Genome-Wide Identification and Functional Validation of Actin Depolymerizing Factor (ADF) Gene Family in Gossypium hirsutum L.

Abstract

The Actin Depolymerizing Factor (ADF) protein, highly conserved among eukaryotes, is essential for plant growth, development, and stress responses. Cotton, a vital economic crop with applications spanning oilseed, textiles, and military sectors, has seen a limited exploration of its ADF gene family. This research has identified 118 unique ADF sequences across four principal cotton species: Gossypium hirsutum L., Gossypium barbadense Linn, Gossypium raimondii, and Asiatic cotton. The study found that the structural domains and physicochemical properties of these proteins are largely uniform across species. The ADF genes were classified into four subfamilies with a notable expansion in groups III and IV due to tandem and chromosomal duplication events. A thorough analysis revealed a high degree of conservation in gene structure, including exon counts and the lengths of introns and exons, with the majority of genes containing three exons, aligning with the characteristics of the ADF family. RNA-seq analysis uncovered a spectrum of responses by GhADFs to various abiotic stresses with GhADF19 showing the most significant reaction. Virus-induced gene silencing (VIGS) experiments were conducted to assess the role of GhADF19 in plant growth under abiotic stress. The results demonstrated that plants with silenced GhADF19 exhibited significantly slower growth rates and lower dry weights when subjected to cold, salt, and drought stress compared to the control group. This marked reduction in growth and dry weight under stress conditions highlights the potential importance of GhADF19 in stress tolerance mechanisms.

1. Introduction

Cotton (Gossypium hirsutum L.), originating from South America, belongs to the genus Gossypium in the Malvaceae family. Archaeological findings suggest its cultivation in parts of northern Chile between 3500 and 2500 BC. The discovery of cotton by ancient cultures led to its introduction to Asia and Africa by Europeans in the 15th century. Today, cotton stands as one of the most pivotal global crops with its seeds serving as a significant source of industrial oil and its fibers playing an essential role in textile industries. However, the intensifying global climate crisis has resulted in a rise in the frequency of extreme weather events, and an increase in the prevalence of pests and diseases has also had a significant impact on cotton production. The occurrence of extreme weather events, including floods, droughts, and heat waves, has the potential to result in a decline in cotton production. Flooding will saturate the soil, directly affecting the growth and physiology of the cotton plant. A reduction in yield can be attributed to the combined effects of increased evaporation and transpiration as well as a reduction in soil water availability, which are both consequences of drought [1]. For example, the economic cost of crop yield loss caused by extreme weather events in developing countries was approximately $80 billion from 2003 to 2014. In the United States, the number of events with losses exceeding $1 billion caused by extreme weather events is also increasing at a steady rate [2]. As evidenced by the data from 2022, the disease resulted in a 8.7% reduction in cotton production in the United States, amounting to a loss of 1.4 million bales. This decline in output is comparable to that observed in 2018–2021 but significantly lower than the average annual output decrease of 12.2% observed over the 22-year period from 2000 to 2021 [3].

Actin Depolymerizing Factors (ADFs) are small, conserved microfilament-binding proteins with molecular weights typically ranging from 15 to 22 kDa. They play a crucial role in regulating the cytoskeleton [4]. Upon binding with both filamentous actin (F-actin) and monomeric actin (G-actin), ADF proteins enhance depolymerization activity [5]. This mechanism allows ADF proteins to modulate actin polymerization within cells, influencing essential cellular processes such as cell division, morphological changes, growth, and motility.

The origin of the ADF gene family dates back to the 1980s when the initial ADF protein was isolated from chicken brain tissue, which was initially termed cofilamentous protein (cofilin) due to its filamentous structure. Subsequent investigations unveiled proteins with sequences akin to cofilin, which were capable of depolymerizing F-actin activity across various tissues. These microfilament-depolymerizing proteins found in mammals and eukaryotic cells were later collectively termed ADF/cofilin [6]. ADF proteins likely played a pivotal role in the evolutionary adaptation of the eukaryotic cytoskeleton. The expansion of the ADF gene family may be attributed to gene duplication events, as suggested by relevant research. These events lead to structural and functional diversifications among different ADF gene family members, enabling them to assume distinct roles in cellular processes. Widely distributed across animal and plant species, the ADF gene family even extends to fungi and other organisms. The plant ADF gene family encompasses several relatively large subfamilies like ADF, cofilin, and TWD. Despite structural variations, these family members share the ability to promote actin depolymerization and participate in biological processes such as plant cell development, growth, intercellular signaling, and stress response.

