Evolutionary divergence of duplicated genomes in newly described allotetraploid cottons.

Allotetraploid cotton (Gossypium) species represents a model system for the study of plant polyploidy, molecular evolution, and domestication. Here, chromosome-scale genome sequences were obtained and assembled for two recently described wild species of tetraploid cotton, Gossypium ekmanianum [(AD)6, Ge] and Gossypium stephensii [(AD)7, Gs], and one early form of domesticated Gossypium hirsutum, race punctatum [(AD)1, Ghp]. Based on phylogenomic analysis, we provide a dated whole-genome level perspective for the evolution of the tetraploid Gossypium clade and resolved the evolutionary relationships of Gs, Ge, and domesticated G. hirsutum. We describe genomic structural variation that arose during Gossypium evolution and describe its correlates-including phenotypic differentiation, genetic isolation, and genetic convergence-that contributed to cotton biodiversity and cotton domestication. Presence/absence variation is prominent in causing cotton genomic structural variations. A presence/absence variation-derived gene encoding a phosphopeptide-binding protein is implicated in increasing fiber length during cotton domestication. The relatively unimproved Ghp offers the potential for gene discovery related to adaptation to environmental challenges. Expanded gene families enoyl-CoA δ isomerase 3 and RAP2-7 may have contributed to abiotic stress tolerance, possibly by targeting plant hormone-associated biochemical pathways. Our results generate a genomic context for a better understanding of cotton evolution and for agriculture.

Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines.

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr-A07, chr-D06, and chr-D07. Notably, chr-D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker-assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker-assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production.

Genome-wide association study for boll weight in Gossypium hirsutum races.

High yield has always been an essential target in almost all of the cotton breeding programs. Boll weight (BW) is a key component of cotton yield. Numerous linkage mapping and genome-wide association studies (GWAS) have been performed to understand the genetic mechanism of BW, but information on the markers/genes controlling BW remains limited. In this study, we conducted a GWAS for BW using 51,268 high-quality single-nucleotide polymorphisms (SNPs) and 189 Gossypium hirsutum accessions across five different environments. A total of 55 SNPs significantly associated with BW were detected, of which 29 and 26 were distributed in the A and D subgenomes, respectively. Five SNPs were simultaneously detected in two environments. For TM5655, TM8662, TM36371, and TM50258, the BW grouped by alleles of each SNP was significantly different. The ± 550 kb regions around these four key SNPs contained 262 genes. Of them, Gh_A02G1473, Gh_A10G1765, and Gh_A02G1442 were expressed highly at 0 to 1 days post-anthesis (dpa), - 3 to 0 dpa, and - 3 to 0 dpa in ovule of TM-1, respectively. They were presumed as the candidate genes for fiber cell differentiation, initiation, or elongation based on gene annotation of their homologs. Overall, these results supplemented valuable information for dissecting the genetic architecture of BW and might help to improve cotton yield through molecular marker-assisted selection breeding and molecular design breeding.

Insights to Gossypium defense response against Verticillium dahliae: the Cotton Cancer.

The soil-borne pathogen Verticillium dahliae, also referred as "The Cotton Cancer," is responsible for causing Verticillium wilt in cotton crops, a destructive disease with a global impact. To infect cotton plants, the pathogen employs multiple virulence mechanisms such as releasing enzymes that degrade cell walls, activating genes that contribute to virulence, and using protein effectors. Conversely, cotton plants have developed numerous defense mechanisms to combat the impact of V. dahliae. These include strengthening the cell wall by producing lignin and depositing callose, discharging reactive oxygen species, and amassing hormones related to defense. Despite the efforts to develop resistant cultivars, there is still no permanent solution to Verticillium wilt due to a limited understanding of the underlying molecular mechanisms that drive both resistance and pathogenesis is currently prevalent. To address this challenge, cutting-edge technologies such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), host-induced gene silencing (HIGS), and gene delivery via nano-carriers could be employed as effective alternatives to control the disease. This article intends to present an overview of V. dahliae virulence mechanisms and discuss the different cotton defense mechanisms against Verticillium wilt, including morphophysiological and biochemical responses and signaling pathways including jasmonic acid (JA), salicylic acid (SA), ethylene (ET), and strigolactones (SLs). Additionally, the article highlights the significance of microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs) in gene expression regulation, as well as the different methods employed to identify and functionally validate genes to achieve resistance against this disease. Gaining a more profound understanding of these mechanisms could potentially result in the creation of more efficient strategies for combating Verticillium wilt in cotton crops.

Genome wide identification of GDSL gene family explores a novel GhirGDSL26 gene enhancing drought stress tolerance in cotton.

