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IJMSInternational Journal of Molecular Sciences
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26 February 2026

17 Pages

Artificial Selection on the GA2ox Gene Family Contributes to Plant Architecture Improvement in Upland Cotton

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1
School of Agriculture and Biomanufacturing, Zhengzhou University, Zhengzhou 450001, China
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Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
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Authors to whom correspondence should be addressed.
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These authors contributed equally to this work.
Int. J. Mol. Sci.2026, 27(5), 2219;https://doi.org/10.3390/ijms27052219
This article belongs to the Section Molecular Plant Sciences
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Abstract

Gibberellins (GAs) play a crucial regulatory role in the growth and development of cotton (Gossypium hirsutum L.). Through bioinformatics analyses, we identified a total of 39 GA2ox genes (encoding gibberellin 2-oxidases) in the cotton genome, designated GhGA2ox1 to GhGA2ox39. Based on phylogenetic analysis, these genes were classified into five groups. We further examined their gene structures, conserved motifs, and chromosomal distributions, revealing that members within the same group shared similar structural and motif organizations. Collinearity and cis-element analyses provided important insights into the evolutionary history and regulatory potential of the GA2ox gene family in cotton. Notably, using nucleotide diversity (π) and population differentiation (FST) analyses across the entire family, we screened and identified nine candidate genes that underwent strong artificial selection during cotton domestication and improvement. Further haplotype-phenotype association analysis identified GH_D09G0919 (GhGA2ox31) as a key regulator of Plant Height (PH). To validate their regulatory roles, we analyzed the genotype distribution in accessions with extreme phenotypes. The results revealed divergent selection histories for these two loci: the favorable allele of GH_D01G0720 (GhGA2ox23) was already fixed in the tested population, whereas GH_D09G0919 maintained significant natural variation. Specifically, the Hap2 allele of GH_D09G0919 was significantly enriched in the shortest accessions compared to the tallest ones. Importantly, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed that the Hap2 allele drives significantly higher gene expression in leaves, suggesting that enhanced GA catabolism underlies the compact phenotype. Additionally, transcriptomic profiling revealed the tissue-specific expression patterns of candidate genes, implying their functional roles in development. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene (AtGA2ox8) confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. These results uncover valuable genetic resources for molecular breeding to shape compact cotton architecture. Collectively, this study aims to analyze the evolutionary patterns of the cotton GA2ox gene family and to identify key genes that regulate plant height under artificial selection, providing theoretical support for molecular breeding of compact plant types.

1. Introduction

Plant architecture is a major determinant of crop yield, and the optimization of plant height during the “Green Revolution” significantly improved lodging resistance and harvest index [1,2]. Gibberellins (GAs) are key phytohormones that regulate seed germination, stem elongation, root and leaf expansion, floral induction, and fruit formation [3,4,5,6,7], and they serve as the primary determinants of plant height. Gibberellin 2-oxidases (GA2oxs), members of the 2-oxoglutarate–Fe(II) oxygenase superfamily, serve as key regulators of GA catabolism. These enzymes catalyze the 2β-hydroxylation of bioactive GAs (e.g., GA1, GA4, GA9, and GA20) and their precursors (GA12 and GA53), converting them into inactive derivatives such as GA8 and GA34, thereby modulating GA homeostasis [8,9].
GA2ox genes have been identified and characterized in diverse plant species, including rice [10], Arabidopsis thaliana [11], maize [12], and tobacco [13]. Overexpression of GA2ox genes typically reduces bioactive GA levels and results in dwarf phenotypes [14]. Functional characterization in model species has confirmed the conserved role of GA2ox genes in regulating plant architecture. For instance, in rice (Oryza sativa), the overexpression of GA2ox genes results in a semi-dwarf phenotype, increased root density, and higher tiller numbers [10]. Similarly, in Arabidopsis thaliana, increasing GA2ox expression levels significantly reduces bioactive GA content, leading to dwarfism and darker green leaves [11]. These findings indicate that GA2ox genes play evolutionarily conserved roles in plant development. In addition, decreased endogenous GA enhances plant tolerance to abiotic stressors such as drought, salinity, and cold, thereby highlighting GA homeostasis’ critical role in both development and stress-response [15,16,17,18,19].
Plant architecture is a pivotal agronomic trait, shaping crop cultivation practices and management strategies. In upland cotton (Gossypium hirsutum L.), plant architecture governs adaptability to high-density planting and efficiency in mechanized harvesting [20,21,22]. Historically, artificial selection has transformed cotton from a spreading, indeterminate wild perennial into a compact, determinate annual crop [23]. Plant height (PH), a core component of cotton plant architecture and a key target in breeding programs, exerts a crucial influence on resource-use efficiency and yield potential [24]. Previous studies have demonstrated that PH is tightly regulated by gibberellin levels, with GA2ox enzymes playing a negative regulatory role by inactivating bioactive GAs, thereby reducing overall plant height [8,25]. Therefore, we propose that the GA2ox gene in cotton also regulates plant height, and its natural genetic variation serves as a promising genetic resource for developing semi-dwarf ideal types in cotton breeding programs. However, systematic research on the GA2ox gene family in cotton has not yet been conducted, limiting their potential application in cotton breeding.
In this study, we performed a comprehensive genome-wide analysis of the GA2ox family in upland cotton, including phylogeny, gene structure, and chromosomal location. More importantly, to bridge the gap between bioinformatics prediction and breeding application, we integrated population genetics (nucleotide diversity, π; population differentiation, FST) with phenotypic data to identify functional variants. We successfully identified key candidate genes and validated their regulatory effects on plant height through the analysis of accessions with extreme phenotypes. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. Our study combines evolutionary insights with genetic validation to provide new targets for molecular breeding, offering valuable resources for developing cotton varieties with compact architecture suitable for mechanized harvesting.

