbaGATA and GATA proteins from S. lycopersicum, C. annuum, S. tuberosum, S. melongena, and A. thaliana.

2.6. Nonsynonymous (Ka) and Synonymous (Ks) Calculation

Ka, Ks, and Ka/Ks substitution rates were calculated using the Nei–Gojobori (NG) method in TBtools v1.12, using the coding sequences, protein sequences, and syntenic gene pairs [44,46].

2.7. Promoter Sequence Analysis of LbaGATA Genes

Based on the wolfberry genome database, the upstream sequences (2.0 kb) from the initiation codon (ATG) of LbaGATAs were extracted using TBtools v1.12 [44] to examine their cis-regulatory elements. PlantCARE was used to predict the cis-acting elements in the promoter sequences [47].

2.8. RNA-seq Analysis

The ground-above tissues at 0, 1, 3, 6, 12, and 24 after salt stress treatments were collected and applied to RNA-seq analysis. Total RNA was extracted from treatment samples using the Trizol method as described previously [12], and mRNA libraries were sequenced on the Illumina HiSeq4000 platform. The raw data were filtered to obtain clean reads. Subsequently, the cleaned reads were mapped to the wolfberry reference genome using HISAT2 v2.05 [48]. Next, the differentially expressed genes (DEGs) between the mapped sequences and the reference genome were identified using the DESeq2 v1.18 [49] with |log2(fold change)| ≥ 1 and false discovery rate < 0.05 parameters. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched with the DEGs were detected with KOBAS v3.0 [50]. There was a significant enrichment of KEGG pathways with a q_value of 0.05. Subsequently, RNA-seq data were used to extract the transcript profiling data of LbaGATA genes, and the heatmap was generated with the corresponding fragments per kilobase of transcript per million mapped reads (FPKM) using TBtools v1.12 [44].

2.9. Quantitative Real-Time PCR Analysis

The qRT-PCR was used to analyze the expression patterns of the LbaGATA genes. Total RNA was extracted from leaves (the sample same as transcriptome analysis) using Trizol reagent (TIANGEN, Beijing, China) following the manufacturer’s instructions. The first-strand cDNA was synthesized using EasyScript One-Step gDNA Removal and cDNA Synthesis SuperMix (TransGen, Beijing, China) according to the manufacturer’s instructions. Next, qRT-PCR was performed on the Bio-Rad CFX96 TouchTM Real-Time PCR detection system (Bio-Rad, Foster City, California, USA). qRT-PCR was performed in a total volume of 15 μL, including 2 μL of cDNA template, 0.6 μL of 10 μM primer mixture, 7.5 μL Mix (TransGen, Beijing, China), and 4.9 μL RNase-free water. The amplification conditions were as follows: 95 °C for 3 min, 40 cycles of 95 °C for 10 s, and 58 °C for 30 s. Actin was used as the reference gene [51]. As shown in Table S1, Primer Premier 5.0 software was used to design gene-specific primers for each LbaGATA gene. Finally, the relative gene expression was calculated using the 2−∆∆Ct method [52]. An independent sample t-test was used to analyze the statistical significance of the data.

3. Results

3.1. Identification and Characterization of the GATA Genes in the Five Solanaceae Species

A total of 159 candidate GATA genes were retrieved from the genomes of the five species. Among them, three sequences lacking the GATA-type zinc-finger motifs were removed. Finally, a total of 156 GATA genes were found in wolfberry (31), tomato (32), pepper (28), potato (36), and eggplant (29) (Table 1). The length of the encoded GATA proteins was 103–955 aa with an average of 309 amino acids across the five species (Table S2 and Figure 1). The GATA protein molecular weight and pI were between 11.434 and 102.734 kDa with an average of 34.232 kDa and between 4.41 and 10.13 with an average of 7.62, respectively (Table S2). All proteins had negative GRAVY values, implying that they were hydrophilic proteins, only differing in their degree of hydrophilicity. Most GATA genes were found in the nucleus, with a few in the cytoplasm and chloroplast, suggesting that GATAs are nuclear-localized transcription factors.

3.2. Phylogenetic Analysis of GATA Proteins in the Five Species from the Solanaceae Family and Arabidopsis

All the 186 GATA proteins, including 31 in wolfberry, 32 in tomato, 28 in pepper, 36 in potato, 29 in eggplant, and 30 in Arabidopsis, were grouped into four subfamilies (Figure 1). Subfamily I was the largest, comprising 101 GATA proteins, followed by 55, 23, and 7 GATA proteins in subfamily II, III, and IV, respectively. The phylogenetic tree had an obvious topology, with proteins in each subfamily clustered in a single branch. The findings demonstrate evolutionarily conserved GATA genes and stronger homology between them when evaluated synchronously.

3.3. Gene Features and Conserved Motifs of the GATA Gene Family

The intron–exon structure and conserved motifs of GATA proteins in five Solanaceae species were analyzed. The Maximum Likelihood phylogenetic tree was constructed using the full-length GATA proteins (Figure 2a and Figures S1–S4). LbaGATA genes contained 2–19 exons, indicating a wide range of variation (Figure 2b). Among the 31 LbaGATA genes in wolfberry, 14 had two exons. Furthermore, the structure of LbaGATA genes was relatively conserved with the same subfamily but varied across different subfamilies. The number of exons was higher for genes belonging to subfamily III and IV and lower for genes in subfamily I and II, except for LbaGATA28 (19).
The conserved LbaGATA protein motifs highlighting their evolutionary relationship and classification are presented in Figure 2c. Among these LbaGATA proteins, there were 20 motifs with 11–50 amino acids in each motif (Table S3). Additionally, nearly all the LbaGATA proteins in the same subfamily had relatively conserved motif composition and arrangement. However, there was a substantial degree of variation in the different subfamilies.
It was found that all LbaGATA proteins contained conserved motifs 1 and 3, except LbaGATA2, which lacked the conserved Motif 3. Precisely, subfamily I contained Motifs 2, 4, 8, and 9, while Motifs 10, 12, and 19 were found only in subfamily II. However, the LbaGATA protein motif composition and arrangement in subfamily III were highly conserved, with only LbaGATA16 lacking Motifs 11 and 3 and LbaGATA18 lacking motif 11. Additionally, the LbaGATA proteins in subfamily IV generally contained more unique Motifs, including Motifs 5, 11, 15, 16, and 17. LbaGATA8 lacked Motif 8 (special to subfamily I and IV) compared to LbaGATA13 and LbaGATA23, which have identical Motif arrangements.

