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Article

Genome-Wide Identification of GASA Gene Family in Ten Cucurbitaceae Species and Expression Analysis in Cucumber

by
Kaijing Zhang
1,
Yuchao Hu
1,
Dekun Yang
1,
Congsheng Yan
2,3,
Nanyang Li
4,
Ziang Li
4,
Martin Kagiki Njogu
5,
Xing Wang
4,* and
Li Jia
2,3,*
1
College of Agriculture, Anhui Science and Technology University, Chuzhou 233100, China
2
Institute of Horticulture, Anhui Academy of Agricultural Sciences, Hefei 230001, China
3
Key Laboratory of Genetic Improvement and Ecophysiology of Horticultural Crop, Hefei 230001, China
4
School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, China
5
Department of Plant Science, Chuka University, Chuka P.O. Box 109-60400, Kenya
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(8), 1978; https://doi.org/10.3390/agronomy12081978
Submission received: 19 July 2022 / Revised: 18 August 2022 / Accepted: 18 August 2022 / Published: 22 August 2022
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Abstract

:
Gibberellic acid-stimulated in Arabidopsis (GASA), a unique small molecular protein of plants, plays an essential role in plant growth and development. The GASA family genes have been identified and studied in many plants. However, the identification of GASA gene family in Cucurbitaceae species has not been reported yet. Therefore, in this study, based on the available genome information on the Cucurbitaceae species, the GASA family genes in 10 Cucurbitaceae species including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), melon (Cucumis melo), pumpkin (Cucurbita moschata), wax gourd (Benincasa hispida), sponge gourd (Luffa cylindrica), bottle gourd (Lagenaria siceraria), bitter gourd (Momordica charantia), chayote (Sechium edule), and snake gourd (Trichosanthes anguina) were identified with bioinformatics methods. To understand the molecular functions of GASA genes, the expression pattern analysis of cucumber GASA family genes in different tissues and stress responses were also analyzed. The results showed that a total of 114 GASA genes were identified in the 10 Cucurbitaceae species, which were divided into three subfamilies. Synteny analysis of GASA genes among cucumber, Arabidopsis and rice showed that nine cucumber GASA genes were colinear with 12 Arabidopsis GASA genes, and six cucumber GASA genes were colinear with six rice GASA genes. The cis-acting elements analysis implied that the cucumber GASA genes contained many cis-elements associated with stress and hormone response. Tissue-specific expression analysis of cucumber GASA family genes revealed that only the CsaV3_2G029490 gene was lowly or not expressed in all tissues, the CsaV3_3G041480 gene was highly expressed in all tissues, and the other seven GASA genes showed tissue-specific expression patterns. Furthermore, nine cucumber GASA family genes exhibited different degrees of regulatory response under GA, abiotic and biotic stresses. Two cucumber GASA genes, CsaV3_3G042060 and CsaV3_3G041480, were differentially expressed under multiple biotic and abiotic stresses, which indicated that these two GASA genes play important roles in the growth and development of cucumber.

1. Introduction

GASA proteins are a class of cysteine-rich peptides (CRPs) that play important roles in regulating plant growth and development [1]. GASA family genes are widely distributed in vascular plants such as ferns, gymnosperms and angiosperms [2]. The protein structures of GASA family members are relatively conservative. Generally, they have a signal peptide consisting of 18–29 amino acids at the N-terminal, a highly variable hydrophilic region consisting of 7–31 polar amino acid residues in the middle, and about 60 amino acids at the C-terminal. The GASA proteins contain a conserved region consisting of 12 cysteine residues and considered to be the critical region of GASA proteins for maintaining spatial structure and function [1,3,4]. Most of GASA family genes are regulated by gibberellin (GA) [5,6].
GASA genes were identified in tomato as early as 1992 [7]. Subsequently, the identification of GASA family genes were reported in many important plants, such as Arabidopsis [8,9,10], maize [11], potato [12], apple [10], wheat [13], rice [14], grape [15], poplar [16], etc. GASA family genes play important regulatory roles in plant hormone signal transduction [4,17], seed germination [18], seed development [9,19], lateral root formation [11], stem growth [6,20,21], leaf growth [22], flowering time [8,21], fruit growth and development [23,24]. In addition, GASA genes also actively respond to high temperature [25,26], low temperature [27], salt damage [28], diseases [29,30,31] and other biological and abiotic stresses.
The Cucurbitaceae, also called cucurbits or the gourd family, are primarily herbaceous annual climbers, vines or woody perennial lianas including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), melon (Cucumis melo), pumpkin (Cucurbita moschata), wax gourd (Benincasa hispida), sponge gourd (Luffa cylindrica), bottle gourd (Lagenaria siceraria), bitter gourd (Momordica charantia), chayote (Sechium edule), snake gourd (Trichosanthes anguina) and many other important economic crops. Cucurbitaceae species play important roles in agricultural production, which is second only to Solanaceae in vegetables [32]. Cucurbitaceae species also have important medicinal and ornamental values [33]. In scientific research, Cucurbitaceae species are used as model plants for studying sexual differentiation and vascular biology [34,35]. As early as 2009, the cucumber genome sequencing project was completed [36,37]. With the rapid development of sequencing technology and genomics, whole genome sequencing projects for Cucurbitaceae species such as melon [38], watermelon [39], pumpkin [40], wax gourd [41], bottle gourd [42], sponge gourd [43], bitter gourd [44], chayote [45] and snake gourd [33] have been successively completed. By using the high-quality genome information, a large number of studies on gene family identification have been finished, such as the identification of WRKY [46,47,48,49], MADS-box [50,51,52], NBS [53,54,55], bZIP [56,57] and other gene families. However, the identification of GASA family genes in Cucurbitaceae species was still not reported, which greatly limited the biological function studies of GASA genes in Cucurbitaceae crops.
Therefore, in this study, GASA family genes were identified with the latest high-quality genome information on 10 Cucurbitaceae species, and the physicochemical characteristics, chromosome locations, gene structures, conserved motifs, phylogenetic tree, cis-acting elements of promoter, and synteny of GASA family genes were analyzed. Moreover, analyses of tissue-specific expression and the expression pattern in response to stresses of cucumber GASA genes were conducted to preliminarily explore the molecular biological functions of GASA family genes in cucumber. The results will lay an important foundation for the further study of molecular biological functions of GASA genes in the Cucurbitaceae species, and provide a theoretical reference for the molecular breeding of Cucurbitaceae species.

2. Materials and Methods

2.1. Identification and Chromosomal Mapping of GASA Family Genes in 10 Cucurbitaceae Species

The probable GASA family genes (E-value < 1 × 10−5) in 10 Cucurbitaceae species genomes were scanned using HMMER 3.0 with the Hidden Markov Model (HMM) model file (PF02704). A Perl script was used to extract the sequence information of candidate GASA proteins. Pfam and SMART (http://smart.embl.de/smart/batch.pl, accessed on 17 April 2022) [58] were used to identify GASA family members. Genes containing the whole GASA domain were chosen as the final candidate GASA genes. The chromosomal locations of the GASA genes were analyzed with TBtools software [59]. The physicochemical characteristics including theoretical isoelectric point (pI), molecular weight, instability index, aliphatic index and grand average of hydropathicity of each GASA protein were calculated via the online tool ExPASy (https://web.expasy.org/protparam/, accessed on 17 April 2022). The subcellular localizations of GASA genes were predicted by the online website CELLO (http://cello.life.nctu.edu.tw/, accessed on 18 April 2022) [60].

2.2. Gene Structure Analysis and Phylogenetic Tree Construction of GASA Family Genes in 10 Cucurbitaceae Species

The General Feature Format 3 (GFF3) files of 10 Cucurbitaceae species were used to draw the structure of GASA genes with TBtools software. The online software MEME (http://meme-suite.org/, accessed on 18 April 2022) [61] was used to analyze the conserved motifs of GASA proteins with the following parameters: a maximum of 10 misfits and an optimum motif width of 6–100 amino acid residues. The upstream sequences (1.5 kb) of the coding sequences of GASA genes were extracted from the genomes of 10 Cucurbitaceae species, and submitted to PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 18 April 2022) [62] to identify the cis-acting elements. The phylogenetic tree was constructed using MEGA 11 software with the neighbor-joining method [63]. The parameters were pairwise deletion and 1000 bootstrap replications.

2.3. Gene Duplication and Synteny Analysis of GASA Family Genes

MCScanX [64] software was used to analyze tandem and segmental duplications of cucumber GASA family genes. The synteny analyses between the cucumber GASA family genes, Arabidopsis genes, and rice genes were conducted with MCScanX software; the collinearity relationships among the GASA family genes in cucumber, Arabidopsis and rice were then visualized by Circos software [65].

2.4. RNA-seq Reanalysis with Cucumber Transcriptome Sequencing Data

The published cucumber transcriptome sequencing data in SRA database (https://www.ncbi.nlm.nih.gov/sra, accessed on 20 April 2022) were downloaded. The downloaded SRA data were converted into Fastq data using fasterq-dump.2.11.0 (https://github.com/ncbi/sra-tools/wiki/HowTo:-fasterq-dump, accessed on 22 April 2022). The quality of Fastq data was then checked through the FastQC software [66]. The joints and low-quality sequences of the Fastq data were removed with Trimmomatic software (version = 0.39) [67], finally obtaining the filtered clean data. The index of cucumber ChineseLong_V3 genome was built with STAR software (version = 2.7.10a). The filtered clean data were compared to cucumber ChineseLong_V3 genome, generating the SAM files. Using the SAMtools software (version = 1.15) [68], the SAM files were converted into sorted BAM files. The expression data of each gene were estimated with StringTie software (v2.2.1) [69]. Finally, based on the counts data for each gene, the analysis of differentially expressed genes was performed with the DESeq2 software [70].

2.5. Tissue-Specific Expression Analysis of Cucumber GASA Family Genes

The transcriptome sequencing project performed in different cucumber tissues was retrieved from the SRA database (PRJNA80169) [71]. The tissue-specific expression analysis of cucumber GASA family genes was analyzed with the above methods. The heatmap was drawn by TBtools software.

