The final stages of myeloproliferative neoplasms (MPNs) are related to myelofibrosis (MF). This study aimed to compare secondary myelofibrosis (SMF), overt (PMF), and prefibrotic primary myelofibrosis (pre-PMF) and determine prognostic factors in clinical and genetic features. This study included 229 patients; 67 (29%), 122 (53%), and 40 (18%) cases were confirmed as SMF, overt PMF, and pre-PMF, respectively. We compare MFs, including pre-PMF, using six scoring stratifications associated with PMF and one scoring system with SMF. We also evaluated the impact of the genetic groups with clustering methods and previously reported genomic groups. We determined the clinical and genetic features associated with disease progression in SMF, overt PMF, and pre-PMF groups.JAK2 V617F mutation was differentially distributed in SMF and PMF, contradictory to CALR and MPL mutations. Regarding nondriver mutations, the occurrence of ASXL1 mutations differed between PMF and SMF or pre-PMF. The three-year overall survival was 91.5%, 85.3%, and 94.8% in SMF, overt PMF, and pre-PMF groups. Various scoring systems could discriminate the overall survival in PMF but not in SMF and pre-PMF. Still, clinical features including anemia and thrombocytopenia were poor prognostic factors throughout the myelofibrosis, whereas mutations contributed differently. Molecular grouping by wild-type SF3B1 and SRSF2/RUNX1/U2AF1/ASXL1/TP53 mutations showed inferior progression-free survival (PFS) in PMF, SMF, and pre-PMF. We determined the clinical and genetic features related to poor prognosis in myelofibrosis.The Philadelphia-negative myeloproliferative neoplasms (MPNs) are divided in three major groups: polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). The 2016 WHO classification incorporates also prefibrotic PMF (pre-PMF) and overt PMF. This study aimed to discriminate the clinical features, genetic alterations, and outcomes in patients with prefibrotic, overt PMF, and secondary MF (SMF). This study included 229 patients with diagnosed myelofibrosis (MF). Among 229 patients, 67 (29%), 122 (53%), and 40 (18%) were confirmed as SMF, overt PMF, and pre-PMF, respectively. The  Philadelphia-negative myeloproliferative neoplasms (MPNs) are clonal hematopoietic disorders characterized by the overproduction of differentiated hematopoietic cells, and are divided into three major subcategories, namely, polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). PV and ET can evolve to secondary forms of myelofibrosis (MF), known as post-polycythemia vera (PPV-MF) and post-essential thrombocythemia myelofibrosis (PET-MF).The progression of myelofibrosis might lead to various pathological conditions, including thrombosis, infection, leukemic transformation, and eventually death . HoweverJAK2, CALR, MPL, and uncommon variants. Recently, evidence for the acquisition of somatic mutations and information on factors influencing clonal outgrowth such as aging and the bone marrow microenvironment have been accumulating . Alr (TP53) , compariutations ,9, and tutations . Furtherand IDH2 ,12, and AF1 Q157 . As the AF1 Q157 ,15,16. HWe included 229 patients who were diagnosed with myelofibrosis at Seoul St. Mary’s Hematology Hospital from December 2001 to August 2021 and provided DNA samples for next-generation sequencing (NGS) analysis. Pathologists confirmed the diagnosis based on the 2016 WHO classification .Most DNA samples were from bone marrow (BM) aspirate samples at the diagnosis of myelofibrosis, regardless of pre-evolving myeloproliferative neoplasm (MPN) disease. This study was approved by the Institutional Review Board of Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul, Korea (KC22RISI0120) and was conducted in accordance with the tenets of the Declaration of Helsinki.Conventional BM karyotyping was performed on G-banded metaphase chromosomes using routine techniques. Karyotypes were interpreted according to ISCN 2016 . JAK2, CALR, and MPL of less than 5% VAF were considered positive with a low allele burden. Using the Integrative Genomic Viewer, the detected variants were manually verified.Regarding molecular analysis, NGS, was performed using a customized myeloid panel (“SM panel”), as described in our previous report . The SM Overall survival (OS) and progression-free survival (PFS) were calculated from the date of diagnosis. OS was defined as the time to death from any cause. PFS was defined as the time to progression to overt myelofibrosis or death in the pre-PMF groups; otherwise, progression to acute leukemia or death was considered the endpoint event.The scoring system consisted of IPSS , DIPSS , DIPSS-pt-test or Mann–Whitney U test were used for continuous variables. Baseline: The clinical and molecular characteristics of patients classified into the three groups were compared: SMF, PMF, and pre-PMF. The chi-square or Fisher’s exact test were used for categorical variables, whereas the two-sample rpart 4.1-10) to discriminate between the MF groups using clinical and genetic variables. To emphasize the effect of the non-driver mutations, we included the other mutations except the JAK2, MPL, and CALR mutations in the clustering analysis. Binary distances were calculated and hierarchical clustering was performed using the Ward’s method. The best proposal cluster-number was calculated using Silhouette, Ratkowsky and Lance, and McClain and Rao indices (R packages Nbclust 3.0). We used the decision tree method . The OS and PFS were estimated using the Kaplan–Meier method, and groups were compared using the log-rank test. The Cox proportional hazards model was used for univariate and multivariate analyses of OS and PFS. Variables with n = 122, 53.3%), followed by PET-MF , pre-PMF , and PPV-MF . In particular, we found that pre-PMF cases had a lower median age (p = 0.003), higher hemoglobin levels (p < 0.001), higher platelet count (p < 0.001), lower peripheral blood blast proportion (p < 0.001), smaller spleen (p < 0.001), and fewer constitutional symptoms (p < 0.001) than other overt MF cases. The clinical and cytogenetic characteristics of patients are summarized in Based on the DIPSS scoring system, we did not identify any differences in unfavorable karyotype abnormalities among the three groups. However, we found that the MIPSS karyotype risk was higher in the PMF group than in the SMF and pre-PMF groups. In the pre-PMF group we did not identify any karyotypes including abnormalities of −7, i(17q), inv(3)/3q21, 12p-/12p11.2, 11q-/11q23, or any other autosomal trisomy not including +8, +9 and complex karyotype.n = 211). The mean number of mutations was 1.80 (range 0–6) in total, including 1.78 (range 1–5) in SMF, 1.91 (range 0–5) in PMF, and 1.65 (range 0–6) in pre-PMF. The genetic landscape in the three groups of MF is shown in JAK2 were the most common , followed by those in ASXL1 , CALR , TET2 , and U2AF1 . Similarly, in the SMF group, mutations in JAK2 were the most common , followed by those in ASXL1 (28.4%), CALR (26.9%), TET2 (13.4%), and SF3B1 (7.5%). In the pre-PMF group, mutations in JAK2 were the most common (50.0%), followed by those in CALR (17.5%), TET2 (17.5%), SF3B1 (10.0%), and DNMT3A (10.0%). However, it was found that the proportion of ASXL1 mutations in the pre-PMF group was lower than that in the SMF and PMF groups (We identified mutations in 92.1% of patients (F groups .p = 0.001), no differences were detected in VAFs of the examined genes, including CALR, MPL, ASXL1, TET2, SF3B1, DNMT3A, MPL, U2AF1, and RUNX1 . Additionally, CALR and TET2 were positively correlated , In the pre-PMF group, we identified a negative correlation between mutated JAK2 and TET2 . The median variant allele frequency (VAF) of gene mutations was 0.37 overall, 0.36 in PMF, 0.39 in SMF, and 0.38 in pre-PMF. In PMF, SMF, and pre-PMF, 8.2%, 16.5%, and 10.5% of homozygous mutations had a higher VAF of 0.70. Except for JAK2  and platelet counts (Y-axis)   . In addi, 46.1%) E. The distribution of the risk stratification system in each subgroup is described in p = 0.026). We recorded 30 deaths among all patients . Among all patients, 48 patients underwent allogeneic hematopoietic stem cell transplantation, including 31 in PMF, 15 in SMF, and 2 in pre-PMF. Among the patients who underwent transplantation, we recorded 10 deaths in the PMF group and 3 deaths in the SMF group.After a median follow-up of 2.7 years , we observed that the 3-year overall survival of patients was 85.3%, 91.5%, and 94.8% in the overt PMF, SMF, and pre-PMF groups  was associated with poor OS, whereas CARL type 1 mutation  correlated with favorable PFS. The results of the univariate analysis are illustrated in  pre-PMF . In modeTP53 and female sex were associated with inferior OS. We also found that female sex, thrombocytopenia, and RUNX1, TP53, ZRSR2, and IDH1 mutations were associated with inferior outcome in PFS.In patients with SMF, the multivariate analysis showed that JAK2, MPL, and CARL driver mutations by five subgroups to calculate the specified mentioned index. Grouping nomenclature indicated the most distributed gene mutations in each group   C,D. Howeorst PFS E. This rSRSF2, U2AF1, SF3B1, IDH1/2, and EZH2. These mutations were associated with poor OS in the pre-PMF group (p = 0.008) /CHIP  for fibrotic progression, which were previously reported by Bartels, et al. . Among t= 0.008)  but not SF3B1 or mutations in SRSF2, RUNX1, U2AF1, ASXL1, and TP53, on the survival outcomes in the MF cohort (p < 0.001), SMF , and pre-PMF groups (100% vs. 50% p < 0.001). We also identified that this high-risk subgroup showed inferior PFS in the PMF, SMF, and pre-PMF groups .Next, we analyzed the effect of high-risk genetic mutations for the progression of myelodysplastic syndrome to AML , that isF cohort . We obseAlthough several previous studies have compared pre-PMF versus ET , pre-PMFA comparison of the clinical features between pre-PMF and PMF showed that patients with pre-PMF were characterized by higher hemoglobin levels and platelet counts, whereas they were less frequently diagnosed with increased peripheral blood blasts, symptoms, and extensive splenomegaly. These findings are consistent with those of a previous study . Similarp = 0.059), which is consistent with the results of previous studies. Comparison of the factors related to survival outcomes obtained in our study with those obtained from the literature revealed certain differences. Among the previously reported variables affecting OS in PET-MF  and SMF ASXL1 mutations were relatively infrequent in the pre-PMF group compared with those in the overt MF group. This result is consistent with the previous reports that the presence of ASXL1 mutations also predicted progression [JAK2 was low in pre-PMF relative to that in overt MF. Based on these findings, homozygosity in the JAK2 mutations or higher VAF indicates higher vulnerability to progression, as shown in ET or PV cases [We analyzed the effect of