Short Time-series Expression Miner Research Articles

Transcriptome Profiling of Different Developmental Stages on Longissimus Dorsi to Identify Genes Underlying Intramuscular Fat Content in Wannanhua Pigs.

Intramuscular fat (IMF) is a key index to measure the tenderness and flavor of pork. Wannanhua pig, a famous indigenous pig breed in Anhui Province, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model for investigating the lipid position trait mechanisms in pigs. However, the regulatory mechanisms of lipid deposition and development in pigs remain unclear. Furthermore, the temporal differences in gene regulation are based on muscle growth and IMF deposition. The purpose of this study was to study the expression changes of longissimus dorsi (LD) at different growth stages of WH pigs at the molecular level, to screen the candidate genes and signaling pathways related to IMF during development by transcriptome sequencing technology, and to explore the transcriptional regulation mechanism of IMF deposition-related genes at different development stages. In total, 616, 485, and 1487 genes were differentially expressed between LD60 and LD120, LD120 and LD240, and LD60 and LD240, respectively. Numerous differentially expressed genes (DEGs) associated with lipid metabolism and muscle development were identified, and most of them were involved in IMF deposition and were significantly up-regulated in LD120 and LD240 compared to LD60. STEM (Short Time-series Expression Miner) analysis indicated significant variations in the mRNA expression across distinct muscle development stages. The differential expression of 12 selected DEGs was confirmed by RT-qPCR. The results of this study contribute to our understanding of the molecular mechanism of IMF deposition and provide a new way to accelerate the genetic improvement of pork quality.

Dynamic and systemic regulatory mechanisms in rainbow trout (Oncorhynchus mykiss) in response to acute hypoxia and reoxygenation stress

Hypoxia frequently occurs in natural aquatic systems and aquaculture environments due to extreme climate fluctuations, high-density farming, environmental pollution and global warming, resulting in serious ecological damage and enormous economic losses. Rainbow trout (Oncorhynchus mykiss), a key economic fish species worldwide, is extremely sensitive to hypoxia. However, the regulatory mechanisms in response to environmental hypoxia and reoxygenation stress remain unknown. Herein, rainbow trout liver transcriptomes and biochemical parameters were investigated in response to hypoxia for different durations (3, 12 and 24 h), reoxygenation (hypoxia for 24 h followed by reoxygenation for 3 h) and normoxia to highlight dynamic changes in molecular regulation and oxidative stress. In RNA-seq analysis, 5906 differentially expressed genes, two significantly expressed gene sets (profiles 10 and 12) and two hypoxia specific modules (MEgreen and MEturquoise) were screened by differential expression analysis, short time-series expression miner (STEM) and weighted gene co-expression network analysis (WGCNA), respectively. The intersection of the above analyses further identified several key hub genes related to hypoxia, including hif-1α, epo, igfbp1, ddit4, pck1, g6pc, cyp1a1 and dusp1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed different metabolic strategies at different stress stages; signal transmission and protein synthesis process were strongly influenced by hypoxia. The immune system was inhibited, and a switch from programmed to pathological cell death was observed from hypoxia for 12 h to 24 h. After reoxygenation for 3 h, mitochondrial oxidative phosphorylation was strongly activated to provide more cellular ATP. Enzymatic and non-enzymatic antioxidant systems clearly coordinate to alleviate oxidative stress injury caused by hypoxia. This study reveals dynamic and systemic regulatory mechanisms in rainbow trout liver, and lays a foundation for further study on the molecular mechanisms governing responses to environmental hypoxia and reoxygenation stress.

Analysis of transcriptome expression profiling data in oral leukoplakia and early and late‑stage oral squamous cell carcinoma.

