Overexpression and knockdown of cotton GhdadD gene reveals its drought and salt stress tolerance role.

The 5'-deoxyadenosine deaminase (DADD), a member of the amidohydrolase family regulates biological purine metabolism. In this study, bioinformatic analysis, overexpression and knockdown of GhdadD gene were detected to identify its potential role in drought and salt stress tolerance. The results revealed that GhdadD was induced by ABA, Auxin, MBS and light responsive elements. In transgenic Arabidopsis, seed germination rate and root length were increased under drought or salt stress. GhdadD overexpressed seedlings resulted in higher plant height, less leaf damage and lower ion permeability. The expression of osmotic stress and ABA-responsive genes were up regulated. While in GhdadD-silenced cotton seedlings, CAT, SOD activity and soluble sugar content were reduced, MDA content was increased, and the stoma opening was depressed under drought or salt stress. Some osmics stress marker genes were also up regulated. These data indicating that GhdadD enhanced plant resistance to drought and salt stress through ABA pathways.

Widespread incomplete lineage sorting and introgression shaped adaptive radiation in the Gossypium genus.

Cotton (Gossypium) stands as a crucial economic crop, serving as the primary source of natural fiber for the textile sector. However, the evolutionary mechanisms driving speciation within the Gossypium genus remain unresolved. In this investigation, we leveraged 25 Gossypium genomes and introduced four novel assemblies-G. harknessii, G. gossypioides, G. trilobum, and G. klotzschianum (Gklo)-to delve into the speciation history of this genus. Notably, we encountered intricate phylogenies potentially stemming from introgression. These complexities are further compounded by incomplete lineage sorting (ILS), a factor likely to have been instrumental in shaping the swift diversification of cotton. Our focus subsequently shifted to the rapid radiation episode during a concise period in Gossypium evolution. For a recently diverged lineage comprising G. davidsonii, Gklo, and G. raimondii, we constructed a finely detailed ILS map. Intriguingly, this analysis revealed the non-random distribution of ILS regions across the reference Gklo genome. Moreover, we identified signs of robust natural selection influencing specific ILS regions. Noteworthy variations pertaining to speciation emerged between the closely related sister species Gklo and G. davidsonii. Approximately 15.74% of speciation structural variation genes and 12.04% of speciation-associated genes were estimated to intersect with ILS signatures. These findings enrich our understanding of the role of ILS in adaptive radiation, shedding fresh light on the intricate speciation history of the Gossypium genus.

Research on landslide susceptibility prediction model based on LSTM-RF-MDBN.

The occurrence of landslide disasters causes huge economic losses and casualties. Although many achievements have been made in predicting the probability of landslide disasters, various factors such as the scale and spatial location of landslide geological disasters should still be fully considered. Further research on how to quantitatively characterize the susceptibility of landslide geological disasters is necessarily important. To this end, taking the Wenchuan earthquake as the research area and extracting eight influencing factors, including terrain information entropy (Ht), lithology, distance from rivers, distance from faults, vegetation coverage (NDVI), distance from roads, peak ground motion acceleration (PGA), and annual rainfall, a landslide susceptibility prediction model was hereby established based on LSTM-RF-MDBN, a landslide susceptibility prediction map was drawn, and the spatial distribution characteristics of landslide disasters were analyzed. The results showed that (1) LSTM had good prediction results for the eight influencing factors, with an average prediction accuracy of 85%; (2) compared with models such as DNN and LR for predicting landslide disaster points, the AUC value of RF for predicting landslide point positions reached 0.88, presenting a higher accuracy compared to other models; (3) the AUC value of the landslide susceptibility prediction model based on LSTM-RF-MDBN reached 0.965, which had a high accuracy in predicting landslide susceptibility. Overall, the research results can provide a scientific basis for selecting the best strategy for landslide disaster warning, prevention, and mitigation.

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.

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.

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.

Identification of salt stress-tolerant candidate genes in the BC2F2 population at the seedling stages of G. hirsutum and G. darwinii using NGS-based bulked segregant analysis.