individual genes on MF by comparing different groups. In this study, gression ,31 in thPV cases . SRSF2 and U2AF1 played a role in PMF, which had a higher incidence than that of SMF [U2AF1 is vital for hematopoiesis and is associated with thrombocytopenia in PMF [U2AF1 mutations and thrombocytopenia; however, this correlation was not observed in the SMF group. SRSF2 mutations were associated with progression in pre-PMF and showed a trend in PMF; however, they were not associated with progression in SMF. However, ZRSR2 mutations were associated with progression in SMF; this mutation has a higher incidence in SMF than in PMF [Courtier et al. suggested the existence of different mutational landscapes in patients with SMF and PMF, owing to the order of occurrence of mutations. They suggested that RNA splicing genes such as t of SMF . Among ta in PMF ,35. In tn in PMF .ASXL1, EZH2, SRSF2, or IDH1/2 were defined as molecular factors of high risk in PMF [TP53 and U2AF1 were associated with poor OS. In addition, mutations in RUNX1, TP53, and U2AF1 were also correlated with inferior PFS. However, Grinfeld et al. reported that leukemic transformation is related to the occurrence of mutations in RUNX1, TP53, and U2AF1 in MPN disease, which are consistent with our results [Our findings on the progression-related genes in PMF showed some discrepancies with those reported by Vannucchi et al. In their study, k in PMF . However results . These dASXL1) or RNA splicing genes . Interestingly, ASXL1, EZH2, SRSF2, IDH1, and IDH mutations were dominant in the third cluster, which was known to be a high-risk group in PMF. This finding indicated that mutations in different genes that frequently occur together need to be considered in addition to the single-gene effect. Within the SMF and pre-PMF groups, the second and third clusters, respectively, showed poor PFS. These findings implied that single genes and clusters of non-driver mutations affect MF survival differently among each group. It might be due to different genetic evolution timing and proportions in each histological MF subtype.Patients had an average of 1.8 mutations, making it difficult to use a single gene as a prognostic factor. This finding was due to varying gene frequencies. The single effect of univariate analysis did not reflect the co-occurrence effect. We compensated this limitation by using a hierarchical clustering method of non-driver mutations. Each subgroup was further divided into sets based on the dominance of either chromatin modifications (To identify the most influential mutation group in PMF in the literature, we applied the concept suggested by Courtier, et al. . They suOur study had several limitations. First, owing to the relatively small number of patients with pre-PMF, it is difficult to draw definite conclusions. Second, our study cohort was limited to a single center; thus, further studies are needed to verify the applicability of our findings to other groups. However, our study demonstrated the clinical and genetic characteristics of MF subtypes, which is important for discriminating secondary MF and prefibrotic MF. In this study, we showed that current risk stratifications are still important for predicting the outcome in patients with overt PMF. However, a widely known GIPSS in overt PMF could not correctly predict the outcome in SMF and pre-PMF. JAK2 inhibitor therapy [SRSF2 mutations [In this study, we investigated distinct clinical and genetic characteristics of patients with prefibrotic PMF, overt PMF, and SMF. Our findings further suggested the mutation profiles that could be widely applied for the stratification of patients with MF, including those with pre-PMF. Using this molecular profiling, symptomatic patients with pre-PMF could be candidates for close monitoring and/or therapeutic application such as  therapy . Furtherutations  or BET iutations  could be


AOX1, PYGM, NOS2, and SLC16A3  were found to have central roles in metabolic changes in response to heat stress. The negative effects of acute heat stress can be attributed to oxidative stress-driven changes at the inflammation metabolism nexus.This study integrates the differentially expressed genes and important metabolites found in the transcriptome and metabolome analyses of in vitro acute heat-stressed bovine granulosa cells. Proteins and vitamin B catabolism were the most; tryptophan, proline, pyridoxine, and riboflavin (downregulated metabolites in heat stress) were enriched in many joint pathways. Genes p-value < 0.05) metabolic pathways where metabolites and genes converged, this study found vitamin B6 metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism, arginine biosynthesis, tryptophan metabolism, arginine and proline metabolism, histidine metabolism, and glyoxylate and dicarboxylate metabolism. Important significant convergent biological pathways included ABC transporters and protein digestion and absorption, while functional signaling pathways included cAMP, mTOR, and AMPK signaling pathways together with the ovarian steroidogenesis pathway. Among the cancer pathways, the most important pathway was the central carbon metabolism in cancer. Through multiple analysis queries, progesterone, serotonin, citric acid, pyridoxal, L-lysine, succinic acid, L-glutamine, L-leucine, L-threonine, L-tyrosine, vitamin B6, choline, and CYP1B1, MAOB, VEGFA, WNT11, AOX1, ADCY2, ICAM1, PYGM, SLC2A4, SLC16A3, HSD11B2, and NOS2 appeared to be important enriched metabolites and genes, respectively. These genes, metabolites, and metabolic, cellular, and cell signaling pathways comprehensively elucidate the mechanisms underlying the intricate fight between death and survival in acute heat-stressed bovine granulosa cells and essentially help further our understanding (and will help the future quest) of research in this direction.Previous studies reported the physical, transcriptome, and metabolome changes in in vitro acute heat-stressed (38 °C versus 43 °C for 2 h) bovine granulosa cells. Granulosa cells exhibited transient proliferation senescence, oxidative stress, an increased rate of apoptosis, and a decline in steroidogenic activity. In this study, we performed a joint integration and network analysis of metabolomic and transcriptomic data to further narrow down and elucidate the role of differentially expressed genes, important metabolites, and relevant cellular and metabolic pathways in acute heat-stressed granulosa cells. Among the significant (raw  Ovarian granulosa cells present in the follicles nurture oocytes and have specialized roles in steroidogenesis in the ovaries ,2. Heat 2 incubator, while the control group of cells remained at 38 °C.The cell collection, culture, and treatment methods followed our previous study ,22,23. I4 for a colorimetric CCK-8 kit  based on cell viability in each well (of 96-well plates). Post-treatment absorbance of cells was measured at a 450 nm wavelength by a plate reader for cell viability, followed by similar repeated measurements at various time intervals (cell proliferation). Similarly, 1 × 104 cells in each well (of 96-well plates) were cultured for fluorocolorimetric ROS assay . Post-treatment fluorescence absorbance of cells was measured at excitation/emission = 485/535 nm by a plate reader for the ROS assay. Using the Annexin V-FITC kit , Annexin V-FITC /PI double staining was performed to evaluate the granulosa cell apoptosis according to the manufacturer’s instructions before being analyzed by flow cytometry. The data were analyzed by Flowjo software (version Win64–10.4.0). Similarly, the determinations of P4 and E2 concentrations in treated cell culture media were measured according to the manufacturer’s protocols of the respective ELISA kits . The data from at least six replicates each for cell proliferation, ROS, apoptosis measurements, and ELISA were analyzed using Graphpad Prism version 9.0.0 for Windows . Analysis of variance was carried out and means were compared through Tukey’s honestly significant difference (HSD) test at a 5% level of significance (α = 0.05). All the data presented in the figures are expressed as means ± standard errors (S.E).Intracellular reactive oxygen species (ROS), apoptosis, and hormone measurement methods followed our previous studies ,22,23. CComprehensive methods of RNA sequencing were explained in our previous articles ,22. In bComprehensive methods involved in the metabolome assay were detailed in our previous study . BrieflyHenceforth, in this study, we conducted a joint integrative analysis of our previous metabolome  and tranhttps://cn.string-db.org/ accessed on 22 April 2022).For this purpose, the “Joint-Pathway Analysis” module of MetaboAnalyst 5.0 was used. Mapping of both gene and metabolite features was assessed and manually corrected in case matching options were available. In the first step, the “Gene-metabolite interaction network” sub-module with default settings was used for the interaction analysis among genes and metabolites. In the second step, the “Metabolite-metabolite interaction network” sub-module with default settings was used for the interaction analysis among metabolites based on both genes and metabolite data input. For the third interactive network analysis, the “Metabolite-gene-disease interaction network” sub-module with default settings was used for the interaction analysis among genes. Moreover, all of the important DEGs found in the integration and network analyses of metabolome and transcriptome data were subjected to a PPI physical network analysis at a medium confidence score of 0.4 using STRING version 11.5 (p < 0.05) difference in cell viability was observed at 24 and 48 h time points between both groups. A significant increase in the intracellular ROS level was observed in the treatment group compared to the control group (p < 0.05) apoptotic rate (p < 0.05) decreased in the culture media of the heat-stressed GCs compared to the control GCs (Bovine granulosa were exposed to in vitro heat stress treatment (43 °C) while the control group remained at 38 °C ,22. Cellol group B. Similatic rate C, as shotic rate D and heatic rate E groups.A total of 256 significant DEGs and 51 differentially expressed important metabolites along with their logFC values were found in the RNA sequencing analysis and LC–MS-based untargeted metabolome analysis, respectively, which were used in this study for integrated analysis of transcriptome and metabolome underlying the biological mechanisms of acute heat-stressed (43 °C for 2 h) bovine granulosa cells. These data came from our previous transcriptome and metabolome investigation performed on the same sample replicates of the acute heat-stressed granulosa cells ,22. The Differentially expressed genes of the transcriptomic data used in the integrated analysis of this study were subjected to the Kyoto encyclopedia of genes and genomics (KEGG) pathway-based enrichment analysis; results of the pathway analysis are