Cotton Breeding Research Articles

Integrating Environmental Covariates into Adaptability and Stability Analyses: A Structural Equation Modeling Approach for Cotton Breeding

Breeding programs rely on genotype-by-environment interaction (GEI) to recommend cultivars for specific locations. GEI describes how different genotypes perform under varying environmental conditions. Several methods were proposed to assess adaptability and stability across environments. These methods utilize various statistical approaches like parametric and non-parametric regression, multivariate analysis techniques, and even Bayesian frameworks and artificial intelligence. The accessibility of environmental data through platforms like NASA POWER allows breeders to integrate this information into a breeding process. It has been done by using multi-omics integration models that combine data across various biological levels to create accurate predictive models. In the context of phenotypic adaptability and stability analysis, structural equation modeling (SEM) offers an interesting approach to integrating environmental covariates. This work aimed to propose a novel approach that integrates weather information into adaptability and stability analysis, combining SEM with the established Eberhart and Russell model. Additionally, a user-friendly applet, denoted ECERSEM-AdaptStab, was made available to perform the analysis. This approach utilized data from 12 cotton cultivar trials conducted across two growing seasons at 19 sites. This approach successfully integrated environmental covariates into a phenotypic adaptability and stability analysis of cotton cultivars. Specifically, the genotypes TMG 41 WS, IMA CV 690, DP 555 BGRR, BRS 286 and BRS 369 RF were recommended for favorable environments, while the genotypes TMG 43 WS, IMA 5675 B2RF, IMA 08 WS, NUOPAL, DELTA OPAL, BRS 335, and BRS 368 RF are more suitable for unfavorable environments.

CVW-Etr: A High-Precision Method for Estimating the Severity Level of Cotton Verticillium Wilt Disease

Cotton verticillium wilt significantly impacts both cotton quality and yield. Selecting disease-resistant varieties and using their resistance genes in breeding is an effective and economical control measure. Accurate severity estimation of this disease is crucial for breeding resistant cotton varieties. However, current methods fall short, slowing the breeding process. To address these challenges, this paper introduces CVW-Etr, a high-precision method for estimating the severity of cotton verticillium wilt. CVW-Etr classifies severity into six levels (L0 to L5) based on the proportion of segmented diseased leaves to lesions. Upon integrating YOLOv8-Seg with MobileSAM, CVW-Etr demonstrates excellent performance and efficiency with limited samples in complex field conditions. It incorporates the RFCBAMConv, C2f-RFCBAMConv, AWDownSample-Lite, and GSegment modules to handle blurry transitions between healthy and diseased regions and variations in angle and distance during image collection, and to optimize the model’s parameter size and computational complexity. Our experimental results show that CVW-Etr effectively segments diseased leaves and lesions, achieving a mean average precision (mAP) of 92.90% and an average severity estimation accuracy of 92.92% with only 2.6M parameters and 10.1G FLOPS. Through experiments, CVW-Etr proves robust in estimating cotton verticillium wilt severity, offering valuable insights for disease-resistant cotton breeding applications.

Genome-wide analysis and prediction of chloroplast and mitochondrial RNA editing sites of AGC gene family in cotton (Gossypium hirsutum L.) for abiotic stress tolerance

