Background Mepiquat chloride (MC) is a widely used plant growth regulator in cotton (Gossypium hirsutum L.). It regulates endogenous hormone content and crosstalk to control plant height and promote lateral root (LR) development. However, the roles of cytokinins (CTKs) in the MC-induced increase in LR number in cotton seedlings remain unclear. Therefore, in this study, whole-genome transcriptome analysis was performed to elucidate the molecular mechanisms, CTK transformation, and CTK signaling pathway response to MC in cotton roots.
Results In the present study, MC reduced the contents of the active CTK trans-zeatin (tZ) and N⁶-isopentenyladenine (iP) but increased the levels of the nucleoside CTK trans-zeatin riboside (tZR) and N⁶-isopentenyladenine riboside (iPR). RNA-seq data showed that the CTK biosynthesis genes GhIPTs and active CTK catabolism genes GhCKXs were obviously upregulated after MC treatment. The CTK-activating enzyme gene GhLOGs was repressed compared with the control. Furthermore, MC inhibited the expression of GhAHK4 and GhARR2/12, which are involved in the CTK signaling pathway, and activated the IAA-IAA14-ARF7/19 signaling module. Meanwhile, MC increased the expression levels of genes involved in sucrose synthesis, the cell cycle, cell division, and cell wall biosynthesis pathways. Silencing the GhCKX family separately decreased the LR number and active indole-3-acetic acid (IAA) level. The expression levels of GhPIN1, GhARF7, GhARF19, GhLBD16, GhLBD18, GhLBD29, and GhLBD33 were downregulated, but GhARR2/12 and GhIAA14 were upregulated. The total content of active CTKs was noticeably increased. The results of silencing the GhLOGs family were opposite to those of silencing GhCKXs. Silencing GhARR12 could upregulate GhPIN1 expression and increase LR number. In addition, the silenced GhCKXs, GhLOGs, and GhARR12 were less responsive to MC-induced LR growth than the control.
Conclusion These results suggested that MC treatment could upregulate CTK-nucleoside biosynthesis and CTK metabolism genes to decrease active CTK levels, promoting crosstalk between CTKs and auxin signaling pathways to enhance LR initiation.

Background Aquaporins (AQPs) are integral membrane proteins belonging to the major intrinsic protein (MIP) family, playing a crucial role in water transport, cell elongation, and stress responses. However, their evolutionary dynamics and functional roles in Gossypium species remain poorly characterized.
Results In the present study, a total of 55, 54, 54, 103, 106, 108, and 104 AQP genes were found in G. herbaceum, G. arboreum, G. raimondii, G. barbadense, G. tomentosum, G. mustelinum, and G. darwinii, respectively. Phylogenetic analysis classified them into five conserved subfamilies (PIP, TIP, NIP, SIP, and XIP), with 95 genes showing synteny across species and 17 displaying divergence, suggesting subgenome differentiation. Transcriptome analysis revealed that specific GbAQP genes are involved in early salt stress responses and fiber development. Physiological assays demonstrated stronger salt tolerance in tetraploid cottons, particularly G. darwinii, compared with diploids. Co-expression network analysis linked AQPs to abiotic stress and fiber traits, and virus-induced gene silencing (VIGS) confirmed four AQP genes as critical for salt tolerance.
Conclusion This study provides comprehensive insights into the evolution, expression, and functional roles of AQPs in cotton, identifying key candidate genes for improving salt tolerance and fiber quality in Gossypium species.

One of the solutions to the global warming risk and other climate issues is to concentrate on research and development of utilizing biomass as a fossil fuel alternative. The current estimate of cotton residue waste in the world is about 50 million tons. This massive volume of biomass waste should be turned into clean energy to avert burning the stalks in open fields after cotton harvesting. Therefore, harmful emissions such as CO₂ will be reduced. This study aims to investigate the published literature to comprehend the bioenergy production from the thermal treatment of cotton stalks, including combustion, pyrolysis, carbonization, torrefaction, liquefaction, and gasification. Furthermore, the future outlook, utilization, and prospective challenges of agricultural biomass for biofuel production are discussed. According to the literature, biochar and bio-oil derived from cotton stalks have high heating values of about 27.5 and 37.2 MJ·kg^-1, respectively. These values are double those of cotton stalk raw materials, which make it a good candidate for bioenergy production. This article offers valuable insight into cotton stalk utilization via thermochemical treatment and provides a solid reference for researchers, policymakers, and other stakeholders in this field.