2.6. The Expression Analysis of Cucumber GASA Family Genes under Stresses

The transcriptome sequencing data of cucumber under stress treatments such as GA (PRJNA376073) [72], high temperature (PRJNA634519) [73], low temperature (PRJNA438923), salt and silicon (PRJNA477930) [74], downy mildew (PRJNA285071) [75], powdery mildew (PRJNA321023) [76], and root-knot nematode (PRJNA419665) [77] were retrieved from the SRA database. The expression profiles of cucumber GASA family genes were analyzed using the above methods, and then the heatmaps were drawn with TBtools software.

3. Results

3.1. Genome-Wide Identification of GASA Genes in 10 Cucurbitaceae Species

Based on the published genome information of Cucurbitaceae species, 9, 9, 11, 9, 9, 8, 15, 10, 16 and 18 GASA family genes were identified in wax gourd, watermelon, pumpkin, cucumber, sponge gourd, bottle gourd, bitter gourd, melon, chayote and snake gourd, respectively (Table 1). The chromosomal locations of GASA family genes in different Cucurbitaceae species were unevenly distributed. For all the 114 GASA proteins identified in the 10 Cucurbitaceae species, the numbers of encoded amino acids varied from 57 to 516, the molecular weight varied from 6.15 to 58.17 kDa, and the aliphatic index varied from 16.98 to 89.14. The isoelectric points (pI) of the 114 GASA proteins ranged from 5.99 to 9.9. Except for CmoCh09G000990.1 (pI = 5.99, was acid protein), the other GASA proteins in 10 Cucurbitaceae species were basic proteins (pI > 7). Among the 114 GASA genes, 42 proteins of GASA genes were stable proteins with an instability index less than 40. The other 72 GASA proteins were unstable proteins with an instability index greater than 40 that were unevenly distributed in the 10 Cucurbitaceae species. A total of 29 GASA proteins were hydrophobic proteins whose average hydrophilic values were greater than zero. The other 85 GASA proteins were hydrophilic proteins whose average hydrophilic values were less than zero, and they were also unevenly distributed in the 10 Cucurbitaceae species. The predicted results of subcellular localization showed that 98 GASA family genes were located in the extracellular matrix, and 16 GASA family members were located in the nucleus and unevenly distributed in the 10 Cucurbitaceae species. (Table 1).

3.2. Phylogenetic Analysis of GASA Family Genes in 10 Cucurbitaceae Species

To clarify the evolutionary relationship of GASA family genes in 10 Cucurbitaceae species, all 114 Cucurbitaceae GASA proteins and 15 Arabidopsis GASA proteins were used to construct a phylogenetic tree by multiple sequence alignment (Figure 1). According to the classification results of Arabidopsis GASA family genes [10], the phylogenetic tree was divided into three subgroups, namely G1, G2 and G3. Among them, the G3 subgroup contained the largest number of GASA genes, a total of 60. The G2 subgroup had the second largest number of GASA genes, totaling 38. The G1 subgroups had the smallest number of GASA genes, at 31. The GASA family proteins in every Cucurbitaceae species could be divided into these three subfamilies.

3.3. The Gene Structure and Conserved Motifs of GASA Family Genes in 10 Cucurbitaceae Species

The diagrams of phylogenetic tree and gene structures of GASA family genes in 10 Cucurbitaceae species were drawn with TBtools software. The results of phylogenetic tree analysis showed that GASA genes of 10 Cucurbitaceae species could be divided into three subgroups, namely G1, G2 and G3 subgroups (Figure 2), which was consistent with the clustering results for GASA proteins in Arabidopsis and 10 Cucurbitaceae species (Figure 1). Among them, there were 54 GASA genes in the G3 subgroup, 34 GASA genes in the G2 subgroup and 26 GASA genes in the G1 subgroup. The gene structure analysis showed that most of the GASA genes in the G2 subgroup were composed of two exons, while most of the GASA genes in the G1 subgroup were composed of four exons. In the G3 subgroup, most of the GASA genes were composed of three or four exons (Figure 2).
A schematic diagram of conserved motifs of GASA proteins in 10 Cucurbitaceae species was constructed with MEME analysis (Figure 2). A total of 10 motifs were revealed in the GASA proteins (Table 2). The motif compositions of GASA proteins in different subgroups were different, while GASA proteins in the same subgroup shared a similar number, type, and order of motifs. For example, most GASA proteins in the G1 subgroup contained motifs 5, 2, 1, 3, 6 and exhibited the same order. In the G3 subgroup, motifs 1 and 3 were found in all GASA proteins and showed the same order. These results indicated that the different distribution of conserved motifs in different subgroups might lead to the evolution of GASA gene functional diversity. The similar conserved motifs of GASA proteins in the same subgroup indicated that they have similar functions.

3.4. Synteny Analysis of GASA Genes among Cucumber, Arabidopsis and Rice

To better understand the molecular functions of cucumber GASA family genes, a synteny analysis of GASA family genes among cucumber, Arabidopsis and rice was conducted. The results showed 23 syntenic relationships between all nine cucumber GASA family genes and 12 Arabidopsis GASA genes (AT5G15230, AT3G10185, AT1G74670, AT3G02885, AT4G09610, AT1G75750, AT2G39540, AT5G59845, AT2G14900, AT2G18420, AT1G10588, AT5G14920). There were eight syntenic relationships between six cucumber GASA genes (CsaV3_3G042990, CsaV3_2G029490, CsaV3_3G041480, CsaV3_3G045860, CsaV3_2G026300, CsaV3_1G008270) and six rice GASA genes (Os05g31280, Os05g35690, Os06g15620, Os09g24840, Os03g14550, Os04g39110). The synteny analysis of GASA family genes in cucumber showed that there were two pairs of cucumber GASA family genes (CsaV3_2G026300/CsaV3_6G043760, CsaV3_2G029490/CsaV3_3G045860) with syntenic relationships, which were segmental duplication gene pairs (Figure 3).

3.5. Analysis of Cis-Acting Elements in Cucumber GASA Genes

The 1.5-kb upstream sequences from the transcription start sites of cucumber GASA family genes were selected to analyze their cis-acting elements in the promoters. The results showed that 14 types of cis-elements were identified (Figure 4). Among them, cis-elements related to light responsiveness were the major type, including ACE, AE-box, ATCT-motif, Box 4, Box II, G-box, GT1-motif, I-box, LAMP-element, etc., accounting for 55% of total cis-elements. In addition, some other cis-elements were also identified, including cis-elements related to hormone response (auxin, gibberellin, salicylic acid, abscisic acid, MeJA), stress response (drought, low temperature, resistance), photoperiod regulation, endosperm expression and meristem expression. The results indicated that cucumber GASA genes play vital roles in plant growth and development.

3.6. Tissue-Specific Expression Analysis of Cucumber GASA Genes

To analyze the tissue-specific expression patterns of GASA genes in cucumber, the transcriptome sequencing data of 10 types of cucumber tissues (obtained from the published SRA data PRJNA80169) [71] were reanalyzed with ChineseLong_V3 genome. The results indicated that the GASA gene CsaV3_2G029490 was lowly or not expressed in the cucumber tissues. The CsaV3_3G041480 gene was highly expressed in all of the cucumber tissues. The CsaV3_3G042990 gene was expressed in all of the cucumber tissues, with the highest expression levels in the male and female flowers, followed by the ovaries, and was lowly expressed in the root, stem, leaf and tendril. The CsaV3_3G045860 gene was mainly expressed in the male and female flowers, but was not expressed in stem and tendril, and lowly expressed in the other tissues. The CsaV3_4G000520 gene was highly expressed in the tendrils and flowers, but was not expressed in the ovaries, and lowly expressed in the root, stem and leaf. The CsaV3_6G043760 gene was lowly expressed in all tissues of cucumber, with a relatively high expression level in the root, and was not expressed in the fertilized ovary. The CsaV3_2G026300 gene was not expressed in the male flower, but was lowly expressed in the root and highly expressed in the other tissues. The CsaV3_1G008270 gene was highly expressed in all cucumber tissues except the root. The CsaV3_3G042060 gene was expressed in all tissues, with lower expression levels in the male and female flowers, and higher expression levels in the other tissues (Figure 5).

3.7. Expression Profiles of Cucumber GASA Genes under GA Treatment

After reanalyzing the transcriptome sequencing data of cucumber under GA treatment (PRJNA376073) [72], an expression heatmap of cucumber GASA family genes in the shoot tip was drawn (Figure 6). The results showed that the expression levels of CsaV3_2G029490, CsaV3_3G042990, CsaV3_4G000520, CsaV3_3G045860 and CsaV3_6G043760 were low in the shoot tip, and did not change under GA treatment. The CsaV3_1G008270 gene was highly expressed in the shoot tip, and not regulated by GA. However, compared with the control, the CsaV3_2G026300 gene was significantly down-regulated after GA treatment for 12 h; the CsaV3_3G042060 gene was significantly down-regulated after GA treatments for 6 h and 12 h; the CsaV3_3G041480 gene was up-regulated after GA treatment for 6 h, but the expression levels were not significantly different.

3.8. Expression Profiles of Cucumber GASA Genes under Abiotic Stresses

To determine the expression profiles of cucumber GASA family genes under high temperature, low temperature, salt and silicon stresses, the published transcriptome sequencing data (PRJNA634519; PRJNA438923; PRJNA477930) [73,74] were re-analyzed with the cucumber ChineseLong_V3 genome. Compared with the control, CsaV3_3G041480 and CsaV3_3G042990 genes were significantly down-regulated under high temperature stress. The other cucumber GASA genes were not significantly affected by high temperature treatment (Figure 7A). Cucumber GASA genes CsaV3_3G041480, CsaV3_1G008270 and CsaV3_3G042990 were significantly down-regulated under low temperature stress (Figure 7B). Under salt stress, CsaV3_3G041480 and CsaV3_3G042060 genes were significantly down-regulated (Figure 7C). Under silicon stress, the CsaV3_3G042060 gene was significantly down-regulated, and the CsaV3_3G045860 gene was significantly up-regulated (Figure 7C).