BackgroundCotton is one of the topmost fiber crops throughout the globe. During the last decade, abrupt changes in the climate resulted in drought, heat, and salinity. These stresses have seriously affected cotton production and significant losses all over the textile industry. The GhAGC kinase, a subfamily of AGC group and member of serine/threonine (Ser/Thr) protein kinases group and is highly conserved among eukaryotic organisms. The AGC kinases are compulsory elements of cell development, metabolic processes, and cell death in mammalian systems. The investigation of RNA editing sites within the organelle genomes of multicellular vascular plants, such as Gossypium hirsutum holds significant importance in understanding the regulation of gene expression at the post-transcriptional level.MethodsIn present work, we characterized twenty-eight GhAGC genes in cotton and constructed phylogenetic tree using nine different species from the most primitive to the most recent.ResultsIn sequence logos analyses, highly conserved amino acid residues were found in G. hirsutum, G. arboretum, G. raimondii and A. thaliana. The occurrence of cis-acting growth and stress-related elements in the promoter regions of GhAGCs highlight the significance of these factors in plant development and abiotic stress tolerance. Ka/Ks levels demonstrated that purifying selection pressure resulting from segmental events was applied to GhAGC with little functional divergence. We focused on identifying RNA editing sites in G. hirsutum organelles, specifically in the chloroplast and mitochondria, across all 28 AGC genes.ConclusionThe positive role of GhAGCs was explored by quantifying the expression in the plant tissues under abiotic stress. These findings help in understanding the role of GhAGC genes under abiotic stresses which may further be used in cotton breeding for the development of climate smart varieties in abruptly changing climate.

Natural variation in GhKASI_A05 modulates cottonseed oil content in Gossypium hirsutum L

Cotton is of great economic value because of its fiber that is used in natural textile commodities and its seeds that contain an edible oil with a high content of unsaturated fatty acids and biodiesel applications. Here, we reported that GhKASI_A05 was associated with the cottonseed oil content (SOC) in a natural population via candidate gene association analysis. An 11-bp Indel located in the GhKASI_A05 promoter was found to contribute to SOC and differential expression in upland cotton inbred accessions. Interaction analysis showed that GhWRI1, an AP2/EREBP family transcription factor, that reportedly functions in plant seed oil and fatty acids (FAs) accumulation, directly bound to AW-box cis-elements in two haplotypes of the GhKASI_A05 promoter and activated the expression of GhKASI_A05 at different levels. The seed-specific overexpression of GhKASI_A05 resulted in increased seed size, weight, and protein content, and C16:0 and C18:1 contents but reduced SOC. Our results provide new insights into the biological function of GhKASI in SOC and effective strategies for cotton breeding in the future.

Natural variations in the Cis-elements of GhRPRS1 contributing to petal colour diversity in cotton.

The cotton genus comprises both diploid and allotetraploid species, and the diversity in petal colour within this genus offers valuable targets for studying orthologous gene function differentiation and evolution. However, the genetic basis for this diversity in petal colour remains largely unknown. The red petal colour primarily comes from C, G, K, and D genome species, and it is likely that the common ancestor of cotton had red petals. Here, by employing a clone mapping strategy, we mapped the red petal trait to a specific region on chromosome A07 in upland cotton. Genomic comparisons and phylogenetic analyses revealed that the red petal phenotype introgressed from G. bickii. Transcriptome analysis indicated that GhRPRS1, which encodes a glutathione S-transferase, was the causative gene for the red petal colour. Knocking out GhRPRS1 resulted in white petals and the absence of red spots, while overexpression of both genotypes of GhRPRS1 led to red petals. Further analysis suggested that GhRPRS1 played a role in transporting pelargonidin-3-O-glucoside and cyanidin-3-O-glucoside. Promoter activity analysis indicated that variations in the promoter, but not in the gene body of GhRPRS1, have led to different petal colours within the genus. Our findings provide new insights into orthologous gene evolution as well as new strategies for modifying promoters in cotton breeding.

Transcriptome Analysis and Identification of Genes Associated with Cotton Seed Size.

Cotton seeds, as the main by-product of cotton, are not only an important raw material for edible oil and feed but also a source of biofuel. The quality of cotton seeds directly affects cotton planting and is closely related to the yield and fiber quality. However, the molecular mechanism governing cotton seed size remains largely unexplored. This study investigates the regulatory mechanisms of cotton seed size by focusing on two cotton genotypes, N10 and N12, which exhibit notable phenotypic variations across multiple environments. Developing seeds were sampled at various stages (5, 20, 30, and 35 DPA) and subjected to RNA-seq. Temporal pattern clustering and WGCNA on differentially expressed genes identified 413 candidate genes, including these related to sugar metabolism that were significantly enriched in transcriptional regulation. A genetic transformation experiment indicated that the overexpression of the GhUXS5 gene encoding UDP-glucuronate decarboxylase 5 significantly increased seed size, suggesting an important role of GhUXS5 in regulating cotton seed size. This discovery provides crucial insights into the molecular mechanisms controlling cotton seed size, helping to unravel the complex regulatory network and offering new strategies and targets for cotton breeding to enhance the economic value of cotton seeds and overall cotton yield.