Salinity is a major threat to the yield and productivity of cotton seedlings. In the present study, we developed a BC2F2 population of cotton plants from Gossypium darwinii (5-7) and Gossypium hirsutum (CCRI 12-4) salt-susceptible parents to identify salt-resistant candidate genes. The Illumina HiSeq™ strategy was used with bulked segregant analysis. Salt-resistant and salt-susceptible DNA bulks were pooled by using 30 plants from a BC2F2 population. Next-generation sequencing (NGS) technology was used for the sequencing of parents and both bulks. Four significant genomic regions were identified: the first genomic region was located on chromosome 18 (1.86 Mb), the second and third genomic regions were on chromosome 25 (1.06 Mb and 1.94 Mb, respectively), and the fourth was on chromosome 8 (1.41 Mb). The reads of bulk1 and bulk2 were aligned to the G. darwinii and G. hirsutum genomes, respectively, leading to the identification of 20,664,007 single-nucleotide polymorphisms (SNPs) and insertions/deletions (indels). After the screening, 6,573 polymorphic markers were obtained after filtration of the candidate regions. The SNP indices in resistant and susceptible bulks and Δ(SNP-index) values of resistant and susceptible bulks were measured. Based on the higher Δ(SNP-index) value, six effective polymorphic SNPs were selected in a different chromosome. Six effective SNPs were linked to five candidate genes in four genomic regions. Further validation of these five candidate genes was carried out using reverse transcription-quantitative polymerase chain reaction (RT-qPCR), resulting in an expression profile that showed two highly upregulated genes in the salt-tolerant species G. darwinii, i.e., Gohir.D05G367800 and Gohir.D12G239100; however, the opposite was shown in G. hirsutum, for which all genes, except one, showed partial expression. The results indicated that Gohir.D05G367800 and Gohir.D12G239100 may be salt-tolerant genes. We are confident that this study could be helpful for the cloning, transformation, and development of salt-resistant cotton varieties.

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.

Genome-wide identification and functional analysis of ICE genes reveal that Gossypium thurberi "GthICE2" is responsible for cold and drought stress tolerance.

Cold stress has been found to have a negative impact on cotton growth and annual production. To address this issue, the utilization of cold-tolerant gene resources from wild species of Gossypium is crucial for genetic improvements in cultivated cotton. ICE (inducer of CBF expression) are the key regulators of cold tolerance in plants, however, there is relatively little information on ICE genes in cotton. Herein, we performed comprehensive bioinformatics analyses of the ICE gene family in eight cotton species. Phylogenetic analysis showed that 52 ICE genes were clustered into four subgroups. Cis-regulatory elements analysis suggests that the expression of ICE genes might be regulated by light, plant hormones, and various environment stresses. Higher expression of GthICE2 was observed in leaves as compared to roots and stems, in response to cold, drought, and exogenous hormone ABA. Furthermore, overexpression of GthICE2 in A. thaliana led to higher germination and survival rates, longer root length, lower ion leakage, and induction under cold and drought stress. Histochemical staining showed that oxidative damage in transgenic lines was much lower compared to wild-type plants. Lower MDA contents and higher SOD and POD activities were observed in overexpressed plants. Y1H and LUC assays revealed that GthICE2 might activate the expression of GthCBF4, a cold-responsive gene, by connecting with the MYC cis-element present in the promoter of GthCBF4. GthICE2 confers cold and drought stress tolerance in cotton. Our findings add significantly to the existing knowledge regarding cold stress tolerance and helps to elucidate cold response mechanisms in cotton.

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.

Comparison of earthquake-induced shallow landslide susceptibility assessment based on two-category LR and KDE-MLR.