In recent years, research on the ADF gene family has predominantly focused on three key areas. Firstly, an analysis of ADF protein structure and function has unveiled the molecular mechanisms underlying ADF protein involvement in cellular processes. For instance, ADF proteins regulate actin depolymerization and polymerization states, thus influencing cell motility and morphogenesis [7]. Secondly, investigations into the role of the ADF gene family in organismal growth and development have revealed its involvement across various kingdoms. In plants, ADF proteins foster cell activity, with specific members like AtADF4 and AtADF9 promoting Arabidopsis growth [8]. Similarly, ZmADF3 facilitates maize root hair elongation, while ZmADF1, OsADF, and AtADF7 contribute to pollen formation and tube elongation in maize, rice, and Arabidopsis [9,10,11], each exerting distinct functions. In animals, ADF proteins are implicated in embryonic and neuronal development [12]. Finally, studies on the ADF gene family’s role in stress response highlight its significance in plant stress mitigation. Notably, proteins like OsADF3, AtADF2, At-ADF4, AtADF5, and TaADF7 exhibit substantial effects on abiotic stress response and disease resistance enhancement [13,14,15,16]. For instance, TaADF7 alters actin dynamics to regulate SOD accumulation in wheat, fortifying wheat resistance against stripe rust.

Recent studies on cotton ADF have revealed that the down-regulation of GhADF6 expression significantly enhances cotton’s resistance to Verticillium wilt, suggesting a crucial role for increased filamentous actin (F-actin) abundance and dynamic protein remodeling in plant defense against pathogen invasion [17]. This likely involves a coordinated expression regulation of actin-binding proteins, including ADF. Furthermore, transgenic cotton seedlings and mature plants expressing GhADF1 exhibit robust tolerance to drought stress, which is accompanied by notable improvements in physiological and biochemical indicators such as photosynthetic rate, MDA content, POD activity, and CAT activity in transgenic cotton leaves. Upon the down-regulation of GhADF1 expression, an analysis of cotton fiber properties reveals a potential role for GhADF1 in controlling fiber elongation as well as the synthesis and deposition of secondary cell wall cellulose in cotton fibers [18].

These studies have validated the function of corresponding genes in cotton disease resistance, cotton response to drought stress, and regulation of cotton fiber elongation. However, the gene family of ADF in cotton has yet to be fully described, and the response mechanism to other abiotic stresses remains to be analyzed. However, filamentous actin in actin has been demonstrated to possess a number of functions, including the regulation of plant growth and the response to abiotic stresses. Accordingly, the present study commenced with the initial screening of all ADF genes in cotton through the analysis of genomic data and transcriptome sequencing results. Subsequently, genes that did not respond to abiotic stress were eliminated through the use of quantitative reverse transcription polymerase chain reaction (qRT-PCR). The remaining genes were then subjected to analysis of their response to abiotic stress through the utilization of virus-induced gene silencing (VIGS) technology. The findings of this study are anticipated to serve as a genetic reference for the breeding of cotton with enhanced resistance.

2. Materials and Methods

2.1. Identification and Physicochemical Properties of Cotton ADF Gene Family Members

In this study, we obtained the whole genome data of cotton TM-1 from the website http://mascotton.njau.edu.cn, accessed on 26 February 2023. Additionally, we acquired the genome data of Asian cotton and Raymond cotton from the website CottonGen (https://cottongen.org/, accessed on 26 February 2023) [19], while the genome data of sea island cotton were obtained from the website http://www.chgc.sh.cn/ (accessed on 26 February 2023). The downloaded content included the whole genome sequence file, protein sequence file and genome annotation file. To identify all ADF family members in the four cotton species, we utilized a combination of two identification methods. Firstly, we downloaded the hidden Markov model, used to identify the ADF gene family protein domain ADF-H domain (PF00160), from the Pfam online database (http://pfam.xfam.org/, accessed on 26 February 2023) [20] and used the hmmsearch function in HMMER 3.0 to search for candidate protein sequences with conserved domains in the protein sequence files of the four cotton species. We set the threshold e < 10⁻⁵. Secondly, we used the local BLASTP method based on the known ADF member IDs in the model species, which were reported in the literature, to download the 12 amino acid sequences of the Arabidopsis ADF gene from the Arabidopsis genome database [21] (https://www.arabidopsis.org/, accessed on 26 February 2023). We also downloaded the 12 amino acid sequences of the rice ADF gene from the rice genome website RGAP (http://rice.uga.edu/, accessed on 26 February 2023) [22]. Using the amino acid sequence of each Arabidopsis thaliana and rice ADF as Quary, we performed a local BLASTP search on the genomes of the four cotton species, and the gene sequences whose E value (expect value) ≤ 1 × 10⁻²⁰ in the results were saved. To ensure that we did not miss any identified ADF family members, we conducted a second round of retrieval of the cotton genome using the above-mentioned candidate sequences retrieved as Quary. Additionally, we submitted the obtained candidate sequences to PFAM, SMART (http://smart.embl-heidelberg.de/, accessed on 26 February 2023) and NCBI CDD database (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 26 February 2023) to predict and verify protein domains [23,24]. We manually removed sequences that lacked domains and incomplete domains based on the prediction results, and we finally obtained candidate proteins that were used for follow-up research analysis. The online tool ProtParam (https://web.expasy.org/protparam/, accessed on 26 February 2023) was used to predict the physicochemical properties of candidate ADF proteins, including the molecular weight (Mw) and isoelectric point (pI) of their protein sequences [25]