3.9. Expression Profiles of Cucumber GASA Genes under Biotic Stresses

To determine the expression profiles of cucumber GASA family genes under downy mildew, powdery mildew and root-knot nematode stresses, the published transcriptome sequencing data (PRJNA285071; PRJNA321023; PRJNA419665) [75,76,77] were re-analyzed with the cucumber ChineseLong_V3 genome. Under downy mildew stress, only the CsaV3_2G029490 gene was significantly down-regulated in both resistant and susceptible materials. The CsaV3_3G041480 gene was significantly up-regulated only in the resistant material (Figure 8A). Under powdery mildew stress, the CsaV3_3G041480 and CsaV3_3G042990 genes were significantly down-regulated in both resistant and susceptible materials, while the CsaV3_1G008270, CsaV3_2G029490 and CsaV3_3G042060 genes were only significantly up-regulated in the susceptible material (Figure 8B). Under root-knot nematode stress, the CsaV3_2G029490 and CsaV3_4G000520 genes were significantly up-regulated in both resistant and susceptible materials, but with different expression patterns. The CsaV3_2G029490 gene was significantly up-regulated at 1 day post inoculation (dpi) in the susceptible material, and then the expression level decreased slowly. In the resistant material, the expression level of the CsaV3_2G029490 gene was significantly up-regulated at 3 dpi. The expression patterns of the CsaV3_4G000520 gene in resistant and susceptible materials were also different. The CsaV3_4G000520 gene was only significantly differentially expressed at 3 dpi in susceptible material, but was significantly differentially expressed at 1 dpi in resistant material. The CsaV3_3G042060 gene was significantly down-regulated in both resistant and susceptible materials, but with different expression patterns. The CsaV3_3G042060 gene was significantly down-regulated at 1 dpi in susceptible material, but was significantly down-regulated at 2 dpi in resistant material. The CsaV3_6G043760 gene was significantly down-regulated only in susceptible material (Figure 8C).

3.10. Regulation Patterns of Cucumber GASA Genes under Stresses

To analyze the expression patterns of cucumber GASA family genes under GA treatment and stress responses, the differentially expressed genes were labeled and drawn into a heatmap (Figure 9). The results showed that nine cucumber GASA family genes were all differentially expressed under different stress responses. The CsaV3_3G042060 and CsaV3_3G041480 genes were differentially expressed under multiple types of abiotic and biotic stresses, indicating that these two GASA genes actively participate in stress responses, which indicates they could be considered as key candidate genes for further studies. The CsaV3_1G008270 and CsaV3_3G042990 genes were differentially expressed under a few abiotic and biotic stresses. The CsaV3_2G026300 gene was differentially expressed only under GA treatment. The CsaV3_3G045860 gene was up-regulated only under salt stress. Additionally, some cucumber GASA family genes, such as CsaV3_4G000520, CsaV3_6G043760 and CsaV3_2G029490, were only involved in response to biotic stresses. The analysis of regulation patterns of cucumber GASA family genes could provide a theoretical reference for further research on molecular biological functions of cucumber GASA genes.

4. Discussion

In recent years, with the rapid development of genome sequencing technology, more and more plant genome information has been published [78]. The identification of many important gene families has gradually been carried out in different plants. GASA is a type of gene family induced by gibberellin, encoding a small molecular polypeptide. Its N-terminal contains a signal peptide, and its C-terminal contains 12 conserved cysteines [79]. The GASA gene family has been successively identified in model plants including Arabidopsis thaliana [8,9,10] and rice [14], and subsequently reported in some important field crops such as maize [11] and wheat [13]. The identification of GASA gene family has also been reported in fruit trees such as apple [10] and grape [15]. However, there were few studies on the identification of GASA gene family in vegetable crops; only the identification of GASA gene family in tomato was reported [14]. As important vegetable crops widely cultivated in the world, Cucurbitaceae is the second largest fruit and vegetable family, and its members are among the most important edible plants in the world, next only to Solanaceae [66]. With the genome resolution of a large number of Cucurbitaceae crops, annotation research on gene function has become a current hotspot [32]. However, research on GASA gene family identification and function in Cucurbitaceae crops has not been performed, which greatly limits the molecular biological function research on GASA genes in Cucurbitaceae species. Therefore, using the genome information on Cucurbitaceae crops, the GASA gene families were identified in 10 Cucurbitaceae crops. Moreover, the expression profiles of GASA family genes in different tissues and stress responses were analyzed in cucumber, which provided a theoretical reference for further study on molecular functions of GASA genes and laid a theoretical basis for cucumber resistance molecular breeding.
In this study, a total of 114 members of the GASA gene family in 10 Cucurbitaceae crops were identified. There were 9, 9, 11, 9, 9, 8, 15, 10, 16 and 18 GASA members in wax gourd, watermelon, pumpkin, cucumber, sponge gourd, bottle gourd, bitter gourd, melon, chayote and snake gourd, respectively. The GASA family gene numbers in Arabidopsis, maize, potato, apple, wheat, grape, Populus Tomentosa, Populus euphratica, and rice were 15, 10, 16, 26, 37, 14, 21, 19 and 9 [10,11,12,13,15,16,79,80], respectively, most of which outnumbered the GASA genes in Cucurbitaceae crops. The analysis of physicochemical characteristics showed that all GASA proteins except CmoCh09G000990.1 in Cucurbitaceae crops were basic proteins, which was similar to the physicochemical characteristics of cocoa GASA proteins (except that one GASA protein was acidic, while the other GASA proteins were basic proteins) [31]. In Arabidopsis, rice, grape and tomato, all of the GASA proteins were basic proteins. Phylogenetic tree analysis of 114 GASA genes divided these GASA genes into three subgroups, namely G1, G2 and G3, which was similar to the clustering results of phylogenetic analysis of GASA family genes in Arabidopsis [10], grape [15] and poplar [16]. There were significant differences in gene structure among the GASA genes within three different subgroups, and the gene structures and conserved motifs of GASA genes in the same subgroup were similar. The analysis of gene duplication events for cucumber GASA family genes found that there were no tandem duplication genes in cucumber. However, there were two segmental duplications in the cucumber GASA gene family. It revealed that the expansion of GASA genes in cucumber mainly resulted from segmental duplications, indicating that each species performed gene expansion in a specific way. This phenomenon also existed in the other plant gene families [81,82]. The synteny analysis of the GASA family genes in Arabidopsis, rice and cucumber found that nine cucumber GASA genes were collinear with Arabidopsis GASA genes, while only six cucumber GASA genes were collinear with rice GASA genes, indicating that the cucumber GASA family genes have higher homology with Arabidopsis GASA genes in evolution.
Due to the rapid development of high-throughput sequencing technology in recent years, many researchers have conducted transcriptome sequencing in cucumber, forming cucumber transcriptome sequencing big data. Therefore, using these transcriptome sequencing data effectively could not only reduce research costs but also enable in-depth data mining. Moreover, the molecular biological functions of different gene families in cucumber could be studied by using cucumber transcriptome sequencing big data under different treatments. In this study, with the published cucumber transcriptome sequencing big data, the tissue-specific expression patterns and the stress-responsive gene expression patterns of nine cucumber GASA family genes were analyzed. The results showed that only CsaV3_2G029490 was lower expressed or not expressed in all tissues. CsaV3_3G041480 was highly expressed in all tissues, while the other cucumber GASA family genes showed a tissue-specific expression pattern. The tissue-specific expression pattern of these GASA family genes in different tissues cooperatively regulated the plant growth and development of cucumber. By analyzing the expression patterns of cucumber GASA genes in response to GA stress, the results showed that CsaV3_2G026300 and CsaV3_3G042060 were induced by GA stress. It was also found that some GASA genes, such as GASA14, were regulated by GA in Arabidopsis and rice [4,5,22]. It was found that CsaV3_3G042060 and GASA14 were orthologous genes. By analyzing the expression profiles of cucumber GASA genes in response to biotic and abiotic stress, the results showed that eight GASA genes, except for CsaV3_2G026300, were involved in stress responses. Among them, CsaV3_3G042060, CsaV3_3G041480, CsaV3_1G008270 and CsaV3_3G042990 were all involved in response to biotic and abiotic stress, CsaV3_3G045860 was only up-regulated in response to silicon stress, and CsaV3_4G000520, CsaV3_6G043760 and CsaV3_3G045860 were only involved in response to biological stress. Previous research has found that the CsGASA4 gene (Csa3G826660 in the cucumber V2 genome and CsaV3_3G041480 in the cucumber V3 genome) is involved in the response to downy mildew and corynespora leaf spot, and is up-regulated in the resistant varieties [83], which is consistent with the expression pattern of CsGASA4 gene in resistant varieties in this study.

5. Conclusions

In this study, a total of 114 GASA family genes were identified in 10 Cucurbitaceae species including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), melon (Cucumis melo), pumpkin (Cucurbita moschata), wax gourd (Benincasa hispida), sponge gourd (Luffa cylindrica), bottle gourd (Lagenaria siceraria), bitter gourd (Momordica charantia), chayote (Sechium edule), and snake gourd (Trichosanthes anguina), which were divided into three subgroups. The gene structure and protein conserved motifs in the same subgroup were highly conservative, and the distributions of exon/intron and motifs were different among different subgroups. The tissue-specific expression patterns and the stress-responsive gene expression patterns of cucumber GASA family genes were analyzed by reanalyzing the cucumber transcriptome sequencing data with cucumber ChineseLong_V3 genome. The results showed that the expression patterns of cucumber GASA family genes in different tissues and stress responses were different, which synergistically regulated the plant growth and development of cucumber. Among them, CsaV3_3G042060 and CsaV3_3G041480 were differentially expressed under multiple biotic and abiotic stresses, indicating that these two GASA genes were actively involved in stress responses. This study will provide a theoretical reference for the further study of molecular biological functions of cucumber GASA genes, and provide favorable genes for cucumber resistance molecular breeding.