Fine-mapping of a major QTL controlling plant height by BSA-seq and transcriptome sequencing in cotton.

GhSOT (GH_D05G3950) plays a negative role in regulating plant height development by modulating the GA signaling. Plant height is an important indicator affecting mechanical harvesting for cotton. Therefore, understanding the genes associated with the plant height is crucial for cotton breeding and production. In this study, we used bulk segregant analysis sequencing to identify a new quantitative trait locu (QTL) called qPH5.1, which is linked to plant height. Local QTL mapping using seven kompetitive allele-specific PCR(KASP) markers and linkage analysis successfully narrowed down qPH5.1 to ~ 0.34 Mb region harbored five candidate genes. Subsequently, RNA sequencing (RNA-seq) analysis and examination of expression patterns revealed that GhSOT exhibited the highest likelihood of being the candidate gene responsible for the plant height at this locus. Seven SNP site variations were identified in the GhSOT promoter between the two parents, and Luciferase experiments confirmed that the promoter of GhSOT from cz3 enhances downstream gene expression more effectively. Additionally, suppression of GhSOT in cz3 resulted in the restoration of plant height, further emphasizing the functional significance of this gene. Application of exogenous gibberellin acid (GA) significantly restored plant height in cz3, as demonstrated by RNA-seq analysis and exogenous hormone treatment, which revealed alterations in genes associated with GA signaling pathways. These results reveal GhSOT is a key gene controlling plant height, which may affect plant height by regulating GA signaling.

IDENTIFICATION CANDIDATE SSR, SNPs AND GENES ASSOCIATED SALT TOLERANCE IN ASIATIC COTTON (GOSSYPIUM ARBOREUM)

Soil is a vital resource for feeding the growing global population. Increased salt tolerance of perennial species used for fodder or fuel production is an important and natural method for controlling the spread of secondary salinity. This study was carried out to identify marker-trait association analysis using 7 traits and one comprehensive index of salt tolerance (CIST) and SSR and SNP markers for 215 accessions of Asiatic cotton (G. arboretum). The traits related to salt tolerance like germination rate (GR), fresh weight (FW), stem length (SL), water content (WC), chlorophyll content (ChlC), electric conduct (EC) and methylene dioxyamphetamine (MDA), of 215 cotton accessions were screened out using 150mM NaCl concentration after 7 days of seed growth. According to a comprehensive index of salt tolerance (CIST), 215 accessions were mainly categorized into four groups, and 11 accessions (top 5%) with high salinity tolerance were selected for breeding. Group 1 contained 12 accessions that were sensitive to high salt treatment (<0.6), group 2 contained 26 accessions that were moderate tolerant to salt treatment (0.6～1.5), group 3 includes 153 accession that were tolerant (1.5～2.5), and group 4 had 24 accessions that were highly tolerant to salt treatment (>2.5). The natural population of 215 accessions of G. arboretum was first classified into 3 main groups by phylogenic analysis, in which Group 2 (G2) and Group 3 (G3) represented the Yellow River and Yangtze River accessions respectively, while Group 1 (G1) contained mixed cotton accessions which belongs to different cotton growing areas in China. The grouped accessions results were largely congruent with the breeding history and ecological region, which indicates the extensive genetic diversity of G. arboretum accessions both in phenotype and genotype. The relative value (R) of the traits was used for marker-trait association analysis. Twenty-two strong SSR marker-trait associations were obtained with strict significant P value i.e. P< 0.01 and four makers including NAU1023, NAU1099, JESPR222, and NAU2783 were significantly related to salt tolerance. The marker NAU2783 was highest associated (P= 1.98E-12) with REC, and with the highest phenotype variation of 20.87%. Some markers are significantly associated with more than two traits. MUSS020 was significantly (P<0.01) related with RFW, and RMDA, NAU1375 was associated with RFW and RSL, while NAU3468 was significantly associated with RFW, RGR, and RWC. By applying the threshold of –log10 P≥4.0, the 2062 SNP markers covered all 13 chromosomes and 100 SNP markers locations that were unknown. Among these 2062 marker‐trait associations, 61 markers were associated with RGR, 187 markers were associated with RFW, 255 markers were associated with RSL, 370 markers were associated with RWC, 190 markers were associated with RChlC, 583 markers were associated with REC, 335 markers were associated with RMDA and 81 markers were associated with CIST. The nine SNP rich regions analysis revealed 143 polymorphisms that distributed 40 candidate genes and significantly associated with salt tolerance. Notably, two SNP rich regions on chromosome 7 were found to be significantly associated with two salinity related traits, RFW and RSL, by the threshold of −log10P ≥ 6.0, and two candidate genes (Cotton_A_37775 and Cotton_A_35901) related to two key SNPs (Ca7_33607751 and Ca7_77004962) were possibly associated with salt tolerance in G. arboreum. The classification information derived from these studies may be used to facilitate the development of salt tolerant cotton accessions that could give economic yield in salinity prone areas. The strong marker-trait association results might provide insights for marker-assistant selecting salt-tolerant varieties and will be useful for future cotton breeding programs.