2.2. Phylogenetic Analysis of ADF Gene in Cotton

Initially, we used the MAFFT version 7 software to conduct multiple sequence alignments of the ADF family members of the four cotton species and the full-length ADF proteins of other species downloaded and obtained [26] while setting the alignment parameters as default. Subsequently, we imported the comparison results into the IQTREE software version 1.6.1 and used the maximum likelihood method (ML) to build a tree. We evaluated the reliability of the constructed phylogenetic tree using the bootstrap method, and the number of repetitions was set to 1000. Finally, we imported the file in treefile format into the online website iTOL (https://itol.embl.de/, accessed on 26 February 2023) for visualization and beautification [24].

2.3. Chromosomal Mapping and Collinearity Analysis of ADF Family Members of Cotton

We extracted the physical location information of all cotton ADF members from the GFF file annotation information in the cotton genome data and visualized it through the Tbtools tool. To investigate the tandem duplication and collinearity events in cotton ADF members, we initially performed localized BLASTP alignment on the amino acid sequences of ADF proteins and set the E-value to 1 × 10⁻⁵. In this study, the screening criteria for tandem duplication genes referred to the methods described in published articles, where two genes with a sequence similarity greater than 70% and located on the same chromosome within a physical range of 200 kb are considered tandem duplication genes. Additionally, we used the MCScanX (https://github.com/wyp1125/MCScanX/, accessed on 26 February 2023) software to analyze the gene replication pattern and obtain the intraspecies collinearity results of cotton. Finally, we used the circos software (V0.69-9) to draw the circos map of the intraspecies collinearity [27]. We also used the same method to identify the collinear relationship between cotton and other cotton species, such as Sea Island cotton, Raymond cotton, and Asian cotton. Lastly, we used the JCVI software (https://github.com/tanghaibao/jcvi/, accessed on 26 February 2023) to display the interspecific collinearity. The values of Ka, Ks and Ka/Ks between collinear gene pairs were calculated by TBtools (V2.097) based on the NG algorithm.

2.4. Gene Structure and Protein Domain Conservation Motif Analysis of ADF Family Members of Cotton

Initially, we extracted the structural information of ADF members from the GFF file in the cotton genome data, including intron, exon, and UTR information. Subsequently, we submitted the relevant data information to the website GSDS (http://gsds.cbi.pku.edu.cn/, accessed on 28 February 2023) for visual analysis. Additionally, we used the MEME software (http://meme-suite.org/, accessed on 28 February 2023) to analyze the conserved motifs of the cotton ADF protein, where the maximum number of motifs that could be recognized was set to 15. Finally, we visualized the conserved motif and gene structure of the ADF protein using the TBtools software (V2.097) [28].

2.5. Analysis of Cis-Acting Elements of ADF Gene Promoter in Cotton

In this study, we utilized the Gtf/Gff3 Sequences Extract function in TBtools (V2.097) to extract the upstream 2000 bp sequence of the translation start site of the ADF family member genes of cotton from the whole genome file of cotton. We then submitted this information to the PlantCare online website (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 28 February 2023) for plant cis-acting regulatory element prediction [29]. Finally, we counted and screened the types and quantities of the obtained cis-acting elements and only selected typical components or components with certain functions for analysis and display. The results were individually de-redundantly mapped to the 2000 bp promoter region of the TBtools protein using TBtools to map the transcription factor binding site information to the 2000 bp promoter region of the TBtools protein. [28].

2.6. Analysis and qPCR Verification of Different Stress Expression Patterns of ADF Gene in Cotton

To explore the expression pattern of ADF genes in cotton under different stresses, we retrieved the FPKM values of cotton under low temperature (4 °C), high temperature (37 °C), salt stress (NaCl), and drought stress (PEG) treatment for 1 h, 3 h, 6 h, 12 h, and 24 h based on the existing transcriptome data in our laboratory. After log2 normalization, we utilized the Tbtools software for cluster analysis and heat map drawing. Additionally, we randomly selected candidate genes and conducted qRT-PCR experiments to verify the reliability of our transcriptome data [28]. (Note: The expression levels of the 7 members located on the scaffold are not reflected in the transcriptome, so they are not used for the research in this section).