2. Results

2.1. Identification and Molecular Characterization of the GhGA2ox Gene Family

After removing redundant sequences, a total of 39 GA2ox family members were identified in the G. hirsutum genome. These genes were designated GhGA2ox1 to GhGA2ox39 according to their physical positions on the chromosomes. The physicochemical properties of the GhGA2ox proteins were further analyzed (Table S2).
Within the gene family, GhGA2ox6 and GhGA2ox25 were the longest genes, with gene lengths of 11,790 bp and 12,253 bp, respectively, whereas the other 37 genes ranged from 1021 to 5219 bp. The CDS lengths of the GhGA2ox gene family ranged from 495 to 1149 bp, corresponding to predicted protein sequences that varied from 164 to 382 amino acids, with molecular weights ranging from 19.051 kDa (GhGA2ox11) to 41.791 kDa (GhGA2ox18). Subcellular localization predictions indicated that most GhGA2ox proteins were localized in the cytoplasm and nucleus, while a few were localized in the extracellular matrix. In addition, three members (GhGA2ox9, GhGA2ox11, and GhGA2ox31) were predicted to be localized to the mitochondria, two members (GhGA2ox7 and GhGA2ox27) were predicted to be associated with the plasma membrane, and two members (GhGA2ox12 and GhGA2ox17) were predicted to be localized to the chloroplasts.

2.2. Chromosomal Distribution and Nomenclature of GhGA2ox Genes

Chromosomal mapping revealed that the 39 GhGA2ox genes were unevenly distributed across 20 chromosomes (Figure 1). Among them, 20 genes were located on the At subgenome, while 19 genes were located on the Dt subgenome. Specifically, three members were mapped to each of chromosomes A01, A08, A13, D01, D09, and D13; two members were found on each of chromosomes A05, A06, A09, A10, D05, D06, and D10; and only one GhGA2ox was detected on each of chromosomes A03, A07, A12, D02, D07, D08, and D12.
Figure 1. Chromosomal distribution of GhGA2ox genes in the G. hirsutum genome. The chromosome names are indicated by yellow text, and the specific positions of the GhGA2ox genes are highlighted in red.

