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. 2026 Apr 28;26:1011. doi: 10.1186/s12870-026-08809-y

Identification and analysis of salt-responsive F-box genes in upland cotton and the potential role of GhFBX83 in salt stress tolerance through regulating ROS homeostasis

Xingyu Liu 1,2,#, Jianguang Liu 1,#, Zhao Geng 1, Guiyuan Zhao 1, Tianyu Feng 1, Yongping Zhou 1, Hanshuang Zhang 1, Pengfei Ai 2,✉, Yongqiang Wang 1,✉
PMCID: PMC13255513  PMID: 42045831

Abstract

Background

The F-box family is among the largest gene families in plants and plays an extremely important role in diverse life processes, including salt responses. Most F-box proteins regulate stress responses through ubiquitin-mediated protein degradation as components of SCF (SKP1-CUL1-F-box) ubiquitin ligase complexes. However, knowledge of cotton F-box (GhFBX) genes and their roles in salt tolerance remains limited. In this study, we performed a comprehensive analysis of the response of GhFBX genes to salt stress in cotton.

Results

160 salt-responsive GhFBX genes, which showed transcriptional expression differences in response to salt, were defined based on transcriptome data analysis, and their conserved domains, phylogenetic relationships, and chromosome locations were characterized. In accordance with the C-terminal conserved domains, the SR GhFBX genes were divided into 10 subfamilies. Phylogenetic analysis revealed that genes with the same C-terminal structural domains were mostly clustered together. The promoter regions of the SR GhFBX genes mainly contain three types of cis-elements, namely, hormone-responsive elements, light-responsive elements, and stress-related elements. To clarify how GhFBX and GhASK proteins interact, we selected 6 SR GhFBX genes and 4 SKP1 genes for interaction analysis using a yeast two-hybrid (Y2H) assay. The results revealed that the SR GhFBX proteins can interact with various GhSKP1-like proteins. In addition, the SR gene GhFBX83 was selected for gene silencing via VIGS. The results revealed that silencing GhFBX83 increased proline (PRO) levels, significantly reduced hydrogen peroxide (H₂O₂) and superoxide anion (O₂⁻) levels, and significantly increased the activities of superoxide dismutase (SOD) and peroxidase (POD) compared to the controls, thereby enhancing salt tolerance. These findings indicate that GhFBX83 acts as a negative regulator in the response to salt stress.

Conclusions

The research identified and analysed 160 salt-responsive (SR) GhFBX genes in Gossypium hirsutum (upland cotton) and GhFBX83 was found to negatively regulate salt tolerance by promoting the accumulation of reactive oxygen species (ROS). This study provides valuable insights into the molecular basis of cotton salt tolerance and lays a foundation for further functional studies on cotton salt resistance breeding.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-026-08809-y.

Keywords: Cotton, F-box gene, Interaction, Salt responses, ROS accumulation

Introduction

During their growth cycles, plants are subjected to diverse abiotic stresses, among which soil salinity poses a critical constraint on crop productivity and global agricultural sustainability [1]. Soil salinization affects approximately 1 billion hectares of land worldwide [2, 3]. Cotton is a globally significant crop known for producing natural fibres, with substantial economic importance [4, 5]. Cotton is extensively cultivated and utilized in the textile industry, representing approximately 35% of the total textile fibre market [6, 7]. Gossypium hirsutum (upland cotton) is an allotetraploid species originating from the hybridization of an A-genome ancestor (Gossypium arboreum) and a D-genome ancestor (Gossypium raimondii) [8]. Its genome comprises two subgenomes, At and Dt, each containing 13 chromosomes [9], with a total genome size of approximately 2.3 Gb [10]. Although cotton is recognized as a pioneer crop in saline soils, its yield and quality significantly decrease when it is exposed to salt stress. Therefore, mining salt-tolerant genes is important for improving cotton salt tolerance and cultivating new cotton varieties.

During long-term evolution, plants have developed various mechanisms to combat environmental stresses, including the regulation of gene expression and modification of proteins. Among them, protein degradation mediated by the ubiquitin–proteasome system (UPS) is an important post-translational modification that regulates a series of cellular processes [11]. The ubiquitin–proteasome pathway involves three sequential enzymatic steps: E1 (ubiquitin-activating enzyme) activates ubiquitin via ATP-dependent adenylation, E2 (ubiquitin-conjugating enzyme) transfers ubiquitin to E3, and E3 (ubiquitin ligase) specifically binds substrate proteins and catalyses ubiquitin transfer to form polyubiquitin chains for proteasomal degradation [12, 13]. On the basis of subunit composition, E3-ubiquitin ligases can be classified into single- and multisubunit classes. Among the multisubunit E3-ubiquitin ligases, the SCF (SKP1-CUL1-F-box) subfamily is the largest and best characterized. This subfamily comprises four components: SKP1, Cullin1, RBX1, and F-box protein [14]. F-box proteins usually contain a conserved F-box motif (~ 40–50 amino acids) at the N-terminus, whereas the C-terminus of F-box proteins contains one variable protein–protein interaction domain, such as a Leu-rich repeat (LRR), Kelch repeat, tetratricopeptide repeat (TPR), or WD40 repeat, which interacts with specific targets. These domains serve to specifically recruit substrate proteins for ubiquitination and subsequent 26 S proteasome degradation.