In-depth analysis of Bt cotton adoption: farmers' opinions, genetic landscape, and varied perspectives—a case study from Pakistan

BackgroundBt technology has played significant role in controlling bollworms and increasing cotton yield in earlier days of its introduction, a subsequent decline in yield became apparent over time. This decline may be attributed to various environmental factors, pest dynamics, or combination of both. Therefore, the present biophysical survey and questionnaire were designed to evaluate the impact of Bt cotton on bollworms management and its effect on reducing spray costs, targeting farmers with varied landholdings and educational backgrounds. Additionally, data on farmers' cultivated varieties and the prevalence of bollworms and sucking insects in their fields were recorded. Subsequently, about eleven thousand cotton samples from farmer fields were tested for Cry1Ac, Cry2Ab and Vip3A genes by strip test.ResultsIn this analysis, 83% of the farmers planting approved varieties believe that Bt technology control bollworms, while 17% hold contradictory views. Similarly, among farmers cultivating unapproved varieties, 77% agree on effectiveness of Bt technology against bollworms, while 23% disagree. On the other hand, 67% of farmers planting approved varieties believe that Bt technology does not reduce spray costs, while 33% agree with the effectiveness. Similarly, 78% of farmers cultivating unapproved varieties express doubt regarding its role to reduce spray costs, while 22% are in favour of this notion. Differences in opinions on the effectiveness of Bt cotton in controlling bollworms and reducing spray cost between farmers planting unapproved and approved varieties may stem from several factors. One major cause is the heavy infestation of sucking insects, which is probably due to the narrow genetic variation of the cultivated varieties. Additionally, the widespread cultivation of unapproved varieties (21.67%) is also an important factor to cause different opinions on the effectiveness of Bt cotton.ConclusionBased on our findings, we propose that the ineffective control of pests on cotton crop may be attributed to large scale cultivation of unapproved varieties and non-inclusion of double and triple transgene technologies in country’s sowing plan. On the basis of our findings, we suggest cotton breeders, regulatory bodies and legislative bodies to discourage the cultivation of unapproved varieties and impure seed. Moreover, the adoption of double and triple Bt genes in cottons with a broad genetic variation could facilitate the revival of the cotton industry, and presenting a promising way forward.

Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.).

