Plant height is a key agronomic trait that influences plant architecture and mechanical harvesting suitability in cotton; however, the molecular mechanisms underlying its dynamic development remain unclear. In this study, two recombinant inbred line (RIL) populations sharing CCRI127 as a common paternal parent (RIL-GH07, n = 150; RIL-2358B, n = 276) were developed. Based on stable plant-height performance across multiple environments, tall and short extreme lines were selected from the two RIL populations for transcriptome sequencing. By integrating differential expression analysis with weighted gene co-expression network analysis (WGCNA), we identified hub genes associated with cotton plant height development, characterized the molecular features and core pathways governing dynamic stem elongation at different growth stages, thereby providing insights into the transcriptional regulation of plant height development in cotton. The two RIL populations showed broadly similar plant-height growth patterns, with slow elongation at 15 DOS, rapid elongation during 30-60 DOS, and reduced growth after 70 DOS. Transcriptome differential expression analysis identified 15,052 non-redundant DEGs, which exhibited clear population- and stage-specific expression patterns. In the GH07 population, the largest number of DEGs was detected at 15 DOS (7193), whereas in the 2358B population relatively large numbers of DEGs were maintained at both 30 DOS (3839) and 70 DOS (3118). Analysis of DEGs shared by the two populations across four developmental stages showed that, in addition to genes with consistent expression trends, each stage also contained a substantial number of DEGs with opposite expression directions. WGCNA identified 25 gene expression modules, among which the green and yellow modules were significantly positively correlated with plant height. Functional enrichment analysis indicated that genes in these two modules were mainly enriched in hormone regulation and signal transduction, protein modification and degradation, and intracellular transport. Seven hub genes were identified by integrating intramodular connectivity and kME values. Functional prediction suggested that these genes may play important roles in cotton plant height development. This study provides genetic resources and a theoretical basis for subsequent functional validation of cotton plant height-related genes and the improvement of plant architecture in cotton.

Climate change has increased the sensitivity of cropping systems to environmental variability, making the genetic dissection of G × E and phenotypic plasticity essential for adaptive breeding. In this study, a recombinant inbred line population of upland cotton was evaluated across 16 environments from multi-year and multi-location field trials to assess the plasticity of yield- and fiber-quality traits. By integrating the Finlay–Wilkinson regression model with CERIS sliding-window analyses, 13 key meteorological factors and 4 principal component variables were identified, together with their effective time windows. QTL mapping based on trait plasticity slopes and environmental response slopes detected 172 environment-associated loci. A major locus at 188 Mb on chr10 influenced boll weight and seed index in response to multiple environmental variables, including photoperiod, cumulative radiation, growing degree days, and the product of radiation and photoperiod, suggesting a key regulatory site for environmental signal perception. Haplotype analysis further supported functional divergence of alleles within this region in relation to environmental adaptation. Overall, this study identifies critical environmental factors shaping cotton yield and fiber quality and reveals multiple G × E–related loci underlying environmental responsiveness and phenotypic plasticity, providing a theoretical foundation for environmentally informed precision breeding.

Soil salinization significantly limis crop yield and lowers produce quality. Wild plant species have developed various strategies to cope with soil salinity. However, the molecular responding mechanism to salt stress of domesticated crops is still open to discussion. Combining analysis of quantitative trait locus (QTL) mapping and transcriptome sequencing is an effective approach to identify candidate genes and study their regulation mechanisms of plant salt tolerance. In this study, 294 BC5F3:5 chromosome segment substitution lines (CSSLs), which were constructed by introgressing chromosome segments of Gossypium barbadense Hai1 into G. hirsutum CCRI36 background, were utilized to evaluate relative germination rate (RGR) of seeds and relative survival rate (RSR) of seedlings under NaCl stress. Two salt-tolerant (ST) and salt-sensitive (SS) lines were screened from the CSSLs. With the basis of the previous SSR-based genotyping data, a total of 14 QTLs of RGR and RSR relating to salt tolerance were detected. Meanwhile, RNA-seq and physiological and biochemical indexes of ST and SS were detected. With the combination of weighted gene co-expression network analysis (WGCNA) and QTL intervals, we identified nine hub genes, four of which have nonsynonymous mutations in the protein sequences between G. hirsutum and G. barbadense. The unqiue common candidate gene located between qRGR-12–1 and qRSR-12–1, namely GH_A12G0809, were chosen to conduct functional validation vis VIGS, which confirmed its negative regulatory contribution to salt tolerance in cotton. Our results establish a foundation for elucidating the molecular mechanisms governing cotton's defense against salt stress.