BACKGROUND: Current climate change scenarios are posing greater threats to the growth and development of plants. Thus, significant efforts are required that can mitigate the negative effects of drought on the cotton plant. GDSL esterase/lipases can offer an imperative role in plant development and stress tolerance. However, thesystematic and functional roles of the GDSL gene family, particularly in cotton under water deficit conditions have not yet been explored. RESULTS: In this study, 103, 103, 99, 198, 203, 239, 249, and 215 GDSL proteins were identified in eight cotton genomes i.e., Gossypium herbaceum (A1), Gossypium arboretum (A2), Gossypium raimondii (D5), Gossypium hirsutum (AD1), Gossypium barbadense (AD2), Gossypium tomentosum (AD3), Gossypium mustelinum (AD4), Gossypium darwinii (AD5), respectively. A total of 198 GDSL genes of Gossypium hirsutum were divided into eleven clades using phylogenetic analysis, and the number of GhirGDSL varied among different clades. The cis-elements analysis showed that GhirGDSL gene expression was mainly related to light, plant hormones, and variable tense environments. Combining the results of transcriptome and RT-qPCR, GhirGDSL26 (Gh_A01G1774), a highly up-regulated gene, was selected for further elucidating its tole in drought stress tolerance via estimating physiological and biochemical parameters. Heterologous expression of the GhirGDSL26 gene in Arabidopsis thaliana resulted in a higher germination and survival rates, longer root lengths, lower ion leakage and induced stress-responsive genes expression under drought stress. This further highlighted that overexpressed plants had a better drought tolerance as compared to the wildtype plants. Moreover, 3, 3'-diaminobenzidine (DAB) and Trypan staining results indicated reduced oxidative damage, less cell membrane damage, and lower ion leakage in overexpressed plants as compared to wild type. Silencing of GhirGDSL26 in cotton via VIGS resulting in a susceptible phenotype, higher MDA and H2O2 contents, lower SOD activity, and proline content. CONCLUSION: Our results demonstrated that GhirGDSL26 plays a critical role in cotton drought stress tolerance. Current findings enrich our knowledge of GDSL genes in cotton and provide theoretical guidance and excellent gene resources for improving drought tolerance in cotton.

Dynamic characteristics and functional analysis provide new insights into the role of GauERF105 for resistance against Verticillium dahliae in cotton.

BACKGROUND: The cotton industry suffers significant yield losses annually due to Verticillium wilt, which is considered the most destructive disease affecting the crop. However, the precise mechanisms behind this disease in cotton remain largely unexplored. METHODS: Our approach involved utilizing transcriptome data from G. australe which was exposed to Verticillium dahliae infection. From this data, we identified ethylene-responsive factors and further investigated their potential role in resistance through functional validations via Virus-induced gene silencing (VIGS) in cotton and overexpression in Arabidopsis. RESULTS: A total of 23 ethylene response factors (ERFs) were identified and their expression was analyzed at different time intervals (24 h, 48 h, and 72 h post-inoculation). Among them, GauERF105 was selected based on qRT-PCR expression analysis for further investigation. To demonstrate the significance of GauERF105, VIGS was utilized, revealing that suppressing GauERF105 leads to more severe infections in cotton plants compared to the wild-type. Additionally, the silenced plants exhibited reduced lignin deposition in the stems compared to the WT plants, indicating that the silencing of GauERF105 also impacts lignin content. The overexpression of GauERF105 in Arabidopsis confirmed its pivotal role in conferring resistance against Verticillium dahliae infection. Our results suggest that WT possesses higher levels of the oxidative stress markers MDA and H2O2 as compared to the overexpressed lines. In contrast, the activities of the antioxidant enzymes SOD and POD were higher in the overexpressed lines compared to the WT. Furthermore, DAB and trypan staining of the overexpressed lines suggested a greater impact of the disease in the wild-type compared to the transgenic lines. CONCLUSIONS: Our findings provide confirmation that GauERF105 is a crucial candidate in the defense mechanism of cotton against Verticillium dahliae invasion, and plays a pivotal role in this process. These results have the potential to facilitate the development of germplasm resistance in cotton.

Decoding the guardians of cotton resilience: A comprehensive exploration of the ßCA genes and its role in Verticillium dahliae resistance.