Previous studies have demonstrated that F-box proteins play pivotal roles in plant adaptation to salt stress by targeting key regulatory proteins for proteasomal degradation. The Arabidopsis F-box protein EST1 reduces salt tolerance by interacting with MKK4 to promote its degradation, thereby suppressing plasma membrane Na⁺/H⁺ antiporter activity, impairing Na⁺ efflux, and increasing cellular Na⁺ accumulation under salt stress [15]. In wheat, TaFBA-2A mediates the ubiquitin-dependent degradation of TaOPR2 to suppress jasmonic acid biosynthesis while improving salt resistance and JA responsiveness in transgenic rice [16]. TaFBA1 enhances Na⁺ efflux through elevated plasma membrane H⁺-ATPase activity and promotes vacuolar Na⁺ sequestration via tonoplast V-ATPase/PPase upregulation in transgenic tobacco, collectively optimizing ion homeostasis and reducing oxidative damage [17]. The expression of the maize F-box protein ZmAFB2 increases salt tolerance in transgenic tobacco by upregulating the transcription of the antioxidant genes ascorbate peroxidase and catalase, thereby improving oxidative stress resistance under high salinity, whereas its expression is modulated by NaCl, salicylic acid, and auxin (IAA) [18]. These findings demonstrate that F-box proteins, which function as core substrate recognition factors within the ubiquitin–proteasome pathway, significantly influence plant developmental responses to salt stress. Elucidating these regulatory mechanisms holds considerable promise for designing crop plants with enhanced adaptive capacity to environmental challenges.

However, F-box proteins constitute a large family, with 592 F-box genes identified by bioinformatics analysis in cotton [19], and only several F-box genes have been found to be involved in the response to salt stress; for example, GhFB15 was reported to modulate the response to salinity by regulating flavonoid biosynthesis [20]. However, the molecular mechanisms of salt stress-responsive F-box proteins in this species remain relatively unknown. In this study, we performed a comprehensive analysis of F-box genes that respond to salt stress in cotton, including phylogenetic analysis, characterization of chromosomal distribution, identification of cis-regulatory elements in gene promoters, examination of tissue-specific expression profiles, and assessment of expression patterns under abiotic stress conditions. Based on phylogenetic classification according to their C-terminal domains, several candidate genes from different subfamilies were selected for qRT‑PCR expression profiling under salt stress. Among these, GhFBX83 exhibited a pronounced down-regulation pattern in response to salt treatment, suggesting its potential role as a negative regulator in salt stress response. Silencing GhFBX83 in cotton was found to enhance salt tolerance by increasing proline content and scavenging reactive oxygen species. This work provides a solid foundation for further investigations into the functions of F-box genes in Gossypium hirsutum (G. hirsutum), particularly in the context of the salt stress response. The insights gained from this research will aid in the development of upland cotton cultivars with improved salt tolerance.

Materials and methods

Identification of salt stress-responsive (SR) GhFBX genes

The reference genome (v3.0) and gene annotation files (v3.1) of G. hirsutum were retrieved from Phytozome [21] (https://phytozome-next.jgi.doe.g.ov/). Total GhFBX genes were identified using hidden Markov model (HMM) profiles of F-box protein domains (PF00646, PF12937, PF13013, PF04300, PF07734, PF07735, PF08268, and PF08387) from the PFAM database [22] (http://pfam.xfam.org/), and these GhFBX genes were screened using HMMER 3.4 software [23]. RNA-seq dataset (PRJNA490626) [24] was downloaded from the NCBI SRA database. This dataset includes transcriptome data from four-week-old cotton seedlings subjected to 0.4 M NaCl treatment, with three biological replicates per treatment. Differentially expressed genes (DEGs) were identified using the DESeq2 package (http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html) with thresholds of |log2 fold change| ≥ 1 and false discovery rate (FDR)-adjusted P < 0.05. Sequences containing complete F-box domains were retained, yielding 160 DEGs. These genes were sequentially renamed according to their chromosomal positions. Molecular weights and isoelectric points (pI) were calculated using the ExPASy Compute pI/Mw tool (https://web.expasy.org/compute_pi/). Subcellular localization was predicted via WoLF PSORT (http://www.genscript.com/psort/wolf_psort.html).

Chromosomal localization and synteny analysis

Chromosomal position information of the SR GhFBX genes was obtained by analysing the gene annotation files of G. hirsutum. The gene IDs were saved as a text file. The chromosomal distribution was subsequently visualized using the “Gene Location Visualize from GTF/GFF” tool in TBtools software. Intra-species collinearity analysis of G. hirsutum duplicated gene pairs was performed using the One Step MCScanX module in TBtools with default parameters.

Motif and conserved domain analysis of the SR GhFBX genes

Conserved domains in the SR GhFBX proteins were analysed via InterPro [25] (https://www.ebi.ac.uk/interpro/). Conserved motifs in the SR GhFBX proteins were identified using the MEME Suite (https://meme-suite.org/meme/) with default parameters and a maximum motif width of 10 residues. Visualization of motif architectures and domain organizations was performed using the iTOL platform (https://itol.embl.de/) [26]. For cis-regulatory element analysis, 2000-bp promoter sequences upstream of the ATG start codon for all 160 SR GhFBX genes were extracted from the G. hirsutum genome. These sequences were submitted to PlantCARE [27] (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/) for cis-element identification, with the results visualized through the iTOL platform (https://itol.embl.de/) [26].

Phylogenetic tree analysis

Multiple sequences of the F-box domains from the 160 SR GhFBX proteins were extracted with the aid of the SeqKit tool (v2.10.0). To investigate the evolutionary relationships among the 160 SR GhFBX proteins, multiple sequences of the F-box domains were aligned using their amino acid sequences and the MUSCLE [28] algorithm in MEGA11 [29] (https://www.megasoftware.net/). The sequence logo was generated using WebLogo [30] (https://weblogo.berkeley.edu/logo.cgi/). A maximum likelihood (ML) phylogenetic tree was constructed with default parameters. The resulting tree was visualized and annotated via the iTOL platform (https://itol.embl.de/) [26] to enable comprehensive evolutionary analysis of the F-box protein clades.