Background Plant natriuretic peptides (PNPs) are a class of peptide hormones that regulate plant responses to salt stress, water balance, and pathogen attacks. However, the precise underlying role of PNPs in plant defense mechanisms remains poorly understood.
Results In this study, we investigated the role of the cotton gene GhEG45 in plant response to Verticillium dahliae infection. GhEG45 overexpression in cotton (Gossypium hirsutum) enhanced resistance to V. dahliae by increasing the expression levels of salicylic acid (SA)-related defense genes and upregulating antioxidant activities. GhEG45 expression was significantly induced by both V. dahliae infection and exogenous treatments with SA, hydrogen peroxide (H₂O₂), and other stress signals, which indicates its potential involvement in modulating plant defense mechanisms via SA signaling, oxidative stress pathways, and cell wall-based defenses. Transcriptomic analysis showed that GhEG45 regulates SA signaling and reactive oxygen species (ROS) metabolism. GhEG45 silencing via virus-induced gene silencing (VIGS) increased susceptibility to V. dahliae, impaired SA signaling, and disrupted ROS regulation.
Conclusions This study provides evidences that GhEG45 plays a pivotal role in defense against V. dahliae infection in cotton, primarily by regulating SA signaling and ROS metabolism. Although GhEG45 shares some functional characteristics with PNPs, further structural and biochemical studies are needed to comprehensively categorize GhEG45 as a natriuretic peptide. Our findings suggest that GhEG45 enhances cotton resistance to V. dahliae by potentiating defense responses.

Background Cotton is an important crop providing the most natural fibers all over the world. The cotton genomics community has utilized whole genome sequencing data to construct an elite gene pool in which functional genes are related to agronomic traits. However, the functional validation of these genes is hindered by time-consuming and inefficient genetic transformation methods. Thus, establishing a transient transformation system of high efficiency is necessary for cotton genomics.
Results To improve the efficiency of transient transformation, we used the protoplasts isolated from the etiolated cotyledon as recipient. The enzymatic digestion buffer comprised 1.5% (w/v) cellulase, 0.75% (w/v) macerozyme, and 1% hemicellulase, osmotically buffered with 0.4 mol·L⁻¹ mannitol. After 5 h of dark incubation at 25 ˚C, uniform cotton protoplasts were successfully isolated with a yield of 4.6 × 10⁶ protoplasts per gram (fresh weight) and 95% viability. We incubated 100 μL protoplasts (2.5 × 10⁵·mL⁻¹) with 15 μg plasmid in the solution of 0.4 mol·L⁻¹ mannitol and 40% PEG 4000 for 15 min, ultimately achieving an optimal transient transfection efficiency of 71.47%.
Conclusions This transient system demonstrated effective utility in cellular biology research through successful applications in subcellular localization analyses, bimolecular fluorescence complementation (BiFC) verification, and prime editing vector validation. Through systematic optimization, we established an efficient and expedited protoplast-based transient transformation system and successfully applied this platform to cotton functional genomics studies.

Background The geo-traceability of cotton is crucial for ensuring the quality and integrity of cotton brands. However, effective methods for achieving this traceability are currently lacking. This study investigates the potential of explainable machine learning for the geo-traceability of raw cotton.
Results The findings indicate that principal component analysis (PCA) exhibits limited effectiveness in tracing cotton origins. In contrast, partial least squares discriminant analysis (PLS-DA) demonstrates superior classification performance, identifying seven discriminating variables: Na, Mn, Ba, Rb, Al, As, and Pb. The use of decision tree (DT), support vector machine (SVM), and random forest (RF) models for origin discrimination yielded accuracies of 90%, 87%, and 97%, respectively. Notably, the light gradient boosting machine (LightGBM) model achieved perfect performance metrics, with accuracy, precision, and recall rate all reaching 100% on the test set. The output of the LightGBM model was further evaluated using the SHapley Additive exPlanation (SHAP) technique, which highlighted differences in the elemental composition of raw cotton from various countries. Specifically, the elements Pb, Ni, Na, Al, As, Ba, and Rb significantly influenced the model's predictions.
Conclusion These findings suggest that explainable machine learning techniques can provide insights into the complex relationships between geographic information and raw cotton. Consequently, these methodologies enhances the precision and reliability of geographic traceability for raw cotton.