2.3. Motif Composition, Exon–Intron Structure, and Phylogenetic Analysis

To investigate the evolutionary relationships of GhGA2ox genes with GA2ox family members from A. thaliana and G. barbadense, a phylogenetic tree was constructed (Figure 2). The results revealed that GA2ox members could be clearly divided into five subfamilies (I, II, III, IV, and V). Subfamily I and II both contained 10 GhGA2ox genes, Subfamily III contained 11 genes, Subfamily IV contained 2 genes, and Subfamily V contained 6 genes, indicating evident divergence of GhGA2ox genes during species evolution.
Figure 2. Phylogenetic analysis of GA2ox genes from three plant species (G. hirsutum., G. barbadense, and A. thaliana). The bootstrap support values are indicated by purple dots at the nodes. The phylogenetic tree is divided into five subfamilies, labeled I–V, which are distinguished by different colored background areas.
Comparative analysis of the evolutionary relationships, gene structures, and conserved motifs of the GhGA2ox family revealed varying degrees of motif loss and structural divergence across the family (Figure 3). In particular, GhGA2ox18 and GhGA2ox37 exhibited substantial motif loss, retaining only five conserved motifs. Taken together, except for GhGA2ox18 and GhGA2ox37, other members within the same subfamily generally exhibited similar gene structures and conserved motif compositions.
Figure 3. Phylogenetic relationships, conserved motifs, domains, and gene structures of GA2ox genes in upland cotton (G. hirsutum). (A) Phylogenetic tree constructed by the neighbor-joining method in MEGA 7 using full-length protein sequences. (B) Distribution of conserved motifs identified with MEME; distinct motifs are shown as colored boxes. (C) Schematic of conserved domains predicted by NCBI Batch CD-Search; colors denote different domain types. (D) Gene structure diagrams showing untranslated regions (UTRs) and coding exons (CDS) based on genome annotation; the x-axis indicates nucleotide length. Genes are displayed in the same order across panels as in (A).

2.4. Cis-Acting Elements in the Promoters of GhGA2ox Genes

To further investigate the potential functions of GhGA2ox genes, cis-acting elements in the promoter regions of all 39 members were analyzed (Figure 4). These cis-elements were primarily classified into four categories: light-responsive elements (e.g., G-box, GT1-motif, Box 4, Box II, AT1-motif, AE-box, and 3-AF3 binding site), hormone-responsive elements (e.g., AuxRR-core, TGA-element, GARE-motif, TCA-element, and ABRE), stress-responsive elements (e.g., abscisic acid (ABA)-responsive element, low-temperature responsive element, TCA-element, GARE-motif, CGTCA-motif, TGACG-motif, MYB-binding site, and anaerobic responsive element), and development-related elements (e.g., RY-element, GATA-motif, and CAT-box).
Figure 4. Cis-acting regulatory elements identified in the promoter regions of GhGA2ox genes.
The presence of such a wide variety of cis-elements suggests that GhGA2ox genes may play key roles in mediating responses to environmental stresses as well as in regulating plant developmental processes.

2.5. Collinearity Analysis of GhGA2ox Gene Family Members

To elucidate the evolutionary mechanisms, particularly duplication events, that contributed to the expansion of the GhGA2ox gene family in upland cotton, an intra-genomic synteny analysis was performed (Figure 5).
Figure 5. Synteny analysis of the GA2ox gene family in upland cotton (G. hirsutum). The inner track and the color gradient scale (from blue to red) in the upper right corner represent the gene density across the chromosomes. The different colored lines in the center connect the segmentally duplicated GhGA2ox gene pairs.
The analysis identified a total of 19 syntenic gene pairs among the 39 GhGA2ox members. Notably, these collinear relationships were found to be almost exclusively inter-subgenomic, linking genes between the At and Dt subgenomes, which is a classic signature of the allotetraploidization event that formed G. hirsutum.
As illustrated in Figure 5, clear homologous syntenic blocks were identified between corresponding chromosomes. For instance, GhGA2ox genes on chromosome A01 showed strong collinearity with those on D01. This pattern was consistently observed across multiple chromosome pairs, including A05–D05, A06–D06, A08–D08, A09–D09, A10–D10, and A13–D13. In contrast, very few or no segmental duplication events (syntenic pairs within the same subgenome, e.g., A01–A03) were detected for this gene family.

2.6. Identification of Candidate GhGA2ox Genes Undergoing Artificial Selection

To investigate the role of the GhGA2ox family in cotton domestication, we performed a comprehensive selection sweep analysis across all 39 GhGA2ox family members. By evaluating nucleotide diversity (π) and population differentiation (FST) in the 1 Mb genomic regions flanking these genes, we successfully identified nine candidate genes (GH_A05G0882, GH_A09G2630, GH_A10G0148, GH_D01G0720, GH_A10G0417, GH_D12G1413, GH_A01G0311, GH_D09G0919 and GH_A08G0065) that exhibited distinct selection signals (Figure 6). Specifically, the analysis revealed that the genetic diversity of cultivated cotton populations (G. hirsutum) was markedly lower than that of wild populations in these regions, indicating “selective sweeps”. Consistently, FST analysis showed high differentiation values between Wild/Landrace and Cultivated populations around these loci. These results suggest that these nine members were putative targets of artificial selection during domestication.
Figure 6. Genetic variation and selection signals of candidate GhGA2ox genes. (A) Nucleotide diversity (π) analysis of nine candidate genes across Wild, Landrace, and Cultivated populations. The green line represents cultivated G. hirsutum, showing reduced diversity in gene regions. (B) Population differentiation (FST) analysis among different populations. The peaks indicate regions with high genetic differentiation. The gray vertical bars indicate the gene body regions. The analysis window is 100 kb with a step size of 20 kb.