The present study screened, potential prognostic biomarkers for oral carcinogenesis. The GSE85195 dataset, which consisted of oral leukoplakia (OL) and early and late-stage oral squamous cell carcinoma (OSCC) samples, was used. The differentially expressed genes (DEGs) in early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups were screened using the limma package in R. The Short Time-series Expression Miner software package was used to cluster DEGs with similar expression patterns in the course of disease progression (from OL to early and then late-stage OSCC). Moreover, the Database for Annotation, Visualization and Integrated Discovery online analysis tool was used to perform Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction (PPI) network was also constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Reverse transcription-quantitative PCR was performed to assess the mRNA expression levels of hub node genes in clinical samples, and receiver operating characteristic curve analysis was performed to assess the prognostic value of the hub genes. A total of 4,595, 6,042 and 2,738 DEGs were screened in the early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups, respectively. A total of 665 overlapping genes were identified when the screened DEGs were compared. Cluster 1 and cluster 7 were identified as the significant clusters, which contained 496 and 341 DEGs, respectively. A PPI network was constructed with 440 interaction pairs. There were five differentially expressed hub nodes identified in different stages from OL to OSCC. The results of the present study indicated that fibronectin 1, signal transducer and activator of transcription 1, collagen type II α1 chain, collagen type X α1 chain and collagen type IV α6 chain might serve as independent diagnostic factors for OL and OSCC, and as prognostic biomarkers for OL carcinogenesis.

Transcriptome sequencing leads to an improved understanding of the infection mechanism of Alternaria solani in potato

BackgroundAlternaria solani (A. solani), the main pathogen of potato early blight, causes serious yield reductions every year. The application of fungicides is the most common and effective method of controlling Alternaria-caused diseases. The differentially expressed transcripts of A. solani infecting potato were identified, revealing a group of valuable candidate genes for a systematic analysis to increase the understanding of the molecular pathogenesis of A. solani, and providing scientific data for formulating additional measures to prevent and control potato early blight. In this study, a deep RNA-sequencing approach was applied to gain insights into A. solani pathogenesis. At 3, 4, and 5 days post inoculation (dpi), RNA samples from the susceptible potato cultivar Favorita infected with A. solani strain HWC-168, were sequenced and utilized for transcriptome analysis, and compared to the transcriptome obtained 0 dpi.ResultsA total of 4430 (2167 upregulated, 2263 downregulated), 4736 (2312 upregulated, 2424 downregulated), and 5043 (2411 upregulated, 2632 downregulated) genes were differentially expressed 3, 4 and 5 dpi, respectively, compared with genes analysed at 0 dpi. KEGG enrichment analysis showed that genes involved in the pathways of amino acid metabolism, glucose metabolism, and enzyme activity were significantly differentially expressed at the late infection stage. Correspondingly, symptoms developed rapidly during the late stage of A. solani infection. In addition, a short time-series expression miner (STEM) assay was performed to analyse the gene expression patterns of A. solani and Profile 17 and 19 showed significant change trends 3, 4 and 5 dpi. Both profiles, but especially Profile 17, included enzymes, including transferases, oxidoreductases, hydrolases and carbohydrate-active enzymes (CAZYmes), which may play important roles in late fungal infection. Furthermore, possible candidate effectors were identified through the adopted pipelines, with 137 differentially expressed small secreted proteins identified, including some enzymes and proteins with unknown functions.ConclusionsCollectively, the data presented in this study show that amino acid metabolism, and glucose metabolism pathways, and specific pathway-related enzymes may be key putative pathogenic factors, and play important roles in late stage A. solani infection. These results contribute to a broader base of knowledge of A. solani pathogenesis in potato, as indicated by the transcriptional level analysis, and provide clues for determining the effectors of A. solani infection.

Time-Series Expression Profile Analysis of Post-Traumatic Joint Contracture in Rats at the Early Stages of the Healing Process.