The DUF538 gene family, harboring unknown functional proteins, has been reported to take active roles in plant development and response to adversities, while few studies of genome-wide identification and functional verification have been performed in cotton. Hence, two ancestral diploid species, G. arboretum and G. raimondii, and two cultivated tetraploid ones, G. hirsutum and G. barbadense, were chosen in this study to investigate the cotton DUF538 gene family, resulting in 37, 37, 70, and 70 members identified, respectively. A phylogenetic tree was constructed on these cotton DUF538 genes, together with 22 A. thaliana ones, which were divided into seven groups unevenly distributed across nearly all chromosomes. High-degree conservatism, while rich in diversity, was separately observed in gene structure and conserved motif analyses between the same groups and different groups, and a great number of gene-replication events were detected from intraspecific and interspecific collinearity analyses, implying this was the driving force for DUF538 family expansion. Multiple cis-acting elements relevant to adversity-stress responses were found in the promoter region, which were consistent with the transcriptome expression analyses in response to low-temperature and drought stress and Verticillium wilt infection. Coincidentally, GhDUF538-7 showed the core position in the protein-protein interaction network and was identified in the overlapping region of the interval of four reported VW resistance-related QTLs. The gene function of GhDUF538-7 was verified via gene cloning, relative expression-pattern detection, and virus-induced gene silencing (VIGS) experiment. The TRV:DUF538-7 plants showed more serious VW symptoms, significantly severe disease indices, relatively higher fungal biomass, and increased brown vascular bundles compared with TRV:00 plants. Significantly lower expression levels of marker genes PR4 and MYC2 in jasmonate signaling pathways indicated GhDUF538-7 as a potentially positive regulatory factor in plant defense via hormone signal transduction. This study not only broadened the research perspective of evolution and functional differentiation of the cotton DUF538 gene family, but it also revealed the cooperative relationship between DUF538-7 and the JA pathway for further molecular mechanisms of cotton resistance to VW infection.

Leucine-rich repeat extensins (LRXs) are essential regulators of plant development, cell wall integrity, and stress responses. However, genome-wide LRX studies in cotton are limited. Analysis of four Gossypium species identified 29, 28, 16, and 16 LRX genes in G. hirsutum, G. barbadense, G. arboreum, and G. raimondii, respectively. Phylogenetic analysis resolved these 89 genes into four subfamilies (I-IV). Structural annotation revealed that cotton LRX family members exhibit conserved domain architectures. This finding was corroborated by motif analysis, which revealed notable conservation in the motif compositions of most cotton LRX proteins, suggesting functional conservation across evolutionary lineages. Distinct spatiotemporal expression patterns were uncovered between G. hirsutum and G. barbadense. Prolonged exposure to extreme temperatures induced widespread down-regulation of most GhLRX genes, whereas genes in subgroup IV were significantly up-regulated under salt and drought stress conditions, respectively. Notably, GhLRX7 showed a more proactive responding profile to Verticillium wilt (VW) infection, which was therefore selected for functional validation employing virus-induced gene silencing in the cotton cultivars MBI9626 and CCRI36. Phenotypic analysis of silenced plants revealed exacerbated disease symptoms compared to wild-type controls, providing direct evidence implicating GhLRX7 as a key contributor to defense against VW.

Verticillium wilt (VW) is a soil-borne fungal plant disease. Gossypium hirsutum varieties with the widest planting area are highly susceptible to VW pathogens, because their narrow genetic background of germplasm resources causes difficulties in cultivating VW-resistant varieties through intraspecific breeding. Therefore, G. barbadense cultivars, harboring a natural VW resistance, become ideal donor materials to cultivate high-yield and multi-resistance chromosome segment substitution lines (CSSLs) through hybridization and backcrossing with G. hirsutum receptor and recurrent parent. In order to investigate the molecular mechanism of cotton response to VW infection, a BC5F3:5 CSSL MBI9626 and its parents, CCRI36 (G. hirsutum) and Hai1 (G. barbadense), were chosen to perform transcriptome and metabolome sequencing on their root samples at 0, 7, and 15 days after inoculation (DAI) of V. dahliae V991. In total, 36,564 differentially expressed genes (DEGs) and 102 differentially accumulated metabolites (DAMs) were separately identified from 12 pairwise comparison groups among the 27 samples. Of those, 125 common DEGs were found to participate in the biological processes of oxylipin metabolism, jasmonic acid (JA) biosynthesis/metabolism, and response to wounding in Gene Ontology (GO) enrichment analyses, while most of the DAMs were significantly enriched in tyrosine, purine, and phenylalanine metabolism pathways in enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG). Having performed a conjoint KEGG analysis of all the DEGs and DAMs, we found two commonly enriched pathways, namely plant hormone signal transduction and flavonoid biosynthesis, which were consistent with the enrichment annotations of the significant model in weighted gene co-expression network analysis on the 2091 DEGs identified by an intersection of the genes in 40 previous QTLs and the total DEGs of this RNA-seq data. Among the ABA signaling pathway, the gene GH_D12G0236 (GHABF3) was selected to be used to perform virus-induced gene silencing (VIGS) verification in CCRI36 and MBI9626, and GHABF3-silenced plants showed a more serious wilting phenotype, an increased disease index (DI), and higher accumulation of fungal biomass compared to their empty-vector plants. These results provide a high-efficiency strategy for screening vital genes affecting cotton VW resistance, and lay a solid foundation for further cotton molecular breeding.