3.4. Gene Duplication Events, Chromosomal Location, and Synteny Analysis of GATA Genes

Further comprehensive analysis of gene duplication events in five Solanaceae species, was conducted, including various types such as whole-genome duplication (WGD), proximal duplication (PD), tandem duplication (TD), transposed duplication (TRD), and dispersed duplication (DSD). The software DupGen_finder v1.10 [45] was used to identify duplicate GATA family gene pairs within five genomes of Solanaceae. The WGD, TD, TRD, and DSD duplication events were present in all the five species from the Solanaceae family, while PD duplication event was traced only in tomato, pepper, and potato. There were 249 duplicate genes in the five species, with DSDs having the largest number of gene pairs (132), followed by WGDs with 73, and TRDs with 28. In contrast, only 24 TD and 3 PD pairs were identified (Figure 3). These results imply that the expansion of the GATA gene family was mainly associated with DSD and WGD events. The WGD pairs in wolfberry (17), tomato (18), potato (16), and eggplant (14) were greater than those in pepper (7), suggesting that WGDs play important roles in the GATA family expansion in wolfberry, tomato, potato, and eggplant (Table S4).
Additionally, most GATA genes were unevenly distributed at both ends of the chromosomes (Figure 4). For wolfberries, 31 GATA genes were located on 11 of the 12 chromosomes. There were seven genes distributed on Chr6, which contained most genes compared to other chromosomes, while Chr7 and Chr10 contained only one GATA gene (Figure 4a). In tomato, there were two clusters of homologous GATA genes on Chr1 and Chr5 (Figure 4b). In pepper, there were three clusters of homologous GATA genes on Chr2, Chr5, and Chr8, with three to four genes per cluster (Figure 4c). In potato, there were two clusters of GATA genes on Chr1 and Chr5, each with three to twelve genes (Figure 4d). In eggplant, two GATA gene clusters were identified on Chr1 and Chr5, with three to five genes per cluster (Figure 4e).
Further intra-genomic collinearity revealed 17 gene pairs in wolfberry, 18 in tomato, 6 in pepper, 18 in potato, and 14 in eggplant (Figure 5 and Table S5). As a result, 270 orthologous gene pairs were identified among the five species based on collinearity analyses of the GATA genes (Figure 5 and Table S6), including 80, 26, 60, 87, and 17 collinear gene pairs between wolfberry and tomato, pepper, potato, eggplant, and Arabidopsis, respectively. These results imply that wolfberry and the other four species in the Solanaceae species have a good collinearity relationship, which suggests a possible evolutionary mechanism between them.

3.5. GATA Genes Evolved under Strong Purifying Selection

In Figure 6 and Table S7, paralogous GATA gene pairs are shown as non-synonymous (Ka), synonymous (Ks), and Ka/Ks. The Ka/Ks ratios of duplicated gene pairs in wolfberry, tomato, pepper, and eggplant were <1, implying that GATA genes evolved under strong purifying selection. However, in potatoes, one DSD gene pairs Soltu.DM.01G043530.1 and Soltu.DM.01G047500.2 (Ka/Ks~1.06) had higher Ka/Ks ratios, implying that this family has a complicated evolutionary history. In wolfberry, the calculated mean Ka/Ks values for WGD, DSD, TD, and TRD gene pairs were 0.22, 0.23, 0.25, and 0.14, respectively (Figure 6 and Table S7). In comparison with the other duplicated gene pairs, the DSD gene pairs had a higher Ka/Ks ratio, indicating a higher rate of evolution (Figure 6a).

3.6. Analysis of LbaGATA Promoter Element Cis-Acting Elements

The LbaGATA gene expression regulation mechanism in the 2000 bp upstream sequences in the promoter regions of the 31 LbaGATA genes is shown in Figure 7a. In total, 14 cis-regulatory elements were identified and grouped into three basic physiological subgroups, including abiotic/biotic stress responsiveness, phytohormones responsiveness, and plant growth and development (Figure 7b). For plant growth and development, the 31 GATA box promoter sequences contained MYB, which was involved in various developmental processes/stresses. In addition, most of the LbaGATA family contained ARE cis-acting elements for anaerobic induction. The subgroup included TGACG-motif, CGTCA-motif, and ABRE, which regulate MeJA response and drought inducibility in phytohormones responsiveness. The members belonged to Subfamily I with high levels of various cis-acting elements, especially LbaGATA13, with most phytohormones related to elements like ABRE and plant growth related to elements like G-box (light responsiveness). However, only LbaGATA19 had AuxRR-core (auxin responsiveness). Meanwhile, LbaGATA4, LbaGATA18, and LbaGATA28 had the GARE motif related to gibberellin responsiveness.

3.7. Role of LbaGATA Family in Response to Salt Stress

To conduct transcript profiling under salt stress, we harvested leaves’ tissues from wolfberry plants after salt treatment for 0 h (control, CK), 1 h, 3 h, 6 h, 12 h, and 72 h. These tissues were subsequently used for RNA-seq analysis. Transcriptome characteristics of biological replicates from the same treatment (Figure S5) were highly correlated (r2 > 0.8), suggesting the reproducibility of transcriptome data. Therefore, these transcriptome data could be used for further analysis. A total of 1437, 3258, 4582, 4518, and 2903 genes were transcriptionally up-regulated or down-regulated at 1, 3, 6, 12, and 24 h after salt treatment, respectively (Figure 8a and Figure 8b). K-means clustering analysis revealed that all the genes were divided into 12 different clusters, which indicated that there were a lot of gene expression differences in different samples (Figure S6). KEGG analysis revealed that the altered genes, 1 h after salt treatment, were enriched in a plant–pathogen interaction, MAPK signaling pathway–plant, and plant hormone signal transduction (Figure 8c). After 3, 6, and 12 h of salt treatment, the enriched genes were involved in the MAPK signaling pathway, ribosomes, photosynthesis, antenna proteins, porphyrin metabolism, carbon fixation in photosynthetic organisms, and circadian rhythm (Figure 8d–f). After 24 h of salt treatment, the altered genes were mainly enriched in ribosomes (Figure 8g).
In order to conduct transcript profiling under salt stress, we extracted the transcriptomic data for the 31 LbaGATA genes. Consequently, 31 LbaGATA genes showed different transcript profiles under salt stress (Figure 9). These genes were divided into three main groups based on their expression profiles. Group I contained 12 genes (LbaGATA4/8/10/11/12/14//15/17/19/20/21/22/24) (Figure 9 and Table S7), of which 11 were increased with an increase in stress duration, especially LbaGATA8, LbaGATA12, LbaGATA17, LbaGATA19, and LbaGATA24, which increased by 2.34, 3.68, 2.07, 2.64, and 3.1-fold, respectively. In group II, the LbaGATAs were transcriptionally decreased at the early stress stages and increased after, such as LbaGATA2/6/22/30. In group III, after salt treatment, there was no significant change in gene expression (Figure 9 and Table S8).