This study aimed to characterize the gene expression profile at the early stages of the healing process of post-traumatic joint contracture (PTJC). Twelve rats were used for PTJC model establishment and were divided into four groups according to the sampling time: S0d, S3d, S7d and S2w. Transcriptome sequencing was performed on fibrotic joint capsule samples in four groups followed by bioinformatics analyses including differentially expressed genes (DEGs) screening, Short Time-series Expression Miner (STEM) analysis, network construction, and pathway analysis. Five important genes were validated by qRT-PCR. A total of 1171, 1052 and 793 DEGs were screened in S3d vs S0d, S7d vs S0d, and S2w vs S0d comparison groups, respectively. A total of 383 overlapping genes were screened out, which were significantly enriched in some inflammatory functions and pathways. Through STEM analysis, three clusters were identified, including 105, 57 and 57 DEGs, respectively. Then, based on the cluster genes, 10 genes, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3, were further selected after PPI and pathway analyses. The expression levels of Il6, Timp1, Cxcl1, Cxcr4 and Mmp3 were validated by qRT-PCR. The present study screened out several genes with significant changes in expression levels at the early stages of the healing process in PTJC, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3. Our study offers a valuable contribution to the understanding pathomechanism of PTJC.

A passage-dependent network for estimating the in vitro senescence of mesenchymal stromal/stem cells using microarray, bulk and single cell RNA sequencing.

Long-term in vitro culture of human mesenchymal stem cells (MSCs) leads to cell lifespan shortening and growth stagnation due to cell senescence. Here, using sequencing data generated in the public domain, we have established a specific regulatory network of "transcription factor (TF)-microRNA (miRNA)-Target" to provide key molecules for evaluating the passage-dependent replicative senescence of mesenchymal stem cells for the quality control and status evaluation of mesenchymal stem cells prepared by different procedures. Short time-series expression miner (STEM) analysis was performed on the RNA-seq and miRNA-seq databases of mesenchymal stem cells from various passages to reveal the dynamic passage-related changes of miRNAs and mRNAs. Potential miRNA targets were predicted using seven miRNA target prediction databases, including TargetScan, miRTarBase, miRDB, miRWalk, RNA22, RNAinter, and TargetMiner. Then use the TransmiR v2.0 database to obtain experimental-supported transcription factor for regulating the selected miRNA. More than ten sequencing data related to mesenchymal stem cells or mesenchymal stem cells reprogramming were used to validate key miRNAs and mRNAs. And gene set variation analysis (GSVA) was performed to calculate the passage-dependent signature. The results showed that during the passage of mesenchymal stem cells, a total of 29 miRNAs were gradually downregulated and 210 mRNA were gradually upregulated. Enrichment analysis showed that the 29 miRNAs acted as multipotent regulatory factors of stem cells and participated in a variety of signaling pathways, including TGF-beta, HIPPO and oxygen related pathways. 210 mRNAs were involved in cell senescence. According to the target prediction results, the targets of these key miRNAs and mRNAs intersect to form a regulatory network of "TF-miRNA-Target" related to replicative senescence of cultured mesenchymal stem cells, across 35 transcription factor, 7 miRNAs (has-mir-454-3p, has-mir-196b-5p, has-mir-130b-5p, has-mir-1271-5p, has-let-7i-5p, has-let-7a-5p, and has-let-7b-5p) and 7 predicted targets (PRUNE2, DIO2, CPA4, PRKAA2, DMD, DDAH1, and GATA6). This network was further validated by analyzing datasets from a variety of mesenchymal stem cells subculture and lineage reprogramming studies, as well as qPCR analysis of early passages mesenchymal stem cells versus mesenchymal stem cells with senescence morphologies (SA-β-Gal+). The "TF-miRNA-Target" regulatory network constructed in this study reveals the functional mechanism of miRNAs in promoting the senescence of MSCs during in vitro expansion and provides indicators for monitoring the quality of functional mesenchymal stem cells during the preparation and clinical application.

Transcriptome Profiling of Developing Testes and First Wave of Spermatogenesis in the Rat.