Cotton is a crucial cash crop widely valued for its fiber. It is an important source of natural fiber and has diverse applications. Improving fiber quality is of significant economic and agricultural importance. Purple acid phosphatases (PAPs) are multifunctional enzymes critical for plant cell wall biosynthesis, root architecture modulation, low-phosphorus stress adaptation, and salt/ROS stress tolerance. In this study, a comprehensive genome-wide analysis of the PAP gene family was performed for four cotton species (G. hirsutum, G. barbadense, G. raimondii, and G. arboreum) to explore its potential role in improving fiber quality. A total of 193 PAP genes were identified in these species, revealing several conserved domains that contribute to their functional diversity. Phylogenetic analysis showed that the cotton PAP2 genes exhibited high homology with NtPAP12, a cell wall synthesis-related gene. Using cotton varieties with contrasting fiber thickness (EZ60, micronaire 4.5 vs. CCRI127, micronaire 3.5), qRT-PCR analysis demonstrated significantly higher expression levels of GhPAP2.2, GhPAP2.6, GhPAP2.8, and GhPAP2.9 in EZ60 fibers during 20–25 DPA compared to CCRI127. These results highlight the potential influence of PAP genes on cotton fiber development and provide valuable insights for improving fiber quality in cotton breeding.

The BSL gene family, comprised of phosphatase genes with kelch domains, plays vital roles in plant responses to brassinosteroid (BR) signaling and immune reactions to abiotic stress. However, there is no BSL-related reports in cotton, which has been regarded as an ideal crop for investigating genome ploidy and tolerance pioneer. In this study, a key drought response gene GHBSL7 was identified via genome-wide analysis of evolutionary trajectories and responses to abiotic stresses of cotton BSL genes. Functional identification using VIGS silence and RNA-seq revealed that GHBSL7 may participate cotton responses to drought through regulating the homeostasis of ROS and glycolytic pathway by regulating TcTPI and GAPDH genes in the central metabolic network. This study provides fundamental insights into the interplay of phytohormone signaling and molecular targets for future development of drought-tolerant cotton cultivars.

Understanding the influence of environmental factors on cotton performance is crucial for enhancing yield and fiber quality in the context of climate change. This study investigates genotype-by-environment (G×E) interactions in cotton, using data from 250 recombinant inbred lines (CCRI70 RILs) cultivated across 14 diverse environments in China’s major cotton cultivation areas. Our findings reveal that environmental effects predominantly influenced yield-related traits (boll weight, lint percentage, and the seed index), contributing to 34.7% to 55.7% of their variance. In contrast fiber quality traits showed lower environmental sensitivity (12.3–27.0%), with notable phenotypic plasticity observed in the boll weight, lint percentage, and fiber micronaire. Employing six machine learning models, Random Forest demonstrated superior predictive ability (R2 = 0.40–0.72; predictive Pearson correlation = 0.63–0.86). Through SHAP-based interpretation and sliding-window regression, we identified key environmental drivers primarily active during mid-to-late growth stages. This approach effectively reduced the number of influential input variables to just 0.1–2.4% of the original dataset, spanning 2–9 critical time windows per trait. Incorporating these identified drivers significantly improved cross-environment predictions, enhancing Random Forest accuracy by 0.02–0.15. These results underscore the strong potential of machine learning to uncover critical temporal environmental factors underlying G×E interactions and to substantially improve predictive modeling in cotton breeding programs, ultimately contributing to more resilient and productive cotton cultivation.