2.7. Cotton Cultivation and Sampling

The cotton seedlings utilized in this experiment were cultivated in an artificial climate chamber under the following conditions: 16 h of illumination at 26 °C, 8 h of darkness at 22 °C, and a humidity level of 50%. The seeds are depilated with concentrated sulfuric acid, then washed with clear water to remove any residual acid, and finally placed in an artificial climate chamber. Subsequently, the seeds should be soaked in water until germination occurs. Then, the seeds should be selected based on the following criteria: full grains, similar size, and no mechanical damage. Following this, the seeds should be planted in Beijing brand plastic seedling pots in accordance with the ratio of nutrient soil: vermiculite: sand = 2:1:1. At the two-leaf stage, cotton seedlings were subjected to a series of treatments, including a salt treatment (320 mM NaCl), a drought treatment (18% PEG 6000), a low-temperature treatment (4 °C), and a high-temperature treatment (37 °C). Samples were collected at 0 h, 1 h, 3 h, 6 h, 12 h, and 24 h.

2.8. Virus-Induced Gene Silencing

The cotton standard line TM-1 was cultivated according to conventional agronomic measures, and VIGS injection was performed when the two cotyledons were completely flattened. We selected a specific fragment on the CDS sequence of the target gene, constructed it into the pTRV2 vector, transformed it into Agrobacterium, and mixed the auxiliary bacteria pTRV1 with other bacteria to be injected in equal proportions before injection. After the injection, the plants needed to be cultured in shading for 24 h and then transferred to the artificial climate chamber. The albino symptoms of the leaves of the plants injected with PDS indicated that the gene silencing was effective. Following the detection of gene silencing efficiency by qPCR, we proceeded to the next step of the abiotic stress experiment. In this experiment, we utilized a 320 mM NaCl solution for salt stress, an 18% PEG 6000 solution for drought treatment, and a 4 °C incubator for low-temperature treatment [30].

2.9. Measurement of Fresh Weight and Dry Weight of Cotton

We chose cotton seedlings with consistent growth and carefully removed them from the nutrition bowl, carefully removed the excess soil at the roots, gently wiped the seedlings with a soft paper towel to remove the water that remained on the surface, and immediately weighed and recorded the fresh weight. Immediately after recording, we put the seedlings into kraft paper bags, sealed them, and dried them in an oven at 70 °C overnight. The next day, the dried seedlings were weighed and the dry weight was recorded [31].

3. Results

3.1. Dentification of ADF Gene Family Members of Four Cotton Species and Analysis of Their Physicochemical Properties

To identify ADF family genes in four cotton species, we employed the known protein sequences of Arabidopsis thaliana AtADFs and rice OsADFs as references. Using the local BLASTP method, we searched the genome protein databases of these cotton species. Combining the results with those from HMM searches, we submitted the resulting candidate protein sequences to Pfam, SMART, and NCBI CDD databases for a further confirmation of domain existence, manually removing redundant sequences. Subsequently, we identified 40, 39, 20, and 19 non-redundant ADF gene sequences in Gossypium hirsutum L., Gossypium barbadense Linn, Gossypium raimondii, and Asiatic cotton, respectively. These genes were sequentially named based on their chromosomal coordinates.

Supplementary Table S1 presents protein length encoded by cotton ADF genes, ranging from 53 to 395 amino acids (aa), with an average length of 151 aa. Protein molecular weights spanned from 6.10 to 44.41 kDa with predicted isoelectric points ranging from 4.46 to 9.4. Additionally, DNA sequences encoded by ADF members varied in length from 939 to 2076 base pairs (bp), averaging 1416 bp. Notably, the physicochemical properties of the 46 GhADFs exhibited differences, which were likely attributable to unconserved amino acid regions.

3.2. Phylogenetic Analysis of ADF Protein in Cotton

To delve deeper into the evolutionary relationships among cotton ADF members, we conducted multiple sequence alignments using MAFFT software (version 7). The analysis encompassed downloaded AtADFs, rice ADFs, tomato ADFs, wheat ADFs, and full-length sequences of ADFs from the three identified cotton species. Subsequently, we employed the maximum likelihood method to explore the phylogenetic evolution of cotton ADF members. As depicted in Figure 1, the resulting phylogenetic tree delineated cotton ADF family members into four distinct subfamilies (I, II, III, IV), aligning with previous studies. Notably, in comparison with ADF gene families from other plants, cotton ADF family members within groups III and IV appeared relatively abundant. We hypothesized that tandem duplication events or chromosome segment duplication events might underlie the expansion of these two groups. We constructed a phylogenetic tree specifically for the 40 cotton ADF members (Figure S1), which corroborated our earlier findings, affirming the reliability of our results for further research endeavors.