Plant Carbonic anhydrases (Cas) have been shown to be stress-responsive enzymes that may play a role in adapting to adverse conditions. Cotton is a significant economic crop in China, with upland cotton (Gossypium hirsutum) being the most widely cultivated species. We conducted genome-wide identification of the ßCA gene in six cotton species and preliminary analysis of the ßCA gene in upland cotton. In total, 73 ßCA genes from six cotton species were identified, with phylogenetic analysis dividing them into five subgroups. GHßCA proteins were predominantly localized in the chloroplast and cytoplasm. The genes exhibited conserved motifs, with motifs 1, 2, and 3 being prominent. GHßCA genes were unevenly distributed across chromosomes and were associated with stress-responsive cis-regulatory elements, including those responding to light, MeJA, salicylic acid, abscisic acid, cell cycle regulation, and defence/stress. Expression analysis indicated that GHßCA6, GHßCA7, GHßCA10, GHßCA15, and GHßCA16 were highly expressed under various abiotic stress conditions, whereas GHßCA3, GHßCA9, GHßCA10, and GHßCA18 had higher expression patterns under Verticillium dahliae infection at different time intervals. In Gossypium thurberi, GthßCA1, GthßCA2, and GthßCA4 showed elevated expression across stress conditions and tissues. Silencing GHßCA10 through VIGS increased Verticillium wilt severity and reduced lignin deposition compared to non-silenced plants. GHßCA10 is crucial for cotton's defense against Verticillium dahliae. Further research is needed to understand the underlying mechanisms and develop strategies to enhance resistance against Verticillium wilt.

An AQI decomposition ensemble model based on SSA-LSTM using improved AMSSA-VMD decomposition reconstruction technique.

Air quality index (AQI) is a key index for monitoring air pollution and can be used as guide for ensuring good public health. Accurate AQI prediction allows timely control and management of air pollution. In this study, a new integrated learning model was constructed to predict AQI. A smart reverse learning approach based on AMSSA was utilized to increase the diversity of populations, and an improved AMSSA (IAMSSA) was established. The optimum parameters with penalty factor α and mode number K of VMD were obtained using IAMSSA. The IAMSSA-VMD was used to decompose nonlinear and non-stationary AQI information series into several regular and smooth sub-sequences. The Sparrow Search Algorithm (SSA) was used to determine the optimum LSTM parameters. The results showed that: (1) IAMSSA exhibits faster convergence and higher accuracy and stability using simulation experiments compared with seven conventional optimization algorithms in 12 test functions. (2) IAMSSA-VMD was used to decompose the original air quality data results in multiple uncoupled intrinsic mode function (IMF) components and one residual (RES). An SSA-LSTM model was built for each IMF and one RES component, which effectively extracted the predicted values. (3) LSTM, SSA-LSTM, VMD-LSTM, VMD-SSA-LSTM, AMSSA-VMD-SSA-LSTM, and IAMSSA-VMD-SSA-LSTM models were used for prediction of AQI based on data from three cities (Chengdu, Guangzhou, and Shenyang). IAMSSA-VMD-SSA-LSTM exhibited the optimal prediction performance with MAE, RMSE, MAPE, and R2 of 3.692, 4.909, 6.241, and 0.981, respectively. (4) Generalization outcomes revealed that the IAMSSA-VMD-SSA-LSTM model had optimal generalization ability. In summary, the decomposition ensemble model proposed in this study has higher prediction accuracy, improved fitting effect and generalization ability compared with other models. These properties indicate the superiority of the decomposition ensemble model and provides a theoretical and technical basis for prediction of air pollution and ecosystem restoration.

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races.

Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein-protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.

Overexpression of cotton GhNAC072 gene enhances drought and salt stress tolerance in transgenic Arabidopsis.

BACKGROUND: Crops face several environmental stresses (biotic and abiotic), thus resulting in severe yield losses. Around the globe abiotic stresses are the main contributors of plant damages, primarily drought and salinity. Many genes and transcription factors are involved in abiotic and biotic stress responses. NAC TF (Transcription Factors) improves tolerance to stresses by controlling the physiological and enzyme activities of crops. RESULTS: In current research, GhNAC072 a highly upregulated TF in RNA-Seq was identified as a hub gene in the co-expression network analysis (WGCNA). This gene was transformed to Arabidopsis thaliana to confirm its potential role in drought and salt stress tolerance. Significant variations were observed in the morpho-physiological traits with high relative leaf water contents, chlorophyll contents, higher germination and longer root lengths of the overexpressed lines and low excised leaf loss and ion leakage as compared to the wildtype plants. Besides, overexpressed lines have higher amounts of antioxidants and low oxidant enzyme activities than the wildtype during the period of stress exposure. CONCLUSIONS: In summary, the above analysis showed that GhNAC072 might be the true candidate involved in boosting tolerance mechanisms under drought and salinity stress.