Plant materials and salt treatment at the seedling stage

The cotton Ji 172 inbred line used in this study was provided by the Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences. Plump cotton seeds of uniform size were sown in autoclaved moist sandy soil. Upon cotyledon expansion, the seedlings were transferred to Hoagland nutrient solution and cultivated in a growth chamber under controlled conditions (25°C, 65% relative humidity, 16 h light/8 h dark photoperiod). Following the emergence of the third true leaf, the plants were subjected to salt stress by treatment with 250 mM NaCl solution. Leaf tissues were collected at six time points (0, 1, 3, 6, 12, and 24 h post-treatment), immediately flash-frozen in liquid nitrogen, and stored at −80°C. Three biological replicates were sampled per time point for subsequent analyses.

RNA extraction and qRT–PCR analysis

Total RNA was isolated using the FastPure Universal Plant Total RNA Isolation Kit (RC411-01; Vazyme, Nanjing, China). Reverse transcription was performed with Hiscript III RT SuperMix for qRT–PCR (+ gDNA wiper) (R323-01, Vazyme, Nanjing, China) and quantified by qRT–PCR with ChamQ Universal SYBR Master Mix on a Bio-Rad CFX96 system under thermal cycling conditions: 95°C for 3 min and 40 cycles of 95°C for 30 s and 58°C for 30 s. Histone was used as the reference gene. Relative mRNA expression levels were calculated using the 2−ΔΔCt method. The real-time qRT–PCR primer sequences are provided in Table S1. All reactions were performed in triplicate.

Virus-Induced gene silencing assays

Ten-day-old cotton seedlings were infiltrated with tobacco rattle virus (TRV)-based VIGS vectors containing either target genes (pTRV2-GhFBX) or an empty vector control (TRV2:00). Agrobacterium tumefaciens strain GV3101 harbouring GhFBX-TRV2 and TRV1 constructs was cultured in Luria–Bertani (LB) broth supplemented with appropriate antibiotics at 28°C. The bacterial suspensions were adjusted to an OD600 of 1.0 in infiltration buffer (10 mM MgCl2, 10 mM MES at a pH of 5.6, 150 µM acetosyringone) and incubated at room temperature for 2–3 h. Equal volumes (1:1 ratio) of TRV1 and TRV2-GhFBX cultures were mixed and infiltrated into fully expanded cotyledons using needleless syringes. The infiltrated plants were monitored for 10 days. The experiment included 20 biological replicates (one plant per replicate) and was repeated three times with consistent results. When the newborn true leaves presented an albino phenotype, VIGS-GhFBX83 and TRV2:00 leaves were collected to test the silencing efficiency. VIGS-GhFBX83 and TRV2:00 plants were treated with 400 mM NaCl, and 0.1 g of leaves was removed after obvious phenotypic changes and stored at −80 °C after flash freezing in liquid nitrogen as a backup. The phenotypes were observed and photographed after 6 days of salt stress.

Measurements of biochemical indices

To quantify the levels of oxidative stress markers and osmolytes, we measured the levels of superoxide anion (O₂⁻), hydrogen peroxide (H₂O₂), malondialdehyde (MDA), and proline (PRO), as well as the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). Specifically, O₂⁻ was detected using a 0.1% NBT solution(SL18061, Coolaber Biotech, Beijing, China), H₂O₂ was assessed with a DAB colour development kit(SK2020,Coolaber Biotech, Beijing, China), and the contents of H₂O₂, O₂⁻, MDA, and PRO, as well as the activities of POD, SOD, and CAT, were quantified using their corresponding assay kits (G0168W, G0116W, G0109W, G0111W, G0107W, G0101W, and G0105W, respectively) from Suzhou Grace Biotechnology. All data presented in this study were collected from more than three independent replicates and were statistically analyzed by Student´s t-test. Standard deviations were calculated for the means and significant differences determined at the significance levels of P < 0.05(*) and P < 0.01(**).

Yeast two-hybrid assay

Y2H analysis was performed to examine interactions between F-box proteins and SKP1 proteins. The coding sequences (CDSs) of GhFBX14, GhFBX50, GhFBX55, GhFBX83, GhFBX127 and GhFBX129 were subsequently cloned and inserted into pGBKT7 bait vectors. Four GhSKP1-like CDSs were subsequently cloned and inserted into pGADT7 prey vectors. Each of the 6 pGBKT7 recombinant constructs was pairwise cotransformed with individual pGADT7-GhSKP1-like constructs into Y2HGold competent yeast cells alongside salmon sperm DNA. Transformed cells were plated on SD/-Leu/-Trp medium and incubated at 30 °C for 2 days. Single colonies were serially diluted and spotted onto SD/-Leu/-Trp/-His/-Ade/X-α-gal quadruple dropout medium. Protein–protein interactions were confirmed by yeast growth after 3–5 days of incubation at 30°C.

Results

SR GhFBX gene identification, genomic distribution and physicochemical property analysis

To identify potential SR GhFBX gene members in cotton, we first used an HMM profile to scan the cotton genome and identified a total of 644 GhFBX genes. Differential expression analysis was subsequently conducted using RNA sequencing data from the RNA-seq dataset (PRJNA490626), which was derived from leaf samples subjected to salt stress. We identified 160 SR GhFBX genes that were differentially expressed following salt stress, and these genes were subsequently renamed GhFBX1–GhFBX160 according to their chromosomal locations (Table S2). Chromosomal location analysis revealed that the expression of the SR GhFBX genes was unevenly distributed across all chromosomes, with the highest numbers found on chromosomes A05 and D05, whereas none were detected on chromosome A04. In addition, the majority of the SR GhFBX genes were located near the ends of the chromosome (Fig. 1).