3.8. qRT-PCR-Based Analyses of Gene Expression

In order to verify the results of RNA-seq, nine LbaGATA genes were selected at random, and their expression levels were determined using qRT-PCR to analyze their expression levels after salt treatment for 0 (CK), 1, 3, 6, 12, and 24 h. All nine LbaGATA genes were up-regulated under salt stress (Figure 10). The expression levels of LbaGATA8, LbaGATA17, LbaGATA19, LbaGATA20, and LbaGATA24 were induced with salt stress at one or more time point/s, which was consistent with the RNA-seq analysis. LbaGATA8 had the highest expression at 6 h, while LbaGATA17, LbaGATA19, LbaGATA20, and LbaGATA24 had the highest expression pattern at 12 h compared to the control (0 h). The results suggest that these LbaGATAs may play an important role in the salt stress response of wolfberries.

4. Discussion

GATA TFs are a member of the zinc-finger proteins, widely identified and functionally characterized in a wide range of plant species [53]. Studies have shown that GATA genes are involved in regulating growth, chlorophyll synthesis, and environmental response. [17,19,54]. However, there is little information about this gene family in wolfberry, and there has not been a systematic study of GATA genes in Solanaceae.
GATA genes exist broadly in plants, with 5335 GATA genes from 165 plant species deposited in the PlantTFDB [55], including 40 GATA genes in kiwifruit, 54 in maize, 92 in soybean, and 6 in sugarcane. However, the sizes of GATA families vary across the different plant species. In this study, the composition of the GATA gene families was also diverse among the five Solanaceae species. Considering the numbers of GATA genes in wolfberry (31), tomato (32), pepper (28), potato (36), and eggplant (29). Generally, the number of GATA genes in potato exceeded the other four Solanaceae species. Additionally, the genome size across the five Solanaceae species varied from 0.785 (tomato) to 3.30 Gb (pepper). This implies that the number of GATA genes in a plant is independent of the genome size. A recent study revealed that wolfberry and other hitherto sequenced Solanaceous plants experienced a whole-genome triplication event [33]. However, GATA genes were identified in four Solanaceae species, except wolfberry. Hence, WGD may not be the major factor driving the expansion of the GATA family in wolfberry and the four other Solanaceae species. Additionally, the GATA genes from all five Solanaceae species were classified into four clades according to their phylogenetic tree, consistent with those of other plant species [56].
Gene duplication contributes to the increase in new functional genetic materials and the development of new species [57]. As a common phenomenon, there are multiple pathways for gene duplication events, and the accumulation of beneficial mutations is preserved through selective evolution [58,59]. Generally, gene duplications are categorized as WGD, PD, TD, DSD, and TRD, which are the primary driving forces behind gene family evolution [45]. Gene duplication patterns contribute differently to gene family expansion. For example, large gene families are commonly affected by DSD and WGD, such as pyrabactin resistance 1-like (PYR/PYL) [60] and BAHD acyltransferase [61]. Similarly, the duplication of the GATA gene has been widely reported [30]. In this study, there were five duplication events identified in five Solanaceae species, including a large number of DSD (50.98%), WGD (33.33%), TRD (11.76%), and TD (3.92%) events in wolfberry, while PD events were not detected. Additionally, the DSD events accounted for 54, 52.78, 53.96, and 53.06% of all the duplication events in tomato, pepper, potato, and eggplant, respectively. Therefore, DSD and WGD are identified as the primary models of GATA gene family expansion in the five Solanaceae species, similar to the GATA family in Arabidopsis [45]. However, the occurrence time of WGD and DSD events in homologous GATA pairs across the five Solanaceae species differed, implying that the evolutionary histories of GATAs are specific. Further, the Ka/Ks ratios of paralogous GATA gene pairs in wolfberry are generally less than 1, which indicates that they have undergone purifying selection. One pair of GATA paralogous genes in potato had undergone positive selection, suggesting that novel functions may have evolved.
Salt stress affects plant growth, resulting in a significant reduction in crop productivity [62]. Increasing evidence has revealed that GATA genes are involved in plant response to salt stress [22]. For example, the analysis of the cis-elements in the promoter regions of CaGATA genes revealed their potential regulation during salinity, heat, cold, and drought stresses in pepper [63]. Herein, several stress-related cis-elements were found in wolfberry, including those for ARE (cis-acting regulatory element essential for anaerobic induction), LTR (low-temperature responsiveness), MBS (MYB binding Site), and AuXRR-core (auxin responsiveness), suggesting that GATA genes potentially regulate drought and salt stress responses in wolfberry. In addition, the RNA-seq data revealed that 12 LbaGATA genes were transcriptionally altered with more than two-fold changes via salt stress, consistent with previous studies that identified four GATA genes in Fagopyrum tataricum and three GATA genes in Brassica napus [28,64]. Another four GATA genes, SiGATA16, SiGATA18, SiGATA22, and SiGATA25, were induced by NaCl in Setaria italica [27]. The altered expression patterns of LbaGATA genes suggest they have functional roles in response to salt stress. Further verification of whether LbaGATAs are involved in response to salt stress revealed that LbaGATA14, LbaGATA15, and LbaGATA24 were highly expressed at 6, 3, and 12 h, respectively. In contrast, the expression levels of LbaGATA8, LbaGATA17, LbaGATA19, LbaGATA20, and LbaGATA25 were always up-regulated under salt stress. Therefore, it is possible that LbaGATA genes contribute to salt stress resistance in wolfberries.

5. Conclusions

In this study, genome-wide identification and bioinformatic analysis of GATA genes were conducted in wolfberry (L. barbarum) and four other Solanaceae species (S. lycopersicum, C. annuum, S. tuberosum, and S. melongena). In total, 156 members of the GATA gene family were identified in the five Solanaceae genomes, of which 31 were found in wolfberry. There are four subfamilies in the GATA family (groups I-IV) based on phylogenetic analyses, conserved domain analyses, and gene structure analyses. DSD and WGD largely contribute to expanding the GATA gene family in the Solanaceae species. In addition, the purifying selection is the main evolutionary force imposed on GATA genes, except for a few gene pairs with Ka/Ks values greater than one. Overall, LbaGATA8, LbaGATA17, LbaGATA19, LbaGATA20, and LbaGATA24 are involved in salt stress responses. The findings in this study will provide a foundation to understand better the molecular evolution of GATA genes in Solanaceae species and their molecular functions in wolfberry and other Solanaceae species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14101943/s1.