2.7. Haplotype-Trait Association and Expression Analysis

Based on the selection signals and sequence variation patterns, we focused on the nine genes with distinct selection signatures to evaluate their effects on plant height via haplotype association analysis (Figure 7A and Figure S1). This analysis identified significant associations between Plant Height (PH) and two genes: GH_D01G0720 (GhGA2ox23) and GH_D09G0919 (GhGA2ox31) (Figure 7A). For GH_D01G0720, statistical analysis showed a significant difference in PH (p = 1.01 × 10−3). The Hap1 was the predominant haplotype (n = 411) and was associated with taller plants. Similarly, GH_D09G0919 also exhibited high significance for PH (p = 4.55 × 10−5), with Hap1 being dominant (n = 423) and associated with significantly higher plant height.
Figure 7. Haplotype association analysis of candidate GhGA2ox genes with plant height. (A) Haplotype analysis of GH_D01G0720 and GH_D09G0919 based on the public core collection. Violin plots show the distribution of Plant Height (PH) for different haplotypes (Hap1 vs. Hap2). The white dots inside the violin plots represent the median values. Statistical significance was determined by one-way ANOVA (* p < 0.05, ** p < 0.01, *** p < 0.001). The sample size (n) for each haplotype is indicated below the x-axis. (B) Validation of GH_D01G0720 and GH_D09G0919 using accessions with extreme phenotypes. The pie charts illustrate the haplotype frequencies within the 10 tallest (High PH Group) and 10 shortest (Low PH Group) accessions selected from the natural population. Hap1 represents the major allele, while Hap2 represents the favorable allele associated with reduced plant height. Note that GH_D01G0720 was fixed (monomorphic for Hap1) in the tested population, whereas GH_D09G0919 maintained significant variation, with Hap2 specifically enriched in the Low PH group. (C) Expression analysis of GH_D09G0919 in representative accessions. qRT-PCR analysis of GH_D09G0919 transcript levels in functional leaves of High-PH (Hap1, n = 8) and Low-PH (Hap2, n = 3) accessions. Each black data point represents a pooled sample from three individual plants. Data are presented as mean ± SE relative to the average expression of the High-PH group. Statistical significance was determined using Student’s t-test (p = 0.016).
To further validate the functional roles of these candidate genes, we analyzed their genotypic distributions using accessions with extreme phenotype (the 10 tallest and 10 shortest varieties selected from our natural population). The results revealed divergent selection histories for these two loci (Figure 7B). For GH_D01G0720, no polymorphism was detected between the High PH and Low PH groups; all 20 accessions carried the Hap1 allele. This indicates that the favorable allele of GH_D01G0720 has likely been fixed in our studied population, limiting its potential for further selection. In contrast, GH_D09G0919 maintained significant genetic variation. In the High PH group, the vast majority of accessions carried the Hap1 allele. Conversely, the Low PH group showed a distinct enrichment of the Hap2 allele (40%), compared to only 20% in the High PH group (Figure 7B). This clear segregation pattern confirms that GH_D09G0919 functions as a key regulator of plant height. To further verify the functional impact of the identified haplotypes, we quantified the transcript levels of GH_D09G0919 in the leaves of representative accessions using qRT-PCR. The expression pattern showed a strong correlation with the plant height phenotype (Figure 7C). The accessions carrying the short-stature associated haplotype (Hap2) exhibited significantly higher transcript levels compared to those carrying the tall-associated haplotype (Hap1) (Student’s t-test, p = 0.016). Notably, the accession with the shortest plant height (MBG248, Hap2) displayed the highest expression level, which was approximately 2.4-fold higher than the average of the Hap1 group. These results suggest that the genetic variation in Hap2 leads to the transcriptional upregulation of GH_D09G0919, thereby enhancing GA catabolism and resulting in a reduced plant height phenotype. Furthermore, transcriptomic profiling revealed tissue-specific expression patterns of these genes (Figure 8).
Figure 8. Tissue-specific expression patterns of candidate GhGA2ox genes. The heatmap illustrates the expression profiles of candidate genes (including GH_D09G0919) across different tissues (e.g., root, stem, leaf, flower, and fiber). The color scale represents the gene expression levels.