Fig. 1.

Fig. 1

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Chromosomal distribution of the SR GhFBX genes in G. hirsutum

Among these SR GhFBX genes, the full lengths of the proteins significantly changed, ranging from 86 to 1345 amino acid residues, with molecular weights (MWs) ranging between 9.74 and 151.10 kDa. However, 96.9% of the SR GhFBX protein lengths ranged from 100 to 700 amino acid residues. The theoretical isoelectric points (pIs) ranged from 4.28 to 10.96 and included 72 alkaline proteins (pI > 7.5), 74 acidic proteins (pI < 6.5) and 14 neutral proteins (pI 6.5–7.5). According to the grand average of hydropathicity (GRAVY) analysis, the majority of the SR GhFBX genes were hydrophobic proteins. Subcellular localization predictions indicated that the SR GhFBX proteins were localized mainly to the nucleus and cytoplasm (Table S2), and these results indicated that different SR GhFBX proteins may play diverse roles in the response to salt stress.

Collinearity analysis of the SR GhFBX genes in G. hirsutum

To reveal the homologous relationships of the SR GhFBX family members in Gossypium hirsutum, gene duplication events of intra-species chromosomal collinearity analysis were analyzed via One Step MCScanX module in TBtools. Genome-wide collinearity analysis of the SR GhFBX genes was performed across the GhAt-GhAt, GhDt-GhDt, and GhAt-GhDt subgenome comparisons. A total of 250 orthologous or paralogous gene pairs were identified, all of which originated from whole-genome duplication or segmental duplication events (Fig. 2; Table S3). Among these gene pairs, there were 39, 38, 173 linear gene pairs that replicated in GhAt-GhAt, GhDt-GhDt, GhAt-GhDt respectively. However, only 62 of these pairs consisted of two genes that were both among the SR GhFBX genes (Table S3) It suggested that some homologous SR GhFBX genes may functionally diverge from each other during the evolutionary process.

Fig. 2.

Fig. 2

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Chromosome collinearity analysis of cotton SR GhFBX genes. A Intragenomic collinearity of SR GhFBX genes within the At subgenome., with green lines representing syntenic relationships between genes. B Intragenomic collinearity of SR GhFBX genes within the Dt subgenome, with blue lines representing syntenic relationships between genes. C Inter-subgenomic collinearity of SR GhFBX genes between the At and Dt subgenomes, with orange-red lines illustrating syntenic relationships across the two subgenomes

Analysis of amino acid residues and conserved domains of SR GhFBX proteins in cotton

F-box proteins usually contain an approximately 40–60 amino acid motif at the N-terminus. To explore the conserved sites of the SR GhFBX domain, we aligned the F-box conserved domain sequences of 160 SR GhFBX proteins according to MUSCLE. A total of 9 highly conserved residues were identified: 1 (Leu, 82.9%), 2 (Pro, 78.8%), 10 (Ile, 73.8%), 11 (Leu, 55.6%), 14 (Leu, 70.6%), 21 (Trp, 76.9%), 22 (Pro, 76.9%), 33 (Val, 76.7%) and 38 (Trp, 62.7%) (Fig. 3, Table S4). As expected, these mostly conserved residues align with those in previous studies of the F-box domain in various plant species [31, 32]. These observations suggested that these conserved sites serve as critical binding sites for F-box proteins to interact with SKP1 proteins.

Fig. 3.

Fig. 3

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Conserved F-box domain analysis of SR GhFBX proteins. Sequence logo of the conserved F-box domain of the 160 F-box proteins. The x-axis represents the positions of the amino acid residues in the F-box domain. The y-axis represents the number of times that the amino acid appears in a particular position. The height of a single letter represents the relative frequency of the corresponding amino acid at that position. * represents the conserved amino acid residues of the SR GhFBX domain

In addition to the N-terminal F-box domain, F-box proteins also contain a variable domain at the C-terminal that is key for recognizing different substrates of the SCF complex to perform diverse biological functions [33]. To study the regularity of the F-box C-terminal domains of the SR GhFBX proteins, we investigated the C-terminal domains of 160 SR GhFBX proteins and found that the SR F-box proteins were divided into 10 groups according to their C-terminal functional domains: FBU (F-box with unknown C-terminal domains), FBK (F-box with Kelch repeats domains), FBL (F-box with leucine-rich repeats domains), FBDL (F-box with C-terminal FBD domains and leucine-rich repeats domains), FBP (F-box with C-terminal Phloem protein 2 domains), FBA (F-box associated domains), FBT (F-box with Tubby domains), FBR (F-box with C-terminal ARM repeats), FBPK (F-box with N-terminal PAS domains and C-terminal Kelch domains) and FBO (F-box with other domains). The members of the FBU, FBK and FBL groups were most abundant in the SR GhFBX protein family (Table S5). A phylogenetic tree was constructed based on the sequencing of the F-box motif, and the 160 SR GhFBX proteins were classified into 5 subfamily groups (GI–GV). Among these subfamily groups, GI contains mainly FBPs and FBUs; GII contains mainly FBKs, FBRs, FBOs and FBUs; GIII contains mainly FBTs and FBPKs; GIV contains mainly FBUs and FBLs; and GV contains mainly FBKs (Fig. 4A). In addition, we analysed the conserved motifs of the SR GhFBX proteins and identified a total of 20 distinct motifs. Further analysis revealed that motif_1, motif_2, motif_4, motif_5 and motif_6 were identified as TUB; motif_3 was identified as part of the F-box motif; motif_8, motif_11, motif_16 and motif_18 were identified as LRR; motif_9, motif_12, motif_13 and motif_14 were identified as PP2; and motif_19 and motif_20 were identified as Kelch (Fig. 4B, Table S6).

