Background: The low genetic diversity of Upland cotton limits the potential for genetic improvement. Making full use of the genetic resources of Sea-island cotton will facilitate genetic improvement of widely cultivated Upland cotton varieties. The chromosome segments substitution lines (CSSLs) provide an ideal strategy for mapping quantitative trait loci (QTL) in interspecific hybridization. Results: In this study, a CSSL population was developed by PCR-based markers assisted selection (MAS), derived from the crossing and backcrossing of Gossypium hirsutum (Gh) and G. barbadense (Gb), firstly. Then, by whole genome re-sequencing, 11,653,661 high-quality single nucleotide polymorphisms (SNPs) were identified which ultimately constructed 1211 recombination chromosome introgression segments from Gb. The sequencing-based physical map provided more accurate introgressions than the PCR-based markers. By exploiting CSSLs with mutant morphological traits, the genes responding for leaf shape and fuzz-less mutation in the Gb were identified. Based on a high-resolution recombination bin map to uncover genetic loci determining the phenotypic variance between Gh and Gb, 64 QTLs were identified for 14 agronomic traits with an interval length of 158 kb to 27 Mb. Surprisingly, multiple alleles of Gb showed extremely high value in enhancing cottonseed oil content (SOC). Conclusions: This study provides guidance for studying interspecific inheritance, especially breeding researchers, for future studies using the traditional PCR-based molecular markers and high-throughput re-sequencing technology in the study of CSSLs. Available resources include candidate position for controlling cotton quality and quantitative traits, and excellent breeding materials. Collectively, our results provide insights into the genetic effects of Gb alleles on the Gh, and provide guidance for the utilization of Gb alleles in interspecific breeding.

Hyperspectral technology has enabled rapid and efficient nitrogen monitoring in crops. However, most approaches involve direct monitoring of nitrogen content or physiological and biochemical indicators directly related to nitrogen, which cannot reflect the overall plant nutritional status. Two important photosynthetic traits, the fraction of absorbed photosynthetically active radiation (FAPAR) and the net photosynthetic rate (Pn), were previously shown to respond positively to nitrogen changes. Here, Pn and FAPAR were used for correlation analysis with hyperspectral data to establish a relationship between nitrogen status and hyperspectral characteristics through photosynthetic traits. Using principal component and band autocorrelation analyses of the original spectral reflectance, two band positions (350–450 and 600–750 nm) sensitive to nitrogen changes were obtained. The performances of four machine learning algorithm models based on six forms of hyperspectral transformations showed that the light gradient boosting machine (LightGBM) model based on the hyperspectral first derivative could better invert the Pn of function–leaves in cotton, and the random forest (RF) model based on hyperspectral first derivative could better invert the FAPAR of the cotton canopy. These results provide advanced metrics for non–destructive tracking of cotton nitrogen status, which can be used to diagnose nitrogen nutrition and cotton growth status in large farms.

The desert moss Syntrichia caninervis has proven to be an excellent plant material for mining resistance genes. The aldehyde dehydrogenase 21 (ScALDH21) gene from S. caninervis has been shown to confer tolerance to salt and drought, but it is unclear how the transgene ScALDH21 regulates tolerance to abiotic stresses in cotton. In the present work, we studied the physiological and transcriptome analyses of non-transgenic (NT) and transgenic ScALDH21 cotton (L96) at 0 day, 2 days, and 5 days after salt stress. Through intergroup comparisons and a weighted correlation network analysis (WGCNA), we found that there were significant differences between NT and L96 cotton in the plant hormone, Ca²⁺, and mitogen-activated protein kinase (MAPK) signaling pathways as well as for photosynthesis and carbohydrate metabolism. Overexpression of ScALDH21 significantly increased the expression of stress-related genes in L96 compared to NT cotton under both normal growth and salt stress conditions. These data suggest that the ScALDH21 transgene can scavenge more reactive oxygen species (ROS) in vivo relative to NT cotton and improve cotton resistance to salt stress by increasing the expression of stress-responsive genes, responding quickly to stress stimuli, enhancing photosynthesis and improving carbohydrate metabolism. Therefore, ScALDH21 is a promising candidate gene to improve resistance to salt stress, and the application of this gene in cotton provides new insights into molecular plant breeding.