Author Contributions

X.W. and L.J. conceived the research and designed the experiments. K.Z. performed research, analyzed the data and wrote the manuscript. Y.H. and D.Y. participated in downloading transcriptome sequencing data and helped with the bioinformatics analysis. C.Y., N.L. and Z.L. analyzed and interpreted the data. M.K.N. wrote and modified the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (32002061), the Key Projects of Anhui Provincial Department of Education (KJ2021A0901), the Anhui Province Vegetable Industry Technology System, the Natural Science Foundation of Hebei Science and Technology program (C2021402014), the University Scientific Research Project of Hebei (QN2022062), the College Students’ Innovative Entrepreneurial Training Plan Program (S202110879222), and the Talent Foundation of Anhui Science and Technology University (NXYJ202103).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data used in this study are presented in the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Silverstein, K.A.; Moskal, W.A., Jr.; Wu, H.C.; Underwood, B.A.; Graham, M.A.; Town, C.D.; VandenBosch, K.A. Small cysteine-rich peptides resembling antimicrobial peptides have been under-predicted in plants. Plant J. 2007, 51, 262–280. [Google Scholar] [CrossRef] [PubMed]
  2. Kumar, A.; Singh, A.; Kumar, P.; Sarkar, A.K. Giberellic Acid-Stimulated Transcript Proteins Evolved through Successive Conjugation of Novel Motifs and Their Subfunctionalization. Plant Physiol. 2019, 180, 998–1012. [Google Scholar] [CrossRef]
  3. Aubert, D.; Chevillard, M.; Dorne, A.-M.; Arlaud, G.; Herzog, M. Expression patterns of GASA genes in Arabidopsis thaliana: The GASA4 gene is up-regulated by gibberellins in meristematic regions. Plant Mol. Biol. 1998, 36, 871–883. [Google Scholar] [CrossRef] [PubMed]
  4. Wang, L.; Wang, Z.; Xu, Y.; Joo, S.-H.; Kim, S.-K.; Xue, Z.; Xu, Z.; Wang, Z.; Chong, K. OsGSR1 is involved in crosstalk between gibberellins and brassinosteroids in rice. Plant J. 2009, 57, 498–510. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, S.; Wang, X. Expression pattern of GASA, downstream genes of DELLA, in Arabidopsis. Chin. Sci. Bull. 2008, 53, 3839–3846. [Google Scholar] [CrossRef] [Green Version]
  6. Ben-Nissan, G.; Lee, J.-Y.; Borohov, A.; Weiss, D. GIP, a Petunia hybrida GA-induced cysteine-rich protein: A possible role in shoot elongation and transition to flowering. Plant J. 2004, 37, 229–238. [Google Scholar] [CrossRef] [PubMed]
  7. Shi, L.; Gast, R.T.; Gopalraj, M.; Olszewski, N.E. Characterization of a shoot-specific, GA3- and ABA-regulated gene from tomato. Plant J. 1992, 2, 153–159. [Google Scholar]
  8. Herzog, M.; Dorne, A.-M.; Grellet, F. GASA, a gibberellin-regulated gene family from Arabidopsis thaliana related to the tomato GAST1 gene. Plant Mol. Biol. 1995, 27, 743–752. [Google Scholar] [CrossRef]
  9. Roxrud, I.; Lid, S.E.; Fletcher, J.C.; Schmidt, E.D.L.; Opsahl-Sorteberg, H.-G. GASA4, One of the 14-Member Arabidopsis GASA Family of Small Polypeptides, Regulates Flowering and Seed Development. Plant Cell Physiol. 2007, 48, 471–483. [Google Scholar] [CrossRef]
  10. Fan, S.; Zhang, D.; Zhang, L.; Gao, C.; Xin, M.; Tahir, M.M.; Li, Y.; Ma, J.; Han, M. Comprehensive analysis of GASA family members in the Malus domestica genome: Identification, characterization, and their expressions in response to apple flower induction. BMC Genom. 2017, 18, 827. [Google Scholar] [CrossRef]
  11. Zimmermann, R.; Sakai, H.; Hochholdinger, F. The Gibberellic Acid Stimulated-Like Gene Family in Maize and Its Role in Lateral Root Development. Plant Physiol. 2010, 152, 356–365. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Nahirñak, V.; Rivarola, M.; De Urreta, M.G.; Paniego, N.; Hopp, H.E.; Almasia, N.I.; Vazquez-Rovere, C. Genome-wide Analysis of the Snakin/GASA Gene Family in Solanum tuberosum cv. Kennebec. Am. Potato J. 2016, 93, 172–188. [Google Scholar] [CrossRef]
  13. Cheng, X.; Wang, S.; Xu, D.; Liu, X.; Li, X.; Xiao, W.; Cao, J.; Jiang, H.; Min, X.; Wang, J.; et al. Identification and Analysis of the GASR Gene Family in Common Wheat (Triticum aestivum L.) and Characterization of TaGASR34, a Gene Associated With Seed Dormancy and Germination. Front. Genet. 2019, 10, 980. [Google Scholar] [CrossRef] [PubMed]
  14. Rezaee, S.; Ahmadizadeh, M.; Heidari, P. Genome-wide characterization, expression profiling, and post-transcriptional study of GASA gene family. Gene Rep. 2020, 20, 100795. [Google Scholar] [CrossRef]
  15. Ahmad, B.; Yao, J.; Zhang, S.; Li, X.; Zhang, X.; Yadav, V.; Wang, X. Genome-Wide Characterization and Expression Profiling of GASA Genes during Different Stages of Seed Development in Grapevine (Vitis vinifera L.) Predict Their Involvement in Seed Development. Int. J. Mol. Sci. 2020, 21, 1088. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Han, S.; Jiao, Z.; Niu, M.-X.; Yu, X.; Huang, M.; Liu, C.; Wang, H.-L.; Zhou, Y.; Mao, W.; Wang, X.; et al. Genome-Wide Comprehensive Analysis of the GASA Gene Family in Populus. Int. J. Mol. Sci. 2021, 22, 12336. [Google Scholar] [CrossRef] [PubMed]
  17. Rubinovich, L.; Ruthstein, S.; Weiss, D. The Arabidopsis Cysteine-Rich GASA5 Is a Redox-Active Metalloprotein that Suppresses Gibberellin Responses. Mol. Plant 2014, 7, 244–247. [Google Scholar] [CrossRef] [Green Version]
  18. Rubinovich, L.; Weiss, D. The Arabidopsis cysteine-rich protein GASA4 promotes GA responses and exhibits redox activity in bacteria and in planta. Plant J. 2010, 64, 1018–1027. [Google Scholar] [CrossRef]
  19. Dong, L.; Wang, F.; Liu, T.; Dong, Z.; Li, A.; Jing, R.; Mao, L.; Li, Y.; Liu, X.; Zhang, K.; et al. Natural variation of TaGASR7-A1 affects grain length in common wheat under multiple cultivation conditions. Mol. Breed. 2014, 34, 937–947. [Google Scholar] [CrossRef]
  20. Wigoda, N.; Ben-Nissan, G.; Granot, D.; Schwartz, A.; Weiss, D. The gibberellin-induced, cysteine-rich protein GIP2 from Petunia hybrida exhibits in planta antioxidant activity. Plant J. 2006, 48, 796–805. [Google Scholar] [CrossRef]
  21. Zhang, S.; Yang, C.; Peng, J.; Sun, S.; Wang, X. GASA5, a regulator of flowering time and stem growth in Arabidopsis thaliana. Plant Mol. Biol. 2009, 69, 745–759. [Google Scholar] [CrossRef] [PubMed]
  22. Sun, S.; Wang, H.; Yu, H.; Zhong, C.; Zhang, X.; Peng, J.; Wang, X. GASA14 regulates leaf expansion and abiotic stress resistance by modulating reactive oxygen species accumulation. J. Exp. Bot. 2013, 64, 1637–1647. [Google Scholar] [CrossRef] [Green Version]
  23. De La Fuente, J.I.; Amaya, I.; Castillejo, C.; Sevilla, J.F.S.; Quesada, M.A.; Botella, M.; Valpuesta, V. The strawberry gene FaGAST affects plant growth through inhibition of cell elongation. J. Exp. Bot. 2006, 57, 2401–2411. [Google Scholar] [CrossRef]
  24. Moyano-Cañete, E.; Bellido, M.L.; García-Caparrós, N.; Medina-Puche, L.; Amil-Ruiz, F.; González-Reyes, J.A.; Caballero, J.L.; Muñoz-Blanco, J.; Portales, R.B. FaGAST2, a Strawberry Ripening-Related Gene, Acts Together with FaGAST1 to Determine Cell Size of the Fruit Receptacle. Plant Cell Physiol. 2012, 54, 218–236. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Ko, C.-B.; Woo, Y.-M.; Lee, D.J.; Lee, M.-C.; Kim, C.S. Enhanced tolerance to heat stress in transgenic plants expressing the GASA4 gene. Plant Physiol. Biochem. 2007, 45, 722–728. [Google Scholar] [CrossRef] [PubMed]
  26. Zhang, S.; Wang, X. Overexpression of GASA5 increases the sensitivity of Arabidopsis to heat stress. J. Plant Physiol. 2011, 168, 2093–2101. [Google Scholar] [CrossRef]
  27. Hou, D.; Bai, Q.; Li, J.; Xie, L.; Li, X.; Cheng, Z.; Gao, J. The Gibberellic Acid-Stimulated Transcript Gene Family in Moso Bamboo: A Genome-Wide Survey and Expression Profiling During Development and Abiotic Stresses. J. Plant Growth Regul. 2018, 37, 1135–1147. [Google Scholar] [CrossRef]