Fig. 4.

Fig. 4

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Phylogenetic tree, gene structure, cis-elements of the promoter region and expression patterns of SR GhFBX genes in different tissues and under salt stress treatment. A Phylogenetic tree of the SR GhFBX proteins. All the SR GhFBX proteins were divided into 5 groups (GI–GV). Different colours represent groups. B Structure and motif analysis of the SR GhFBX proteins. Different coloured boxes represent different motifs. Different coloured lines and fonts represent different subfamilies. C Cis-acting regulatory elements in the promoter regions of the SR GhFBX genes. Circles with different colours represent different cis-elements. D Heatmap of the expression patterns of the SR GhFBX genes in different tissues. The scale bar on the right is marked according to the TPM values. E Heatmap of the expression patterns of the SR GhFBX genes in response to salt stress. The scale bar on the right is marked according to the log2 fold change

Cis-regulatory elements in SR GhFBX gene promoters are responsive to salt stress

To elucidate the potential regulatory mechanisms underlying salt stress responses, the 2000-bp upstream promoter regions of 160 SR GhFBX genes were analysed to identify cis-regulatory elements. A total of 23 unique cis-elements or binding sites were identified, including important elements involved in the light response, stress response and hormone response (Fig. 4C). Five stress-related elements were identified, namely, LTRs, MBSs, TC-rich repeats, ARE and WUN. These cis-acting elements are involved in the response to low temperature, anaerobic conditions, salt stress and drought. Notably, the ARE is most frequently observed in the promoter region of SR GhFBX genes. Ten cis-acting elements were also found to be related to the light response, including Box 4 elements, G-box, I-box, AE-box and others. We observed that the Box 4 element appears with a high frequency among the light-responsive cis-acting regulatory elements, with the promoter regions of 148 genes containing the Box 4 motif, averaging 3.9 Box cis elements per gene. In addition, we identified seven hormone-related elements, namely, the CGTCA motif (MeJA responsiveness), TGACG motif (MeJA responsiveness), ABRE (abscisic acid responsiveness), P-box (gibberellin responsiveness), TCA element (salicylic acid responsiveness), AuxRR core (auxin responsiveness) and TGA element (auxin-responsive element).

Further analysis revealed that the distribution of certain cis-elements varied among these groups, with some elements showing group-specific enrichment while others exhibited relatively uniform distribution across all groups. Specifically, Box 4, I-box, and GATA-motif were predominantly enriched in Group Ⅲ; AE-box was mainly concentrated in Group Ⅳ; GA-motif and P-box were primarily enriched in Group Ⅱ; and LTR and TCA-element were mainly concentrated in Group Ⅰ. In contrast, elements such as G-box, GT1-motif, MBS, CGTCA-motif, TGACG-motif, ABRE, and ARE exhibited relatively uniform distribution across groups (Table S7).

Among the 160 SR GhFBX genes, the GhFBX158 promoter region, which contains 54 cis-acting elements, has the greatest number of cis-acting elements, whereas the GhFBX75 promoter region has the fewest, with only 8 cis-acting elements (Table S7). These results suggested that these 160 SR GhFBX genes are not only involved in salt stress regulation but also closely associated with various aspects of other stress responses and plant growth and development.

Expression pattern analysis of the SR GhFBX genes

To investigate the tissue-specific expression patterns of the SR GhFBX genes, we analysed the expression profiles of nine tissue types on the basis of publicly available transcriptomic data from the RNA-seq dataset (PRJNA490626). Tissue-specific expression analysis revealed that most of the SR GhFBX genes (103 out of 160) were expressed in all 9 tissue types (Fig. 4D). Notably, 23 SR GhFBX genes were highly expressed with transcripts per million (TPM) values greater than 5 (Table S8). However, some SR GhFBX genes exhibited tissue-specific expression patterns. For example, GhFBX79 was predominantly expressed in bracts, whereas the expression of GhFBX114 was specific to roots, with minimal expression detected in other tissues. Overall, some genes in the same subfamilies tended to exhibit similar expression patterns (Table S8).

We further analysed their transcript levels using RNA-seq data from leaves after NaCl treatment at 1 h, 3 h, 6 h, 12 h, and 24 h (Fig. 4E). We identified 103 genes whose expression responded to salt stress within 1 h, among which 62 were significantly upregulated and 41 were significantly downregulated, suggesting that these genes can rapidly respond to salt stress. Additionally, the expression of 47 genes significantly changed under salt stress at 24 h, among which 27 were significantly upregulated and 20 were significantly downregulated (Table S8). To validate the accuracy of the changes in transcription of the salt-responsive genes identified in the RNA-seq data, we selected 3 FBPKs (GhFBX1, GhFBX74, and GhFBX152), 2 FBKs (GhFBX83 and GhFBX158), 3 FBPs (GhFBX45, GhFBX127, and GhFBX129) and 2 FBLs (GhFBX30 and GhFBX50) on the basis of their domains for qRT–PCR analysis (Table S8). After salt stress treatment, the expression levels of the screened genes GhFBX1, GhFBX74, GhFBX127 and GhFBX152 significantly increased, whereas those of GhFBX83 significantly decreased (Fig. 5).

Fig. 5.