Water scarcity is the major limiting factor for oasis-desert agricultural production of cotton. It is necessary to improve cotton for drought tolerance and minimize drought-related crop losses, and the transgenic approach is efficient for cotton improvement. In order to evaluate the value of ScALDH21 transgenic cotton (G. hirsutum L.), it was tested in the main cotton region of south Xinjiang, in an environment of extreme drought around the desert. Transgenic cotton, overexpressing aldehyde dehydrogenase gene (ScALDH21) from the desiccation-tolerant moss Syntrichia caninervis in cotton variety Xin Nong Mian 1, was field-tested under six treatments based on three irrigation schedules and two irrigation levels (full (FI) and deficit (DI) irrigation) as follows: root zone model-simulated forecast irrigation (F) (FFI and FDI), soil moisture sensor-based irrigation (S) (SFI and SDI), and flood irrigation based on experience estimates (E) (EFI and EDI) to evaluate growth and yield performances. The results revealed that plant height and leaf area increased significantly in ScALDH21-transgenic cotton genotypes under all treatments. Physiological parameters such as chlorophyll content, net photosynthesis rate, and instantaneous water use efficiency were not significantly highly in transgenic lines compared to non-transgenic plants (NT). However, transgenic lines showed significantly improved yield and superior fiber quality than NT plants regardless of irrigation. The results demonstrate that ScALDH21-transgenic lines were excellent compared to NT plants under different water deficiency conditions. The study also provides guidelines for optimal irrigation protocol and minimum water requirements for the use of the ScALDH21-transgenic cotton lines in arid zones.

Verticillium wilt, caused by the pathogenic fungus Verticillium dahliae, has emerged as a severe threat to cotton globally. However, little is known about the genetic diversity of this pathogen in an infected single cotton plant. In this study, we isolated three new V. dahliae strains from the disease stems of Gossypium hirsutum from the cotton field in Western China and assessed their pathogenicity to the cotton cultivar Xinnongmian-1 and its two transgenic lines, as well as two laboratory strains, VD592 and VD991. These three new V. dahliae strains were identified using DNA barcodes of tryptophan synthase (TS), actin (ACT), elongation factor 1-α (EF), and glyceraldehyde-3-phosphate dehydrogenase (GPD). Moreover, the haplotype analysis revealed that the three new races had distinct haplotypes at the TS locus. Furthermore, the results of culture features and genetic diversity of ISSR (inter-simple sequence repeat) revealed that there were separate V. dahliae strains, which were strong defoliating pathotypes belonging to race 2 type, as determined by particular DNA marker recognition. The identified strains demonstrated varied levels of pathogenicity by leaf disc and entire plant inoculation methods. Conservatively, these strains showed some pathogenicity on cotton lines, but were less pathogenic than the reference strains. The findings revealed that several strong defoliating V. dahliae pathotypes coexist on the same cotton plant. It indicats the importance of regular monitoring as an early warning system, as well as the detection and reporting of virulent pathogen strains and their effects on crop response.

The glycosyltransferase 92 (GT92) gene belongs to the glycosyltransferase gene family. In the plant genome, it is one of the numerous genes involved in sugar metabolism and glycosylation modification. Nonetheless, the GT92 sub-family assumes a vital function in facilitating plants’ adaptation to adverse environments and modulating plant growth, development, and the processes of organogenesis. To date, comprehensive characterization and systematic investigation of GT92 in cotton remain underexplored. In this study, we systematically analyzed the structural features, phylogenetic tree, gene architecture, expression profiles, evolutionary relationships, and selective pressures of GT92 gene family members across four Gossypium species using bioinformatics approaches for the first time. Collectively, 44 GT92 genes were identified, including 14 in G. hirsutum. Based on the phylogenetic tree, GT92 protein sequences from the four cotton species were clustered into five distinct subfamilies. Chromosomal mapping of these genes was performed, and their structural details were visualized. We further predicted cis-acting elements in G. hirsutum GT92 genes and characterized duplication patterns across the four Gossypium species. Ka/Ks ratios of orthologous gene pairs were calculated to investigate selective pressures among the species. RNA-seq data from G. hirsutum and G. barbadense revealed GT92 expression patterns. WGCNA (Weighted Gene Co-expression Network Analysis) identified GhGT92_5 and GhGT92_6 as members of the MEtan module, which was significantly negatively correlated with the 6-hour time point post-drought stress. Mfuzz trend analysis classified GhGT92_5 and GhGT92_6 into Cluster13 and Cluster14, respectively. qRT-PCR validated their roles under drought and salt stress conditions. Subcellular localization showed GhGT92_5 primarily distributed in the plasma membrane and chloroplasts, while GhGT92_6 was localized in the endoplasmic reticulum and chloroplasts. All of these findings have expanded our understanding of the GT92 family members, establishing a basis for more in-depth exploration of the stress-tolerance mechanisms of this gene in cotton.