2.8. Functional Characterization of the GH_D01G0720 Homolog in Arabidopsis

To further investigate the biological function of GH_D01G0720, we analyzed the phenotype of the T-DNA insertion mutant of its closest Arabidopsis homolog, AtGA2ox8 (AT4G21200). PCR genotyping confirmed the homozygous insertion of T-DNA in the atga2ox8 mutant, as evidenced by the presence of a specific band with the T-DNA primer pair (LBb1.3 + RP) and the absence of amplification with the wild-type primer pair (LP + RP) (Figure 9A). Phenotypic observation revealed that the confirmed homozygous mutant plants exhibited a distinct short-stature phenotype compared to the wild-type (Figure 9B). Statistical analysis showed that the plant height of the mutant lines was significantly reduced by approximately 36% (p = 0.0078) (Figure 9C). The growth inhibition observed in the mutant suggests that the loss of this gene disrupts the delicate homeostasis of GA metabolism, potentially triggering feedback mechanisms that limit vegetative growth. This observation implies that GH_D01G0720 likely plays a similarly conserved role in cotton.
Figure 9. Functional validation of the GH_D01G0720 homolog (AtGA2ox8) in Arabidopsis. (A) PCR genotyping of the atga2ox8 mutant (SALK_040686). Lane M: DNA marker; Lane WT: wild-type (Col-0); Lanes #1 and #2: homozygous mutant lines. The upper panel (or left panel) shows the reaction with wild-type specific primers (LP + RP), where the absence of bands indicates the disruption of the native gene in the mutant. The lower panel (or right panel) shows the reaction with the T-DNA-specific primer (LBb1.3 + RP), where the presence of bands confirms the T-DNA insertion. (B) Phenotypic comparison of 20-day-old wild-type (Col-0) and atga2ox8 plants grown under long-day conditions. The mutant exhibits a reduced height phenotype. (C) Statistical analysis of plant height between Col-0 and Mutant lines. The bar chart represents the mean plant height (cm), with error bars indicating the standard error (SE). Individual data points are shown as gray dots. Statistical significance was determined using Student’s t-test (** p < 0.01).