Cottonseed is a globally significant oilseed crop due to its high contribution to vegetable oil supply. The process of lipid accumulation is essential for seed maturation and oil buildup. In this study, we analyzed lipid metabolites and gene expression patterns related to fatty acid synthesis in two cotton genotypes with varying oil content. Our lipid analysis identified 588 kinds of lipids in developing embryos of upland cotton, with glycerophospholipids (64.29 %), glycerolipids (17.69 %), and saccharolipids (13.61 %) being the main components. Transcriptome analysis of key genes involved in fatty acid biosynthesis and lipid droplet formation revealed potential regulatory regions influencing lipid content in developing embryos of upland cotton. This research provides valuable insights into the lipidome profiles during embryo development and lays the groundwork for future investigations on lipid accumulation in economically important crops.

Arabinogalactan proteins (AGPs) constitute a diverse class of hydroxyproline-rich glycoproteins implicated in various aspects of plant growth and development. However, their functional characterization in cotton (Gossypium spp.) remains limited. As a globally significant economic crop, cotton serves as the primary source of natural fiber, making it essential to understand the genetic mechanisms underlying its growth and development. This study aims to perform a comprehensive genome-wide identification and characterization of the AGP gene family in Gossypium spp., with a particular focus on elucidating their structural features, evolutionary relationships, and functional roles. A genome-wide analysis was conducted to identify AGP genes in Gossypium spp., followed by classification into distinct subfamilies based on sequence characteristics. Protein motif composition, gene structure, and phylogenetic relationships were examined to infer potential functional diversification. Subcellular localization of a key candidate gene, GhAGP50, was determined using fluorescent protein tagging, while gene expression patterns were assessed through β-glucuronidase (GUS) reporter assays. Additionally, hormonal regulation of GhAGP50 was investigated via treatments with methyl jasmonate (MeJA), abscisic acid (ABA), indole-3-acetic acid (IAA), and gibberellin (GA). A total of 220 AGP genes were identified in Gossypium spp., comprising 19 classical AGPs, 28 lysine-rich AGPs, 55 AG peptides, and 118 fasciclin-like AGPs (FLAs). Structural and functional analyses revealed significant variation in gene organization and conserved motifs across subfamilies. Functional characterization of GhAGP50, an ortholog of AGP18 in Arabidopsis thaliana, demonstrated its role in promoting epidermal hair formation in leaves and stalks. Subcellular localization studies indicated that GhAGP50 is targeted to the nucleus and plasma membrane. GUS staining assays revealed broad expression across multiple tissues, including leaves, inflorescences, roots, and stems. Furthermore, hormonal treatment experiments showed that GhAGP50 expression is modulated by MeJA, ABA, IAA, and GA, suggesting its involvement in hormone-mediated developmental processes. This study presents a comprehensive genome-wide analysis of the AGP gene family in cotton, providing new insights into their structural diversity and functional significance. The identification and characterization of GhAGP50 highlight its potential role in epidermal hair formation and hormonal regulation, contributing to a deeper understanding of AGP functions in cotton development. These findings offer a valuable genetic resource for future research aimed at improving cotton growth and fiber quality through targeted genetic manipulation.

Cotton is a widely grown crop to produce natural textile fiber, and improving the fiber strength (FS) is one of the main targets that cotton breeders focus on. The long-term natural selection and domestication have produced abundant germplasm resources of Gossypium hirsutum, and exploring genetic underpinnings underlying these FS innovation in elite collections is crucial. PCAMP is proposed as a most optimized NGS based bulked segregant analysis (NGS-BSA) for the high-resolution identification of markers linked to specific genomic regions through pairwise comparing multiple BSA bulks. In this study, we firstly applied PCAMP to resolved the FS genetic architecture in G. hirsutum cv. CCRI127. As an extension for PCAMP approach, graded bulks were constructed using F-2 segregants with the FS phenotype revalidated by F-2:3 lines, and then, a major QTL was eventually narrowed to 2.47 Mb from 8.14 Mb generated by traditional BSA approaches. Subsequently, through a saturated genetic map constructed in this locus, an novel FS gene, GhCKX1, predicted to produce a cytokinin (CTK) oxidase was isolated. It can negatively modulate the CTK signaling circuit via irreversible degradation of CTKs, resulting in an additional cell wall thickness to xylem tracheary elements in transgenic lines of Arabidopsis thaliana. Thus, the GhCKX1 gene will be an potential genetic target, with which, we can genetically manipulate the secondary wall synthesis in unicellular cotton fibers.