Fig. 5

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Relative expression patterns of 10 GhFBX genes in response to salt stress. Each subplot illustrates the relative expression changes of the corresponding GhFBX gene over time (0 h, 1 h, 3 h, 6 h, 12 h, 24 h) under salt stress. The grey bars represent the relative expression levels determined by qRT–PCR using the 2−∆∆ct method. (Student’s t test, * P < 0.05 and ** P < 0.01)

SR GhFBX candidate proteins interact with SKP1 proteins

Previous studies have shown that F-box proteins primarily function by forming SCF (SKP1–Cullin–F-box) E3 ubiquitin ligase complexes to mediate ubiquitin-dependent protein degradation and that the highly conserved F-box motif mediates the interaction between SKP1 and F-box proteins [14]. To investigate the interaction between F-box and SKP1 proteins in cotton, we selected 4 GhSKP1-like genes (GhSKP1-like_6A, GhSKP1-like_4D, GhSKP1-like_6D, and GhSKP1-like_11A) from different branches of the phylogenetic tree on the basis of previous cluster analysis studies [34]. Given that the highly conserved F-box motif mediates the interaction between SKP1 and F-box proteins, we selected six SR GhFBX genes for yeast two-hybrid (Y2H) hybridization experiments on the basis of phylogenetic analysis results of the F-box domain sequences. These included two FBPs (GhFBX127 and GhFBX129), two FBKs (GhFBX14 and GhFBX83), one FBL (GhFBX50), and one FBU (GhFBX55). The results indicated that different GhFBX proteins selectively bind to specific GhSKP1-like family members (Fig. 6, Fig S2). All six selected SR GhFBX could interact with GhSKP1-like_6A and GhSKP1-like_4D. GhFBX50, GhFBX55, GhFBX83, and GhFBX129 could bind only to GhSKP1-like_6A and GhSKP1-like_4D. GhFBX14 could bind to GhSKP1-like_6A, GhSKP1-like_4D, and GhSKP1-like_11A, whereas GhFBX127 could bind to all four GhSKP1-like proteins. These specific interactions may play multiple functional roles in the response of cotton to salt stress.

Fig. 6.

Fig. 6

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Interaction assay for GhSKP1-like and F-box proteins. A Schematic diagram of the interaction assay between GhSKP1-like and F-box proteins. B Yeast two-hybrid interaction assays for GhSKP1-like and F-box proteins

Functional identification of GhFBX83 in response to salt stress

To further investigate the role of GhFBX genes in salinity adaptation, we selected the salt stress negatively responsive gene GhFBX83 for functional studies on the basis of quantitative analysis and GhSKP1-like gene interaction results. To investigate the function of GhFBX83 in response to salt stress, we employed virus-induced gene silencing (VIGS) to decrease its transcript level in cotton. The vectors TRV2:CLA and TRV2:00 were utilized as positive and negative controls, respectively. The success of the VIGS experiment was confirmed when the albino phenotype was observed on TRV2:CLA cotton plants, and the silencing of GhFBX83 in the plants was verified by qRT–PCR. The results indicated that when the GhFBX83 gene was silenced in the plants, no significant phenotypic changes were observed (Fig. S3). When the expression level of GhFBX83 significantly decreased in the VIGS-GhFBX83 plants, both the TRV2:00 plants and VIGS-GhFBX83 plants were treated with 400 mM NaCl for 6 days. The leaves of the TRV2:00 plants turned yellow–green, indicating obvious stress symptoms, whereas the leaves of the VIGS-GhFBX83 plants were less affected (Fig. 7A, B). We further examined the physiological and biochemical responses of GhFBX83-silenced plants under salt stress. DAB and NBT staining revealed that under salt stress conditions, compared with TRV2:00 plants, VIGS-GhFBX83 plants accumulated fewer ROS (Fig. 7C). Consistent with these observations, the levels of hydrogen peroxide (H₂O₂) and superoxide anion (O₂⁻) were significantly reduced in the GhFBX83-silenced plants (Fig. 7D, E). Furthermore, proline (PRO) content increased significantly in the silenced plants relative to the controls, whereas malondialdehyde (MDA) content showed no significant difference between the two groups (Fig. 7F, G). Moreover, we measured the activities of antioxidant enzymes. The activities of superoxide dismutase (SOD) and peroxidase (POD) were significantly higher in the VIGS-GhFBX83 plants than in the TRV2:00 controls, while catalase (CAT) activity showed no significant difference between the two groups(Fig. 7H, I, J). These results indicated that silencing GhFBX83 could increase plant salt tolerance through regulating proline production and the reactive oxygen species scavenging capacity.

Fig. 7.

Fig. 7

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Silencing of GhFBX83 via VIGS increased salt tolerance in cotton. A Whole-plant phenotypes of TRV2:00 (control) and GhFBX83-silenced plants after 6 days of 400 mM salt treatment. B Leaf phenotypes of TRV2:00 and VIGS-GhFBX83 after 6 days of salt treatment. C Detection of leaf reactive oxygen species (ROS) accumulation by NBT staining (superoxide anion, top) and DAB staining (hydrogen peroxide, bottom). D Superoxide anion (O₂⁻) content; E Hydrogen peroxide (H₂O₂) content; F Proline content; G Malondialdehyde (MDA) content; H Superoxide dismutase (SOD) activity; I Peroxidase (POD) activity; J Catalase (CAT) activity. The data represent the means ± SD of triplicate biological results (* P < 0.05, ** P < 0.01, Student’s t test)

Discussion

In plants, the F-box superfamily is widely distributed and plays important roles in plant growth, development, and stress responses [35]. Although some functions of F-box genes have been investigated, the F-box gene family is extensive, and the roles of the majority of F-box genes remain poorly understood. Notably, the functions of F-box family genes in cotton under salt stress have not been thoroughly elucidated. In this study, a total of 644 GhFBX genes and 160 SR GhFBX genes were identified on the basis of the new version of the cotton genome and salt stress-induced transcriptome data. We found that approximately one-quarter of the GhFBX genes were regulated by salt stress, with similar results observed in poplar, where 82 out of 245 PtrFBX genes responded to salt stress [36]. These findings indicate that F-box family genes are widely involved in the salt stress response process. F-box proteins usually regulate plant stress responses by forming SCF complexes that mediate the ubiquitination and degradation of stress-related proteins. These stress-responsive proteins may function as either positive or negative regulators; therefore, F-box proteins modulate stress response proteins through upregulation or downregulation of their expression. This study revealed that the majority of the SR GhFBX genes (103 SR GhFBX genes) responded extremely rapidly to salt stress and were significantly differentially expressed as early as 1 h after salt stress treatment, with 62 upregulated genes and 41 downregulated genes (Table S8). These genes may be early response genes in the salt stress signal transduction process.