3. Discussion

Extensive research has demonstrated that GA2ox genes, which belong to the gibberellin oxidase gene family, play a crucial role in gibberellin (GA) metabolism and significantly shape plant architecture [26,27]. Members of the GA2ox family are indispensable for the growth and development of various plants [28,29,30,31]. Previous studies have identified 12 GA2ox genes in maize [12], 11 in grapevine [32], and 10 in soybean [33]. In rice and A. thaliana, 11 and 9 GA2ox family members have been reported, respectively [10,11]. However, GA2ox family members in cotton had not been characterized prior to this study.
In this study, 39 GA2ox genes were identified in the upland cotton genome, distributed across both the At and Dt subgenomes. Phylogenetic analysis revealed that duplicated genes exhibit close evolutionary relationships and share highly similar conserved motifs, including their number, position, and gene structures. These features suggest that the At and Dt subgenomes most likely originated from a common ancestor. Taken together, these results indicate that Whole-Genome Duplication (WGD) was the dominant evolutionary force driving the expansion and retention of the GhGA2ox gene family in upland cotton [22].
In the phylogenetic tree constructed in this study, genes such as GhGA2ox1, GhGA2ox9, GhGA2ox12, GhGA2ox14, GhGA2ox17, GhGA2ox21, GhGA2ox29, GhGA2ox30, GhGA2ox33, and GhGA2ox36 showed high similarity to AtGA2ox4 (AT1G47990) and AtGA2ox6 (AT1G02400) (Figure 2). Given that AtGA2ox4 and AtGA2ox6 function as C19-GA2oxs to inactivate bioactive GAs and repress stem elongation [9], it is inferred that these clustered cotton genes likely serve as key regulators of plant height. To further understand the structural basis underlying the potential functions of these homologous genes, we examined their gene organizations. While most candidate genes maintained conserved structures, analysis revealed that motif losses occurred in specific family members (e.g., GhGA2ox18 and GhGA2ox37), indicating structural divergence. Furthermore, bioinformatic prediction suggested that GhGA2ox proteins are localized in the cytoplasm, nucleus, extracellular matrix, chloroplasts, mitochondria, and plasma membrane (Table S2). Moreover, analysis of cis-acting elements revealed that GhGA2ox promoters are enriched with motifs associated with light responsiveness, hormone signaling, stress response, and plant development. Many of these genes may also be regulated by GA signaling [26]. Interestingly, some promoters lacked GA-responsive elements, suggesting that their functions might be mediated by other factors within the GA signaling pathway, indirectly regulating endogenous GA levels.
Nucleotide diversity (π) and population differentiation (FST) analyses identified nine GhGA2ox members as putative targets of artificial selection during domestication. Among them, haplotype analysis revealed that both GH_D01G0720 and GH_D09G0919 are significantly associated with plant height in the public core collection (Figure 7A). However, our analysis of extreme phenotypes highlighted a distinct divergent fate for these two loci. The favorable allele of GH_D01G0720 appears to have been fixed during historical breeding processes, as no polymorphic sites were detected in our breeding lines. This fixation limits the utility of GH_D01G0720 for further genetic improvement in modern cultivars. Although GH_D01G0720 shows no functional variation in the tested upland cotton population, our functional analysis of its Arabidopsis homolog, AtGA2ox8 (AT4G21200), provides crucial evidence for its regulatory role. Interestingly, the loss-of-function atga2ox8 mutant displayed a short-stature phenotype, contrasting with the elongation often observed in other GA2ox mutants. AtGA2ox8 is a C20-GA2ox that targets GA precursors [9,11]. We hypothesize that this phenotype might be associated with a potential feedback loop system regulating GA homeostasis [26]. However, since direct GA quantification was not performed in this study, this mechanism remains speculative. Future biochemical investigations involving precise GA profiling are required to fully validate this hypothesis and elucidate the complex hormonal dynamics. This suggests that GH_D01G0720 likely plays a conserved and critical role in maintaining the precise homeostasis of GA precursors, which might explain why its function has been fixed during cotton domestication. In contrast, GH_D09G0919 maintains significant genetic variation. Specifically, the allele associated with reduced plant height (Hap2) was notably enriched in the short accessions but remained at a lower frequency in the tall group (Figure 7B). This suggests that GH_D09G0919 represents a valuable and underutilized genetic resource. Introgression of the specific Hap2 allele into elite cultivars offers a promising strategy to shape compact plant architecture suitable for high-density planting and mechanical harvesting.
Transcriptomic profiling provided further insights into the regulatory mechanism of GH_D09G0919. Interestingly, GH_D09G0919 was predominantly expressed in root and leaf tissues, rather than in the elongating stem (Figure 8). Roots are the primary sites for GA biosynthesis, while leaves serve as active pools for bioactive GAs. We propose a “source-sink” regulatory model where GH_D09G0919 modulates plant height by inactivating bioactive GAs or their precursors in the synthesis (root) and source (leaf) organs, thereby reducing the systemic GA pool available for internode elongation [34]. Crucially, our qRT-PCR results reinforce this model by demonstrating that accessions carrying the height-reducing allele (Hap2) maintain significantly higher transcript levels of GH_D09G0919 in leaves compared to those with the tall allele (Hap1). This suggests that the genetic variation in Hap2 leads to a “gain-of-function” expression phenotype, enhancing GA catabolism in source tissues and ultimately constraining vertical growth. This distinct spatial expression pattern suggests a sophisticated regulatory strategy that coordinates whole-plant growth without directly inhibiting stem cell expansion.

4. Materials and Methods

4.1. Genome-Wide Identification and Sequence Characterization

The genome assembly and annotation files of G. hirsutum [35] were downloaded from the CottonGen database (https://www.cottongen.org/, accessed on 21 February 2026). The GA2ox gene family was characterized by two conserved domains: DIOX_N (non-heme dioxygenase in morphine synthesis N-terminal) and 2OG-FeII_Oxy (2-oxoglutarate–Fe(II) oxygenase superfamily). The corresponding Pfam entries (PF14226 and PF03171) were retrieved from the Pfam database (http://pfam.xfam.org/, accessed on 21 February 2026) [36], and initial searches were performed against the G. hirsutum genome using the “hmmersearch” module of TBtools (v2.096) [37]. Candidate GA2ox genes were screened for the presence of both domains. In addition, amino acid sequences of A. thaliana GA2ox proteins were used as queries in local Basic Local Alignment Search Tool (BLAST, v2.17.0) searches, and candidate homologs with E-values < 1.0 × 10−20 were retained. Coding sequences (CDS), genomic DNA sequences, and deduced protein sequences of the candidates were obtained. All putative GA2ox genes were further validated using the CottonFGD database (https://cottonfgd.net/, accessed on 21 February 2026), and their genomic sequence information was extracted with TBtools.