illustrated in Statistical results of the transcriptomic-enriched pathway analyses and a list of enriched genes in each pathway are given in Significant DEGs and important metabolites found in heat-stressed granulosa cells were subjected to the integrated KEGG-based pathway enrichment analysis, as illustrated in Statistical summary results of the top enriched pathway of the integrated analysis are detailed in Several important metabolites found in the metabolomes of heat-stressed granulosa cells are few (in number). A joint pathway analysis of data involving only metabolic pathways was carried out . The staA joint analysis of metabolome and transcriptome data under  was querFurthermore, a network analysis of all pathways was carried out using transcriptome and metabolome data input. Additionally, a joint metabolic analysis of transcriptome data under  was querSignificantly differentially expressed genes and metabolites were used to carry out the KEGG-based interactive network analysis among them, as shown in the interaction network illustration in A joint interaction network among metabolites based on the KEGG database is illustrated in Significantly differentially expressed genes and metabolites were used to carry out the KEGG-based interactive disease network analysis, as shown in the interaction network illustration in GNB3, KDR, CYP1B1, ADCY2, RGS9, INSRR, GSTA5, VEGFA, ADH6, IGF2, and MDM4 were the central network nodes.To obtain functional insights into the DEGs found in multiple integrations and the network analysis of transcriptomes and metabolomes, all DEGs were combined and a physical protein–protein interaction (PPI) network analysis (STRING) with a medium confidence score (0.4) was carried out, as presented in Heat stress caused by biochemical alterations in the maternal reproductive system has been attributed to low conception rates and higher embryonic losses in cattle ,27,28. GPYGM, IGF2, MAOB, INSL3, AOC2, AOX1, ATP2A1, SLC2A4, SLC27A5, ADH6, NOS2, etc. These genes are particularly involved in catabolic support to heat-stressed granulosa cells, as shown by starch and sucrose metabolism and various amino acid metabolism pathways.A pronounced decline of cell proliferation potential was observed in heat-stressed granulosa cells. Earlier studies also reported similar results, where acute heat-stressed 45 ℃) granulosa cells regained proliferation by 48 h after the completion of heat treatment ,20,30. H5 ℃ granuSLC7A11 [PPARGC1A and upregulation of SIRIT1, SLC2A4, HMGCS1, and SERBP1 [ATP-binding cassette (ABC) transporters constitute a superfamily of conserved membrane proteins responsible for the transport of nutrients across cells . This paSLC7A11 —may be aSLC7A11 ,22. AnotSLC7A11  appear tSLC7A11 ,4. FurthSLC7A11 . The mosSLC7A11 . In our SLC7A11 ,53. The SLC7A11 , it is cd SERBP1 ,54. GlutCYP1B1, PYGM, ICAM1, HSD11B2, and OXT. Downregulation of HSD11B2 is justifiable as there is evidence of the low steroidogenic capacity of heat-stressed granulosa cells [ADCY2, CYP1B1, and PLA2G4B. This decline in the steroidogenic activity of GCs can be attributed to the transcriptional downregulation of STAR, CYP11A1 [ICAM1 and PYGM are probably interesting findings. Amino acid catabolism and altered immune response in the shape of upregulated cytokine signaling may explain its role in heat-stressed granulosa cell adaptation and cancer cells. The highly upregulated PYGM gene, an enzyme involved in glycogenolysis, is involved in diverse insulin and glucagon signaling, necroptosis, inflammatory response, cellular energy support, and cancer progression [ICAM1 in the one-carbon metabolism pathway through an integrated analysis is an important finding because its upregulation reduces ovarian cancer cell growth [A joint network analysis of metabolites and genes revealed sa cells ,21; howe CYP11A1 . This st CYP11A1 ,56; upre CYP11A1 . Furthergression . Similarl growth ; at the l growth .SLC16A3, a monocarboxylate transporter [SLC16A3 is particularly shown as a prognostic biomarker of cancer aversion [MDM4 and CSNK1B being interconnected as well as nodes toward the involvement of the p53 signaling pathway at the conjunction of metabolic pathways through complex transcription mechanisms. Our transcriptomics study (reporting upregulation of p21 and p16 and downregulation of p53) is interesting, suggesting cell cycle arrest in heat-stressed granulosa cells [MDM4 activity, and upregulated p21 and p16, a fight between cell senescence and apoptosis can be assumed [MDM4, IGF2, PPARGC1A, PPARGC1B, and upregulated HIF1A suggest the interconnecting role of p53 and heat-stressed mitochondrial damage [Four cancer pathway enrichments were observed in this study, characterized by the upregulation of glutamine, citric acid, leucine, arginine, tyrosine, and the downregulation of progesterone. These findings are related to cancer, as heat-stressed cells resemble the cancer phenotype; at the same time, heat treatment is a potential therapy for the treatment of tumors. Heat treatment has been long regarded as an important treatment option for cancer ; howevernsporter . This gensporter , which insporter ,65. The aversion ,65; its aversion . In thissa cells . In the  assumed ,68,69. S assumed . Metabol assumed . Recentl assumed . Cell cy assumed . Heat st assumed  and upre assumed ,73. Highl damage ,74, as sl damage ,76.MAOB, AOC2, and upregulated AOX1, ADH6 pairs involved in vitamin B6 and amino acid metabolism may be considered important candidate genes. This study provided additional evidence of the transcriptional suppression of the steroidogenic potential of heat-stressed granulosa cells in the forms of ADCY2, CYP1B1, and PLA2G4B; COL11A2 (a downregulated gene) may be considered a universal candidate gene involved in amino acid metabolism. Furthermore, upregulated ICAM1 and PYGM are likely interesting findings regarding the inflammation metabolism nexus in granulosa cells exposed to heat stress. Moreover, via the demonstrations of various cell signaling and metabolic pathways, this integrative analysis of metabolome and transcriptome acute heat-stressed granulosa cells provided an interesting conjecture of metabolites and genes through an integrated analysis of transcriptome and metabolome data.The etiology of various changes in heat-stressed granulosa can be (at least in part) attributed to varying degrees of cellular stress, impairment in lipid transport and metabolism, the inflammation–metabolism nexus, and disruption in energetic metabolism. Threonine, phenylalanine, and proline appeared to be the only downregulated abundant amino acids in various pathways. Similarly, the involvement of downregulated succinic acid, vitamin B6, and riboflavin in many pathways are important as well as nodes toward the simple sugars and vitamin importance in the fight against heat stress at the cellular level. Since we observed cell proliferation activity recovery after heat stress, upregulated choline and citric acid metabolites may primarily be considered important metabolites involved in heat-stressed granulosa cells. Downregulated


Gossypium spp.) growth, production, development, and production worldwide. Some wild diploid cotton species are remarkably tolerant of water deficit and constitute an important reservoir for understanding the molecular mechanisms of Gossypium spp. drought tolerance and improving cultivated upland cotton. Here, we utilized RNA-Seq technology to characterize the leaf transcriptomes of a wild African diploid cotton species, Gossypium anomalum, under drought stress. A total of 12,322 differentially expressed genes (DEGs) were identified after mapping valid clean reads to the reference genome of G. anomalum, of which 1243 were commonly differentially expressed at all stages of drought stress. These genes were significantly enriched for molecular functions Gene Ontology terms related to cytoskeleton, hydrolase activity, cellular redox, and binding. Additionally, a substantial proportion of enriched biological process terms concerned cell or subcellular processes, while most in the cellular components category concerned membrane function and photosynthesis. An enrichment analysis against the Kyoto Encyclopedia of Genes and Genomes showed the top significantly enriched pathways to be photosynthesis-antenna proteins, amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, MAPK signaling pathway, glutathione metabolism, and plant hormone signal transduction. The DEGs also exhibited interestingly significant enrichments for drought stress-induced tandemly repeated genes involved in iron ion binding, oxidoreductase activity, heme binding, and other biological processes. A large number of genes encoding transcription factors, such as MYB, bHLH, ERF, NAC, WRKY, and bZIP, were identified as playing key roles in acclimatizing to drought stress. These results will provide deeper insights into the molecular mechanisms of drought stress adaptation in Gossypium spp.Drought stress is a key limiting factor for cotton ( Drought is one of the major abiotic stresses that limits plant growth, development, and production worldwide ,2. Some Gossypium spp.) is cultivated worldwide and constitutes the preeminent source of natural fibers for the textile industry [Gossypium hirsutum L. 1), commonly known as upland cotton, is responsible for ~90% of the world’s annual cotton production on account of its relatively high yield potential and moderate fiber quality [Cotton , a diploid wild species in Gossypium with a close relative A-genome species, grows widely in arid to extremely arid parts of Africa across the southern Sahara from the Sudan to the upper reaches of the valley of the Baraka River in Eritrea [G. anomalum exhibits phenotypes that make plants more resistant to drought stress, such as small and deeply parted palmate leaves, thick and hard seed coats, and dense hairs. Previous literature has documented its drought tolerance [G. anomalum has been limited. To date, there were no transcriptomic data of G. anomalum under drought stress deposited in the NCBI database . Eritrea ; thus, t Eritrea ,23. Morpolerance ,24,25,26G. anomalum seedlings during different stages of stress and to identify key regulators or pathways involved in this response. These transcriptomic data provide a useful resource for further research that will ultimately construct a comprehensive understanding of the molecular mechanisms for drought tolerance in Gossypium spp. that might be of value in cotton breeding programs.Here, we performed RNA-Seq with the aim of characterizing dynamic changes of the molecular responses to drought stress in G. anomalum seedlings and absolute soil water content (ASWC) decreased especially in later periods (7 d and 10 d) under drought stress , plants at 7 d and 10 d exhibited a slight leaf curl and chlorosis (The relative water content (RWC) of t stress . This wahlorosis .