Author Contributions

F.Z. designed the project and drafted the manuscript. Y.W. contributed the resources and collected data. X.S. conducted the experiments. Y.Y. performed the bioinformatics analysis. X.W. and Y.Y. were responsible for revising the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Key Research and Development projects of Ningxia Hui Autonomous Region (2022BBF02008), the Scientific and Technological Innovation Guidance Program of Ningxia Academy of Agricultural and Forestry Sciences (NKYJ-20-13), the Natural Science Foundation of Ningxia (2023AAC05049), the Leading Talents of Technological Innovation in Ningxia Hui Autonomous Region (2022GKLRLX09), and The Natural Science Foundation for Outstanding Youth of Ningxia (2022AAC05046).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The wolfberry (L. barbarum L.) genome sequence was downloaded from the NCBI database (https://www.ncbi.nlm.nih.gov/genome/?term=PRJNA640228, accessed on 15 September 2022). The Solanum lycopersicum, Capsicum annuum, Solanum tuberosum, and Solanum melongena genome sequences were downloaded from the Sol Genomics Network (https://solgenomics.net/, accessed on 10 October 2022) and Spud DB (http://spuddb.uga.edu/index.shtml), while the Arabidopsis GATA protein sequences were obtained from the TAIR website (https://www.arabidopsis.org/, accessed on 10 October 2022). All transcriptome data sets in this study have been uploaded to the NCBI (SRA) under the accession number PRJNA936477.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zhang, H.; Zhu, J.; Gong, Z.; Zhu, J.K. Abiotic stress responses in plants. Nat. Rev. Genet. 2022, 23, 104–119. [Google Scholar] [CrossRef]
  2. Reboledo, G.; Agorio, A.; Ponce De Leon, I. Moss transcription factors regulating development and defense responses to stress. J. Exp. Bot. 2022, 73, 4546–4561. [Google Scholar] [CrossRef] [PubMed]
  3. Reyes, J.C.; Muro-Pastor, M.I.; Florencio, F.J. The GATA family of transcription factors in Arabidopsis and rice. Plant Physiol. 2004, 134, 1718–1732. [Google Scholar] [CrossRef] [PubMed]
  4. Zhang, X.; Chen, L.; Shi, Q.; Ren, Z. SlMYB102, an R2R3-type MYB gene, confers salt tolerance in transgenic tomato. Plant Sci. 2020, 291, 110356. [Google Scholar] [CrossRef] [PubMed]
  5. Gao, Y.F.; Liu, J.K.; Yang, F.M.; Zhang, G.Y.; Wang, D.; Zhang, L.; Ou, Y.B.; Yao, Y.A. The WRKY transcription factor WRKY8 promotes resistance to pathogen infection and mediates drought and salt stress tolerance in Solanum lycopersicum. Physiol. Plant. 2020, 168, 98–117. [Google Scholar] [CrossRef]
  6. Wang, W.; Qiu, X.; Yang, Y.; Kim, H.S.; Jia, X.; Yu, H.; Kwak, S.S. Sweetpotato bZIP Transcription Factor IbABF4 Confers Tolerance to Multiple Abiotic Stresses. Front. Plant Sci. 2019, 10, 630. [Google Scholar] [CrossRef]
  7. Waseem, M.; Nkurikiyimfura, O.; Niyitanga, S.; Jakada, B.H.; Shaheen, I.; Aslam, M.M. GRAS transcription factors emerging regulator in plants growth, development, and multiple stresses. Mol. Biol. Rep. 2022, 49, 9673–9685. [Google Scholar] [CrossRef]
  8. Diao, P.; Chen, C.; Zhang, Y.; Meng, Q.; Lv, W.; Ma, N. The role of NAC transcription factor in plant cold response. Plant Signal. Behav. 2020, 15, 1785668. [Google Scholar] [CrossRef]
  9. Wu, Y.; Zhang, L.; Nie, L.; Zheng, Y.; Zhu, S.; Hou, J.; Li, R.; Chen, G.; Tang, X.; Wang, C.; et al. Genome-wide analysis of the DREB family genes and functional identification of the involvement of BrDREB2B in abiotic stress in wucai (Brassica campestris L.). BMC Genom. 2022, 23, 598. [Google Scholar] [CrossRef]
  10. Qian, Y.; Zhang, T.; Yu, Y.; Gou, L.; Yang, J.; Xu, J.; Pi, E. Regulatory Mechanisms of bHLH Transcription Factors in Plant Adaptive Responses to Various Abiotic Stresses. Front. Plant Sci. 2021, 12, 677611. [Google Scholar] [CrossRef]
  11. Yin, Y.; Guo, C.; Shi, H.; Zhao, J.; Ma, F.; An, W.; He, X.; Luo, Q.; Cao, Y.; Zhan, X. Genome-Wide Comparative Analysis of the R2R3-MYB Gene Family in Five Solanaceae Species and Identification of Members Regulating Carotenoid Biosynthesis in Wolfberry. Int. J. Mol. Sci. 2022, 23, 2259. [Google Scholar] [CrossRef] [PubMed]
  12. Yin, Y.; Shi, H.; Mi, J.; Qin, X.; Zhao, J.; Zhang, D.; Guo, C.; He, X.; An, W.; Cao, Y.; et al. Genome-Wide Identification and Analysis of the BBX Gene Family and Its Role in Carotenoid Biosynthesis in Wolfberry (Lycium barbarum L.). Int. J. Mol. Sci. 2022, 23, 8440. [Google Scholar] [CrossRef]
  13. Tiika, R.J.; Wei, J.; Ma, R.; Yang, H.; Cui, G.; Duan, H.; Ma, Y. Identification and expression analysis of the WRKY gene family during different developmental stages in Lycium ruthenicum Murr. fruit. PeerJ 2020, 8, e10207. [Google Scholar] [CrossRef]
  14. Kobayashi, K.; Masuda, T. Transcriptional Regulation of Tetrapyrrole Biosynthesis in Arabidopsis thaliana. Front. Plant Sci. 2016, 7, 1811. [Google Scholar] [CrossRef] [PubMed]
  15. Scazzocchio, C. The fungal GATA factors. Curr. Opin. Microbiol. 2000, 3, 126–131. [Google Scholar] [CrossRef] [PubMed]
  16. Bi, Y.M.; Zhang, Y.; Signorelli, T.; Zhao, R.; Zhu, T.; Rothstein, S. Genetic analysis of Arabidopsis GATA transcription factor gene family reveals a nitrate-inducible member important for chlorophyll synthesis and glucose sensitivity. Plant J. 2005, 44, 680–692. [Google Scholar] [CrossRef]
  17. Zhang, C.; Huang, Y.; Xiao, Z.; Yang, H.; Hao, Q.; Yuan, S.; Chen, H.; Chen, L.; Chen, S.; Zhou, X.; et al. A GATA Transcription Factor from Soybean (Glycine max) Regulates Chlorophyll Biosynthesis and Suppresses Growth in the Transgenic Arabidopsis thaliana. Plants 2020, 9, 1036. [Google Scholar] [CrossRef]