3.3. Chromosomal Mapping of ADF Family Members in Cotton

Tandem duplication and chromosome segment duplication represent the primary mechanisms of plant genome amplification, increasing genome diversity. In order to gain insight into the effects of gene differentiation and duplication on the formation of cotton ADF gene families, we initiated a chromosome mapping exercise for all identified candidate genes. As illustrated in Figure 2, 33 cotton ADFs were distributed across 26 chromosomes, with seven located on scaffolds, exhibiting a heterogeneous distribution pattern. The greatest number of family members was identified on chromosome D09, with four ADFs, which was followed by three family members each on chromosomes A01, A03, A09, and D01. Furthermore, two additional GhADFs were identified on chromosomes A12, A13, D03, and D12 with individual members present on chromosomes A05, A07, A11, D02, D07, D08, and D11. No ADF family members were identified on the remaining chromosomes. It is noteworthy that the majority of ADF genes are situated in the telomeric region of the chromosomes. The telomeric region is a region of relatively low gene density on the chromosome, which may render these genes more susceptible to replication events. This provides further evidence that the location of genes on chromosomes may influence the frequency and outcome of their replication. In particular, genes situated in the telomeric regions of chromosomes may be more prone to replication errors or events due to the intrinsic replication properties of the region. This may result in the expansion of gene families and the emergence of novel functions.

3.4. Collinearity Analysis and KA, KS Analysis of ADF Family Members of Cotton

In plants, gene family expansion is instrumental in facilitating adaptation to diverse environmental conditions. To elucidate the expansion mechanism of the ADF gene family in cotton, we conducted an analysis of gene duplication events within the cotton genome.

As detailed in Supplementary Table S2, we identified two tandem duplication events within the cotton ADF family, involving GhADF2 and GhADF3 as well as GhADF18 and GhADF19, which are both located on chromosomes A01 and D01. Notably, these tandemly duplicated gene pairs are situated within subgroup III. It is noteworthy that the sequence similarity of these tandemly repeated gene pairs exceeded 90%, indicating their likely origination from the same ancestral gene during evolution, retaining similar biological functions.

Additionally, as depicted in Figure 3a and Supplementary Table S2, we observed a total of 32 GhADFs located within fragment replacement regions, yielding a total of 83 pairs of fragment replacement events.

Furthermore, we investigated the syntenic relationships of the ADF family across various cotton species. Figure 3b illustrates 30 collinear gene pairs between the ADF family in cotton and Asian cotton, 69 syntenic gene pairs with Sea Island cotton, and 30 syntenic gene pairs with Raymond cotton. To assess whether the selection experienced by duplicated ADF family genes is advantageous, we calculated the non-synonymous differentiation level (Ka), synonymous difference level (Ks), and Ka/Ks ratios. Analysis revealed abnormal Ka/Ks values for 15 pairs of duplicated genes, which was possibly due to genome assembly issues. Additionally, a distribution of Ka/Ks values was observed, with most values less than 1, suggesting that strong purifying selection is acting upon these genes post-duplication. Notably, Ka/Ks values were equal to 0 for 6 duplicated gene pairs, which is consistent with the general observation that Ka/Ks values are typically less than 1, indicating a lack of positive selection pressure.

3.5. Gene Structure and Conserved Motif Analysis of ADF Gene in Cotton

The diversity in gene structure offers valuable insights into gene function and evolutionary relationships. Therefore, we conducted an analysis of the gene structure of ADF family genes in cotton.

According to the evolutionary tree, the gene structure of the 40 ADF members can be categorized into four groups. Group I comprises five members with three exons, while GhADF30 stands out with five exons. Group II includes five members with three exons, one with two exons, and one with a single exon. Group III encompasses nine members with three exons and three members with two exons. In group IV, nine members feature three exons, two have seven exons, three possess two exons, and one consists of a single exon. Notably, most members exhibit three exons, aligning with typical ADF family characteristics. The gene structure remains highly conserved within members of the same evolutionary branch or subgroup, encompassing exon and intron numbers and lengths. Notably, while exon lengths within the same subgroup are similar, intron lengths display considerable variation. We speculate that changes in exon numbers, as well as the length and distribution of introns, may have contributed to functional diversity among these genes during evolution. To delve deeper into the structural and functional diversity of cotton ADF family members, we subjected the full-length sequences of 40 GhADF proteins to the online program MEME. The analysis predicted 10 conserved motifs, as depicted in Figure 4. Notably, the number, type, and sequence of motifs among ADF members in different subgroups exhibit a degree of conservatism, validating the reliability of our constructed evolutionary tree, which is consistent with earlier findings. Group I features a distinctive motif 8, while GhADF14 and GhADF31 in group IV possess specific motifs 5, 6, 7, and 9. Motif 9 exclusively appears in groups IV and III. Most members harbor motifs 1, 2, 4, and 10, which constitute part of the conserved ADF protein domain.

3.6. Analysis of Cis-Acting Elements of ADF Gene in Cotton

During the growth and development of plants, they encounter a myriad of biotic and abiotic stresses from the external environment with cis-acting elements playing a pivotal role in regulating gene transcription initiation and interactions with regulatory factors. To delve deeper into the potential functions and transcriptional regulation of GhADFs genes, we utilized the online prediction tool PlantCARE to analyze the promoter region (2000 bp upstream of ATG) of each cotton ADF family member.