Background The bromodomain (BRD) proteins play a pivotal role in regulating gene expression by recognizing acetylated lysine residues and acting as chromatin-associated post-translational modification-inducing proteins. Although BRD proteins have been extensively studied in mammals, they have also been characterized in plants like Arabidopsis thaliana and Oryza sativa, where they regulate stress-responsive genes related to drought, salinity, and cold. However, their roles in cotton species remain unexplored.
Results In this genome-wide comparative analysis, 145 BRD genes were identified in the tetraploid species (Gossypium hirsutum and G. barbadense), compared with 82 BRD genes in their diploid progenitors (G. arboreum and G. raimondii), indicating that polyploidization significantly influenced BRD gene evolution. Gene duplication analysis revealed 78.85% of duplications were segmental and 21.15% were tandem among 104 in-paralogous gene pairs, contributing to BRD gene expansion. Gene structure, motif, and domain analyses demonstrated that most genes were intron-less and conserved throughout evolution. Syntenic analysis revealed a greater number of orthologous gene pairs in the Dt sub-genome than in the At sub-genome. The abundance of regulatory, hormonal, and defense-related cis-regulatory elements in the promoter region suggests that BRD genes play a role in both biotic and abiotic stress responses. Protein-protein interaction analysis indicated that global transcription factor group E (GTE) transcription factors regulate BRD genes. Expression analysis revealed that BRD genes are predominantly involved in ovule development, with some genes displaying specific expression patterns under heat, cold, and salt stress. Furthermore, qRT-PCR analysis demonstrated significant differential expression of BRD genes between the tolerant and sensitive genotype, underscoring their potential role in mediating drought and salinity stress responses.
Conclusions This study provides valuable insights into the evolution of BRD genes across species and their roles in abiotic stress tolerance, highlighting their potential in breeding programs to develop drought and salinity tolerant cotton varieties.

Background Cotton is an industrial crop renowned for its multifaceted applications in the textiles, pharmaceuticals, and biofuel industries. Plant regeneration through somatic embryogenesis (SE) plays a crucial role in the genetic improvement of cotton. There is a strong correlation between SE and zygotic embryogenesis (ZE) in plants. Furthermore, the strategy of ectopic expression of cotton genes into the model plant Arabidopsis has been a widely accepted approach for functional study.
Result Based on previous spatial transcriptomics of cotton somatic embryos, two genes, GhHAT5 and GhCRK29, were identified. They are highly expressed in cotyledon and epidermal cells of cotton cotyledonary embryos, respectively. In this study, GhHAT5 and GhCRK29 were ectopically expressed in Arabidopsis to investigate their functions. The result showed that in Arabidopsis zygotic embryos, the overexpression of GhHAT5 promoted the development of apical embryonic upper-tier cells and embryonic cotyledon, while the overexpression of GhCRK29 promoted the development of apical embryonic lower-tier cells and embryonic radicle. Given the similarities between somatic and zygotic embryogenesis, these findings suggest that GhHAT5 and GhCRK29 are involved in cotton SE. We also speculate that these genes may promote the expression of the Arabidopsis endogenous gene AtSCR, which is crucial for embryonic development.
Conclusion These results revealed that GhHAT5 and GhCRK29 regulate embryonic development and are essential in advancing our understanding of cotton SE and facilitating targeted genetic manipulation strategies to improve industrial crop traits and agricultural sustainability.

Cotton is an essential agricultural commodity, but its global yield is greatly affected by climate change, which poses a serious threat to the agriculture sector. This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton. This paper discusses the effects of rising temperatures, changing precipitation patterns, and extreme weather events on cotton yield. It then explores various genomic strategies, such as genomic selection and marker-assisted selection, which can be used to develop stress-tolerant cotton varieties. The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production. Furthermore, this paper presents advanced prospects, including genomic selection, gene editing, multi-omics integration, highthroughput phenotyping, genomic data sharing, climate-informed breeding, and phenomics-assisted genomic selection, for enhancing stress resilience in cotton. Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change, ensuring the sustainable and prosperous future of cotton production.