Understanding genotype-environment interactions and trait relationships is pivotal for guiding breeding efforts aimed at stabilizing cotton varieties across diverse environments while boosting yield and fiber quality. The study aimed to assess genotypic variability and stability in 10 agronomic and fiber quality traits across four environments (Anyang in 2020 and 2021 and Weixian in 2020 and 2021) for three parental lines (ZR014121, CCRI60, and EZ60) and their corresponding 498 recombinant inbred lines (RILs) populations. The results indicated that the analysis of variance showed significant genotype and genotype-by-environment effects for all measured traits. Analysis of correlation revealed highly significant positive correlations between seed cotton yield and each of boll weight (r = 0.95), lint yield (r = 0.90), and between boll weight and lint yield (r = 0.90), while highly significant negative correlations were noticed between fiber maturity and fiber elongation (r = −0.52) and between fiber length and lint percentage (r = −0.38). Furthermore, the weighted average of absolute scores (WAASB) was calculated for each trait, revealing moderate to high stability for some yield traits and fiber quality parameters. Also, the multi-trait stability index (MTSI) applied to these RILs populations identified G13 as the most stable line (MTSI = 5.5) and S23 as the least stable (MTSI = 12.1). Selecting 25 RILs with the lowest MTSI values (5.5–6.47) revealed elite stable lines with favorable trait values, providing a valuable genetic resource for developing high-performance cotton cultivars in diverse environments.

Fiber length (FL) is one of the primary factors used to determine the quality of cotton fibers, serving as a primary target for the domestication and breeding of cotton plants through artificial selection. While many studies have identified quantitative trait loci (QTLs) associated with fiber length, few efforts have explored the mechanisms underlying the development of cotton fibers through fine mapping or the validation of related candidate genes. In a previous study, qFL-A12 - 2 was identified as a QTL on chromosome A12 that was associated with higher levels of fiber quality in the MBI7747 (BC 4 F 3:5 ) chromosome segment substitution line (CSSL). For fine mapping the QTL, a single-segment substitution line (CSSL-023) screened from BC 5 F 2 was backcrossed with the recurrent parental CCRI45 line to establish a large segregation population. Subsequently, 2092 individual BC 6 F 2 specimens were utilized in a fine-mapping effort employing highly dense simple sequence markers, which narrowed qFLA12 - 2 to a 0.65 Mb genomic region in Gossypium hirsutum containing 12 annotated genes. The most promising candidate gene within this interval was identified through qRT-PCR and complete coding sequence comparative analyses as GhALMT12_A12 , which encodes an aluminum-activated malate transporter. Two non-synonymous mutations were identified when the protein-coding portions of GhALMT12_A12 were compared among the Hai1, MBI7747, and CCRI45 varieties. Verification of GhALMT12_A12 silencing by VIGS in cotton revealed that the FL of silenced plants was significantly shorter than that of the control plants. When overexpressed, GhALMT12_A12 significantly enhanced Arabidopsis resistance to salt stress and drought conditions through altering ion transport. The outcomes underscore the notable function of GhALMT12_A12 in developing cotton fibers, providing a fundamental basis for scholars aiming at augmenting the length of cotton fibers.

Upland cotton accounts for a high percentage (95%) of the world’s cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.

Upland cotton (Gossypium hirsutum) is one of the important crops to produce natural fiber, and fiber length (FL) and fiber strength (FS) are important fiber quality traits. In this study, we developed a population of recombinant inbred lines (RILs) with the parents 0–153 (P1, high fiber quality) and sGK9708 (P2, low fiber quality), which were constructed for detection of elite alleles. According to the RNA-seq data of P1, P2, 69307 (L1, high fiber quality) and 69362 (L2, low fiber quality), 350/90, 71/132, 214/120, 199/201, and 287/229 genes were differentially expressed (up-/down-regulated) in high quality fiber lines (P1 and L1) in contrary to low quality fiber lines (P2 and L2) at 5, 10, 15, 20 and 25 days post-anthesis (DPA), respectively. Short Time-series Expression Miner (STEM) analysis detected the presence of five expression profiles, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation were investigated to determine the functional differences between specific genes of profile 7 and 26. A total of 234 differentially expressed genes (DEGs) belong to quantitative trait locus loci (QTLs) controlling FL and FS. Co-expression network analysis revealed the presence of two modules which were associated with various stages of fiber development. The weighted gene co-expression network analysis (WGCNA) was also carried out to distinguish 13 hub genes in blue module and 24 hub genes in turquoise module. The alignment between quantitative real-time PCR and RNA-seq data gave the clue for guaranteeing reliability of selected candidate genes for further analysis. In this study, we combine the identified genes from FL and FS QTLs with the results of STEM, WGCNA and time-course analysis. In addition, six candidate genes (GH_A04G0817, GH_A05G0644, GH_A08G0267, GH_A11G0850, GH_D02G1011 and GH_D11G3494) were selected as candidate genes to improve cotton fiber quality.