  28. Alonso-Ramírez, A.; Rodríguez, D.; Reyes, D.; Jiménez, J.A.; Nicolás, G.; López-Climent, M.; Gómez-Cadenas, A.; Nicolas, C. Evidence for a Role of Gibberellins in Salicylic Acid-Modulated Early Plant Responses to Abiotic Stress in Arabidopsis Seeds. Plant Physiol. 2009, 150, 1335–1344. [Google Scholar] [CrossRef] [Green Version]
  29. Segura, A.; Moreno, M.; Madueño, F.; Molina, A.; García-Olmedo, F. Snakin-1, a Peptide from Potato That Is Active Against Plant Pathogens. Mol. Plant-Microbe Interact. 1999, 12, 16–23. [Google Scholar] [CrossRef] [Green Version]
  30. Berrocal-Lobo, M.; Segura, A.; Moreno, M.; López, G.; García-Olmedo, F.; Molina, A. Snakin-2, an Antimicrobial Peptide from Potato Whose Gene Is Locally Induced by Wounding and Responds to Pathogen Infection. Plant Physiol. 2002, 128, 951–961. [Google Scholar] [CrossRef] [Green Version]
  31. Faraji, S.; Mehmood, F.; Malik, H.; Ahmed, I.; Heidari, P.; Poczai, P. The GASA Gene Family in Cacao (Theobroma cacao, Malvaceae): Genome Wide Identification and Expression Analysis. Agronomy 2021, 11, 1425. [Google Scholar] [CrossRef]
  32. Ma, L.; Wang, Q.; Zheng, Y.; Guo, J.; Yuan, S.; Fu, A.; Bai, C.; Zhao, X.; Zheng, S.; Wen, C.; et al. Cucurbitaceae genome evolution, gene function, and molecular breeding. Hortic. Res. 2022, 9, uhab057. [Google Scholar] [CrossRef] [PubMed]
  33. Ma, L.; Wang, Q.; Mu, J.; Fu, A.; Wen, C.; Zhao, X.; Gao, L.; Li, J.; Shi, K.; Wang, Y.; et al. The genome and transcriptome analysis of snake gourd provide insights into its evolution and fruit development and ripening. Hortic. Res. 2020, 7, 199. [Google Scholar] [CrossRef] [PubMed]
  34. Sui, X.; Nie, J.; Li, X.; Scanlon, M.J.; Zhang, C.; Zheng, Y.; Ma, S.; Shan, N.; Fei, Z.; Turgeon, R. Transcriptomic and functional analysis of cucumber (Cucumis sativus L.) fruit phloem during early development. Plant J. 2018, 96, 982–996. [Google Scholar] [CrossRef] [Green Version]
  35. Bhowmick, B.; Jha, S. Dynamics of sex expression and chromosome diversity in Cucurbitaceae: A story in the making. J. Genet. 2015, 94, 793–808. [Google Scholar] [CrossRef]
  36. Huang, S.; Li, R.; Zhang, Z.; Li, L.; Gu, X.; Fan, W.; Lucas, W.J.; Wang, X.; Xie, B.; Ni, P.; et al. The genome of the cucumber, Cucumis sativus L. Nat. Genet. 2009, 41, 1275–1281. [Google Scholar] [CrossRef] [Green Version]
  37. Li, Q.; Li, H.; Huang, W.; Xu, Y.; Zhou, Q.; Wang, S.; Ruan, J.; Huang, S.; Zhang, Z. A chromosome-scale genome assembly of cucumber (Cucumis sativus L.). GigaScience 2019, 8, giz072. [Google Scholar] [CrossRef] [Green Version]
  38. Garcia-Mas, J.; Benjak, A.; Sanseverino, W.; Bourgeois, M.; Mir, G.; González, V.M.; Hénaff, E.; Câmara, F.; Cozzuto, L.; Lowy, E. The genome of melon (Cucumis melo L.). Proc. Natl. Acad. Sci. USA 2012, 109, 11872–11877. [Google Scholar] [CrossRef] [Green Version]
  39. Guo, S.; Zhang, J.; Sun, H.; Salse, J.; Lucas, W.J.; Zhang, H.; Zheng, Y.; Mao, L.; Ren, Y.; Wang, Z.; et al. The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions. Nat. Genet. 2013, 45, 51–58. [Google Scholar] [CrossRef] [Green Version]
  40. Sun, H.; Wu, S.; Zhang, G.; Jiao, C.; Guo, S.; Ren, Y.; Zhang, J.; Zhang, H.; Gong, G.; Jia, Z.; et al. Karyotype Stability and Unbiased Fractionation in the Paleo-Allotetraploid Cucurbita Genomes. Mol. Plant 2017, 10, 1293–1306. [Google Scholar] [CrossRef] [Green Version]
  41. Xie, D.; Xu, Y.; Wang, J.; Liu, W.; Zhou, Q.; Luo, S.; Huang, W.; He, X.; Li, Q.; Peng, Q.; et al. The wax gourd genomes offer insights into the genetic diversity and ancestral cucurbit karyotype. Nat. Commun. 2019, 10, 5185. [Google Scholar] [CrossRef] [PubMed]
  42. Wu, S.; Shamimuzzaman, M.D.; Sun, H.; Salse, J.; Sui, X.; Wilder, A.; Wu, Z.; Levi, A.; Xu, Y.; Ling, K.; et al. The bottle gourd genome provides insights into Cucurbitaceae evolution and facilitates mapping of a Papaya ring-spot virus resistance locus. Plant J. 2017, 92, 963–975. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Pootakham, W.; Sonthirod, C.; Naktang, C.; Nawae, W.; Yoocha, T.; Kongkachana, W.; Sangsrakru, D.; Jomchai, N.; U-Thoomporn, S.; Sheedy, J.R.; et al. De novo assemblies of Luffa acutangula and Luffa cylindrica genomes reveal an expansion associated with substantial accumulation of transposable elements. Mol. Ecol. Resour. 2021, 21, 212–225. [Google Scholar] [CrossRef]
  44. Urasaki, N.; Takagi, H.; Natsume, S.; Uemura, A.; Taniai, N.; Miyagi, N.; Fukushima, M.; Suzuki, S.; Tarora, K.; Tamaki, M.; et al. Draft genome sequence of bitter gourd (Momordica charantia), a vegetable and medicinal plant in tropical and subtropical regions. DNA Res. 2017, 24, 51–58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Fu, A.; Wang, Q.; Mu, J.; Ma, L.; Wen, C.; Zhao, X.; Gao, L.; Li, J.; Shi, K.; Wang, Y.; et al. Combined genomic, transcriptomic, and metabolomic analyses provide insights into chayote (Sechium edule) evolution and fruit development. Hortic. Res. 2021, 8, 35. [Google Scholar] [CrossRef] [PubMed]
  46. Ling, J.; Jiang, W.; Zhang, Y.; Yu, H.; Mao, Z.; Gu, X.; Huang, S.; Xie, B. Genome-wide analysis of WRKY gene family in Cucumis sativus. BMC Genom. 2011, 12, 471. [Google Scholar] [CrossRef] [Green Version]
  47. Yang, X.; Li, H.; Yang, Y.; Wang, Y.; Mo, Y.; Zhang, R.; Zhang, Y.; Ma, J.; Wei, C.; Zhang, X. Identification and expression analyses of WRKY genes reveal their involvement in growth and abiotic stress response in watermelon (Citrullus lanatus). PLoS ONE 2018, 13, e0191308. [Google Scholar] [CrossRef]
  48. Bankaji, I.; Sleimi, N.; Vives-Peris, V.; Gómez-Cadenas, A.; Pérez-Clemente, R.M. Identification and expression of the Cucurbita WRKY transcription factors in response to water deficit and salt stress. Sci. Hortic. 2022, 256, 108562. [Google Scholar] [CrossRef]
  49. Chen, Y.; Jing, X.; Wang, S.; Wang, J.; Zhang, S.; Shi, Q. Genome-wide Analysis of WRKY Transcription Factor Family in Melon (Cucumis melo L.) and Their Response to Powdery Mildew. Plant Mol. Biol. Rep. 2021, 39, 686–699. [Google Scholar] [CrossRef]
  50. Hu, L.F.; Liu, S.Q. Genome-wide analysis of the MADS-box gene family in cucumber. Genome 2012, 55, 245–256. [Google Scholar] [CrossRef]
  51. Wang, P.; Wang, S.; Chen, Y.; Xu, X.; Guang, X.; Zhang, Y. Genome-wide Analysis of the MADS-Box Gene Family in Watermelon. Comput. Biol. Chem. 2019, 80, 341–350. [Google Scholar] [CrossRef] [PubMed]
  52. Hao, X.; Fu, Y.; Zhao, W.; Liu, L.; Bade, R.; Hasi, A.; Hao, J. Genome-wide Identification and Analysis of the MADS-box Gene Family in Melon. J. Am. Soc. Hortic. Sci. 2016, 141, 507–519. [Google Scholar] [CrossRef] [Green Version]
  53. Wan, H.; Yuan, W.; Bo, K.; Shen, J.; Pang, X.; Chen, J. Genome-wide analysis of NBS-encoding disease resistance genes in Cucumis sativus and phylogenetic study of NBS-encoding genes in Cucurbitaceae crops. BMC Genom. 2013, 14, 109. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Hassan, Z.; Rahim, A.; Jung, H.-J.; Park, J.-I.; Kim, H.-T.; Nou, I.-S. Genome-Wide Characterization of NBS-Encoding Genes in Watermelon and Their Potential Association with Gummy Stem Blight Resistance. Int. J. Mol. Sci. 2019, 20, 902. [Google Scholar] [CrossRef] [Green Version]
  55. Zhang, W.; Yuan, Q.; Wu, Y.; Zhang, J.; Nie, J. Genome-Wide Identification and Characterization of the CC-NBS-LRR Gene Family in Cucumber (Cucumis sativus L.). Int. J. Mol. Sci. 2022, 23, 5048. [Google Scholar] [CrossRef]
  56. Baloglu, M.C.; Eldem, V.; Hajyzadeh, M.; Unver, T. Genome-Wide Analysis of the bZIP Transcription Factors in Cucumber. PLoS ONE 2014, 9, e96014. [Google Scholar] [CrossRef] [Green Version]
  57. Unel, N.M.; Cetin, F.; Karaca, Y.; Altunoglu, Y.C.; Baloglu, M.C. Comparative identification, characterization, and expression analysis of bZIP gene family members in watermelon and melon genomes. Plant Growth Regul. 2019, 87, 227–243. [Google Scholar] [CrossRef]
  58. 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]