−2 s−1), transpiration rate , and stomatal conductance , also significantly decreased (p < 0.01) at 5 d, 7 d, and 10 d under drought stress, while the intercellular CO2 concentration  steadily increased (p < 0.05)  , indicatp < 0.05, p < 0.01) in G. anomalum leaves (2O2) content showed no obvious changes at 3 d into treatment but was significantly increased (p < 0.01) at 5 d, 7 d, and 10 d  scavenging ability and control intracellular homeostasis [p < 0.05, p < 0.01) compared to the control (0 d)  significantly increased  . CAT actol (0 d) . These rG. anomalum leaves at 0, 3, 5, 7, and 10 d of drought treatment with three replications. Each sample was represented by at least 39,188,662 raw reads, which is sufficient for a quantitative analysis of gene expression. After quality checks and adapter removal, 39,142,792–50,408,364 clean reads were obtained for further analysis. The Q20 and Q30 values across all samples were ≥ 96.80% and 91.48%, respectively. Of the total clean reads, 91.59–95.79% were mapped and 89.14–93.30% uniquely so to the reference sequence of G. anomalum [de novo assembled, resulting in 1820 new contigs with a mean length of 1383 bp. A summary of RNA-Seq data is given in To conduct a broader survey of genes involved in drought tolerance, RNA-Seq was performed for anomalum . AdditioG. anomalum, the 3 d, 5 d, 7 d, and 10 d libraries were compared with the control (0 d). This determination of expression changes uncovered 12,322 differentially expressed genes (DEGs) at the threshold of |log2FoldChange| ≥ 1 and padj ≤ 0.05, of which 11,606 were mapped on the reference genome of G. anomalum and 716 were annotated as novel in the current study (To identify genes that undergo significant expression changes during drought stress in nt study . Regardint study . The numnt study .−∆Ct method) (Goano05G2948), probable glutathione S-transferase (Goano03G0271), WRKY transcription factor 18 (Goano06G1393), scarecrow-like protein 13 (Goano05G1959), myb-related protein 108 (Goano11G1258), myb-related protein Myb4 (Goano13G2422), phenylpropanoid: glucosyltransferase 1 (Goano13G2723), phosphorylated protein of 32 kDa (Goano12G1626), protein phosphatase 2C , catalase isozyme 1 (Goano01G1791), ubiquitin carboxyl-terminal hydrolase 12 (Goano10G2669), and proline transporter 1 (Goano10G3130). The expression patterns of these 12 selected drought-responsive genes, as determined by qRT-PCR, were obviously consistent with the RNA-seq data  using gene-specific primers and the relative threshold cycle (Ct) method (2 method) . These sseq data , thus coTo decipher the biological processes affected by drought stress, a GO-based classification of the DEGs was carried out using the biological process (BP), cellular component (CC), and molecular function (MF) terms. A total of 7234 DEGs were annotated with 42 functional terms ; howeverpadj ≤ 0.05), including 43 MF terms, 31 BP terms, and 16 CC terms , amino sugar and nucleotide sugar metabolism (ko00520), starch and sucrose metabolism (ko00500), MAPK signaling pathway (ko04016), glutathione metabolism (ko00480), and plant hormone signal transduction (ko04075) .A total of 1243 genes exhibited differential expression in all stages of drought stress . The expOf these 1243 common DEGs, 776 genes were found to have GO annotations based on sequence similarity. These genes represented 36 terms in all, which included 13 BP, 11 CC, and 12 MF terms. The most-represented GO terms were metabolic, cellular, and single-organism process in the BP category; cell part, cell, and organelle in the CC category; and binding and catalytic activity in the MF category. The GO terms of these 1243 common DEGs are presented in The annotation of these 1243 common DEGs based on the KEGG database revealed 225 genes to be associated with six definite pathway groups, including 396 in metabolism, 58 in genetic information processing, 29 in environmental information processing, ten in cellular processes, 16 in organismal systems, and one in human diseases . A largeG. anomalum genome, of which 704 were differentially expressed in response to drought stress. A GO enrichment analysis indicated these drought stress-modulated tandemly repeated genes to be associated with 82 GO terms, of which the top four most significantly enriched were GO:0005506 (iron ion binding), GO:0016705 , GO:0020037 (heme binding), and GO:0046906 (tetrapyrrole binding)  .Pairwise comparisons of each drought treatment timepoint against the control  revealed a total of 951 transcription factors (TFs) to be differentially expressed . These TG. anomalum during drought stress and identified 12,322 DEGs that are altered in response to drought stress. These DEGs exhibited significant enrichments for molecular functions GO terms related to cytoskeleton, hydrolase activity, cellular redox, and binding; biological processes terms involving the cell or subcellular processes; and cellular component terms concerned with membrane function and photosynthesis. These findings are in agreement with other studies [The diversity of modern cultivated upland cotton has been dramatically constricted due to extensive selection within limited resources, and it has become a major bottleneck in improving cotton drought tolerance. Wild cotton relatives represent potentially valuable gene pools and are the primary source of drought-responsive genes. Here, we performed an RNA-Seq analysis of leaves from the wild African cotton species  studies ,34,35 an studies , droughtGhCBF3, AREB1, and AREB2 in cotton has been shown to improve drought tolerance due to the higher chlorophyll, proline, and relative water contents [GhPYL9-11A in transgenic Arabidopsis plants [G. anomalum. These included two genes encoding SnRK2 (Goano08G2297 and Goano06G0436), which improves drought tolerance by enhancing ABA signaling [Goano08G1795 and Goano04G2489), an ABA receptor that takes part in triggering ABA responses [GhMPK3, GhMAP3K1, GhMKK4, and GhMPK6, have previously been implicated in the responses of G. hirsutum L. and G. barbadense L. to drought stress [GhMAP3K49 is significantly induced by ABA and ROS, and its product interacts with GhMKK9 and GhMKK4 in a complete cascade [MKK2 (Goano07G0148 and novel.1799), MPK6 (Goano01G1166), MARK3/6 (Goano01G1166 and Goano02G1761), MKK9 (Goano12G0072), and MAPK17/18 (Goano10G0114) were up-regulated, especially in the later periods stage of drought stress, which heavily implicates MAPK pathways in the response to drought. To date, only one gene conferring drought tolerance, namely Goano05G0268, has been cloned from G. anomalum [Broadly speaking, plant hormones regulate stress-mediated signaling pathways in plant adaptation to abiotic stress . Concerncontents ,39. Addis plants . This stignaling , and twoesponses . Severalt stress ,50,51. G cascade . A novel cascade . In thisTaCYP81D5, a gene isolated from a salt stress-related hotspot region which consisted of five tandemly distributed copies, enhanced the salinity tolerance at both seedling and reproductive stages via accelerating ROS [TaCYP81D5 alone had no effect on salinity tolerance, but the knockdown of all TaCYP81D members in the cluster induced the sensitivity to salt stress [G. anomalum exhibited an interestingly significant enrichment for drought stress-induced tandemly repeated genes involved in iron ion binding, oxidoreductase activity, heme binding, tetrapyrrole binding, transferase activity, and other biological processes. These enrichments suggest a characteristically higher overall stress-tolerant evolution of the species.The high proportions of repetitive elements and transposons in the genome makes it easy to generate duplicated gene fragments/alleles with no function, neo-function, redundant function, or enhanced function ,55. For ting ROS . The knot stress . In thisGossypium spp. Further analysis of these drought-responsive genes without functional annotation will enhance our understanding of drought tolerance mechanisms in plants.The common DEGs that exhibited an altered expression throughout the drought treatment in this study included a large proportion  without a GO annotation. Moreover, many of these genes exhibited a substantial change in expression levels during drought stress. These results suggest that more unknown genes or complex pathways are involved in the response to drought tolerance in Gossypium species G. anomalum were pre-germinated in distilled deionized water in a plant incubator at 60% humidity, 16 h day/8 h night, and a day/night temperature of 28/23 °C. Then, germinated seeds were planted in commercial sterilized soil and cultured in the same conditions for 15 days.Seeds of the wild The uniformly developed seedlings with three true leaves were first well-watered, and then water was withheld to induce drought stress. The second leaf from the top of five individual seedlings in each biological replicate was collected at 0, 3, 5, 7, and 10 d after beginning the drought treatment. All samples were frozen immediately in liquid nitrogen and then stored at −70 °C for the extraction of RNA.G. anomalum and absolute soil water content (ASWC) were determined by the drying method [The relative water content (RWC) of g method ,58.2 concentration in the reference leaf chamber was controlled at a constant value of 400 μmol mol−1, and the photosynthetically active radiation and air relative humidity were set to 1500 μmol m−2 s−1 and 50%, respectively. The experimental apparatus automatically recorded the Pn, Tr, Gs, and Ci of the second leaf from the top of five individual seedlings at 0, 3, 5, 7, and 10 d after drought stress.The LI-6800 portable photosynthesis system  was used to observe the photosynthetic parameters of the seedlings. The CO2O2, and PRO contents, CAT, SOD, and POD activity of the second leaf from the top of five individual seedlings at 0, 3, 5, 7, and 10 d after drought stress were measured by assay kits .The MDA, HTotal RNA for each sample was extracted using the RNAprep Pure Plant Plus Kit  following the manufacturer’s instructions. The total RNA amounts and integrity were assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system .RNA-seq libraries were constructed using the Illumina TruSeq Stranded RNA Library Preparation Kit , and then quantified with a Qubit2.0 Fluorometer . After all libraries were constructed, they were pooled according to the effective concentration and the target amount of data, then sequenced on the Illumina NovaSeq 6000 platform (150 bp paired-end).G. anomalum [de novo assembled using StringTie (v1.3.3b) with a novel network flow algorithm [After the adapter removal and quality checks, we aligned the valid clean data to the reference genome of anomalum  using thanomalum . To supplgorithm . Subsequlgorithm  was usedDESeq2 R package (1.20.0) [2FoldChange| ≥ 1 and padj ≤ 0.05.Using the (1.20.0) , a diffe−5 against the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Upon the GO functional classification and KEGG pathway analysis, the functional category distribution frequency was respectively calculated for biological process level 2 terms and metabolic pathways. Compared to the reference gene background of G. anomalum, a GO and KEGG enrichment analysis was performed for DEGs in each the four comparisons using an FDR adjusted p-value ≤0.05 as the cutoff. The number of DEGs in every GO term and KEGG pathway were displayed using the edgeR package.The functional annotation of all genes was performed according to the best BLAST hit by BLASTP  using BLASTx (version 5.0).