4.2. Chromosomal Localization

To determine the chromosomal distribution of GhGA2ox genes, genomic feature format (GFF) and fasta (FA) files of G. hirsutum were used to extract gene positions and chromosome lengths. Chromosomal mapping was conducted using TBtools, and the identified genes were designated GhGA2ox1 to GhGA2ox39 based on their physical order along the chromosomes.

4.3. Phylogenetic Analysis of the GA2ox Gene Family

Full-length GA2ox protein sequences were aligned using ClustalW (version 2.1) implemented in MEGA (version 7.0) [38]. A phylogenetic tree was constructed using the Neighbor-Joining (NJ) method and evaluated with 1000 bootstrap replicates. Reported GA2ox sequences of A. thaliana and Gossypium barbadense L. were downloaded from Ensembl Plants (https://plants.ensembl.org/index.html, accessed on 21 February 2026) and included for comparison. The phylogenetic tree was visualized and annotated using iTOL (https://itol.embl.de/, accessed on 21 February 2026).

4.4. Gene Structure and Conserved Motif Analysis

Conserved motif distributions were identified using TBtools [39] based on the full-length GA2ox protein sequences. Genomic and CDSs of GhGA2ox genes were retrieved from CottonGen. The XML, NWK, and GFF3 files were then used in TBtools to generate a phylogenetic tree integrating gene structures and conserved motifs.

4.5. Cis-Acting Element Prediction in GhGA2ox Promoters

Promoter sequences (2000 bp upstream of the transcription start site) of each GhGA2ox gene were extracted and submitted to PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 21 February 2026) [40]. Potential cis-acting elements were identified, and their distribution patterns were visualized using TBtools.

4.6. Collinearity Analysis of the GhGA2ox Gene Family

Collinearity relationships among GhGA2ox genes were analyzed using TBtools based on the G. hirsutum genome sequence [39] obtained from CottonGen. Genome-wide sequence alignments and collinearity mapping were conducted to assess gene duplication events and visualize the results.

4.7. Haplotype and Population Genetic Analysis

4.7.1. Plant Materials and Data

Genomic variation data (single nucleotide polymorphisms, SNPs) were retrieved from the CottonMD database [41], encompassing the core collection primarily derived from Ma et al. [42]. This population consists of 419 G. hirsutum accessions collected from diverse geographic origins, including the Yellow River region, Yangtze River region, and Northwestern China, ensuring broad genetic representativeness. The high-density SNP dataset was utilized to characterize the haplotypes of candidate genes (e.g., GH_D09G0919). Phenotypic data for Plant Height (PH) were obtained from the study by Guo et al. [43] and our independent validation experiments. To ensure the accuracy of the association analysis, we performed a validation using accessions with extreme phenotypes. We selected 20 representative accessions from the natural population, consisting of the 10 tallest and 10 shortest varieties, and the genotype frequencies were compared. A sample size of 10 accessions per extreme group was selected to provide adequate statistical power and mitigate the influence of individual genetic background noise. Furthermore, the extreme phenotypes of these selected accessions were highly stable, as they were determined based on phenotypic evaluations across multiple environments.

4.7.2. Haplotype Analysis

Haplotypes for the key candidate genes were defined using SNPs (minor allele frequency, MAF > 0.05) within their respective gene regions. Associations between major haplotypes and phenotypic data (PH) were evaluated using one-way Analysis of Variance (ANOVA). Significance levels were indicated by asterisks: * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Given that this analysis targeted a pre-screened subset of nine candidate genes exhibiting strong selection signals, raw p-values were initially used. Notably, the significant associations identified for GH_D01G0720 and GH_D09G0919 remain robust even when applying a conservative Bonferroni correction for multiple testing (adjusted significance threshold α = 0.05/9 ≈ 0.0055).