  59. Chen, C.J.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.H.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef]
  60. Yu, C.S.; Lin, C.J.; Hwang, J.K. Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci. 2004, 13, 1402–1406. [Google Scholar] [CrossRef] [Green Version]
  61. Bailey, T.L.; Williams, N.; Misleh, C.; Li, W.W. MEME: Discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 2006, 34, W369–W373. [Google Scholar] [CrossRef]
  62. Lescot, M.; Déhais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouzé, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef] [PubMed]
  63. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef]
  64. Wang, Y.; Tang, H.; DeBarry, J.D.; Tan, X.; Li, J.; Wang, X.; Lee, T.-H.; Jin, H.; Marler, B.; Guo, H.; et al. MCScanX: A toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012, 40, e49. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Krzywinski, M.; Schein, J.; Birol, I.; Connors, J.; Gascoyne, R.; Horsman, D.; Jones, S.J.; Marra, M.A. Circos: An information aesthetic for comparative genomics. Genome Res. 2009, 19, 1639–1645. [Google Scholar] [CrossRef] [Green Version]
  66. Brown, J.W.; Pirrung, M.; McCue, L.A. FQC Dashboard: Integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics 2017, 33, 3137–3139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  68. Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R.; 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25, 2078–2079. [Google Scholar] [CrossRef] [Green Version]
  69. Pertea, M.; Pertea, G.M.; Antonescu, C.M.; Chang, T.-C.; Mendell, J.T.; Salzberg, S.L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015, 33, 290–295. [Google Scholar] [CrossRef] [Green Version]
  70. Varet, H.; Brillet-Guéguen, L.; Coppée, J.-Y.; Dillies, M.-A. SARTools: A DESeq2- and EdgeR-based R pipeline for comprehensive differential analysis of RNA-Seq data. PLoS ONE 2016, 11, e0157022. [Google Scholar] [CrossRef] [Green Version]
  71. Li, Z.; Zhang, Z.; Yan, P.; Huang, S.; Fei, Z.; Lin, K. RNA-Seq improves annotation of protein-coding genes in the cucumber genome. BMC Genom. 2011, 12, 540. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Zhang, Y.; Zhao, G.; Li, Y.; Mo, N.; Zhang, J.; Liang, Y. Transcriptomic Analysis Implies That GA Regulates Sex Expression via Ethylene-Dependent and Ethylene-Independent Pathways in Cucumber (Cucumis sativus L.). Front. Plant Sci. 2017, 8, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Chen, C.; Chen, X.; Han, J.; Lu, W.; Ren, Z. Genome-wide analysis of the WRKY gene family in the cucumber genome and transcriptome-wide identification of WRKY transcription factors that respond to biotic and abiotic stresses. BMC Plant Biol. 2020, 20, 443. [Google Scholar] [CrossRef] [PubMed]
  74. Zhu, Y.; Yin, J.; Liang, Y.; Liu, J.; Jia, J.; Huo, H.; Wu, Z.; Yang, R.; Gong, H. Transcriptomic dynamics provide an insight into the mechanism for silicon-mediated alleviation of salt stress in cucumber plants. Ecotoxicol. Environ. Saf. 2019, 174, 245–254. [Google Scholar] [CrossRef] [PubMed]
  75. Burkhardt, A.; Day, B. Transcriptome and Small RNAome Dynamics during a Resistant and Susceptible Interaction between Cucumber and Downy Mildew. Plant Genome 2016, 9, 69. [Google Scholar] [CrossRef] [Green Version]
  76. Xu, Q.; Xu, X.; Shi, Y.; Qi, X.; Chen, X. Elucidation of the molecular responses of a cucumber segment substitution line carrying Pm5.1 and its recurrent parent triggered by powdery mildew by comparative transcriptome profiling. BMC Genom. 2017, 18, 21. [Google Scholar] [CrossRef] [Green Version]
  77. Wang, X.; Cheng, C.; Zhang, K.; Tian, Z.; Xu, J.; Yang, S.; Lou, Q.; Li, J.; Chen, J.-F. Comparative transcriptomics reveals suppressed expression of genes related to auxin and the cell cycle contributes to the resistance of cucumber against Meloidogyne incognita. BMC Genom. 2018, 19, 583. [Google Scholar] [CrossRef]
  78. Sun, Y.; Shang, L.; Zhu, Q.-H.; Fan, L.; Guo, L. Twenty years of plant genome sequencing: Achievements and challenges. Trends Plant Sci. 2021, 27, 391–401. [Google Scholar] [CrossRef]
  79. Wu, K.; Qu, Y.; Rong, H.; Han, X.; Tian, Y.; Xu, L. Identification and Expression Analysis of the Populus trichocarpa GASA-Gene Family. Int. J. Mol. Sci. 2022, 23, 1507. [Google Scholar] [CrossRef]
  80. Muhammad, I.; Li, W.-Q.; Jing, X.-Q.; Zhou, M.-R.; Shalmani, A.; Ali, M.; Wei, X.-Y.; Sharif, R.; Liu, W.-T.; Chen, K.-M. A systematic in silico prediction of gibberellic acid stimulated GASA family members: A novel small peptide contributes to floral architecture and transcriptomic changes induced by external stimuli in rice. J. Plant Physiol. 2019, 234–235, 117–132. [Google Scholar] [CrossRef]
  81. Zhang, S.; Chen, C.; Li, L.; Meng, L.; Singh, J.; Jiang, N.; Deng, X.-W.; He, Z.-H.; Lemaux, P.G. Evolutionary Expansion, Gene Structure, and Expression of the Rice Wall-Associated Kinase Gene Family. Plant Physiol. 2005, 139, 1107–1124. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Jain, M.; Tyagi, A.K.; Khurana, J.P. Genome-wide analysis, evolutionary expansion, and expression of early auxin-responsive SAUR gene family in rice (Oryza sativa). Genomics 2006, 88, 360–371. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Qin, Z.; Yu, S.; Liu, D.; Xin, M.; Zhou, X. Cloning and bioinformatics analysis of CsGASA4 gene in cucumber. J. Northeast. Agric. Univ. 2018, 49, 19–26. [Google Scholar]
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Figure 1. The phylogenetic tree of GASA proteins from Arabidopsis and 10 Cucurbitaceae species.
Figure 1. The phylogenetic tree of GASA proteins from Arabidopsis and 10 Cucurbitaceae species.
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Figure 2. Exon-intron structures of GASA genes and a schematic diagram of the amino acid motifs of GASA proteins in 10 Cucurbitaceae species.
Figure 2. Exon-intron structures of GASA genes and a schematic diagram of the amino acid motifs of GASA proteins in 10 Cucurbitaceae species.
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Figure 3. Syntenic relationships of GASA gene family in cucumber, Arabidopsis and rice.
Figure 3. Syntenic relationships of GASA gene family in cucumber, Arabidopsis and rice.
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Figure 4. Cis-elements analysis of the promoters of cucumber GASA family genes. (A) The types and numbers of various cis-elements in the promoters of each cucumber GASA gene. (B) The relative proportions of different types of cis-elements in the promoters of cucumber GASA genes are displayed by doughnut chart.
Figure 4. Cis-elements analysis of the promoters of cucumber GASA family genes. (A) The types and numbers of various cis-elements in the promoters of each cucumber GASA gene. (B) The relative proportions of different types of cis-elements in the promoters of cucumber GASA genes are displayed by doughnut chart.
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Figure 5. Expression heatmap of cucumber GASA gene family in different tissues. The data in the boxes indicate the original FPKM values.
Figure 5. Expression heatmap of cucumber GASA gene family in different tissues. The data in the boxes indicate the original FPKM values.
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Figure 6. Expression heatmap of cucumber GASA family genes under GA treatment. CT: control treatment; GA_6 h: GA treatment for 6 h; GA_12 h: GA treatment for 12 h. The data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
Figure 6. Expression heatmap of cucumber GASA family genes under GA treatment. CT: control treatment; GA_6 h: GA treatment for 6 h; GA_12 h: GA treatment for 12 h. The data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