Spermatogenesis is a complicated course of several rigorous restrained steps that spermatogonial stem cells undergo to develop into highly specialized spermatozoa; however, specific genes and signal pathways, which regulate the amplification, differentiation and maturation of these cells, remain unclear. We performed bioinformatics analyses to investigate the dynamic changes of the gene expression patterns at three time points in the course of the first wave of rat spermatogenesis. Differently expressed genes (DEGs) were identified, and the features of DEGs were further analyzed with GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) and Short Time-series Expression Miner (STEM). A total of 2954 differentially expressed genes were identified. By using STEM, the top 10 key genes were selected in the profile according to the enrichment results, and the distinguishable biological functions encoded by these DEGs were automatically divided into three parts. Genes from 6, 8 and 10 days were related to biosynthesis, immune response and cell junction, and genes from 14, 15 and 16 days were related to energy metabolic pathways. The results also suggest that genes from 29, 31 and 35 days may shift metabolic to sperm motility, sperm flagellum and cilium movement.

Transcriptome Profiling Reveals Candidate Genes Related to Stipe Gradient Elongation of Flammulina filiformis.

Stipe gradient elongation is an important and remarkable feature in the development of most mushroom fruiting bodies. However, its molecular mechanism has rarely been described. Here, the decreasing trend of stipe elongation and increasing trend of cell length in a gradient from the top to the base of the stipe were determined in a model basidiomycete mushroom: Flammulina filiformis. According to RNA-seq results, 1409 differentially expressed genes (DEGs) were identified among elongation region (ER), transition region (TR), and stable region (SR) samples, including 26 transcription factors (TFs). Based on Short Time-series Expression Miner (STEM) clustering of DEGs, clusters 1 and 3, with obvious expression trends that were consistent with or in contrast to the elongation rate, were screened. The cluster 1 DEGs were mainly involved in the GO cellular component category and KEGG genetic information processing class; however, the cluster 3 DEGs were mainly involved in metabolic processes. Furthermore, qRT-PCR confirmed that key genes of the long-chain fatty acid synthesis pathway were involved in stipe gradient elongation and regulated by NADPH oxidase-derived ROS signaling molecules. These findings provide an essential basis for understanding the molecular mechanism of stipe gradient elongation.

ACSF2-mediated ferroptosis is involved in ulcerative colitis

AimsTo investigate the role of ferroptosis-related genes in the induction into ulcerative colitis (UC) and provide new strategies for the prevention and treatment of UC. Materials and methodsWe screened the UC dataset from the GEO database and obtained ferroptosis-related genes from FerrDB and GeneCards. The R package “CancerSubtypes” was performed to identify the UC subtypes, followed by Short Time-series Expression Miner (STEM) analysis. The key genes were further screened by machine learning algorithms (LASSO and SVM-RFE). WB and IHC verified the changes in the expression content of ACSF2 in vivo and in vitro models. The changes in intracellular ROS and Fe2 + levels were detected. Key findingsThrough bioinformatics analysis, we selected the ferroptosis-related gene ACSF2 (acyl CoA synthetase family member 2), which is significantly associated with immune-related pathways “Toll-like receptor signaling pathway”, “NF-kappa B signaling pathway” and “NOD-like receptor signaling pathway”. The expression of ACSF2 was significantly down-regulated in UC animals, Salmonella typhimurium colitis models and cell models, while the ferroptosis inhibitor Fer-1 reversed the expression of ACSF2 in LPS-induced cell models, indicating that the ferroptosis-related gene ACSF2 plays an important role in mediating ferroptosis and inflammation, and is expected to become a new target for further research. SignificanceFerroptosis is closely associated with the development of UC, and the ferroptosis-related gene ACSF2 can be used as a potential biomarker for the diagnosis and treatment of UC.