  18. Guo, J.; Bai, X.; Dai, K.; Yuan, X.; Guo, P.; Zhou, M.; Shi, W.; Hao, C. Identification of GATA Transcription Factors in Brachypodium distachyon and Functional Characterization of BdGATA13 in Drought Tolerance and Response to Gibberellins. Front. Plant Sci. 2021, 12, 763665. [Google Scholar] [CrossRef]
  19. Zhao, T.; Wu, T.; Pei, T.; Wang, Z.; Yang, H.; Jiang, J.; Zhang, H.; Chen, X.; Li, J.; Xu, X. Overexpression of SlGATA17 Promotes Drought Tolerance in Transgenic Tomato Plants by Enhancing Activation of the Phenylpropanoid Biosynthetic Pathway. Front. Plant Sci. 2021, 12, 634888. [Google Scholar] [CrossRef]
  20. Nutan, K.K.; Singla-Pareek, S.L.; Pareek, A. The Saltol QTL-localized transcription factor OsGATA8 plays an important role in stress tolerance and seed development in Arabidopsis and rice. J. Exp. Bot. 2019, 71, 684–698. [Google Scholar] [CrossRef]
  21. Zhang, H.; Wu, T.; Li, Z.; Huang, K.; Kim, N.-E.; Ma, Z.; Kwon, S.-W.; Jiang, W.; Du, X. OsGATA16, a GATA Transcription Factor, Confers Cold Tolerance by Repressing OsWRKY45–1 at the Seedling Stage in Rice. Rice 2021, 14, 42. [Google Scholar] [CrossRef] [PubMed]
  22. Zhu, H.; Zhai, H.; He, S.; Zhang, H.; Gao, S.; Liu, Q. A novel sweetpotato GATA transcription factor, IbGATA24, interacting with IbCOP9-5a positively regulates drought and salt tolerance. Environ. Exp. Bot. 2022, 194, 104735. [Google Scholar] [CrossRef]
  23. Wei, X.; Li, Y.; Zhu, X.; Liu, X.; Ye, X.; Zhou, M.; Zhang, Z. The GATA transcription factor TaGATA1 recruits demethylase TaELF6-A1 and enhances seed dormancy in wheat by directly regulating TaABI5. J. Integr. Plant Biol. 2022, 65, 1262–1267. [Google Scholar] [CrossRef]
  24. An, Y.; Han, X.; Tang, S.; Xia, X.; Yin, W. Poplar GATA transcription factor PdGNC is capable of regulating chloroplast ultrastructure, photosynthesis, and vegetative growth in Arabidopsis under varying nitrogen levels. Plant Cell Tissue Organ Cult. (PCTOC) 2014, 119, 313–327. [Google Scholar] [CrossRef]
  25. Feng, X.; Yu, Q.; Zeng, J.; He, X.; Liu, W. Genome-wide identification and characterization of GATA family genes in wheat. BMC Plant Biol. 2022, 22, 372. [Google Scholar] [CrossRef] [PubMed]
  26. Yu, R.; Chang, Y.; Chen, H.; Feng, J.; Wang, H.; Tian, T.; Song, Y.; Gao, G. Genome-wide identification of the GATA gene family in potato (Solanum tuberosum L.) and expression analysis. J. Plant Biochem. Biotechnol. 2021, 31, 37–48. [Google Scholar] [CrossRef]
  27. Lai, D.; Yao, X.; Yan, J.; Gao, A.; Yang, H.; Xiang, D.; Ruan, J.; Fan, Y.; Cheng, J. Genome-wide identification, phylogenetic and expression pattern analysis of GATA family genes in foxtail millet (Setaria italica). BMC Genom. 2022, 23, 549. [Google Scholar] [CrossRef]
  28. Yao, X.; Zhou, M.; Ruan, J.; He, A.; Ma, C.; Wu, W.; Lai, D.; Fan, Y.; Gao, A.; Weng, W.; et al. Genome-Wide Identification, Evolution, and Expression Pattern Analysis of the GATA Gene Family in Tartary Buckwheat (Fagopyrum tataricum). Int. J. Mol. Sci. 2022, 23, 12434. [Google Scholar] [CrossRef] [PubMed]
  29. Zhang, K.; Jia, L.; Yang, D.; Hu, Y.; Njogu, M.K.; Wang, P.; Lu, X.; Yan, C. Genome-Wide Identification, Phylogenetic and Expression Pattern Analysis of GATA Family Genes in Cucumber (Cucumis sativus L.). Plants 2021, 10, 1626. [Google Scholar] [CrossRef] [PubMed]
  30. Manzoor, M.A.; Sabir, I.A.; Shah, I.H.; Wang, H.; Yu, Z.; Rasool, F.; Mazhar, M.Z.; Younas, S.; Abdullah, M.; Cai, Y. Comprehensive Comparative Analysis of the GATA Transcription Factors in Four Rosaceae Species and Phytohormonal Response in Chinese Pear (Pyrus bretschneideri) Fruit. Int. J. Mol. Sci. 2021, 22, 12492. [Google Scholar] [CrossRef]
  31. Fernandez-Pozo, N.; Menda, N.; Edwards, J.D.; Saha, S.; Tecle, I.Y.; Strickler, S.R.; Bombarely, A.; Fisher-York, T.; Pujar, A.; Foerster, H.; et al. The Sol Genomics Network (SGN)—From genotype to phenotype to breeding. Nucleic Acids Res. 2015, 43, D1036–D1041. [Google Scholar] [CrossRef]
  32. Hirsch, C.D.; Hamilton, J.P.; Childs, K.L.; Cepela, J.; Crisovan, E.; Vaillancourt, B.; Hirsch, C.N.; Habermann, M.; Neal, B.; Buell, C.R. Spud DB: A Resource for Mining Sequences, Genotypes, and Phenotypes to Accelerate Potato Breeding. Plant Genome 2014, 7, plantgenome2013.12.0042. [Google Scholar] [CrossRef]
  33. Cao, Y.-L.; Li, Y.-l.; Fan, Y.-F.; Li, Z.; Yoshida, K.; Wang, J.-Y.; Ma, X.-K.; Wang, N.; Mitsuda, N.; Kotake, T.; et al. Wolfberry genomes and the evolution of Lycium (Solanaceae). Commun. Biol. 2021, 4, 671. [Google Scholar] [CrossRef]
  34. Finn, R.D.; Bateman, A.; Clements, J.; Coggill, P.; Eberhardt, R.Y.; Eddy, S.R.; Heger, A.; Hetherington, K.; Holm, L.; Mistry, J.; et al. Pfam: The protein families database. Nucleic Acids Res. 2014, 42, D222–D230. [Google Scholar] [CrossRef] [PubMed]
  35. Letunic, I.; Khedkar, S.; Bork, P. SMART: Recent updates, new developments and status in 2020. Nucleic Acids Res. 2021, 49, D458–D460. [Google Scholar] [CrossRef]
  36. Lu, S.; Wang, J.; Chitsaz, F.; Derbyshire, M.K.; Geer, R.C.; Gonzales, N.R.; Gwadz, M.; Hurwitz, D.I.; Marchler, G.H.; Song, J.S.; et al. CDD/SPARCLE: The conserved domain database in 2020. Nucleic Acids Res. 2020, 48, D265–D268. [Google Scholar] [CrossRef] [PubMed]
  37. Artimo, P.; Jonnalagedda, M.; Arnold, K.; Baratin, D.; Csardi, G.; de Castro, E.; Duvaud, S.; Flegel, V.; Fortier, A.; Gasteiger, E.; et al. ExPASy: SIB bioinformatics resource portal. Nucleic Acids Res. 2012, 40, W597–W603. [Google Scholar] [CrossRef] [PubMed]