−20, and homologous genes with a maximum of five intervening genes were defined as tandem duplicates [clusterProfiler package with the cutoff set at the adjusted p value < 0.05 [To identify tandemly repeated genes, all genes anchored to the chromosomes were compared by BLASTP  was used as an internal standard to normalize the total amount of cDNA in each reaction. Gene-specific primers for the candidate genes were designed with the Beacon Designer software (® Premix Ex TaqTM (Tli RNaseH Plus) kit (TaKaRa) according to the manufacturer’s instructions, and all reactions were run as three technical replicates on a QuantStudio 5 Real-Time PCR System. Relative transcript levels were computed using the 2–ΔCt method .For qRT-PCR, cotton endogenous histone-3 , including 43 in the molecular functions category, 31 in the biological processes group, and 16 in the cellular components cluster, respectively. An enrichment analysis against the KEGG showed the top significantly enriched pathways to be photosynthesis-antenna proteins, amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, MAPK signaling pathway, glutathione metabolism, and plant hormone signal transduction. In addition, the DEGs included tandemly repeated genes and transcription factors, such as MYB, bHLH, ERF, NAC, WRKY, and bZIP. The data presented here provide deeper insights into the molecular mechanisms of drought stress adaptation in Gossypium spp.RNA-Seq was performed on leaves from drought-treated


Regulator of calcineurin 2 (RCAN2) has been reported to promote food intake and weight gain in animal studies. However, its effect on body weight in humans is unclear.This study aimed to investigate the relationship between serum RCAN2 concentrations and participants with overweight/obesity.A cross-sectional study was performed in 872 Chinese adults, including 348 participants with normal weight (NW), 397 participants with overweight (OW), and 127 participants with obesity (OB). All participants were divided into NW, OW and OB groups according to their body mass index (BMI). Serum RCAN2 concentrations were determined by enzyme-linked immunosorbent assay.p < 0.001). The percentages of OW/OB gradually increased in tandem with increasing tertiles of RCAN2 (p < 0.001). Additionally, serum RCAN2 concentrations were significantly correlated with a series of anthropometric and metabolic parameters, predominantly including body weight, BMI, SBP, DBP, total cholesterol, triglycerides, HDL-C, LDL-C . Furthermore, logistic regression analysis showed that the risk of OW/OB was significantly increased with the increase of serum RCAN2 concentrations. Receiver operation characteristic (ROC) curve analysis revealed that serum RCAN2, especially serum RCAN2/(AST/ALT) ratio, might serve as a candidate biomarker for obesity.Serum RCAN2 concentrations gradually increased with the increase of BMI (Serum RCAN2 concentrations were increased in subjects with OW/OB. The increased serum RCAN2 concentrations were associated with the increased risks of OW/OB. According to the World Health Organization (WHO), overweight (OW) or obesity (OB) refers to the excessive or abnormal accumulation of fat in organs and tissues of the body, thereby increasing health risks . Obesity3)-responsive gene in cultured skin fibroblasts  was initially discovered as a thyroid hormone  investigate the serum RCAN2 concentrations of 348 participants with normal weight, 397 participants with overweight, and 127 participants with obesity; 2) analyze the correlation between serum RCAN2 concentrations and clinical indicators and metabolic indicators; 3) explore the diagnostic value of serum RCAN2 for discriminating individuals with obesity from controls.2, overweight (OW) group (24 ≤ BMI ≤ 28 kg/m2), and obesity (OB) group (BMI > 28 kg/m2) : normal weight (NW) group (18.5 ≤ BMI<24 kg/m8 kg/m2) . All subAll protocols followed the ethical guidelines of the 1964 Declaration of Helsinki and were approved by the Human Research Ethics Committee of the Southwest Medical University Hospital (license number: KY2021086). Informed written consent was obtained from all participants.2). Waist circumference (WC) and hip circumference (HC) were measured using a cloth tape. Waist-to-hip ratio (WHR) was calculated as WC (cm)/HC (cm). After resting for at least 5 minutes, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate were measured using a medical automatic electronic blood pressure monitor . All anthropometric parameters were measured by professionally trained nurses.After overnight fasting, all participants underwent anthropometric measurements with light clothing and no footwear. Body height and weight were measured using an ultrasound analyzer , BMI was calculated as weight (kg)/height  was used to detect alanine aminotransferase (ALT), aspartate aminotransferase (AST), total protein (TP), albumin (ALB), globulin (GLO), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP), urea nitrogen (urea), uric acid (UA), creatinine (Crea), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), and homocysteine (HCY). Peripheral white blood cell (WBC) and neutrophil (NEU) counts were measured using an automated blood cell counter .Serum RCAN2 concentrations were quantified using a commercial enzyme-linked immunosorbent assay (ELISA) kit  according to the manufacturer’s protocol. Serum samples were diluted 10-fold prior to the assay. The intra- and inter-test variations were less than 8% and less than 12%, respectively. The detection range of the kit is 0.156ng/mL - 10ng/mL.n (%). The differences between groups of continuous variables were evaluated by Student’s t-test or Mann-Whitney U-test and one-way analysis of variance (ANOVA) or Kruskal-Wallis test. Bonferroni-corrected p-values were used in multiple testing. The differences between groups of categorical variables were accessed by Chi-square test. In order to assess the correlation between serum RCAN2 concentrations and other variables, the data was analyzed by Pearson correlation or Spearman correlation test. Multiple liner regression analysis was conducted with naturally logarithmic transformed serum RCAN2 as dependent variable and other parameters as independent variables. Binary logistic regression analysis was performed to explore the risks of serum RCAN2 concentrations for overweight/obesity. The diagnostic value of serum RCAN2 or serum RCAN2/(AST/ALT) ratio for the obesity was accessed by the area under the receiver operating characteristic (ROC) curve (AUC). Two-tailed p < 0.05 was considered statistically significant. All statistical analysis and graphics were performed using SPSS 25.0  and GraphPad Prism 8.0 .Continuous variables are expressed as mean ± standard deviation (SD), Categorial variables were expressed as p < 0.05) among the three groups. RCAN2 concentrations were gradually increased  (p < 0.01). We also compared the differences in RCAN2 levels between men and women in the same BMI classification, men with normal weight and overweight have significantly higher RCAN2 levels, but this difference was not significant in subjects with obese . As displayed in the p < 0.001).All subjects were divided into three groups according to serum RCAN2 tertiles . As shown in p < 0.05) in all subjects. In the group with normal weight, serum RCAN2 concentrations were positively correlated with BW, height, WHR, SBP, DBP, ALT, AST, TP, ALB, GLO, GGT, TC, TG, LDL-C and FBG . In the overweight group, serum RCAN2 concentrations were positively correlated with age, BW, WHR, SBP, DBP, ALT, AST, IBIL, GGT, UA, Crea, TC and TG, negatively correlated with AST/ALT and eGFR . In the group with obesity, serum RCAN2 concentrations were positively correlated with AST/ALT, UA, TC and TG, and negatively correlated with WBC, NEU, and DBIL .Correlation analysis was used to investigate the relationship between metabolic parameters and serum RCAN2 concentrations. As depicted in The independent variables associated with the concentration of serum RCAN2 were discussed by multiple linear regression analysis. As shown in p < 0.001). After adjusting for age and sex in Model 1, the tendency still existed with an OR of 2.509 . In model 2, even further adjusting for WC, HC, WHR, WBC, NEU, ALT, AST, AST/ALT, TP, ALB, GLO, A/G, TBIL, DBIL, GGT, ALP, Urea, UA, Crea, FBG, HCY, eGFR, Height, and heart rate, the increased OR of obesity in the highest RCAN2 concentrations was also observed and higher than in model 1 . Similarly, subjects in the highest tertile of RCAN2 concentrations had an increased risk of overweight when compared with those in the lowest tertile of RCAN2 concentrations .To investigate the relationship between serum RCAN2 concentrations and the risks of overweight and obesity, participants with overweight/obesity and normal weight were stratified into three parts based on serum RCAN2 tertiles. As shown in When considered as continuous variables, every 1-unit increase in serum RCAN2 concentrations was associated with 9.9%, 9.3%, and 10.2% increases, respectively, in risk of overweight in univariate model, model 1 and model 2. For obesity risk, in univariate model, model 1 and model 2, every 1-unit increase in serum RCAN2 concentrations was associated with an increased risk of 17.5%, 17.6% and 224.4%, respectively Table 2.p < 0.001, sensitivity = 55.1%, specificity = 69.5%). Diagnosis value accuracy was improved when use serum RCAN2/(AST/ALT) ratio as a biomarker, with AUC of 0.818 , sensitivity of 76.0% and specificity of 75.4% . Hence, circulating FT3 may not affect serum RCAN2 concentrations.RCAN2 has two primary transcripts, RCAN2-3 and RCAN2-1 (formerly named ZAKI-4α and ZAKI-4β) , 35. RCAin liver . In all The present study also has several limitations worth mentioning. Firstly, RCAN2 has two different splicing variants: RCAN2-1 and RCAN2-3. RCAN2-3 seems to play a major role in regulating body weight. The relationship between RCAN2-1 and RCAN2-3 and overweight/obesity was not investigated separately, so it is not clear which splicing variant is more important in regulating human weight. Secondly, all participants in this study were primarily from China. Therefore, the extrapolation of serum RCAN2 in participants with overweight/obesity diagnosed by BMI criteria should be conducted in other races. Thirdly, this is a cross-sectional study and therefore no causal a conclusion could be drawn between serum RCAN2 concentrations and the increased risk of overweight/obesity. Thus, larger longitudinal intervention studies are needed to confirm our findings in the future. Fourthly, small number and the relatively large span of BMI of participants with obesity led to increased data heterogeneity. In the future research, a larger population and further stratified analysis for obese adults are needed. Finally, all subjects were recruited from physical examination center, which may exist a selection bias. Despite these limitations, this study also has strength. This is the first study to investigate serum RCAN2 concentrations in participants with overweight/obesity and the findings indicated that RCAN2 is a risk factor for overweight/obesity.This study found that serum RCAN2 concentrations were significantly increased in patients with overweight and obesity. The percentages of OW/OB subjects gradually increased in tandem with increasing tertiles of RCAN2. The increased serum RCAN2 concentrations were associated with the increased risks of overweight/obesity. Serum RCAN2, especially RCAN2/(AST/ALT) ratio might be the candidate diagnostic markers for obesity.