Transcriptome analysis provides insights into lignin synthesis and MAPK signaling pathway that strengthen the resistance of bitter gourd (Momordica charantia) to Fusarium wilt

Fusarium wilt is a typical soil-borne disease caused by Fusarium oxysporum f. sp. momordicae (FOM) in bitter gourd. In this study, by comparing sequencing data at multiple time points and considering the difference between resistant (R) and susceptible (S) varieties, differentially expressed genes were screened out. Short time-series expression miner analysis revealed the upregulated expression trend of genes, which were enriched in phenylpropanoid biosynthesis, plant–pathogen interaction, and mitogen-activated protein kinase signaling pathway. Further, observation of the microstructure revealed that the R variety may form tyloses earlier than the S variety to prevent mycelium diffusion from the xylem vessel. After Fusarium wilt infection, the enzymatic activities of superoxide dismutase, peroxidase, phenylalanine ammonia lyase, and catalaseas well as levels of superoxide anion and malondialdehyde were increased in the R variety higher than those in the S variety. This study provides a reference to elucidate the disease resistance mechanism of bitter gourd.

Identification of Key Genes Associated with Risk and Prognosis of Neuroblastoma.

Neuroblastoma is a childhood malignancy with high morbidity and mortality. We identified key biomarkers associated with neuroblastoma risk and prognosis. The gene modules most associated with neuroblastoma risk were derived by WGCNA. Modular genes were intersected with differentially expressed genes between patients with high-risk (HR) and non-high-risk (NHR) to obtain risk genes, and enrichment analysis was performed. After incorporating risk genes into Cox regression analysis, LASSO algorithm, and K-M survival analysis, key genes were identified and introduced into four external datasets for validation. We performed short time-series expression miner analysis and single-sample genome enrichment analysis. Finally, we evaluated the difference in DNA methylation levels to identify meaningful methylation marks. We identified 5 key genes (ANO6, CPNE2, DST, PLXNC1, SCN3A) for neuroblastoma risk and prognosis, which correlated closely with known neuroblastoma biomarkers. All key genes showed a progressive downregulation trend with increasing risk levels of neuroblastoma. The immune infiltration of 14 immune cells was significantly different between HR-NB and NHR-NB, and most immune cells were negatively correlated with key genes. Furthermore, the expression of ANO6, CPNE2, DST, and PLXNC1 was modified by DNA methylation. This study identified 5 key genes for neuroblastoma risk and prognosis that were potential biomarkers.

Persistent dysregulation of genes in the development of endometriosis.

Endometriosis is a chronic condition that affects women of child-bearing age. Since the etiology and pathogenesis of endometriosis have not been fully elucidated, it is important to investigate the mechanisms that lead to the deterioration of endometriosis. In this study, the transcriptome data of patients with normal, mild, and severe endometriosis were examined using the GSE51981 dataset obtained from the Gene Expression Omnibus database. Short Time Series Expression Miner (STEM) was used to screen the genes with continuous expression disorder in the development process, and the core genes were identified by constructing a protein-protein interaction network. The molecular mechanisms of endometriosis were examined using enrichment analysis. Finally, the transcription factors that regulate the core genes were predicted and the comprehensive mechanisms involved in the development of endometriosis were examined. A total of 3,472 differentially expressed genes were identified from the normal, mild, and severe endometriosis samples. These were allocated into 12 modules and HRAS, HSP90AA1, TGFB1, TP53, and UBC were selected as the core genes. Enrichment analysis showed that the genes in modules 6, 7, and 9 were significantly related to oxygen levels, metallic processes, and hormone levels, respectively. Transcription factor prediction analysis showed that TP53 regulates HRAS to participate in immune related signaling pathways. Drug prediction analysis identified 792 drugs that interact with the targeted core genes. This study explored the molecular mechanisms involved in the development of endometriosis and identified potential biomarkers of endometriosis. This data may provide novel targets and research directions for the diagnosis and treatment of endometriosis.

Time-Series Transcriptomic Analysis Reveals the Molecular Profiles of Diapause Termination Induced by Long Photoperiods and High Temperature in Chilo suppressalis.