  38. Horton, P.; Park, K.J.; Obayashi, T.; Fujita, N.; Harada, H.; Adams-Collier, C.J.; Nakai, K. WoLF PSORT: Protein localization predictor. Nucleic Acids Res. 2007, 35, W585–W587. [Google Scholar] [CrossRef] [PubMed]
  39. Edgar, R.C. MUSCLE v5 enables improved estimates of phylogenetic tree confidence by ensemble bootstrapping. bioRxiv 2021. [Google Scholar] [CrossRef]
  40. Nguyen, L.T.; Schmidt, H.A.; von Haeseler, A.; Minh, B.Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 2015, 32, 268–274. [Google Scholar] [CrossRef]
  41. Letunic, I.; Bork, P. Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021, 49, W293–W296. [Google Scholar] [CrossRef]
  42. Hu, B.; Jin, J.; Guo, A.Y.; Zhang, H.; Luo, J.; Gao, G. GSDS 2.0: An upgraded gene feature visualization server. Bioinformatics 2015, 31, 1296–1297. [Google Scholar] [CrossRef] [PubMed]
  43. Bailey, T.L.; Boden, M.; Buske, F.A.; Frith, M.; Grant, C.E.; Clementi, L.; Ren, J.; Li, W.W.; Noble, W.S. MEME SUITE: Tools for motif discovery and searching. Nucleic Acids Res. 2009, 37, W202–W208. [Google Scholar] [CrossRef]
  44. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  45. Qiao, X.; Li, Q.; Yin, H.; Qi, K.; Li, L.; Wang, R.; Zhang, S.; Paterson, A.H. Gene duplication and evolution in recurring polyploidization-diploidization cycles in plants. Genome Biol. 2019, 20, 38. [Google Scholar] [CrossRef]
  46. Hurst, L.D. The Ka/Ks ratio: Diagnosing the form of sequence evolution. Trends Genet. 2002, 18, 486. [Google Scholar] [CrossRef] [PubMed]
  47. Lescot, M.; Dehais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouze, 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]
  48. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef]
  49. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef]
  50. Bu, D.; Luo, H.; Huo, P.; Wang, Z.; Zhang, S.; He, Z.; Wu, Y.; Zhao, L.; Liu, J.; Guo, J.; et al. KOBAS-i: Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res. 2021, 49, W317–W325. [Google Scholar] [CrossRef]
  51. Liu, Y.; Zeng, S.; Sun, W.; Wu, M.; Hu, W.; Shen, X.; Wang, Y. Comparative analysis of carotenoid accumulation in two goji (Lycium barbarum L. and L. ruthenicum Murr.) fruits. BMC Plant Biol. 2014, 14, 269. [Google Scholar] [CrossRef] [PubMed]
  52. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  53. Schwechheimer, C.; Schroder, P.M.; Blaby-Haas, C.E. Plant GATA Factors: Their Biology, Phylogeny, and Phylogenomics. Annu. Rev. Plant Biol. 2022, 73, 123–148. [Google Scholar] [CrossRef] [PubMed]
  54. An, Y.; Zhou, Y.; Han, X.; Shen, C.; Wang, S.; Liu, C.; Yin, W.; Xia, X. The GATA transcription factor GNC plays an important role in photosynthesis and growth in poplar. J. Exp. Bot. 2020, 71, 1969–1984. [Google Scholar] [CrossRef] [PubMed]
  55. Guo, A.Y.; Chen, X.; Gao, G.; Zhang, H.; Zhu, Q.H.; Liu, X.C.; Zhong, Y.F.; Gu, X.; He, K.; Luo, J. PlantTFDB: A comprehensive plant transcription factor database. Nucleic Acids Res. 2008, 36, D966–D969. [Google Scholar] [CrossRef] [PubMed]
  56. Shi, M.; Huang, Q.; Wang, Y.; Wang, C.; Zhu, R.; Zhang, S.; Kai, G. Genome-wide survey of the GATA gene family in camptothecin-producing plant Ophiorrhiza pumila. BMC Genom. 2022, 23, 256. [Google Scholar] [CrossRef] [PubMed]
  57. Panchy, N.; Lehti-Shiu, M.; Shiu, S.H. Evolution of Gene Duplication in Plants. Plant Physiol. 2016, 171, 2294–2316. [Google Scholar] [CrossRef]
  58. Irish, V.F.; Litt, A. Flower development and evolution: Gene duplication, diversification and redeployment. Curr. Opin. Genet. Dev. 2005, 15, 454–460. [Google Scholar] [CrossRef] [PubMed]
  59. Huang, Y.; Chen, J.; Dong, C.; Sosa, D.; Xia, S.; Ouyang, Y.; Fan, C.; Li, D.; Mortola, E.; Long, M.; et al. Species-specific partial gene duplication in Arabidopsis thaliana evolved novel phenotypic effects on morphological traits under strong positive selection. Plant Cell 2022, 34, 802–817. [Google Scholar] [CrossRef]
  60. Wang, G.; Qi, K.; Gao, X.; Guo, L.; Cao, P.; Li, Q.; Qiao, X.; Gu, C.; Zhang, S. Genome-wide identification and comparative analysis of the PYL gene family in eight Rosaceae species and expression analysis of seeds germination in pear. BMC Genom. 2022, 23, 233. [Google Scholar] [CrossRef]
  61. Liu, C.; Qiao, X.; Li, Q.; Zeng, W.; Wei, S.; Wang, X.; Chen, Y.; Wu, X.; Wu, J.; Yin, H.; et al. Genome-wide comparative analysis of the BAHD superfamily in seven Rosaceae species and expression analysis in pear (Pyrus bretschneideri). BMC Plant Biol. 2020, 20, 14. [Google Scholar] [CrossRef] [PubMed]
  62. Zhao, S.; Zhang, Q.; Liu, M.; Zhou, H.; Ma, C.; Wang, P. Regulation of Plant Responses to Salt Stress. Int. J. Mol. Sci. 2021, 22, 4609. [Google Scholar] [CrossRef] [PubMed]
  63. Yu, C.; Li, N.; Yin, Y.; Wang, F.; Gao, S.; Jiao, C.; Yao, M. Genome-wide identification and function characterization of GATA transcription factors during development and in response to abiotic stresses and hormone treatments in pepper. J. Appl. Genet. 2021, 62, 265–280. [Google Scholar] [CrossRef] [PubMed]
  64. Zhu, W.; Guo, Y.; Chen, Y.; Wu, D.; Jiang, L. Genome-wide identification, phylogenetic and expression pattern analysis of GATA family genes in Brassica napus. BMC Plant Biol. 2020, 20, 543. [Google Scholar] [CrossRef] [PubMed]
Genes 14 01943 g001