As illustrated in Figure 5 and Supplementary Table S3, we categorized the predicted cis-acting elements into four types, each serving distinct functions: light response, hormone response, growth and development regulation, and stress response. For this study, we focused on cis-acting elements with specific functions, excluding ubiquitous elements such as CAAT-box, TATA-box, and TATC-box.

Our analysis revealed a widespread occurrence of light-responsive cis-elements in each ADF family member of cotton, including L-box and TCT-motif. Similarly, most members harbored elements associated with hormone responses, such as ABRE, ERE, P-box, TCA-element, TGA-element, and TGACG-motif, indicating their potential involvement in regulating hormone responses. Additionally, we identified growth-related elements in the cotton ADF family, such as TGA-element, CAT-box, RY-element, CCGTCC-box, and dOCT.

Regarding abiotic stress response, the promoter region of 35 ADF family members in cotton contained elements associated with environmental stress response. For instance, seven members contained DRE elements implicated in responses to low temperature, salt, and drought stress. Moreover, 11 members featured MBS elements linked to drought stress response, while 8 members contained TC-rich repeats, and all 16 members harbored W-box elements, which are both widely involved in regulating stress response in plants.

In conclusion, our research underscores the significant role of GhADFs in hormone regulation networks and stress responses in cotton. Additionally, these findings provide valuable insights for the further exploration of adversity stress responses in cotton.

3.7. Analysis of Expression Patterns of ADF Family Members in Cotton under Different Stresses

In order to explore whether the ADF family of cotton plays an important role in the regulation of stress responses, we used transcriptome data to explore the expression levels of members under different stresses. As shown in Figure 6, most GhADFs responded to different degrees under the treatment of abiotic stress. After treatment at 4 °C and 37 °C for 1 h, the expression levels of GhADF31, GhADF5 and other genes were down-regulated, and the expression levels continued to decrease after 1 h, indicating that these genes may play a negative regulatory role in low temperature and 37 °C stress. On the contrary, the expression levels of GhADF28, GhADF7 and other genes increased rapidly after 1 h of low-temperature treatment, and GhADF6, GhADF16, and GhADF30 reached the peak value after 1 h of low-temperature treatment, indicating that these genes can respond rapidly after low-temperature treatment of 37 °C. Under the treatment of 37 °C, the expression levels of most ADF members changed significantly at 1 h and 24 h, while under the treatment of NaCl and PEG, the expression levels of most members changed significantly at 6 h, 12 h and 24 h. At the same time, we also found that there are genes that respond to all stresses, such as GhADF27, GhADF28, GhADF23, etc.; there are also some members whose expression patterns are quite different under different stresses, such as GhADF9 at 4 °C and PEG treatment. The expression level increased significantly and reached the peak at 12 h, but there was almost no change in the expression level under the treatment of NaCl and 37 °C. GhADF34 had no change under the treatment of 4 °C, and the expression level reached the peak at 24 h under the stress of 37 °C. Two genes, GhADF17 and GhADF22, did not change significantly under the four stress treatments, which may be related to other biological regulation processes.

3.8. qRT-PCR Verification of ADF Family Members of Cotton

The analysis of transcriptome data revealed that most GhADFs members exhibited different expression patterns under various stress treatments. To validate the credibility of the aforementioned outcomes, we randomly selected some candidate genes whose expression levels changed and conducted qRT-PCR experiments. According to quantitative results, most ADF members responded to NaCl, low temperature, and PEG stress to varying degrees. As depicted in Figure 7, under NaCl stress, GhADF32 was up-regulated to more than three times that of the control group at 24 h, GhADF19 was up-regulated to nearly four times that of the control group at 3 h, GhADF13 and GhADF20 showed the same expression pattern, and their expression levels decreased after treatment and returned to the control state at 24 h. Under low-temperature treatment, the expression level of GhADF12 decreased after 3 h of treatment, then increased linearly, and peaked at 24 h. The expression levels of GhADF13 and GhADF20 continued to decrease after treatment, indicating that they may play a negative regulatory role in low-temperature response. The expressions of GhADF5 and GhADF35 were rapidly up-regulated after low-temperature treatment for 3 h, which may be related to the signal reception in the early stage of low-temperature regulation. Under PEG treatment, the expression levels of GhADF32 and GhADF20 continued to decrease after PEG treatment, and they returned to the control level at 24 h; the expression levels of GhADF8 and GhADF13 also continued to decrease after PEG treatment, and they returned to half the level of the control group at 24 h. The expression of GhADF24 continued to decrease after PEG treatment, indicating that it may play a negative regulatory role, while the expressions of GhADF5, GhADF19, and GhADF35 were significantly up-regulated 3 h after PEG treatment, which may be related to early signal reception. It is worth mentioning that GhADF35 was strongly expressed in all three stresses, which may play a crucial role in early signal reception. Under PEG treatment, the expression level was nearly 20 times that of the control group; conversely, GhADF13 showed a down-regulation trend in expression level after early stress, indicating its possible involvement in negative regulation. In summary, by conducting qRT-PCR experiments and comparing them with RNA-seq data, we observed that the RNA-seq data used were more accurate and the conclusions were relatively reliable. Therefore, this can lay a solid foundation for our subsequent selection of candidate genes.