A GWAS in an elite diversity panel, evaluated across 10 environments, identified genomic regions regulating six fiber quality traits, facilitating genomics-assisted breeding and gene discovery in upland cotton. In this study, an elite diversity panel of 348 upland cotton accessions was evaluated in 10 environments across the US Cotton Belt and genotyped with the cottonSNP63K array, for a genome-wide association study of six fiber quality traits. All fiber quality traits, upper half mean length (UHML: mm), fiber strength (FS: gtex-1), fiber uniformity (FU: %), fiber elongation (FE: %), micronaire (MIC) and short fiber content (SFC: %), showed high broad-sense heritability (> 60%). All traits except FE showed high genomic heritability. UHML, FS and FU were all positively correlated with each other and negatively correlated with FE, MIC and SFC. GWAS of these six traits identified 380 significant marker-trait associations (MTAs) including 143 MTAs on 30 genomic regions. These 30 genomic regions included MTAs identified in at least three environments, and 23 of them were novel associations. Phenotypic variation explained for the MTAs in these 30 genomic regions ranged from 6.68 to 11.42%. Most of the fiber quality-associated genomic regions were mapped in the D-subgenome. Further, this study confirmed the pleiotropic region on chromosome D11 (UHML, FS and FU) and identified novel co-localized regions on D04 (FU, SFC), D05 (UHML, FU, and D06 UHML, FU). Marker haplotype analysis identified superior combinations of fiber quality-associated genomic regions with high trait values (UHML = 32.34mm; FS = 32.73gtex-1; FE = 6.75%). Genomic analyses of traits, haplotype combinations and candidate gene information described in the current study could help leverage genetic diversity for targeted genetic improvement and gene discovery for fiber quality traits in cotton.

TRACING THE DIVERSITY OF CULTIVATED TRANSGENIC COTTON IN PAKISTAN BY SSR BASED DNA FINGERPRINTING

The introduction of transgenic Bacillus thuringiensis (Bt) cotton is one of the success stories of applying biotechnology in agriculture. It also decreased the use of insecticides and the production cost as an environmental and economic benefit, respectively. The use of selective genotypes as a parental material for Bt cotton breeding has resulted in the multiplication of limited germplasm. The main objective of the study was to find out the genetic diversity of cultivated Bt cotton genotypes by fingerprinting. Twenty-two SSR markers were used to analyze the genetic differences in Bt cotton genotypes, collected from two different sources i.e., research institutes and open market. Results showed that the Polymorphism information content (PIC) value ranged from zero to 0.673. A UPGMA based dendrogram divided all the genotypes into four main clusters. Eighty-six percent similarity was observed between VH-282 and AS-01 while the lowest similarity of 45% was found between IUB-222 and FH-167.This diversity of newly introduced transgenic genotypes will help to detect the diverse lines to be used in future for broadening the genetic base of Bt cotton in Pakistan. Another observation was that a genotype, FH-114 oBtained from two sources was clustered in two different clades. This showed the presence of name variants for a particular genotype depicting adulteration of seed available in seed market which need to be addressed. Though the adoption of Bt cotton was rapid, but the economic impact of this adoption was not significant in Pakistan as compared to other developing countries. The identified problem might be one of the reasons, limiting the benefits of this technology to be harvested out of it.

Characterization of Strubbelig-Receptor Family (SRF) Related to Drought and Heat Stress Tolerance in Upland Cotton (Gossypium hirsutum L.)

Cotton is one of the world’s leading fiber crops, but climate change, drought, heat, and salinity have significantly decreased its production, consequently affecting the textile industries globally. To acclimate to these environmental challenges, a number of gene families involved in various molecular, physiological, and hormonal mechanisms play crucial roles in improving plants response to various abiotic stresses. One such gene family is the GhSRF, a Strubbelig-Receptor family (SRF), and member of the leucine-rich repeat (LRR-V) group. This family encodes leucine-rich repeat transmembrane receptor-like kinases (LRR-RLKs) and have not yet been explored in cotton. Arabidopsis thaliana Strubbelig-Receptor gene sequences were used as queries to identify the homologs in cotton, with subsequent support from the literature and functional prediction through online data. In the current study, a comprehensive genome-wide analysis of cotton was conducted, identifying 22 SRF putative proteins encoded by 22 genes. We performed the detailed analysis of these proteins, including phylogeny, motif and gene structure characterization, promoter analysis, gene mapping on chromosomes, gene duplication events, and chromosomal sub-cellular localization. Expression analysis of putative genes was performed under drought and heat stress conditions using publicly available RNAseq data. The qRT-PCR results showed elevated expression of GhSRF2, GhSRF3, GhSRF4, GhSRF10, and GhSRF22 under drought and heat stress. So, it could be speculated that these genes may play a role in drought and heat tolerance in cotton. These findings could be helpful in cotton breeding programs for the development of climate-resilient cultivars.