4.7.3. Detection of Selection Signals and Population Genetic Analysis

To systematically identify GhGA2ox family members that underwent artificial selection, we calculated nucleotide diversity (π) and population differentiation (FST) for all 39 identified GhGA2ox genes using the resequencing data. The analysis was performed on the genomic regions spanning ~1 Mb surrounding each gene. The calculations were conducted using VCFtools (version 0.1.16) with a sliding window of 100 kb and a step size of 20 kb. This comprehensive scanning approach allowed us to capture a broad selection of footprints across the gene family and identify candidate loci with distinct divergence patterns (high FST peaks and reduction in π) for subsequent trait association analysis.

4.8. RNA Extraction and qRT-PCR Validation

Total RNA was extracted from the functional leaves of representative cotton accessions grown under identical greenhouse conditions, using the RNAprep Pure Plant Kit (Tiangen Biotech, Beijing, China) according to the instructions. To minimize individual plant variation, each biological replicate consisted of pooled leaf tissue from three independent plants. The extracted RNA was converted into cDNA using the HiScript III All-in-one RT SuperMix Perfect for qPCR (Vazyme) to serve as the template for quantitative real-time PCR (qRT-PCR). The specific primers and internal reference gene (GhActin) sequences are listed in Table S1. qRT-PCR was carried out on an ABI 7500 System according to the manufacturer’s protocol. The qRT-PCR analysis was performed using three independent biological replicates (each with three technical replicates), and the relative expression levels were calculated using the 2 − Δ Δ C t   method. Prior to relative quantification, the amplification efficiencies of all primer pairs were evaluated using standard curves and were confirmed to be within the acceptable range of 90–110%. The specific efficiency values for each primer are listed in Supplementary Table S1. Statistical significance was determined using Student’s t-test (p < 0.05).

4.9. Phenotypic Analysis of Arabidopsis Mutants

The T-DNA insertion mutant for the Arabidopsis homolog AtGA2ox8 (AT4G21200), designated as atga2ox8 (SALK_040686), was obtained from Arashare (http://www.arashare.cn/, accessed on 21 February 2026). Genomic DNA was extracted from fresh leaves using the cetyltrimethylammonium bromide (CTAB) method. Genotyping was performed using gene-specific primers (LP and RP) to detect the wild-type allele and a T-DNA border primer (LBb1.3) combined with RP to detect the T-DNA insertion; the specific sequences of these primers are listed in Supplementary Table S1. Homozygous mutant lines and wild-type (Col-0) plants were grown in a growth chamber under long-day conditions (16 h light/8 h dark) at 22 °C. Phenotypic traits, including plant height, were measured at 20 days after germination.

5. Conclusions

In this study, we performed a comprehensive genome-wide analysis of the GA2ox gene family in G. hirsutum, identifying 39 members classified into five subfamilies. Evolutionary analyses revealed that Whole-Genome Duplication (WGD) and purifying selection were the primary driving forces for family expansion and retention. Crucially, by integrating selection sweep analysis with the analysis of extreme phenotypes, we pinpointed GH_D09G0919 (GhGA2ox31) as a key domestication gene regulating cotton architecture. Furthermore, functional characterization of the GH_D01G0720 ortholog in Arabidopsis confirmed the conserved role of this gene family in regulating plant height and maintaining GA homeostasis. Expression analysis further confirmed that the height-reducing allele (Hap2) drives significantly higher transcriptional activity, providing a mechanistic basis for the compact phenotype. Unlike GH_D01G0720, which has been fixed in the tested population, GH_D09G0919 retains valuable natural variation associated with reduced plant height. Collectively, our findings highlight GH_D09G0919 as a vital candidate target for molecular breeding to improve cotton architecture for mechanized harvesting.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms27052219/s1.

Author Contributions

T.W.: Bioinformatic analysis, conducted experiments, and wrote the original draft; T.W., K.X., H.Y., S.Y. and J.G.: analyzed the data; Y.Y., H.S. and G.L.: conceived and designed the experiments; G.L.: writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Key R&D Program of Henan Province (Grant No. 241111114200), the Independent Fund of State Key Laboratory of Cotton Bio-breeding and Integrated Utilization (Grant Nos. CB2025C12 and CB2024C05), the Natural Science Foundation of Xinjiang Uygur Autonomous Region (2025D01A18), the Kashgar Regional Science and Technology Plan (KS2024014), the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences (Grant No. CAAS-ASTIP-2016-ICR) and the China Agriculture Research System—Cotton (Grant No. CARS-15-02).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.

Acknowledgments

We are grateful for the computational resource support by the National Supercomputing Center in Zhengzhou.

Conflicts of Interest

The authors declare no conflicts of interest.

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