Figure 1. A phylogenetic analysis of GATA proteins in five Solanaceae species and Arabidopsis. The phylogenetic tree was constructed based on protein matrix using IQ-TREE v2 and grouped into four subfamilies (I–IV) with different colors. The bootstrap values are shown at each node. Green triangles, red rectangles, blue dots, gray triangles, yellow dots, and purple rectangles indicated the GATA proteins of Arabidopsis (AtGATA), wolfberry (LbaGATA), tomato (SlGATA), pepper (CaGATA), potato (StGATA), and eggplant (SmGATA), respectively.
Figure 1. A phylogenetic analysis of GATA proteins in five Solanaceae species and Arabidopsis. The phylogenetic tree was constructed based on protein matrix using IQ-TREE v2 and grouped into four subfamilies (I–IV) with different colors. The bootstrap values are shown at each node. Green triangles, red rectangles, blue dots, gray triangles, yellow dots, and purple rectangles indicated the GATA proteins of Arabidopsis (AtGATA), wolfberry (LbaGATA), tomato (SlGATA), pepper (CaGATA), potato (StGATA), and eggplant (SmGATA), respectively.
Genes 14 01943 g001
Genes 14 01943 g002
Figure 2. Phylogenetic relationship, conserved protein motifs, and gene structure in LbaGATA genes. (a) The Maximum Likelihood (ML) phylogeny includes 31 GATA proteins from wolfberry, grouped into 4 subfamilies, sequentially designated as Subfamily I to Subfamily IV. (b) Exon/intron structures of LbaGATA genes. Green boxes indicate exons, and introns are represented with black lines. A scale at the bottom can indicate the length of exons. (c) The motif composition of LbaGATA proteins. Twenty conserved motifs were performed using MEME, displayed in different colored boxes. The sequence information is shown in Table S2. Protein length can be estimated with the scale at the bottom.
Figure 2. Phylogenetic relationship, conserved protein motifs, and gene structure in LbaGATA genes. (a) The Maximum Likelihood (ML) phylogeny includes 31 GATA proteins from wolfberry, grouped into 4 subfamilies, sequentially designated as Subfamily I to Subfamily IV. (b) Exon/intron structures of LbaGATA genes. Green boxes indicate exons, and introns are represented with black lines. A scale at the bottom can indicate the length of exons. (c) The motif composition of LbaGATA proteins. Twenty conserved motifs were performed using MEME, displayed in different colored boxes. The sequence information is shown in Table S2. Protein length can be estimated with the scale at the bottom.
Genes 14 01943 g002
Genes 14 01943 g003
Figure 3. Gene duplications (TD, tandem duplicates; DSD, dispersed duplicates; WGD, whole-genome duplicates; PD, proximal duplicates; and TRD, transposed duplicates) of the GATA gene family in the five Solanaceae species. Different colored bars indicate different gene duplications.
Figure 3. Gene duplications (TD, tandem duplicates; DSD, dispersed duplicates; WGD, whole-genome duplicates; PD, proximal duplicates; and TRD, transposed duplicates) of the GATA gene family in the five Solanaceae species. Different colored bars indicate different gene duplications.
Genes 14 01943 g003
Genes 14 01943 g004
Figure 4. Syntenic relationship and chromosomal localization of the GATA gene family. (a) Wolfberry; (b) tomato; (c) pepper; (d) potato; and (e) eggplant. The different chromosomes were mapped with the GATA genes in the five Solanaceae species in different colors. Red line indicates the presence of duplicate gene pairs.
Figure 4. Syntenic relationship and chromosomal localization of the GATA gene family. (a) Wolfberry; (b) tomato; (c) pepper; (d) potato; and (e) eggplant. The different chromosomes were mapped with the GATA genes in the five Solanaceae species in different colors. Red line indicates the presence of duplicate gene pairs.
Genes 14 01943 g004
Genes 14 01943 g005
Figure 5. Synteny analysis of GATA genes in Lycium barbarum and five other plant species (Solanum lycopersicum, Capsicum annuum, Solanum tuberosum, Solanum melongena, and Arabidopsis thaliana). The gray lines represent collinear blocks in L. barbarum and the other plant genomes, while red lines highlight syntenic GATA gene pairs in L. barbarum.
Figure 5. Synteny analysis of GATA genes in Lycium barbarum and five other plant species (Solanum lycopersicum, Capsicum annuum, Solanum tuberosum, Solanum melongena, and Arabidopsis thaliana). The gray lines represent collinear blocks in L. barbarum and the other plant genomes, while red lines highlight syntenic GATA gene pairs in L. barbarum.
Genes 14 01943 g005
Genes 14 01943 g006
Figure 6. Analysis of the Ka/Ks values of GATA genes in five species of Solanaceae. Comparison of Ka/Ks values for different models of gene duplications. The x-axis represents five different duplication types. The y-axis indicates the Ka/Ks ratio. WGD, whole-genome duplicates; DSD, dispersed duplicates; TD, tandem duplicates; PD, proximal duplicates; and TRD, transposed duplicates. (a): wolfberry; (b): tomato; (c): pepper; (d): potato; (e): eggplant.
Figure 6. Analysis of the Ka/Ks values of GATA genes in five species of Solanaceae. Comparison of Ka/Ks values for different models of gene duplications. The x-axis represents five different duplication types. The y-axis indicates the Ka/Ks ratio. WGD, whole-genome duplicates; DSD, dispersed duplicates; TD, tandem duplicates; PD, proximal duplicates; and TRD, transposed duplicates. (a): wolfberry; (b): tomato; (c): pepper; (d): potato; (e): eggplant.
Genes 14 01943 g006
Genes 14 01943 g007
Figure 7. Cis-acting elements analysis in the promoter of LbaGATA Genes. (a) Special coding colors indicate cis-acting elements on the upstream regions of LbaGATA genes with functional similarity. (b) Abiotic/biotic stress, phytohormone responses, and plant growth development for cis-elements are represented using different colors.