Integrative physiology and transcriptome sequencing reveal differences between G. hirsutum and G. barbadense in response to salt stress and the identification of key salt tolerance genes

BackgroundSoil salinity is one of the major abiotic stresses that threatens crop growth. Cotton has some degree of salt tolerance, known as the “pioneer crop” of saline-alkali land. Cultivation of cotton is of great significance to the utilization of saline-alkali land and the development of cotton industry. Gossypium hirsutum and G. barbadense, as two major cotton species, are widely cultivated worldwide. However, until recently, the regulatory mechanisms and specific differences of their responses to salt stress have rarely been reported.ResultsIn this study, we comprehensively compared the differences in the responses of G. hirsutum acc. TM-1 and G. barbadense cv. Hai7124 to salt stress. The results showed that Hai7124 exhibited better growth than did TM-1 under salt stress, with greater PRO content and antioxidant capability, whereas TM-1 only presented greater K+ content. Transcriptome analysis revealed significant molecular differences between the two cotton species in response to salt stress. The key pathways of TM-1 induced by salt are mainly related to growth and development, such as porphyrin metabolism, DNA replication, ribosome and photosynthesis. Conversely, the key pathways of Hai7124, such as plant hormone signal transduction, MAPK signaling pathway-plant, and phenylpropanoid biosynthesis, are mainly related to plant defense. Further comparative analyses of differentially expressed genes (DEGs) revealed that antioxidant metabolism, abscisic acid (ABA) and jasmonic acid (JA) signalling pathways were more strongly activated in Hai7124, whereas TM-1 was more active in K+ transporter-related genes and ethylene (ETH) signalling pathway. These differences underscore the various molecular strategies adopted by the two cotton species to navigate through salt stress, and Hai7124 responded more strongly to salt stress, which explains the potential reasons for the greater salt tolerance of Hai7124. Finally, we identified 217 potential salt tolerance-related genes, 167 of which overlapped with the confidence intervals of significant SNPs identified in previous genome-wide association studies (GWASs), indicating the high reliability of these genes.ConclusionsThese findings provide new insights into the differences in the regulatory mechanisms of salt tolerance between G. hirsutum and G. barbadense, and identify key candidate genes for salt tolerance molecular breeding in cotton.

Quantitative Trait Loci Mapping and Candidate Gene Analysis for Fiber Quality Traits in Upland Cotton

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 13 major effect QTLs that contributed more than 10% toward phenotypic variation (PV) and 9 stable QTLs that could be repeatedly mapped in different generations. Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosomes D1 and D11. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18–21.45% of PV and qFS-A11-1 in F2:3, F2:4, and F2:5 with 6.05–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, while Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

GhSBI1, a CUP-SHAPED COTYLEDON 2 homologue, modulates branch internode elongation in cotton.