3.9. Functional Analysis of GhADF19

According to the results of fluorescence quantification, four candidate genes GhADF2, GhADF5, GhADF18, and GhADF19 were screened for VIGS gene silencing. When the leaves of cotton seedlings injected with PDS were albino, it indicated that other genes were also silenced successfully. As shown in Figure 8a, it was found that the growth of the leaves and plants of the control group TRV:00 (hereinafter referred to as the control group) was significantly better than that of the silenced plants under drought stress, cold stress, and salt stress. The material measurement results are shown in Figure 8b. The dry matter synthesis of plants with the GhADF19 gene silenced under drought stress and cold stress decreased most significantly compared with the other three genes. The results of qRT-PCR silencing efficiency detection are shown in Figure 8c. The gene expression levels in the young Agrobacterium cotton inoculated with TRV:GhADF19 were significantly reduced under different stress treatments, by 68.24%, 81.19%, and 66.82%, respectively. Among them, the plants with the GhADF19 gene silenced had the worst growth condition, with severe leaf wilting, and some plants were close to death. These results indicated that the GhADF19 gene may be involved in the stress response of upland cotton. Phenotypic images of untreated cotton seedlings inoculated with TRV:GhADF19 have been uploaded to the Supplementary File (12d-COLD.HEIC, 12d-NACL.HEIC, 12d-PEG.HEIC).

4. Discussion

In plant cells, the Actin Depolymerizing Factor (ADF) protein plays a crucial role in plant growth, development, and responses to external environmental changes by interacting with actin. While the ADF family has been extensively studied and analyzed in various plant species, its exploration in cotton remains relatively obscure. Therefore, this study aims to systematically analyze the ADF family in cotton at a genome-wide level.

4.1. Identification and Evolutionary Analysis of ADF Family in Cotton

In this study, we conducted a comprehensive search of the Gossypium hirsutum L. genome using both BLASTP and HMM search methods, resulting in the identification of 40 ADF gene family members. To compare differences across various cotton species, we extended our analysis to include Gossypium barbadense Linn with 39 members, Gossypium raimondii with 20 members, and Asiatic cotton with 19 members. Notably, the number of ADF genes in tetraploid cotton was approximately twice that of diploid cotton, indicating a potential gene expansion event associated with polyploidization. Upon constructing the phylogenetic evolutionary tree, we observed a relatively conservative distribution of the ADF family across cotton species, which is comparable to findings in Arabidopsis [32]. However, we noted varying degrees of expansion in groups III and IV, particularly in land cotton, which are likely attributed to duplication events.

Consistent with prior research, the ADF family in land cotton was categorized into four primary branches. Furthermore, we identified notable differences between monocots and dicots across all four branches of the ADF family. For instance, in group I, Arabidopsis exhibited only two members [33], while tomato had a solitary ADF member. Conversely, in group II, Arabidopsis featured only one member [4], whereas tomato had two ADF members. These distinctions underscore the divergence in ADF gene distribution between monocots and dicots.

4.2. Expansion Mechanism of Cotton ADF Family

There are notable differences in the number of ADF family members among various species. In our study, we identified a total of 40 members in the cotton genome, surpassing the counts found in most known species. For instance, Arabidopsis has 12, maize has 13, rice has 12, tomato has 11, and poplar has 14 ADF proteins [32,33,34,35]. This quantitative contrast can generally be attributed to three factors: the species’ genome size, the occurrence of duplication events within the family, and chromosomal ploidy. Previous research has suggested that in higher plants, the ADF gene family tends to be relatively small. However, the presence of 40 ADF genes in cotton could be linked to its tetraploid nature. Notably, the cotton genome size is 2173 Mb, which is significantly larger than that of Arabidopsis (125 Mb) and poplar (485 Mb). Additionally, being tetraploid likely contributed to the expansion of the ADF family members. Although diploid cotton varieties such as Raymond and Asiatic cottons also exhibit higher ADF gene counts compared to other species, chromosomal ploidy alone may not fully account for this discrepancy.