Geological hazards caused by strong earthquakes have caused continuous social and economic losses and destruction of the ecological environment in the hazard area, and are mostly manifested in the areas with frequent occurrence of geological hazards or the clustering of geological hazards. Considering the long-term nature of earthquakes and geological disasters in this region, this paper takes ten earthquake-stricken areas in Wenchuan earthquake zone as examples to collect shallow landslide data in 2010, combined with the spatial location of landslides and other factors. Kernel density estimation (KDE) method is used to analyze the spatial characteristics of shallow landslide. Taking the space of shallow landslide as the characteristic variable and fully considering the regulating factors of earthquake-induced landslide: terrain complexity, distance to river, distance to fault, distance to road, lithology, normalized vegetation difference index (NDVI) and ground peak acceleration (PGA) as independent variables, based on KDE and polynomial logistic regression (MLR), A quantitative model of shallow landslide in the earthquake area is constructed. The results show that: (1) PGA has the greatest impact on landslide in the study area. (2) Compared with the two-category logistic regression (two-category LR) model, the susceptibility map of landslide prediction results based on the KDE-MLR landslide susceptibility prediction model is more consistent with the actual situation. (3) The prediction accuracy of the model validation set is 70.7%, indicating that the landslide susceptibility prediction model based on KDE-MLR can effectively highlight the spatial characteristics of shallow landslides in 10 extreme disaster areas. The research results can provide decision-making basis for shallow landslide warning and post-disaster reconstruction in earthquake-stricken areas.

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.

Corrigendum: Genome-wide identification and expression analysis elucidates the potential role of PFK gene family in drought stress tolerance and sugar metabolism in cotton.

[This corrects the article DOI: 10.3389/fgene.2022.922024.].

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.

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.

Genome-Wide Identification and Expression Analysis Elucidates the Potential Role of PFK Gene Family in Drought Stress Tolerance and Sugar Metabolism in Cotton.

Drought has been identified as a major threat for global crop production worldwide. Phosphofructokinase (PFK) is vital for sugar metabolism. During phosphorylation, plants have two enzymes: ATP-dependent phosphofructokinase (PFK) and pyrophosphate-dependent fructose-6-phosphate phosphotransferase (PFP). Genome-wide identification led to the identification of 80 PFK genes, 26 genes in G. hirsutum and G. barbadense, and 14 genes in G. arboreum and G. raimondii. Phylogenetic, gene structure, and motif analyses showed that PFK genes were grouped into two main categories, namely, PFK and PFP, with 18 and 8 genes in the allotetraploid species and 10 PFK and 4 PFP genes in the diploid species, respectively. Using the RNA-seq expressions of 26 genes from GhPFK, a co-expression network analysis was performed to identify the hub genes. GhPFK04, GhPFK05, GhPFK09, GhPFK11, GhPFK13, GhPFK14, and GhPFK17 in leaves and GhPFK02, GhPFK09, GhPFK11, GhPFK15, GhPFK16, and GhPFK17 in root tissues were found as hub genes. RT-qPCR analysis validated the expressions of identified hub genes. Interestingly, GhPFK11 and GhPFK17 were identified as common hub genes, and these might be the true candidate genes involved in the drought stress tolerance. In the KEGG enrichment analysis, amino acids such as L-valine, L-histidine, L-glutamine, L-serine, L-homoserine, L-methionine, L-cysteine, and gluconic acid were significantly upregulated, whereas sugars, mainly fructose-1-phosphate, D-mannitol, D-sorbitol, dulcitol, and lactose, were significantly downregulated during drought stress. Genome-wide analysis paves the way for a deeper understanding of the PFK genes and establishes the groundwork for future research into PFK's role in enhancing drought stress tolerance and sugar metabolism in cotton.

Leaf trait covariation and controls on leaf mass per area (LMA) following cotton domestication.