Survival and adaptation to seasonal changes are challenging for insects. Many temperate insects such as the rice stem borer (Chilo suppressalis) overcome the adverse situation by entering diapause, wherein development changes dynamically occur and metabolic activity is suppressed. The photoperiod and temperature act as major environmental stimuli of diapause. However, the physiological and molecular mechanisms that interpret the ecologically relevant environmental cues in ontogenetic development during diapause termination are poorly understood. Here, we used genome-wide high-throughput RNA-sequencing to examine the patterns of gene expression during diapause termination in C. suppressalis. Major shifts in biological processes and pathways including metabolism, environmental information transmission, and endocrine signalling were observed across diapause termination based on over-representation analysis, short time-series expression miner, and gene set enrichment analysis. Many new pathways were identified in diapause termination including circadian rhythm, MAPK signalling, Wnt signalling, and Ras signalling, together with previously reported pathways including ecdysteroid, juvenile hormone, and insulin/insulin-like signalling. Our results show that convergent biological processes and molecular pathways of diapause termination were shared across different insect species and provided a comprehensive roadmap to better understand diapause termination in C. suppressalis.

Identification and Characterization of Circular RNAs Involved in the Flower Development and Senescence of Rhododendron delavayi Franch

Floral development and senescence are a crucial determinant for economic and ornamental value. CircRNAs play an essential role in regulating plant growth and development; however, there is no systematic identification of circRNAs during the lifespan of flowers. This study aims to explore the expression profile and functional role of circRNAs in the full flowering stages of Rhododendron delavayi Franch. We carried out transcriptome sequencing of the six stages of Rhododendron delavayi Franch flowers to identify the circular RNA expression profile. In addition, using bioinformatics methods, we explored the functions of circRNAs, including analysis of the circRNA-miRNA-mRNA network, short time-series expression miner (STEM), and so on. We identified 146 circRNAs, of which 79 were differentially expressed from the budding to fading stages. Furthermore, using STEM analysis, one of the 42 circRNA expression model profiles was significantly upregulated during the senescence stage, including 16 circRNAs. Additionally, 7 circRNA-miRNA-mRNA networks were constructed with 10 differentially expressed circRNAs, in which some target mRNA may regulate the development and senescence of the Rhododendron flowers. Finally, by analyzing the correlation between circRNAs and mRNA, combined with existing reports, we proposed that circRNAs play a regulatory role during flower development and senescence by mediating the jasmonate signaling pathway. Overall, these results provide new clues to the potential mechanism of circRNAs acting as novel post-transcriptional regulators in the development and senescence process of flowers.

Blood Transcriptome Analysis of Beef Cow with Different Parity Revealed Candidate Genes and Gene Networks Regulating the Postpartum Diseases.

Maternal parity is an important physiological factor influencing beef cow reproductive performance. However, there are few studies on the influence of different calving periods on early growth and postpartum diseases. Here, we conducted blood transcriptomic analysis on cows of different parities for gene discovery. We used Short Time Series Expression Miner (STEM) analysis to determine gene expression levels in cows of various parities and divided multiple parities into three main periods (nulliparous, primiparous, and multiparous) for subsequent analysis. Furthermore, the top 15,000 genes with the lowest median absolute deviation (MAD) were used to build a co-expression network using weighted correlation network analysis (WGCNA), and six independent modules were identified. Combing with Exon Wide Selection Signature (EWSS) and protein-protein interaction (PPI) analysis revealed that TPCN2, KIF22, MICAL3, RUNX2, PDE4A, TESK2, GPM6A, POLR1A, and KLHL6 involved in early growth and postpartum diseases. The GO and KEGG enrichment showed that the Parathyroid hormone synthesis, secretion, and action pathway and stem cell differentiation function-related pathways were enriched. Collectively, our study revealed candidate genes and gene networks regulating the early growth and postpartum diseases and provided new insights into the potential mechanism of reproduction advantages of different parity selection.

Abscisic acid induces the expression of AsKIN during the recovery period of garlic cryopreservation.