Branch length is an important plant architecture trait in cotton (Gossypium) breeding. Development of cultivars with short branch has been proposed as a main object to enhance cotton yield potential, because they are suitable for high planting density. Here, we report the molecular cloning and characterization of a semi-dominant quantitative trait locus, Short Branch Internode 1(GhSBI1), which encodes a NAC transcription factor homologous to CUP-SHAPED COTYLEDON 2 (CUC2) and is regulated by microRNA ghr-miR164. We demonstrate that a point mutation found in sbi1 mutants perturbs ghr-miR164-directed regulation of GhSBI1, resulting in an increased expression level of GhSBI1. The sbi1 mutant was sensitive to exogenous gibberellic acid (GA) treatments. Overexpression of GhSBI1 inhibited branch internode elongation and led to the decreased levels of bioactive GAs. In addition, gene knockout analysis showed that GhSBI1 is required for the maintenance of the boundaries of multiple tissues in cotton. Transcriptome analysis revealed that overexpression of GhSBI1 affects the expression of plant hormone signalling-, axillary meristems initiation-, and abiotic stress response-related genes. GhSBI1 interacted with GAIs, the DELLA repressors of GA signalling. GhSBI1 represses expression of GA signalling- and cell elongation-related genes by directly targeting their promoters. Our work thus provides new insights into the molecular mechanisms for branch length and paves the way for the development of elite cultivars with suitable plant architecture in cotton.

GhWRKY40 Interacts with an Asparaginase GhAPD6 Involved in Fiber Development in Upland Cotton (Gossypium hirsutum L.).

Fiber quality improvement is a primary goal in cotton breeding. Identification of fiber quality-related genes and understanding the underlying molecular mechanisms are essential prerequisites. Previously, studies determined that silencing the gene GhWRKY40 resulted in longer cotton fibers; however, both the underlying mechanisms and whether this transcription factor is additionally involved in the regulation of cotton fiber strength/fineness are unknown. In the current study, we verified that GhWRKY40 influences the fiber strength, fiber fineness, and fiber surface structure by using virus-induced gene silencing (VIGS). Potential proteins that may interact with the nucleus-localized GhWRKY40 were screened in a yeast two-hybrid (Y2H) nuclear-system cDNA library constructed from fibers at 0, 10, and 25 days post-anthesis (DPA) in two near-isogenic lines differing in fiber length and strength. An aspartyl protease/asparaginase-related protein, GhAPD6, was identified and confirmed by Y2H and split-luciferase complementation assays. The expression of GhAPD6 was approximately 30-fold higher in the GhWRKY40-VIGS lines at 10 DPA and aspartyl protease activity was significantly upregulated in the GhWRKY40-VIGS lines at 10-20 DPA. This study suggested that GhWRKY40 may interact with GhAPD6 to regulate fiber development in cotton. The results provide a theoretical reference for the selection and breeding of high-quality cotton fibers assisted by molecular technology.

Comprehensive analysis of drought tolerance in pure lines derived from half-diallel crosses of upland cotton (Gossypium hirsutum L.)

Drought has a significant impact on plants, affecting their growth, development and survival. This study focuses on evaluating the impact of drought stress, a significant abiotic factor, on the agronomic and fiber parameters of potential cotton (Gossypium hirsutum L.) lines with the aim of developing drought-tolerant varieties. The experiment involved two irrigation regimes—well-watered (100% field capacity) and deficit irrigation (50% field capacity)—conducted on F9–F10 generations. Key fiber parameters, including fiber length, boll weight, fiber strength, and lint percentage, were identified as crucial selection criteria under both well-watered and deficit irrigation conditions. Notably, boll number emerged as the decisive parameter in both F9 and F10 generations. The study employed univariate and multivariate analyses, such as PCA, heat map cluster, correlation analysis, and decision tree, which consistently highlighted fiber length, boll weight, fiber strength and lint (ginning) percentage the key factor. In the F10 generation, the integration of decision tree and heat map cluster results led to the identification of 8 promising lines. These selected genotypes have potential for inclusion in future cotton breeding programmes, offering the opportunity to increase drought tolerance and improve cotton yield and productivity. Their resilience to environmental stresses makes them promising candidates for improving overall cotton performance under challenging conditions.