BACKGROUND AND AIMS: The process of domestication has driven dramatic shifts in plant functional traits, including leaf mass per area (LMA). It remains unclear whether domestication has produced concerted shifts in the lower-level anatomical traits that underpin LMA and how these traits in turn affect photosynthesis. METHODS: In this study we investigated controls of LMA and leaf gas exchange by leaf anatomical properties at the cellular, tissue and whole-leaf levels, comparing 26 wild and 31 domesticated genotypes of cotton (Gossypium). KEY RESULTS: As expected, domesticated plants expressed lower LMA, higher photosynthesis and higher stomatal conductance, suggesting a shift towards the 'faster' end of the leaf economics spectrum. At whole-leaf level, variation in LMA was predominantly determined by leaf density (LD) both in wild and domesticated genotypes. At tissue level, higher leaf volume per area (Vleaf) in domesticated genotypes was driven by a simultaneous increase in the volume of epidermal, mesophyll and vascular bundle tissue and airspace, while lower LD resulted from a lower volume of palisade tissue and vascular bundles (which are of high density), paired with a greater volume of epidermis and airspace, which are of low density. The volume of spongy mesophyll exerted direct control on photosynthesis in domesticated genotypes but only indirect control in wild genotypes. At cellular level, a shift to larger but less numerous cells with thinner cell walls underpinned a lower proportion of cell wall mass, and thus a reduction in LD. CONCLUSIONS: Taken together, cotton domestication has triggered synergistic shifts in the underlying determinants of LMA but also photosynthesis, at cell, tissue and whole-leaf levels, resulting in a marked shift in plant ecological strategy.

Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races.

Drought seriously threats the growth and development of Gossypium hirsutum L. To dissect the genetic basis for drought tolerance in the G. hirsutum L. germplasm, a population, consisting of 188 accessions of G. hirsutum races and a cultivar (TM-1), was genotyped using the Cotton80KSNP biochip, and 51,268 high-quality single-nucleotide polymorphisms (SNPs) were obtained. Based on the phenotypic data of eight drought relative traits from four environments, we carried out association mapping with five models using GAPIT software. In total, thirty-six SNPs were detected significantly associated at least in two environments or two models. Among these SNPs, 8 and 28 (including 24 SNPs in 5 peak regions) were distributed in the A and D subgenome, respectively; eight SNPs were found to be distributed within separate genes. An SNP, TM73079, located on chromosome D10, was simultaneously associated with leaf fresh weight, leaf wilted weight, and leaf dry weight. Another nine SNPs, TM47696, TM33865, TM40383, TM10267, TM59672, TM59675, TM59677, TM72359, and TM72361, on chromosomes A13, A10, A12, A5, D6, and D9, were localized within or near previously reported quantitative trait loci for drought tolerance. Moreover, 520 genes located 200 kb up- and down-stream of 36 SNPs were obtained and analyzed based on gene annotation and transcriptome sequencing. The results showed that three candidate genes, Gh_D08G2462, Gh_A03G0043, and Gh_A12G0369, may play important roles in drought tolerance. The current GWAS represents the first investigation into mapping QTL for drought tolerance in G. hirsutum races and provides important information for improving cotton cultivars.

Transcriptomics for Drought Stress Mediated by Biological Processes in-relation to Key Regulated Pathways in Gossypium darwinii.

BACKGROUND: Wild cotton Gossypium darwinii, an allotetraploid harbours important traits useful for tolerating abiotic stress, i.e., drought, salt and good genetic stability, hence these characteristics can be transferred to cultivated cotton for genetic improvement. MATERIALS AND METHODS: In this study, we analyzed the RNA-seq transcriptomes from leaves of G. darwinii seedlings with and without drought stress. A total of 86.7 million valid reads with an average length of 95.79 bp were generated from the two samples and 58,960 transcripts with a length of more than 500 bp were assembled. We searched the known proteins on the strength of sequence similarity; these transcripts were annotated with COG, KEGG and GO functional categories. According to gene expression abundance RPKM value, we carried out RT-qPCR analysis to determine the expression pattern of the obtained transcription factors. RESULTS: A total of 58,960 genes was differentially expressed (DEG), with 32,693 and 25,919 genes found to be upregulated and downregulated, respectively. Through gene ontology and KEGG pathways, the upregulated genes were found to associate with all the GO terms, molecular functions (MF), biological process (BP) and cellular components (CC), which are highly linked to enhancing drought stress tolerance. CONCLUSION: The study provides an in-depth knowledge of regulation of pathways and genes involved in photosynthesis during drought stress in G. darwinii. These pathways and genes were found to be significantly downregulated and this information could be further utilized by cotton breeders in developing a more drought tolerant cotton germplasm.