Cis-acting elements serve as recognition and binding sites for transcription factors, playing a crucial role in the regulation of gene expression. In this study, we observed a correlation between the distribution of specific cis-elements and the salt-responsive expression patterns of GhFBX genes following 1 h of NaCl treatment. When examining the salt‑responsive expression patterns following 1 h of NaCl treatment, we observed that down‑regulated GhFBX genes exhibited a higher abundance of ABRE and P‑box elements compared to up‑regulated ones, while up‑regulated genes showed a greater enrichment of TC‑rich repeats. In addition, the distribution of cis-elements was found to vary among different phylogenetic groups of GhFBX genes. Box 4, I-box, and GATA-motif were more enriched in Group Ⅲ; AE-box in Group Ⅳ; GA-motif and P-box in Group Ⅱ; and LTR and TCA-element in Group Ⅰ. In contrast, elements such as G-box, GT1-motif, MBS, CGTCA-motif, TGACG-motif, ABRE, and ARE were relatively evenly distributed across all groups. Collectively, these observations suggest that the group-specific distribution of certain cis-elements, along with the differential enrichment of ABRE, P-box, and TC-rich repeats in salt-responsive genes, might contribute to the divergent transcriptional behaviors of GhFBX genes under salt stress.

The F-box gene family consists of numerous members characterized by significant variability. Usually, the F-box motif at the N-terminus is relatively conserved. In contrast, the protein-binding sequences at the C-terminus, which interact with different target substrates, are diverse. Previous studies have indicated that the F-box motif at the N-terminus and the protein–protein interaction domain at the C-terminus of F-box proteins may evolve synchronously. In soybean and Medicago truncatula (M. truncatula), phylogenetic trees were constructed on the basis of F-box domain sequences, where F-box proteins containing identical C-terminal conserved domains typically clustered within the same branch [31, 37]. In this study, similar results were obtained for the SR GhFBX gene family through F-box domain clustering analysis (Fig. 4A). These findings suggested that genes with similar F-box domains regulate downstream proteins through their corresponding C-terminal domains, thereby exhibiting similar functions.

In this study, eleven domain types were identified in SR F-box proteins, namely, the FBK, FBL, FBDL, FBP, FBA, FBT, FBR, FBPK, FBW, and FBO subfamilies. These SR GhFBX proteins contain nearly all the major domain types (Table S5). No specific types were enriched in the C-terminal domains of SR F-box proteins. Previous experimental studies have confirmed these results. For example, cotton GhFB15 belongs to the FBU subgroup, and silencing of this gene can increase the flavonoid content and ROS-scavenging capacity, thereby increasing salt tolerance [20]. In Arabidopsis, AtPP2-B11 is classified as belonging to the FBP subgroup and plays a positive regulatory role in the salt stress response, with overexpression of AtPP2-B11 resulting in decreased Na+ accumulation [38]. In apples, MdMAX2 belongs to the FBL subgroup, whose members improve both drought resistance and salt tolerance by enhancing ABA-mediated stomatal closure and reducing transpiration [39]. These results indicate that the F-box family is extensively involved in plant responses to salt stress through different physiological metabolic pathways.

In addition, the results of this study revealed that silencing GhFBX83, which belongs to the FBK subgroup, increased plant salt tolerance and reduced reactive oxygen species (ROS) generation. This suggests that GhFBX83 may negatively regulate salt tolerance, and the function is associated with reduced ROS accumulation. However, the precise molecular mechanism by which GhFBX83 regulates ROS homeostasis remains unclear. As an F-box protein, GhFBX83 is predicted to function as a component of the SKP1-Cullin-F-box (SCF) E3 ubiquitin ligase complex, potentially targeting specific substrate proteins for degradation. Through this ubiquitination activity, GhFBX83 may negatively regulate salt tolerance either by promoting the degradation of positive regulators of antioxidant defense or by preventing the degradation of negative regulators involved in ROS-scavenging pathways.