Subsequently, we delved into the role of duplication events in the ADF family of cotton. Our collinearity analysis revealed that 85% (34/40) of GhADFs were implicated in gene tandem duplication and chromosome segment duplication events. Specifically, we identified two pairs of tandem duplication genes and 83 pairs of chromosome segment duplication genes. Notably, chromosome segment duplication emerged as the primary driving force behind the expansion of the ADF family in cotton. This finding aligns with previous studies in wheat, maize, and tomato, where chromosome segment duplication predominantly influenced family expansion [36]. For instance, wheat’s ADF family showed four pairs of chromosome segment duplication events without any tandem duplication events, while tomato exhibited 17 chromosome segment duplication events without any tandem duplications. Thus, we infer that chromosome segment duplication likely serves as the primary mechanism driving the expansion of the ADF family in higher plants.

In our analysis, we observed that 10 members of group III and 11 members of group IV of the cotton ADF gene family were associated with chromosome segment duplication events, constituting significant proportions of their respective groups. Consequently, we concluded that the expansion of the cotton ADF family primarily occurred through tandem duplication events and chromosome segment duplication events with the latter being the major driving force. Our findings are consistent with previous research [36], indicating that whole-genome duplication during cotton genome differentiation could also contribute significantly to the increased number of ADF family members in cotton.

4.3. Cotton ADF Family Involved in Abiotic Stress

According to existing studies, ADF proteins play crucial roles in various biological processes such as plant growth and development as well as responses to both biotic and abiotic stresses [37]. Prior research has established the involvement of ADF genes in regulating plant responses to low temperatures [34]. Analysis of cis-acting elements has revealed the presence of elements associated with low-temperature response in the promoter sequences of over one third of GhADFs, including DRE, LTR, MBS, and TC-rich repeats. This suggests that these genes may indeed participate in the response to low-temperature stress.

In our study, transcriptome data coupled with qPCR experiments confirmed that ADF expression is induced by low temperatures. For instance, genes like GhADF5, GhADF31, GhADF11, and GhADF23 exhibited negative feedback regulation during early stress response, while others like GhADF27 and GhADF28 responded rapidly, potentially reflecting their involvement in upstream signal reception and transduction. Moreover, genes such as GhADF30, GhADF33, and GhADF16 showed a rapid increase in expression during late treatment, possibly indicating their role in cold acclimation. These genes could serve as candidate targets for further investigation, aligning with previous findings regarding the involvement of ADF in low-temperature responses in other species like wheat and tomato [4,36].

4.4. Limitations and Prospects

While our study indicates that the GhADF19 gene may be a significant contributor to the cotton plant’s response to abiotic stressors such as drought and salinity, several constraints remain. First, the functional validation of the GhADF19 gene was primarily conducted under experimental conditions, and its performance under diverse environmental conditions remains to be validated. Secondly, although marker-assisted selection (MAS) has the potential to accelerate the breeding process, the quality and quantity of available markers restrict the breadth and efficacy of its implementation. Future research should concentrate on the following areas: firstly, a comprehensive examination of the function of the GhADF19 gene and its regulatory mechanism in response to adversity; secondly, the validation of the function of the GhADF19 gene through transgenic techniques. Thirdly, the development of more precise molecular markers will enhance the accuracy of MAS. Fourthly, the integration of the GhADF19 gene and other QTLs using genome-wide selection methods will facilitate the production of more drought- and salinity-adapted cotton varieties. These strategies will facilitate the effective utilization of the GhADF19 gene in breeding programs to enhance cotton productivity and environmental adaptation.

5. Conclusions

The identification and analysis of the ADF gene family in four cotton species, namely Gossypium hirsutum, Gossypium barbadense Linn, Gossypium raimondii, and Asiatic cotton, revealed a total of 40, 39, 20, and 19 non-redundant ADF gene sequences, respectively. These sequences were further characterized based on their physical and chemical properties, including protein length, molecular weight, and isoelectric point. The analysis showed variations in these properties among the ADF gene family members, which was potentially attributed to unconserved amino acid regions.

Furthermore, phylogenetic analysis divided the ADF family members into four subfamilies, with groups III and IV being relatively larger compared to other plants, which was possibly due to tandem duplication events or chromosomal segment duplication events. Chromosome mapping revealed an uneven distribution of ADF genes across chromosomes and scaffolds. Additionally, gene duplication analysis and collinearity analysis highlighted the expansion of the ADF gene family in cotton through tandem duplication and chromosome segment duplication events.

Conserved gene structures and motifs were identified among ADF family members, suggesting evolutionary conservation within specific branches or subgroups. Analysis of cis-acting elements in the promoter regions revealed their roles in light response, hormone response, growth and development regulation, and stress response.

Transcriptome analysis under various abiotic stresses showed that most GhADFs responded to different degrees of stress. Further validation through qPCR experiments identified four genes, GhADF2, GhADF5, GhADF18, and GhADF19, which exhibited high responses to abiotic stress. These genes were selected for subsequent VIGS verification, confirming their importance in stress responses as evidenced by the worsened growth conditions under drought, low temperature, and salt stress compared to the control group.