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Figure 7. Expression heatmaps of cucumber GASA family genes under abiotic stresses. (A) Expression patterns of cucumber GASA family genes under high temperature stress. (B) Expression patterns of cucumber GASA family genes under low temperature stress. (C) Expression patterns of cucumber GASA family genes under salt and silicon stresses. CT: control treatment; HT_3 h: high temperature treatment for 3 h; HT_6 h: high temperature treatment for 6 h; CS_2 h: low temperature treatment for 2 h; CS_6 h: low temperature treatment for 6 h; CS_12 h: low temperature treatment for 12 h; NaCl: salt stress treatment. Silicon: silicon stress treatment. In each figure, the data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
Figure 7. Expression heatmaps of cucumber GASA family genes under abiotic stresses. (A) Expression patterns of cucumber GASA family genes under high temperature stress. (B) Expression patterns of cucumber GASA family genes under low temperature stress. (C) Expression patterns of cucumber GASA family genes under salt and silicon stresses. CT: control treatment; HT_3 h: high temperature treatment for 3 h; HT_6 h: high temperature treatment for 6 h; CS_2 h: low temperature treatment for 2 h; CS_6 h: low temperature treatment for 6 h; CS_12 h: low temperature treatment for 12 h; NaCl: salt stress treatment. Silicon: silicon stress treatment. In each figure, the data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
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Figure 8. Expression heatmaps of cucumber GASA family genes under biotic stresses. (A) Expression patterns of cucumber GASA family genes under downy mildew stress. (B) Expression patterns of cucumber GASA family genes under powdery mildew stress. (C) Expression patterns of cucumber GASA family genes under root-knot nematode stress. S: susceptible plants; R: resistant plants; 1 dpi, 2 dpi, 3 dpi, 4 dpi and 6 dpi are 1, 2, 3, 4 and 6 days post inoculation, respectively; CT: control; 48 hpi: 48 h post inoculation. In each figure, the data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
Figure 8. Expression heatmaps of cucumber GASA family genes under biotic stresses. (A) Expression patterns of cucumber GASA family genes under downy mildew stress. (B) Expression patterns of cucumber GASA family genes under powdery mildew stress. (C) Expression patterns of cucumber GASA family genes under root-knot nematode stress. S: susceptible plants; R: resistant plants; 1 dpi, 2 dpi, 3 dpi, 4 dpi and 6 dpi are 1, 2, 3, 4 and 6 days post inoculation, respectively; CT: control; 48 hpi: 48 h post inoculation. In each figure, the data in the left boxes indicate the original FPKM values. The data in the right boxes are log2(fold-change) values highlighted by red (up-regulation) and green (down-regulation) colors.
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Figure 9. Expression patterns heatmap of cucumber GASA family genes under abiotic and biotic stresses. GA: gibberellin treatment; HT: high temperature stress; CS: low temperature stress; NaCl: salt stress; Silicon: silicon stress; DM: downy mildew stress; PM: powdery mildew stress; RKN: root-knot nematode stress. Gray color represents expression level that was not changed, red color represents up-regulated expression, green color represents down-regulated expression.
Figure 9. Expression patterns heatmap of cucumber GASA family genes under abiotic and biotic stresses. GA: gibberellin treatment; HT: high temperature stress; CS: low temperature stress; NaCl: salt stress; Silicon: silicon stress; DM: downy mildew stress; PM: powdery mildew stress; RKN: root-knot nematode stress. Gray color represents expression level that was not changed, red color represents up-regulated expression, green color represents down-regulated expression.
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Table
Table 1. The physiochemical characteristics of GASA family genes in 10 Cucurbitaceae species.
Table 1. The physiochemical characteristics of GASA family genes in 10 Cucurbitaceae species.
SpeciesGene IDChromosome LocationNumber of Amino Acid (aa)Molecular Weight (kDa)Theoretical pIInstability IndexAliphatic IndexGrand Average of HydropathicitySubcellular Location
Wax gourd (Benincasa
hispida)		Bhi03M000750Chr3: 19,311,494 .. 19,311,920 (−)808.779.0439.5882.88−0.021Extracellular
Bhi04M000133Chr4: 3,757,574 .. 3,758,363 (+)9710.339.2153.7968.450.073Extracellular
Bhi04M000374Chr4: 10,323,755 .. 10,323,929 (−)576.159.3332.8122.28−0.749Nuclear
Bhi08M001209Chr8: 42,837,600 .. 42,840,156 (+)11512.918.9144.9559.30−0.355Extracellular
Bhi09M001786Chr9: 59,471,263 .. 59,472,200 (+)13915.009.1055.6789.140.310Extracellular
Bhi09M001788Chr9: 59,495,483 .. 59,496,419 (+)10111.017.9943.6465.740.031Extracellular
Bhi11M000974Chr11: 34,037,800 .. 34,038,470 (+)8910.089.4032.3163.480.111Extracellular
Bhi11M001327Chr11: 45,095,365 .. 45,097,267 (−)13314.808.9764.5161.58−0.074Extracellular
Bhi11M002565Chr11: 83,283,688 .. 83,287,470 (−)23224.489.8489.3257.93−0.311Nuclear
Watermelon (Citrullus
lanatus)		Cla97C01G013050.1Chr1: 26,879,226 .. 26,881,027 (−)11412.728.9745.9456.40−0.393Extracellular
Cla97C01G016400.2Chr1: 30,120,921 .. 30,122,856 (−)9910.849.2452.8770.91−0.159Extracellular
Cla97C02G033610.2Chr2: 7,155,664 .. 7,157,420 (+)8810.119.6233.1159.89−0.086Extracellular
Cla97C05G099600.2Chr5: 28,631,501 .. 28,637,708 (+)21623.238.7645.5865.51−0.024Extracellular
Cla97C08G157880.1Chr8: 25,344,837 .. 25,345,286 (+)9710.189.0745.7478.560.187Extracellular
Cla97C10G193530.1Chr10: 21,997,173 .. 21,997,578 (+)8910.089.1537.2753.71−0.054Extracellular
Cla97C10G196435.1Chr10: 26,191,272 .. 26,194,258 (−)14115.559.0766.4545.67−0.453Extracellular
Cla97C10G197380.1Chr10: 27,180,180 .. 27,181,843 (+)21622.789.6889.5754.58−0.385Nuclear
Cla97C11G215390.1Chr11: 11,861,823 .. 11,863,862 (−)10611.789.4650.6371.79−0.183Extracellular
Pumpkin
(Cucurbita moschata)		CmoCh01G020290.1Chr1: 14,246,135 .. 14,247,088 (−)10610.908.6154.8481.040.235Extracellular
CmoCh05G001560.1Chr5: 678,878 .. 679,725 (+)859.189.1932.6874.590.054Extracellular
CmoCh07G006840.1Chr7: 3,085,589 .. 3,086,076 (+)9410.048.9743.3471.60−0.068Extracellular
CmoCh09G000990.1Chr9: 477,271 .. 484,805 (+)51658.175.9954.7485.41−0.103Nuclear
CmoCh11G010460.1Chr11: 5,816,242 .. 5,817,492 (−)10811.899.4536.9350.65−0.201Extracellular
CmoCh11G014010.1Chr11: 9,853,936 .. 9,855,463 (−)889.869.6329.2765.450.036Extracellular
CmoCh12G003610.1Chr12: 2,236,117 .. 2,237,074 (+)9710.169.0853.1175.570.186Extracellular
CmoCh14G006410.1Chr14: 3,223,478 .. 3,225,060 (−)20321.479.8284.4960.00−0.342Nuclear
CmoCh14G011310.1Chr14: 7,958,822 .. 7,959,972 (−)11712.798.8250.2149.23−0.406Extracellular
CmoCh15G000310.1Chr15: 218,843 .. 220,014 (−)10611.909.5964.3271.79−0.166Extracellular
CmoCh18G001170.1Chr18: 823,704 .. 825,231 (+)11512.229.3651.0654.26−0.184Extracellular
Cucumber (Cucumis
sativus)		CsaV3_1G008270.1Chr1: 5,210,806 .. 5,212,803 (+)11513.059.1944.3553.39−0.414Extracellular
CsaV3_2G026300.1Chr2: 18,030,665 .. 18,031,342 (+)859.479.2034.9764.24−0.171Extracellular
CsaV3_2G029490.1Chr2: 19,316,885 .. 19,317,559 (−)616.599.1156.3936.89−0.408Nuclear
CsaV3_3G041480.1Chr3: 33,839,191 .. 33,840,892 (−)10411.469.6434.1254.52−0.183Extracellular
CsaV3_3G042060.1Chr3: 34,217,470 .. 34,219,983 (−)23124.249.7784.0567.06−0.263Nuclear
CsaV3_3G042990.1Chr3: 34,899,642 .. 34,900,907 (+)11712.949.1254.6961.62−0.215Extracellular
CsaV3_3G045860.1Chr3: 37,493,613 .. 37,494,832 (−)10210.598.5760.5976.570.249Extracellular
CsaV3_4G000520.1Chr4: 298,937 .. 299,297 (+)8910.169.4130.9559.10−0.115Extracellular
CsaV3_6G043760.1Chr6: 25,805,953 .. 25,806,385 (−)808.829.1537.5370.62−0.148Extracellular
Sponge gourd (Luffa
cylindrica)		Lcy01g018340.1Chr1: 39,876,992 .. 39,877,586 (−)859.399.2726.8763.06−0.111Extracellular
Lcy04g015090.1Chr4: 47,422,624 .. 47,423,017 (−)9410.088.8746.9075.640.007Extracellular
Lcy06g003590.1Chr6: 3,388,158 .. 3,389,543 (+)11412.748.8854.6855.53−0.361Extracellular
Lcy07g018230.1Chr7: 46,850,291 .. 46,852,453 (−)10911.929.5745.4052.94−0.043Extracellular