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Human Research Ethics Committee of the Southwest Medical University Hospital (license number: KY2021086). The patients/participants provided their written informed consent to participate in this study.JF and YX conceived, designed and supervised the study; XT, QR, YZ, and TY provided research guidance; HW, XF, and QR collected the data and biological samples; HW, XF, and QR performed the measurements of serum RCAN2 concentrations; HW and XF analyzed the data and wrote the manuscript; and QR, YZ, XT, TY, JF, and YX critically reviewed and edited the manuscript. All authors read and approved the final manuscript.The Natural Science Foundation of China (grant no. 81970676), the Doctor Initiation Fund of the Affiliated Hospital of Southwest Medical University (grant no. 19064), the Key Project of Natural Science of Southwest Medical University (grant no. 2020ZRZD003).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Increasing evidence has supported a link between obstructive sleep apnea (OSA) and cognition, and blood-brain barrier (BBB) dysfunction which can be reflected by paroxysmal slow wave events (PSWEs) may be a potential mechanism. The purpose of our study was to investigate the correlation between the PSWEs and cognitive impairment in patients with OSA, with a focus on the possible mechanism.In total, 339 subjects with subjective snoring complaints from the Sleep Medicine Center underwent magnetic resonance imaging and whole-night polysomnography. OSA was defined as apnea-hypopnea index (AHI) ≥ 5 events/h. MCI was defined as the MoCA < 26 and met the criteria: (1) subjective cognitive impairment; (2) objective impairment in one or more cognitive domains; (3) slightly impaired complex instrumental daily abilities, but independent daily living abilities; and (4) no dementia. The PSWEs calculated by self-developed Python scripts were defined for EEG recordings as a median power frequency of < 6 Hz for more than five consecutive seconds. Serum cyclophilin A (CyPA) and matrix metalloproteinase-9 (MMP-9) levels and amyloid-β 42 levels in neuron-derived exosomes were determined. The participants who received continuous positive airway pressure (CPAP) were followed up and their PSWEs were recalculated after 1 year of treatment.n = 157), OSA-MCI group (n = 118), and controls  (n = 64). The total PSWEs and the occurrence per minute of PSWEs at stage REM in the OSA+MCI group were higher than those in the OSA-MCI and control groups. The duration ratio of PSWEs at stage REM in the OSA+MCI group significantly increased. The total PSWEs and PSWEs at the F4-M1, O1-M2, and O2-M1 channels in stage REM were independently associated with cognitive impairment in OSA patients. There were positive correlations between the PSWEs and serum CyPA and MMP-9 levels in patients with OSA. The mediation analysis showed that the relationship between mean SaO2 and percentage of sleep time spent with oxygen saturation <90% with MoCA scores was mediated by the total PSWEs (proportion of mediation 77.89% and 82.89%). The PSWEs were negatively correlated with global cognitive performance and cognitive subdomains. After 1 year of CPAP treatment, the total PSWEs, PSWEs in stage REM, and serum CyPA and MMP-9 levels decreased significantly, and MoCA scores were improved compared with baseline.A total of 339 participants were divided into the OSA+MCI group (The PSWEs were implicated in cognitive impairment in patients with OSA, and the mechanisms of cognitive impairment due to hypoxia in OSA patients could be BBB dysfunction. The PSWEs can be used as a marker of cognitive impairment in patients with OSA.This trial is registered on the Chinese Clinical Trial Registry, number ChiCTR1900021544. The trial was registered on February 27, 2019. An increasing number of studies support the link between obstructive sleep apnea (OSA) and cognitive impairment, and the underlying mechanisms may involve blood-brain barrier dysfunction. This study analyzed EEG spectral features during a night of sleep in order to identify the correlation between paroxysmal slow wave events (PSWEs) and cognitive impairment in patients with OSA. Our study shows associations of increased PSWE occurrences with cognitive impairment in patients with OSA, and the PSWEs was correlated with levels of cognitive impairment. The mechanisms of cognitive impairment due to hypoxia in OSA patients could be blood-brain barrier dysfunction reflected by the PSWEs. The results suggest that the PSWEs may be a marker for cognitive impairment in OSA patients in assessing disease burden to guide therapeutic decisions.Obstructive sleep apnea (OSA), a highly prevalent worldwide public health problem, is characterized by repetitive episodes of apnea-hypopnea due to partial or complete upper airway obstruction during sleep, resulting in recurrent intermittent hypoxia and sleep fragmentation . ResearcThe blood-brain barrier (BBB) is a selective diffusion barrier located in the brain capillaries, and it maintains homeostasis by tightly regulating the movement of molecules, ions, and cells between the blood and the central nervous system , 6. ThusIn this study, we recruited patients with snoring as the chief complaint, established cross-sectional and longitudinal studies, analyzed PSG recordings from OSA patients, and calculated the occurrence and duration of PSWEs. We put forward a hypothesis that the PSWEs were associated with cognitive impairment in patients with OSA and were related to the levels of cognitive impairment in patients with OSA.This cross-sectional study included participants with subjective snoring complaints recruited from the Sleep Medicine Center of Weihai Municipal Hospital from June 2019 to June 2021. The controls were recruited from community. The inclusion criteria were participants aged 35 to 80 years old without neuropsychological evaluation in the last year and without history of major surgery or trauma in the previous 3 months. No subjects had a previous diagnosis of OSA or dementia, and none had received treatment for snoring.The exclusion criteria were any previous or current history of neurological or psychiatric disorders that might confuse cognition, including stroke, intracranial infection, traumatic brain injury, hydrocephalus, epilepsy, brain tumors, neurodegenerative diseases , other sleep disorders , schizophrenia, major depression, and medication use known to affect cognition or sleep . Participants were excluded if they were diagnosed with abnormal thyroid function, autoimmune system diseases, pregnancy, severe cardiopulmonary insufficiency, hepatic failure, kidney failure, or cognitive impairment without OSA.For the longitudinal study, we identified the enrolled OSA patients treated with continuous positive airway pressure (CPAP) and reassessed them after 1 year.A total of 445 participants conforming to the inclusion criteria were recruited: 15 participants refused to participate in the study, and 72 participants were excluded according to the exclusion criteria. The study and procedures were approved by the same hospital ethics committee. Patients were informed that some of the collected data would be used for research purposes, and informed consent was obtained from all of the subjects before study enrollment.All of the participants were interviewed to collect information about general health, for instance, age, sex, body mass index (BMI), hypertension, diabetes mellitus, hyperlipidemia, educational attainment, tobacco use (within the previous 3 months), and alcohol consumption (≥ 300 g per week). Serum total cholesterol, low-density lipoprotein cholesterol (LDL-C), triglyceride, and glucose levels were measured.Hypertension was defined as a blood pressure ≥ 140/90 mmHg in 3 different measurements or current use of antihypertensive drugs. Diabetes mellitus was defined as repeated fasting glucose levels ≥ 126 mg/dl, glucose loads ≥ 200 mg/dl 2 h after oral glucose administration, or current use of antidiabetic medications. Hyperlipidemia was defined as total cholesterol levels ≥ 200 mg/dl, triglyceride levels ≥ 150 mg/dl, LDL-C levels ≥ 130 mg/dl, or the use of lipid-lowering drugs.Brain MRI scans, including head T1-weighted, T2-weighted, T2-weighted fluid-attenuated inversion recovery (FLAIR), and susceptibility-weighted imaging (SWI) sequences, were performed using a 3.0-T Skyra magnetic resonance scanner . FLAIR images were acquired with the following parameters: repetition time (TR)/echo time (TE) = 9000/96 ms; field of view (FOV) = 240 × 240 mm; matrix size = 512 × 512; section thickness = 5 mm. SWI images were acquired with TR = 29 ms, TE = 20 ms, flip angle = 15°, matrix = 448 × 168, FOV = 230 × 173 mm, and slice thickness = 2.0 mm.http://www.slicer.org)  and control groups  and control  groups, regardless of the location of the scalp electrode .As shown in Fig. CI , but we found no significant differences between the OSA+MCI and OSA-MCI groups or between the OSA-MCI and control groups % vs 3.88 (4.38)%, P = 0.016; F3, 5.16 (8.53)% vs 4.33 (4.88)%, P = 0.006; F4, 4.60 (8.48)% vs 4.11 (4.49)%, P = 0.003; T3, 3.86 (8.17)% vs 3.73 (4.30)%, P = 0.005; T4, 4.27 (9.54)% vs 4.17 (4.64)%, P = 0.005; O1, 5.91 (13.40)% vs 5.12 (5.88)%, P = 0.023; O2, 5.58 (13.73)% vs 4.43 (4.96)%, P = 0.12] and control  groups, regardless of the location of the scalp electrode , and we did not find statistically significant differences in the voltage of PSWEs between the three groups .As shown in Fig. P = 0.035) and the occurrence per minute of the PSWEs at the C4-M1 , O1-M2 , and O2-M1  channels for stage R were independent influence factors of cognitive impairment in patients with OSA when adjusting for age, sex, BMI, and education. The total PSWEs  and the occurrence per minute of the PSWEs at the F4-M1 , O1-M2 , and O2-M1  channels for stage R were independent influence factors of cognitive impairment in patients with OSA when adjusting for age, sex, education, vascular risk factors , HAMD scores, Aβ42, and AHI, indicating increased odds of being cognitively impaired with higher PSWEs in patients with OSA  1.113, 95% confidence intervals (CIs) 1.007–1.229, P = 0.020), C4-M1 , F3-M2 , F4-M1 , O1-M2 , O2-M1 , T3-M2 , and T4-M1  channels for stage R were independent influence factors of cognitive impairment in patients with OSA when adjusting for age, sex, education, vascular risk factors , HAMD scores, Aβ42, and AHI, indicating that a higher duration of PSWEs for stage R was independently associated with the higher risk of cognitive impairment in patients with OSA.The duration ratios of the PSWEs at the C3-M2  0.000, P = 0.001; β 0.138, SE 0.034, P = 0.023; β −0.355, SE 0.048, P < 0.001; β 0.130, SE 0.009, P = 0.029, respectively) when adjusting for age, sex, and vascular risk factors . Similar to the total PSWE findings, the mean SaO2 had a significant, negative effect on the occurrence per minute of PSWEs in the F4-M1, O1-M2, and O2-M1 channels in stage R , but no effect of WMH volume, total CSVD burden, or ESS was found.Multivariable linear regression analysis was performed Table . We founn = 275). Positive correlations were identified between the total PSWEs and serum CyPA and MMP-9 levels , but weakly. There were positive but weak correlations between the PSWEs at F4-M1, O1-M2, and O2-M1 in stage R and serum CyPA  and MMP-9  levels.Additionally, Spearman’s correlation coefficients were used to verify the correlation between the PSWEs and serological indicators associated with the breakdown of the BBB (serum CyPA and MMP-9 levels) in patients with OSA  using Spearman’s correlation coefficients. Higher scores indicated better cognitive performance and lower scores, in contrast, poorer cognitive function. We also found that the total PSWEs had a weak negative correlation with all of the cognitive subdomains, including visuoexecutive function, naming, attention, language, abstraction, delayed recall and orientation . There were negative correlations between the PSWEs at F4-M1, O1-M2, and O2-M1 in stage R and cognitive performance, but the correlations were weak. The details are provided in Table Moreover, we observed a weak negative correlation between the total PSWEs and global cognitive function (described using MoCA scores) , serum CyPA levels , and serum MMP-9 levels  decreased significantly, and MoCA scores  were improved compared with baseline. Most remarkably, the total PSWEs after CPAP treatment were significantly lower than those at baseline , and the occurrence per minute of PSWEs in stage R was also significantly reduced at either EEG electrode   the occurrence of total PSWEs and PSWEs in stage REM after 1 year of CPAP intervention was significantly lower than at baseline.In this research, we found some interesting results: (1) the total PSWEs in the OSA+MCI group were higher than those in the OSA-MCI and control groups, and the occurrence per minute and duration ratio of PSWEs in stage REM in the OSA+MCI group significantly increased in frontal, parietal, temporal, and occipital regions; (2) the total PSWEs were independent influencing factors of cognitive impairment in patients with OSA and were positively correlated with serum CyPA and MMP-9 levels, while the total PSWEs had a significantly negative correlation with global cognitive function and all of the cognitive subdomains; (3) the relationship between mean SaOA growing body of evidence has linked OSA to cognitive impairment. Chronic intermittent hypoxia, carbon dioxide retention, and sleep fragmentation in patients with OSA not only increases oxidative stress but also could activate oxygen sensors, perpetuate the state of chronic inflammation, induce neurological imbalance, increased blood pressure, and endocrine disturbance, and affect BBB permeability, thereby altering neuronal morphology and synaptic plasticity and leading to cognitive impairment , 22–24, 2 had a detrimental effect on PSWEs, suggesting that the occurrence of PSWEs was significantly increased by hypoxia but not by AHI. It is worth noting that the relationship between the mean oxygen saturation and the percentage of time with oxygen saturation less than 90% during sleep with MoCA scores was mediated by the total PSWEs. Collectively, BBB dysfunction in patients with OSA was more aggravated with hypoxia, rather than the severity of OSA, leading to cognitive impairment. Like other studies [Currently, the CyPA-MMP-9 signaling pathway is presumed to be involved in regulating BBB permeability, because its activation may lead to degradation of tight junctions and basement membrane proteins, resulting in BBB damage –36. In o studies , we alsoExosomes derived from the central nervous system can pass through the BBB and exist in the peripheral blood , and a sLimitations of this study should be addressed. First, because the inclusion criteria allowed for snoring patients, there was selection bias in the study population, resulting in too small sample sizes of the participants without OSA and the possibility of residual confounding. The replication and validation of the results in a larger community sample, including a group with MCI but no OSA, are required. Second, because of the fragmented sleep of OSA patients, we did not choose to analyze the EEG of the entire night but only a fragment of different sleep periods. Finally, due to insufficient patient compliance, few patients received CPAP treatment, affecting the evaluation of outcomes.In summary, the occurrence and duration of PSWEs were increased in OSA patients with cognitive impairment. The PSWEs were implicated in cognitive impairment and its levels in patients with OSA, and odds of being cognitively impaired were increased with the increased occurrence of PSWEs. Our study revealed that hypoxia in OSA patients can lead to cognitive impairment through BBB dysfunction. After 1 year of CPAP treatment, the PSWEs decreased significantly. The results suggest that the PSWEs may be a marker for cognitive impairment in patients with OSA.


Verticillium, representing one of the world’s major pathogens, causes Verticillium wilt in important woody species, ornamentals, agricultural, etc., consequently resulting in a serious decline in production and quality, especially in cotton. Gossupium hirutum and Gossypium barbadense are two kinds of widely cultivated cotton species that suffer from Verticillium wilt, while G. barbadense has much higher resistance toward it than G. hirsutum. However, the molecular mechanism regarding their divergence in Verticillium wilt resistance remains largely unknown. In the current study, G. barbadense cv. Hai7124 and G. hirsutum acc. TM-1 were compared at 0, 12, 24, 48, 72, 96, 120, and 144 h post-inoculation (hpi) utilizing high throughput RNA-Sequencing. As a result, a total of 3,549 and 4,725 differentially expressed genes (DEGs) were identified, respectively. In particular, the resistant type Hai7124 displayed an earlier and faster detection and signaling response to the Verticillium dahliae infection and demonstrated higher expression levels of defense-related genes over TM-1 with respect to transcription factors, plant hormone signal transduction, plant-pathogen interaction, and nucleotide-binding leucine-rich repeat (NLR) genes. This study provides new insights into the molecular mechanisms of divergence in Verticillium wilt resistance between G. barbadense and G. hirsutum and important candidate genes for breeding V. dahliae resistant cotton cultivars. Due to their sessile nature, plants fatally suffer from an extensive diversity of abiotic and biotic stresses. When it comes to biotic setbacks, plants respond to pathogen infection using a two-branched innate immune system: pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) . EssentiVerticillium represents one of the world’s major pathogens, causing Verticillium wilt in many plants , and signal transduction pathways related to salicylic acid (SA), jasmonic acid (JA), or ethylene (ET) (GhMYB36 encodes an R2R3-type MYB protein in Gossupium hirsutum (G. hirsutum) and is involved in drought tolerance and Verticillium wilt resistance in Arabidopsis and cotton by enhancing the expression of resistance genes  positively regulate disease resistance via a silencing approach. In contrast, lncRNA2 and its regulating gene Polygalacturonase 12 (GbPG12) negatively regulated resistance to V. dahliae  . More imce genes . In addifections . Long no dahliae . By iden dahliae . Apart f are two kinds of widely cultivated allotetraploid cotton species that originated from a hybridization event between G. arboreum and G. raimondii about 1–2 million years ago  and TM-1  multiple hours after V. dahliae infection to identify common and different gene expression and regulation networks, aiming to gain new insight into the divergence of Verticillium wilt resistance between G. barbadense and G. hirsutum and generate a substantial understanding of host-pathogen interactions and the defense mechanisms in plants.Due to the lack of disease-resistant germplasm resources in G. barbadense) and TM-1 (G. hirsutum), were used in present study. Seedlings were grown in a controlled-environment growth room at 22°C ± 2°C with a photoperiod scheme of 16-h light/8-h dark. After 14 days sowing, we divided these cotton seedings into two identical groups, one inoculated with a V. dahliae strain Vd991 spore suspensions (107 conidia/ml in sterile distilled water), the other was treated with equal volume of water as a negative control (mock). The mix of leaves, roots and stems of Verticillium wilt group and mock group’s samples at 0, 12, 24, 48, 72, 96, 120 and 144 hpi were collected respectively. Three biological replicates were performed for each cultivar at each time under fungal and water inoculated treatments. All these samples were instantly frozen in liquid nitrogen and stored at -80°C.Two cotton species, Hai7124 . The clean reads were generated by processing the raw data whose format was FASTQ to fastp  along with DNase treatment, and then high-throughput sequencing platform was adopted using the Illumina HiSeq 4000 platform for RNA sequencing. A total of 90 libraries were constructed for Hai7124 and TM-1 | > 2 were considered to be differentially expressed genes (DEGs). In addition, Venn diagrams were generated using these DEGs via TBtools version 1.0986853  with the R package modelsficients  with R ve DESeq2  thus lea.0986853 . Gene OnPF00931), TIR (PF01582), CC (PF05659), LRR  domains was obtained from Pfam website,3 and was employed as a query to identify all possible NLR genes using HMMER (V3.0) software (We defined as nucleotide-binding leucine-rich repeat (NLR) genes that contained at least a nucleotide-binding , a Toll/software  in Hai71software  respectiV. dahliae