Figure 7. Cis-acting elements analysis in the promoter of LbaGATA Genes. (a) Special coding colors indicate cis-acting elements on the upstream regions of LbaGATA genes with functional similarity. (b) Abiotic/biotic stress, phytohormone responses, and plant growth development for cis-elements are represented using different colors.
Genes 14 01943 g007
Genes 14 01943 g008
Figure 8. Transcriptomic analysis of wolfberry seedlings under salt stress. (a) Numbers and Venn diagram (b) of differentially expressed genes under salt treatment for 0 h (CK), 1 h, 3 h, 6 h, 12 h, and 24 h as compared to the transcript level at 0 h after salt treatment. (c–g) Analysis of KEGG enrichment pathways for DEGs under salt treatment for 1 h (c), 3 h (d), 6 h (e), 12 h (f), and 24 h (g). Rich factor is represented by the horizontal axis, and pathway name is indicated by the vertical axis. The size of the dots represents the number of genes in the pathway, and the color indicates q-value. Wolfberry seedings were exposed to the salt stress of 300 mM of NaCl for 0 h (CK), 1 h, 3 h, 12 h, and 24 h.
Figure 8. Transcriptomic analysis of wolfberry seedlings under salt stress. (a) Numbers and Venn diagram (b) of differentially expressed genes under salt treatment for 0 h (CK), 1 h, 3 h, 6 h, 12 h, and 24 h as compared to the transcript level at 0 h after salt treatment. (c–g) Analysis of KEGG enrichment pathways for DEGs under salt treatment for 1 h (c), 3 h (d), 6 h (e), 12 h (f), and 24 h (g). Rich factor is represented by the horizontal axis, and pathway name is indicated by the vertical axis. The size of the dots represents the number of genes in the pathway, and the color indicates q-value. Wolfberry seedings were exposed to the salt stress of 300 mM of NaCl for 0 h (CK), 1 h, 3 h, 12 h, and 24 h.
Genes 14 01943 g008
Genes 14 01943 g009
Figure 9. The heatmap of the 31 LbaGATA genes under salt stress using the TBtools v1.12. Wolfberry seedlings were exposed to the salt stress of 300 mM of NaCl for 0 (control, CK), 1, 3, 6, 12, and 24 h. Heatmaps were generated using the FPKM values of the 31 salt-stress-responsive LbaGATAs using the TBtools v1.12. The color scale beside the heatmap indicates gene expression levels, blue color indicates low transcript abundance, and red color indicates high transcript abundance.
Figure 9. The heatmap of the 31 LbaGATA genes under salt stress using the TBtools v1.12. Wolfberry seedlings were exposed to the salt stress of 300 mM of NaCl for 0 (control, CK), 1, 3, 6, 12, and 24 h. Heatmaps were generated using the FPKM values of the 31 salt-stress-responsive LbaGATAs using the TBtools v1.12. The color scale beside the heatmap indicates gene expression levels, blue color indicates low transcript abundance, and red color indicates high transcript abundance.
Genes 14 01943 g009
Genes 14 01943 g010
Figure 10. Gene expression patterns of nine GATA genes verified using qRT-PCR analysis under salt stress treatment. The left-hand y-axis represents the relative expression levels obtained using qRT-PCR analysis, and the right-hand y-axis represents the FPKM values ascertained using RNA-seq analysis. Wolfberry seedlings were exposed to the salt stress of 300 mM of NaCl for 0 h (CK), 1 h, 3 h, 6 h, 12 h, and 24 h. The qRT-PCR data were normalized against LbaActin, and the expression level at the first timepoint (0 h, CK) was set as 1. Three biological replicates are depicted with error bars.
Figure 10. Gene expression patterns of nine GATA genes verified using qRT-PCR analysis under salt stress treatment. The left-hand y-axis represents the relative expression levels obtained using qRT-PCR analysis, and the right-hand y-axis represents the FPKM values ascertained using RNA-seq analysis. Wolfberry seedlings were exposed to the salt stress of 300 mM of NaCl for 0 h (CK), 1 h, 3 h, 6 h, 12 h, and 24 h. The qRT-PCR data were normalized against LbaActin, and the expression level at the first timepoint (0 h, CK) was set as 1. Three biological replicates are depicted with error bars.
Genes 14 01943 g010
Table 1. Information on the genomes of five Solanaceae species and GATA gene numbers identified.
Table 1. Information on the genomes of five Solanaceae species and GATA gene numbers identified.
Common NameScientific
Name		Chromosome Number (2n)Genome SizeGenome Gene NumberGATA GenesGene Name Prefix
WolfberryL. barbarum241.67 Gb3,358131Lba
TomatoS. lycopersicum24785 Mb3,407532Sl
PepperC. annuum243.3 Gb3,533628Ca
PotatoS. tuberosum24741.6 Mb4,485136St
EggplantS. melongena241.07 Gb3,656829Sm
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

Zhang, F.; Wu, Y.; Shi, X.; Wang, X.; Yin, Y. Comparative Analysis of the GATA Transcription Factors in Five Solanaceae Species and Their Responses to Salt Stress in Wolfberry (Lycium barbarum L.). Genes 2023, 14, 1943. https://doi.org/10.3390/genes14101943

AMA Style

Zhang F, Wu Y, Shi X, Wang X, Yin Y. Comparative Analysis of the GATA Transcription Factors in Five Solanaceae Species and Their Responses to Salt Stress in Wolfberry (Lycium barbarum L.). Genes. 2023; 14(10):1943. https://doi.org/10.3390/genes14101943

Chicago/Turabian Style

Zhang, Fengfeng, Yan Wu, Xin Shi, Xiaojing Wang, and Yue Yin. 2023. "Comparative Analysis of the GATA Transcription Factors in Five Solanaceae Species and Their Responses to Salt Stress in Wolfberry (Lycium barbarum L.)" Genes 14, no. 10: 1943. https://doi.org/10.3390/genes14101943

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