The interactions of F-box proteins with SKP1 proteins are pivotal for enabling the SCF complex to specifically recognize and degrade target substrates [40]. Previous studies have shown that F-box proteins can physically interact with multiple SKP1 proteins and that the binding between SKP1-like proteins and F-box proteins varies [41, 42]. In different plant species, the number of F-box genes far exceeds that of SKP1 genes. There are 21 SKP1 genes [43] and 692 F-box genes [44] in Arabidopsis, 15 SKP1-like genes [45] and 285 F-box genes [46] in chickpea, and 32 SKP1-like genes [47] and 779 F-box genes [33] in rice. The number of F-box genes far exceeds the number of SKP1-like genes, and one SKP1-like gene could interact with multiple F-boxes. However, an F-box protein can also interact with multiple different SKP1 proteins; for example, rice OsFBX148 can simultaneously form an SCF complex with OSK4, OSK7, and OSK17 [48]. Multiple distinct F-box proteins can interact with the same SKP1 protein; for example, Arabidopsis F-box AtFBS1, AtFBS2, and AtFBS4 can bind to both ASK1 and ASK2 [49–52]. Multiple lemon F-box proteins specifically recognize ClSKP1-6 and ClSKP1-14 [53]. In this study, we investigated the interactions between 4 GhSKP1-likes and 6 SR GhFBXs using Y2H experiments and reported that GhFBX50, GhFBX55, GhFBX83 and GhFBX129 can interact with both GhSKP1-like_6A and GhSKP1-like_4D proteins. Furthermore, GhFBX127 was found to interact with the GhSKP1-like_6A, GhSKP1-like_4D, GhSKP1-like_6D, and GhSKP1-like_11A proteins. Based on these interaction patterns, the six GhFBXs could be classified into three types. Notably, the interaction pattern characterized by specific binding to only GhSKP1-like_6A and GhSKP1-like_4D represented the second type and contained the largest number of members, including GhFBX50, GhFBX55, GhFBX83, and GhFBX129. Functional validation of GhFBX83 revealed that its silencing enhances salt tolerance in plants, indicating that GhFBX83 acts as a negative regulator of salt stress, further supporting the potential involvement of GhSKP1-like_6A and GhSKP1-like_4D in salt stress response.

Previous studies have shown that the F-box motif links F-box proteins with other components of the SCF complex through binding to SKP1 [54]. Theoretically, F-box proteins with similar F-box motif sequences should have similar binding abilities with SKP1 proteins. However, our phylogenetic analysis revealed that although the F-box motifs of GhFBX55, GhFBX129, and GhFBX127 clustered together, their interaction patterns with GhSKPs differed. GhFBX127 interacted with all four GhSKP1-likes, whereas GhFBX55 and GhFBX129 only interacted with GhSKP1-like_6A and GhSKP1-like_4D. Additionally, although GhFBX83 and GhFBX14 are closely related phylogenetically, their interactions with GhSKPs also differed. Moreover, among the four GhSKP1-likes, GhSKP1-like_6A and GhSKP1-like_4D are closely related [34] and exhibit identical interaction patterns with F-box proteins, as both interact with all six GhFBXs. In contrast, GhSKP1-like_6A and GhSKP1-like_4D are distantly related to GhSKP1-like_6D and GhSKP1-like_11A and display distinct interaction patterns. Specifically, GhSKP1-like_6A and GhSKP1-like_4D interact solely with GhFBX127, whereas GhSKP1-like_11A interacts with both GhFBX14 and GhFBX127. These results suggested that the interaction between SKP1 proteins and F-box proteins involves relatively complex protein spatial conformations and that the interaction between SKP1 and F-box proteins may also be influenced by domains other than the F-box motif. However, owing to certain limitations in our protein interaction experiments, this hypothesis still requires further experimental validation.

Conclusions

In this paper, 160 of SR GhFBX genes were identified, primarily encompassing 10 subfamilies of GhFBX genes in cotton. The analysis of cis-acting elements in SR GhFBX genes revealed numerous cis-elements or binding sites associated with light response, stress response, and hormone response. Furthermore, SR GhFBX proteins are capable of interacting with diverse GhSKP1-like proteins, indicating that SR GhFBX genes exhibit multiple binding modes in response to salt stress. Silencing GhFBX83 in cotton was found to enhance salt tolerance by increasing proline content and scavenging reactive oxygen species. This study provides valuable insights into the molecular basis of cotton salt tolerance and lays a foundation for further functional studies on cotton salt resistance breeding.

Supplementary Information

Supplementary Material 1. (290.2KB, xlsx)
Supplementary Material 2. (2.2MB, docx)

Acknowledgements

We thank AJE (https://www.aje.cn/) for editing the English text of a draft of this manuscript.

Abbreviations

SR GhFBX genes

Salt-responsive cotton F-box genes

SCF

SKP1-CUL1-F-box

UPS

Ubiquitin–proteasome system

MWs

Molecular weights

pIs

Isoelectric points

GRAVY

Grand average of hydropathicity

ML

Maximum likelihood

MDA

Malondialdehyde

PRO

Proline

H2O2

Hydrogen peroxide

O2−

Superoxide anion

VIGS

Virus-induced gene silencing

Y2H

Yeast two-hybrid

ROS

Reactive oxygen species

Authors’ contributions

Y.Q. Wang and P.F. Ai performed project conception and experiment design; X.Y. Liu, J.G. Liu, Z. Geng, G.Y Zhao, T.Y. Feng, Y.P. Zhou and H.S. Zhang conducted the experiments and analyzed the data; X.Y. Liu, J.G. Liu and Y.Q. Wang wrote the original manuscript; J.G. Liu and Y.Q. Wang coordinated the overall study and thoroughly revised and finalized the manuscript. All authors read and approved the manuscript.

Funding

This study was funded by Hebei Natural Science Foundation (C2023301050), Basic research fund of Hebei Academy of Agriculture and Forestry Sciences(2024070203).

Data availability

RNA-seq data used in this study are publicly available from the NCBI (National Center for Biotechnology and Information) SRA, with the access number PRJNA490626. All data generated or analyzed during this study are included in supplementary information files.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Xingyu Liu and Jianguang Liu contributed equally to this work.

Contributor Information

Pengfei Ai, Email: apf2002@sina.com.

Yongqiang Wang, Email: Wangyongqiang502@126.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (290.2KB, xlsx)
Supplementary Material 2. (2.2MB, docx)

Data Availability Statement

RNA-seq data used in this study are publicly available from the NCBI (National Center for Biotechnology and Information) SRA, with the access number PRJNA490626. All data generated or analyzed during this study are included in supplementary information files.

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