Lcy09g000520.1Chr9: 508,156 .. 510,023 (−)10912.199.6150.4368.07−0.186Extracellular
Lcy09g017660.1Chr9: 35,628,176 .. 35,629,130 (−)10611.819.6732.9251.60−0.288Extracellular
Lcy09g018840.1Chr9: 41,976,742 .. 41,978,205 (−)22123.449.7980.5758.19−0.388Nuclear
Lcy12g021390.1Chr12: 48,438,825 .. 48,439,301 (−)10110.808.2940.8782.080.156Extracellular
Lcy12g021440.1Chr12: 48,464,326 .. 48,464,817 (−)10611.428.6544.3079.150.072Extracellular
Bottle gourd (Lagenaria siceraria)Lsi01G009320.1Chr1: 7,534,930 .. 7,535,476 (+)808.829.0437.1775.50−0.077Extracellular
Lsi03G005590.1Chr3: 6,743,934 .. 6,745,226 (−)10011.349.4738.4365.300.034Extracellular
Lsi03G010390.1Chr3: 19,955,854 .. 19,956,253 (+)8910.189.3334.2859.10−0.003Extracellular
Lsi03G014250.1Chr3: 25,218,255 .. 25,221,595 (+)21222.559.4592.3751.42−0.493Nuclear
Lsi04G017450.1Chr4: 24,750,180 .. 24,751,157 (−)11111.868.8148.8272.070.142Extracellular
Lsi08G013250.1Chr8: 21,566,057 .. 21,567,220 (+)14715.879.3651.9882.380.149Extracellular
Lsi08G015100.1Chr8: 23,193,981 .. 23,195,157 (−)14215.468.9823.2766.62−0.246Extracellular
Lsi09G009210.1Chr9: 11,377,348 .. 11,377,967 (+)829.379.5022.4740.37−0.466Extracellular
Bitter gourd (Momordica charantia)MC01g0899.1Chr1: 14,806,676 .. 14,807,137 (−)9510.158.8739.9278.950.022Extracellular
MC02g0120.1Chr2: 1,223,343 .. 1,224,955 (+)10811.648.8951.4651.67−0.060Extracellular
MC03g1060.1Chr3: 16,943,540 .. 16,943,725 (−)626.659.3246.7831.45−0.556Nuclear
MC04g0594.1Chr4: 5,232,091 .. 5,232,267 (−)596.789.8461.7229.83−0.764Nuclear
MC04g1197.1Chr4: 19,993,730 .. 19,993,924 (+)657.309.0026.9124.00−0.606Extracellular
MC04g1983.1Chr4: 26,610,157 .. 26,612,959 (+)10912.189.7567.0771.65−0.229Extracellular
MC04g_new0671.1Chr4: 26,612,371 .. 26,616,386 (−)37041.558.9544.2774.08−0.235Extracellular
MC08g0576.1Chr8: 4,660,922 .. 4,661,179 (+)869.839.0331.6762.33−0.073Extracellular
MC08g0741.1Chr8: 6,030,387 .. 6,030,572 (−)626.498.9843.7244.19−0.285Extracellular
MC08g1334.1Chr8: 12,401,247 .. 12,401,444 (+)667.589.0336.5956.06−0.459Extracellular
MC08g1395.1Chr8: 14,414,051 .. 14,414,239 (+)637.169.1345.2016.98−0.767Nuclear
MC10g0377.1Chr10: 3,011,243 .. 3,011,419 (+)596.619.1834.3824.75−0.781Nuclear
MC11g0104.1Chr11: 764,783 .. 764,971 (+)636.498.8975.9743.49−0.068Extracellular
MC11g0105.1Chr11: 765,959 .. 768,132 (+)15316.958.6554.3685.420.065Extracellular
MC00g0794.1scaffold142: 23,557 .. 24,251 (−)11612.969.1055.4847.07−0.324Extracellular
Melon
(Cucumis melo)		MELO3C018503.2.1Chr1: 721,831 .. 722,928 (−)8810.139.7130.0661.02−0.174Extracellular
MELO3C011008.2.1Chr3: 27,015,343 .. 27,016,361 (+)9710.479.3459.9775.460.080Extracellular
MELO3C010822.2.1Chr3: 28,229,740 .. 28,230,991 (−)859.449.3033.7467.65−0.080Extracellular
MELO3C003753.2.1Chr4: 3,727,349 .. 3,728,176 (+)10010.818.6545.7570.300.079Extracellular
MELO3C026601.2.1Chr4: 25,918,328 .. 25,919,317 (−)11712.959.1252.4057.52−0.302Extracellular
MELO3C009926.2.1Chr4: 26,961,415 .. 26,964,335 (+)22223.649.7293.6355.72−0.386Nuclear
MELO3C009872.2.1Chr4: 27,411,710 .. 27,412,273 (+)808.939.5534.3223.12−0.761Extracellular
MELO3C017982.2.1Chr7: 26,076,528 .. 26,081,332 (−)8910.219.3635.5050.34−0.134Extracellular
MELO3C007600.2.1Chr8: 3,965,613 .. 3,966,256 (−)9410.198.9638.1067.34−0.077Extracellular
MELO3C002243.2.1Chr12: 23,960,061 .. 23,961,357 (−)12614.289.0752.5658.81−0.456Extracellular
Chayote
(Sechium edule)		Sed0003696.1Chr1: 12,188,492 .. 12,189,979 (−)11212.578.8749.7554.02−0.271Extracellular
Sed0004582.1Chr1: 18,633,871 .. 18,636,202 (−)10811.538.7941.9966.020.053Extracellular
Sed0003671.1Chr1: 60,857,945 .. 60,859,823 (−)10911.988.4762.2157.43−0.079Extracellular
Sed0018489.1Chr3: 4,097,163 .. 4,099,736 (+)10912.029.3350.5864.50−0.239Extracellular
Sed0001116.1Chr3: 5,503,219 .. 5,504,432 (−)9510.719.0126.5661.580.155Extracellular
Sed0023008.1Chr4: 35,040,789 .. 35,043,255 (−)11513.119.1755.3261.91−0.248Extracellular
Sed0019149.1Chr6: 5,108,016 .. 5,110,361 (+)22323.499.5789.9470.36−0.114Nuclear
Sed0023122.1Chr6: 5,770,438 .. 5,772,489 (+)10411.489.6131.1457.21−0.129Extracellular
Sed0021074.1Chr8: 27,782,007 .. 27,783,423 (−)10611.919.7843.6554.34−0.238Extracellular
Sed0023101.1Chr10: 25,350,679 .. 25,351,022 (+)869.648.8723.2662.33−0.071Extracellular
Sed0017754.1Chr10: 36,389,392 .. 36,391,330 (−)8810.019.6236.5962.05−0.042Extracellular
Sed0026538.1Chr11: 26,467,504 .. 26,468,286 (−)9810.528.8156.2572.760.095Extracellular
Sed0005060.1Chr12: 7,036,681 .. 7,038,107 (+)11112.469.1671.3957.93−0.377Extracellular
Sed0023421.1Chr13: 20,866,691 .. 20,868,746 (+)10711.168.2449.5679.250.396Extracellular
Sed0020400.1Chr13: 20,881,190 .. 20,882,081 (+)10611.378.4937.9872.74−0.007Extracellular
Sed0017657.1Chr14: 17,756,540 .. 17,757,298 (−)9610.358.9727.9171.98−0.072Extracellular
Snake gourd (Trichosanthes anguina)Tan0003426.1Chr1: 6,253,789 .. 6,254,353 (+)8910.189.4227.9259.100.010Extracellular
Tan0008780.1Chr1: 115,842,003 .. 115,843,341 (−)9610.508.6447.6687.400.329Extracellular
Tan0000180.1Chr1: 115,844,096 .. 115,847,359 (−)10411.068.8649.8872.310.176Extracellular
Tan0005239.1Chr1: 115,863,453 .. 115,866,091 (−)10310.958.9252.4583.400.235Extracellular
Tan0020894.1Chr2: 14,079,327 .. 14,080,681 (−)8910.299.6844.1963.60−0.048Extracellular
Tan0006783.1Chr2: 81,798,300 .. 81,799,073 (+)859.329.2728.2764.24−0.115Extracellular
Tan0018763.1Chr2: 90,173,196 .. 90,174,289 (−)929.879.1940.2763.700.142Extracellular
Tan0011393.1Chr3: 72,374,679 .. 72,375,090 (−)808.739.1732.5574.25−0.138Extracellular
Tan0001400.1Chr5: 70,569,691 .. 70,571,409 (−)11112.508.6062.4957.03−0.353Extracellular
Tan0005034.1Chr6: 74,131,427 .. 74,134,375 (+)11613.009.2949.1456.47−0.337Extracellular
Tan0020433.1Chr7: 12,409,140 .. 12,411,750 (+)11412.989.9055.9643.68−0.402Extracellular
Tan0017829.1Chr7: 48,550,357 .. 48,551,678 (−)10611.709.6125.7050.66−0.282Extracellular
Tan0016087.1Chr7: 61,289,275 .. 61,291,288 (−)23425.139.7580.7954.49−0.357Nuclear
Tan0009191.1Chr10: 27,664,301 .. 27,664,945 (+)10311.458.8769.3641.65−0.545Extracellular
Tan0010233.1Chr11: 862,587 .. 863,083 (+)9510.559.0939.8663.68−0.161Extracellular
Tan0017564.1Chr11: 863,623 .. 865,822 (−)10912.179.4850.3577.80−0.024Extracellular
Tan0010840.1Chr11: 12,544,995 .. 12,546,455 (−)9510.889.3033.2245.26−0.180Extracellular
Tan0013993.1Contig00035: 215,038 .. 215,449 (−)9410.138.8638.1969.36−0.170Extracellular
Table
Table 2. The motif information on GASA proteins in 10 Cucurbitaceae species.
Table 2. The motif information on GASA proteins in 10 Cucurbitaceae species.
MotifSequenceNumber of Amino AcidPfam Annotation
motif 1CMRACGTCCARCKCVPPGTYGNKEVCP27GASA (Significant)
motif 2QPIDCGGACARRCSKASRKKR21GASA (Insignificant)
motif 3CYABMTTH8-
motif 4PPVKPPYT8-
motif 5LLSSLLLLLSFLDSS15-
motif 6GRPKCP6-
motif 7MKYCRICCSKCKCVP15GASA (Insignificant)
motif 8ANGLSQEKDAVYPHVPVPVPA21-
motif 9SGQMVITTQVDNPLP15-
motif 10MVNSIDGVAABPVKI15-
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Zhang, K.; Hu, Y.; Yang, D.; Yan, C.; Li, N.; Li, Z.; Njogu, M.K.; Wang, X.; Jia, L. Genome-Wide Identification of GASA Gene Family in Ten Cucurbitaceae Species and Expression Analysis in Cucumber. Agronomy 2022, 12, 1978. https://doi.org/10.3390/agronomy12081978

AMA Style

Zhang K, Hu Y, Yang D, Yan C, Li N, Li Z, Njogu MK, Wang X, Jia L. Genome-Wide Identification of GASA Gene Family in Ten Cucurbitaceae Species and Expression Analysis in Cucumber. Agronomy. 2022; 12(8):1978. https://doi.org/10.3390/agronomy12081978

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Zhang, Kaijing, Yuchao Hu, Dekun Yang, Congsheng Yan, Nanyang Li, Ziang Li, Martin Kagiki Njogu, Xing Wang, and Li Jia. 2022. "Genome-Wide Identification of GASA Gene Family in Ten Cucurbitaceae Species and Expression Analysis in Cucumber" Agronomy 12, no. 8: 1978. https://doi.org/10.3390/agronomy12081978

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