Introduction: The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. Objectives: This study was to identify superior loci for the improvement of fiber quality and yield. Methods: Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was con-structed to validate genetic effects of the candidate loci. Results: A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02: C45Clu-193) were further validated in the segregating population. Conclusion: The combining of genome-wide introgressions and kmer genotyping strategy showed signif-icant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future. (c) 2023 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Cotton is an important fiber crop. The cotton fiber is an extremely long trichome that develops from the epidermis of an ovule. The trichome is a general and multi-function plant organ, and trichome birefringence-like (TBL) genes are related to trichome development. At the genome-wide scale, we identified TBLs in four cotton species, comprising two cultivated tetraploids (Gossypium hirsutum and G. barbadense) and two ancestral diploids (G. arboreum and G. raimondii). Phylogenetic analysis showed that the TBL genes clustered into six groups. We focused on GH_D02G1759 in group IV because it was located in a lint percentage-related quantitative trait locus. In addition, we used transcriptome profiling to characterize the role of TBLs in group IV in fiber development. The overexpression of GH_D02G1759 in Arabidopsis thaliana resulted in more trichomes on the stems, thereby confirming its function in fiber development. Moreover, the potential interaction network was constructed based on the co-expression network, and it was found that GH_D02G1759 may interact with several genes to regulate fiber development. These findings expand our knowledge of TBL family members and provide new insights for cotton molecular breeding.

Cotton (Gossypium spp. L.) is a major origin of natural fiber, and is projected at 117 million bales worldwide for 2021/22. A variety of biotic and abiotic stresses have considerable negative impacts on cotton. The significantly decreased applications of chemical insecticidal sprays in the agro-ecosystem have greatly affected the biodiversity and dynamics of primary and secondary insects. Various control measures were taken around the globe to increase production costs. Temperature, drought, and salinity, and biotic stresses such as bacteria, viruses, fungi, nematodes, insects, and mites cause substantial losses to cotton crops. Here, we summarize a number of biotic and abiotic stresses upsetting Bt cotton crop with present and future biotechnology solution strategies that include a refuge strategy, multi-gene pyramiding, the release of sterile insects, seed mixing, RNAi, CRISPR/Cas9, biotic signaling, and the use of bioagents. Surveillance of insect resistance, monitoring of grower compliance, and implementation of remedial actions can lead to the sustainable use of cotton across the globe.

KEY MESSAGE:The fiber length-related qFL-A12-5 identified in CSSLs introgressed from Gossypium barbadense into Gossypium hirsutum was fine-mapped to an 18.8 kb region on chromosome A12, leading to the identification of the GhTPR gene as a potential regulator of cotton fiber length. Fiber length is a key determinant of fiber quality in cotton, and it is a key target of artificial selection for breeding and domestication. Although many fiber length-related quantitative trait loci have been identified, there are few reports on their fine mapping or candidate gene validation, thus hampering efforts to understand the mechanistic basis of cotton fiber development. Our previous study identified the qFL-A12-5 associated with superior fiber quality on chromosome A12 in the chromosome segment substitution line (CSSL) MBI7747 (BC4F3:5). A single segment substitution line (CSSL-106) screened from BC6F2 was backcrossed to construct a larger segregation population with its recurrent parent CCRI45, thus enabling the fine mapping of 2852 BC7F2 individuals using denser simple sequence repeat markers to narrow the qFL-A12-5 to an 18.8 kb region of the genome, in which six annotated genes were identified in Gossypium hirsutum. Quantitative real-time PCR and comparative analyses led to the identification of GH_A12G2192 (GhTPR) encoding a tetratricopeptide repeat-like superfamily protein as a promising candidate gene for qFL-A12-5. A comparative analysis of the protein-coding regions of GhTPR among Hai1, MBI7747, and CCRI45 revealed two non-synonymous mutations. The overexpression of GhTPR resulted in longer roots in Arabidopsis, suggesting that GhTPR may regulate cotton fiber development. These results provide a foundation for future efforts to improve cotton fiber length.