Combining high-throughput deep learning phenotyping and GWAS to reveal genetic variants of fruit branch angle in upland cotton

Cotton (Gossypium spp.), an economically and strategically significant crop in China, faces challenges such as rising cultivation costs and conflicts between grain and cotton cultivation. These challenges underscore the need for enhancing yields per unit area. In response, this study employs deep learning techniques, combined with high-throughput angle detection, to conduct genome-wide association studies (GWAS) on 355 upland cotton accessions, identify key SNPs and candidate genes for plant architecture by fruit branch angle (FBA) influences planting density, yield, and mechanized harvesting. A convolutional neural network (CNN)-based software was developed for rapid and accurate branch angle detection, showing high correlation with both AutoCAD and manual measurements. Significant phenotypic variation in FBA was observed across various cotton planting regions, with the Northwest Inland Region (NIR) exhibiting notably smaller angles. In total, 107 significant Single Nucleotide Polymorphisms (SNPs) were detected across 45 quantitative trait loci (QTL), and three potential candidate genes (Ghir_A11G034910, Ghir_D05G007790, and Ghir_D05G031350) were identified, providing insights into the genetic basis of FBA and presenting valuable genetic resources for cotton breeding programs.

Exploring genotypic variations in cotton associated with growth and nitrogen use efficiency

Low nitrogen (N) is a major limitation of cotton sustainability and productivity. N-efficient genotype cultivation can enhance productivity under the economical N usage. This study was conducted to characterize 15 cotton genotypes for N use efficiency (NUE) under differential N (0.0125 and 0.125 g kg−1 of sand) supply. All studied traits significantly responded to genotypes and N treatments. Under low N conditions, plants experienced reduced seedling height, root weight, shoot weight and total biomass (TDM) production, chlorophyll content, photosynthetic efficiency, NPK content, and N uptake efficiency (NUpE). Thus, intercellular CO2 concentration, photosynthetic N use efficiency (PNUE), and NUtE enhanced in low N supply, although these changes varied in magnitude. Based on variations in TDM production (14.6–33.1%) and NUtE (3.3–20.4%), GH-Uhad, FH-Anmol, FH-Super, GH-Haadi, and SLH-Chandani were categorized as efficient and responsive (ER), while J-7, CIM-343, FH-155, FH-492, FH-444 found as inefficient and non-responsive. The efficient and non-responsive group contained FH-142, GH-Baghdadi, and FH-490 whereas FH-152 and Cyto-179 were classified as inefficient and responsive. The scoring method provided further insight into genotypic NUE related to biomass distribution, photosynthetic rate (Pn), NUpE, and NUtE under low N. The highest cumulative score (15-18) of ER genotypes for these attributes indicated selected traits orchestrated to determine the NUE. Moreover, agronomical and NUE-related traits were positively associated with Pn, suggesting that photosynthesis is a primary manipulator of plant growth which coordinates biomass production and NUE. Overall, cultivars exhibited greater genotypic variation for NUE, providing a scientific basis to evaluate the existing germplasm and proposing that cultivation of N-efficient genotypes can decrease N application and help cotton breeding for sustainable production.

Advances in genome sequencing and artificially induced mutation provides new avenues for cotton breeding.

Cotton production faces challenges in fluctuating environmental conditions due to limited genetic variation in cultivated cotton species. To enhance the genetic diversity crucial for this primary fiber crop, it is essential to augment current germplasm resources. High-throughput sequencing has significantly impacted cotton functional genomics, enabling the creation of diverse mutant libraries and the identification of mutant functional genes and new germplasm resources. Artificial mutation, established through physical or chemical methods, stands as a highly efficient strategy to enrich cotton germplasm resources, yielding stable and high-quality raw materials. In this paper, we discuss the good foundation laid by high-throughput sequencing of cotton genome for mutant identification and functional genome, and focus on the construction methods of mutant libraries and diverse sequencing strategies based on mutants. In addition, the important functional genes identified by the cotton mutant library have greatly enriched the germplasm resources and promoted the development of functional genomes. Finally, an innovative strategy for constructing a cotton CRISPR mutant library was proposed, and the possibility of high-throughput screening of cotton mutants based on a UAV phenotyping platform was discussed. The aim of this review was to expand cotton germplasm resources, mine functional genes, and develop adaptable materials in a variety of complex environments.