colonization between Hai7124 and TM-1, the FPKM of the unique DEGs from these two cultivars was used to construct the co-expression networks by way of the R package WGCNA   . Adjacennalysis) . CytoscaG. barbadense cultivars show significantly higher resistance to Verticillium wilt than G. hirsutum. Using the cultivars Hai7124 (G. barbadense) and TM-1 (G. hirsutum), we performed a disease resistance investigation in the greenhouse to make further comparisons of their resistance differences. The symptoms resulting from V. dahliae (Vd991) infection were observed for Hai7124 and TM-1 in the greenhouse. The wilt leaves and chlorosis in TM-1 were much more severe than that in Hai7124 at 50 days post-inoculation | > 2 was 3,549 DEGs in Hai7124 and 4,725 DEGs in TM-1 from all 7 time points. In detail, 2,288, 1,593, 631, 85, 1,225, 112, and 117 DEGs were observed at 12, 24, 48, 72, 96, 120, and 144 hpi in Hai7124, respectively, and 1,246, 555, 38, 396, 3,407, 15, and 131 DEGs were identified in TM-1 at 12, 24, 48, 72, 96, 120, and 144 hpi, respectively. The largest number of DEGs  in TM-1 induced by V. dahliae infection occurred remarkably later than that of Hai7124 . The former was at 24 hpi and the latter was at 12 hpi. The quantity and time change tendency of the DEGs revealed that the patterns of these two cultivars responding to V. dahliae attacks were similar from the aspect of the whole pathogen resistance phase but differed for the small stages  in Hai7124 and 2,496 (36.87%) in TM-1 were unique, and 2,229 DEGs (41.29%) were shared , showingThe DEGs in Hai7124 were significantly enriched for 59 GO terms, and there were less than 82 GO terms for TM-1 . Among tV. dahliae showed an identical trend in general, but there were large differences in the subtleties. For the quantity and tendency of DEGs by number, they were similar from the aspect of the whole pathogen resistance phase, but the gap in the number of DEGs was quite large at the common key peak time point for Hai124 and TM-1. Moreover, for the enrichment analysis results based on DEGs, Hai7124 and TM-1 showed roughly similar resistance response processes, including protein ubiquitination and cellular oxidant detoxification, in response to the V. dahliae infection, but inter-species biases in the extent and intensity of these identical‘ or unique biological processes existed. There were different focuses and distinct mechanisms among them. For instance, the DEGs in Hai7124 played roles in the signal transduction process and exocytosis to activate the wide response, while TM-1 focused on physical defense by utilizing genes that take part in cell wall construction, such as hydrolase activity and cellulose microfibril organization, with 91 DEGs associated with the cell wall in TM-1, whereas there were only 26 in Hai7124.In summary, the gene expression patterns of Hai7124 and TM-1 in response to GH_A07G1749), a Germin-like protein subfamily 1 member (GH_D11G2744), and an unknown gene (GH_D05G3868). There were 11 genes at 72 hpi, including 4 F-box protein , 2 genes with unknown functions (GH_A13G0280 and GH_D10G1713), an ethylene-responsive transcription factor (ERF) gene GH_D11G0433, a basic chitinase named GH_A06G0558, a Glutamine synthetase nodule isozyme GH_A11G1761, a Glucan endo-1,3-beta-glucosidase (GH_D09G1316), and a nodulin MtN21/EamA-like transporter family gene (GH_D06G0451). Moreover, only one gene was in common at 120 hpi encoding the protein plant natriuretic peptide A (GH_A08G0955). Finally, two genes, ethylene-responsive transcription factor (GH_D04G1148) and protein ASPARTIC protease in guard cell 2 (GH_D05G0626), were prominent at 144 hpi , shows strongly enhanced tolerance to drought stress  that TM-1 activated intensive resistance responses. These results suggested the inequivalent distribution of plant disease resistance bioprocesses activated by DEGs may gradually result in the divergence of Verticillium wilt tolerance between G. barbadense and G. hirsutum.In summary, when Verticillium wilt began to invade the cotton plants at 12, 24, and 96 hpi, G. barbadense and G. hirsutum. We defined TF DEGs throughout the whole defense stage , and 616 unique TFs were identified in total (396 in Hai7124 vs. 476 in TM-1). Among these, 256 TFs were shared by the two species. For the 396 TFs in Hai7124, they consisted of 148 AP2/ERFs, 63 WRKYs, 34 MYBs, 21 MYB-related, 27 bHLHs, 18 GRASs, 13 NACs, 8 HSFs, 7 bZIPs, 7 GATAs, 5 LBDs, 4 SBPs, 3 Trihelixs, and 2 C2H2s. The TF number showed a zigzag trend from the time of the invasion of V. dahliae in Hai7124 that started at its highest level of 286 TFs at 12 hpi, then decreased to 12 TFs at 72 hpi and followed another small climax at 96 hpi with 171 TFs, and then decreased rapidly to a low level , including GH_A07G0890 (NAC), which had been verified to function in relation to stress-induced fruit ripening in banana , which are members of the ethylene-responsive transcription factors (GH_D09G1895 (bHLH), GH_A01G0041 (bZIP), and GH_A08G0250 (MYB)  . Moreove50 (MYB) . Among t network .V. dahliae in the G. barbadense plants was completed. In contrast, the trend of the quantitative changes of the plant hormone signal transduction genes was completely divergent in TM-1. A small peak was found at 12 hpi and 24 hpi (13 and 11 DEGs) and reached its highest point at 96 hpi (87 DEGs) (GH_D01G1847 (gibberellin receptor GID1), GH_A01G0218 (jasmonate-zim-domain protein 10), and GH_A07G2361 . Instead, for TM-1, the vast majority of genes remained at normal expression levels from 0 to 48 h and did not respond until 72 hpi, as seen for GH_D09G0917 (TIFY 5A), which serves as JAZ and plays an important role in JA signal transduction  (20 genes), which are involved in the regulation of the jasmonic acid-mediated signaling pathway, Gibberellin signaling DELLA protein (8 genes), auxin-responsive protein SAUR (7 genes), auxin responsive GH3 gene family (CH3) (4 genes), protein brassinosteroid insensitive 1(BRI1) (4 genes), auxin-responsive protein (IAA) (4 genes), gibberellin receptor (GID1) (3 genes), salicylate activated NPR1, which interacts with TGA transcription factors to induce the expression of a large set of pathogenesis-related proteins (TGA) (2 genes) , jasmoni87 DEGs) . The gensduction . We infeGH_D07G2416 (SAG101) as an example, it encodes a senescence-associated carboxylesterase 101 and provides a major barrier to infection by both host-adapted and non-host pathogens during plant immunity . The gene expression levels of the green module (393 genes) showed an increase at 12 hpi, 24 hpi, 72 hpi, 96 hpi, and 144 hpi in Hai7124, while in terms of TM-1, the expression level of the genes in the green module did not begin to rise until 72 hpi. Simultaneously, the transcript levels of the grey module genes (886 genes) in Hai7124 were soaring at 12 hpi and 24 hpi. Meanwhile, although the genes in this module were also upregulated at 12 hpi and 24 hpi in TM-1, the intensity was 0.34 and 0.054, respectively, which were far less than that of Hai7124 (0.52 and 0.34), and its expression level stabilized at a relatively low level in the later stage of V. dahliae infection.To further understand the relationship between gene regulation and cotton defensive resistance to enerated . In totaenerated . The greV. dahliae resistance in cotton were identified using the criteria of eigengene connectivity (KME) > 0.98  > 0.98 . ConsistV. dahliae response  of the response . Genes wresponse . It turnV. dahliae colonization is critical for mining key genes for breeding disease-resistant and high-yield varieties. In the current study, we observed the disease symptoms after treating with V. dahliae and confirmed that the G. barbadense Hai7124 showed a stronger tolerance over G. hirsutum TM-1 (V. dahliae infection was remarkably later than that of Hai7124 (96 hpi)  fight against Ascochyta lentis infection during the first 24 hpi  , 3A. SpeRs genes . The resof WGCNA  also supt 24 hpi .V. dahliae, the dominant biological responses and the active molecules were completely different at different times  signaling pathway, membrane trafficking, transporters, and protein phosphatases. All of these are closely linked to the plant immune system against pathogens. Many TF families have been previously reported to be differentially expressed in plants as a reaction to bacterial, fungal, and viral infection . MAPK caV. dahliae than TM-1.Among these genes, the most interesting genes, RPM1 and RPS2, belong to NLRs and are confirmed to recognize pathogen effector perturbations and activate ETI . CoincidV. dahliae from further invasion of the cotton. While in terms of TM-1’s delayed resistance system, the pathogenic bacteria received less resistance during the colonization process, resulting in more irreversible physiological and biochemical damage to the cotton plant, which ultimately manifested as the relatively weak resistance to Verticillium wilt. In addition, this phenomenon may indicate that TM-1’s disease resistance was not a typical sensitive type, and the defense was weak in the initial stage such that only small amounts of pathogens were invaded.Overall, these results finally showed that Hai714 opened a stronger and more extensive defense system involving TFs, plant hormones, the plant-pathogen interaction, PTI and ETI responses, and other processes effectively preventing G. barbadense and G. hirsutum was performed to clarify their response mechanisms when Verticillium wilt attacked. Both Hai7124 and TM-1 showed consistent trends of differential gene expression within 12 hpi of V. dahliae invasion that was reduced at 48 h and then, increased to a greater extent and intensity at 96 h. While Hai7124 initiated more DEGs at the early response stage over TM-1 and the co-expression of these genes developed a broader resistance response, TM-1 increased to “catch up” with the resistant type only at 96 hpi, suggesting a delayed recognition and response to V. dahliae compared to Hai7124. Moreover, for the essential resistance-related genes, including TFs, plant hormone signal transduction, the plant-pathogen interaction, and NLRs, Hai7124 adopted a more immediate, powerful, and extensive response mode to actively fight against the invasion of V. dahliae in the critical early stages over TM-1. All these phenomena might contribute to the disease defense mechanisms and lay the foundation for candidate gene investigation in cotton and other plants.In this study, a comparative transcriptome analysis between https://www.ncbi.nlm.nih.gov/genbank/, PRJNA839539.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: YH and TZ conceived and designed the experiments. LH and ZH performed the experiments and wrote the manuscript. YZ and ZS performed the experiments and FD analysis of RNA-seq data. JC, SJ, CH, YC, JZ, and BX revised the manuscript. GQ, YWC, LX, and SY performed the experiments. All authors contributed to the article and approved the submitted version.