Abscisic acid induced the expression of AsKIN during the recovery period of garlic cryopreservation. AsKIN was identified as a gene involved in cold and osmotic stress resistance. Cryopreservation has been proven to be effective in removing viruses from garlic. However, oxidative damage in cryopreservation has a significant impact on the survival after preservation. Abscisic acid (ABA) has been shown to reduce oxidative stress and promote the survival after cryopreservation. However, it is not clear which genes play important roles in this process. In this study, we added ABA to the dehydration step and analyzed the transcriptomic divergences between the ABA-treated group and the control group in three cryogenic steps (dehydration, unloading and recovery). By short time-series expression miner (STEM) analysis and weighted gene co-expression network analysis (WGCNA), the recovery step was identified as the period of significant changes in gene expression levels in cryopreservation. The addition of ABA promoted the upregulated expression of microtubule-related genes in the recovery step. We further identified AsKIN as a hub gene in the recovery step and verified its function. The results showed that overexpression of AsKIN enhanced the tolerance of Arabidopsis to oxidative stress in cryopreservation, influenced the expression of genes in response to cold and osmotic stress and promoted plant growth after stress. The AsKIN gene is likely to be involved in the plant response to cold stress and osmotic stress. These results reveal the molecular mechanisms of ABA in cryopreservation and elucidate the potential biological functions of the kinesin-14 subfamily.

Biosynthetic mechanisms of isoflavone accumulation affected by different growth patterns in Astragalus mongholicus products

BackgroundAt present, Astragalus mongholicus products on the market represent two growth patterns: imitative wild A. mongholicus (WAM) and cultivated A. mongholicus (CAM). The 6-year-old WAM (A6) and 2-year-old CAM (B2) products are often sold as commodities. This study aimed to explore the effects of the abovementioned growth patterns on the biosynthetic mechanisms of isoflavone accumulation in A. mongholicus products.ResultsIn this paper, the content of calycosin-7-O-β-D-glucoside in 6-year-old WAM (A6) was significantly higher than that in 2-year-old CAM (B2) based on high-performance liquid chromatography. Tissue anatomy indicated that A6 has developed phloem fibers, thickened secondary walls, and a more well-developed vascular system than B2. Thirteen differentially accumulated metabolites were found in A6 and B2 by UHPLC-ESI-Q-TOF-MS/MS, of which isoflavones were highly and significantly enriched in A6. By combining transcriptomics and metabolomics analysis, we found that the metabolomics profile was the same as the transcriptomics profile in both A6 and B2. In total, 11 novel isoflavone-related genes were isolated using BLAST and functional annotation through RNA-Seq and Iso-Seq. The results of integrated analysis, Short Time-series Expression Miner analysis, and Pearson correlation analysis showed that the regulation of four key enzymes, cinnamate 4-hydroxylase, 6-deoxychalcone synthase, chalcone reductase, and chalcone isomerase, led to the high accumulation of isoflavones in A6. In addition, AmUFGT (c778119) and AmUCGT (c303354) were predicted to be 7-O-glycosyltransferases by phylogenetic analysis; these genes catalyze formononetin and calycosin, respectively.ConclusionsThe findings of this work will clarify the differences in the biosynthetic mechanism of isoflavone accumulation between A6 and B2, which will guide the cultivation of A. mongholicus.

Fucose as a potential therapeutic molecule against the immune-mediated inflammation in IgA nepharopathy: An unrevealed link.

BackgroundIgA nephropathy (IgAN) is an autoimmune disease that affects people of any age and is an important cause of end-stage renal disease. However, the pathogenesis and pathophysiology of IgAN is not clear. This article aimed to explore the immune-mediated inflammation and genetic mechanisms in IgAN.MethodsThe transcriptome sequencing data of IgAN glomeruli in the Gene Expression Omnibus database were downloaded. Single-sample gene set enrichment analysis was used to estimate the immune microenvironment of the merged microarray data and GSE141295. IgAN samples were divided into two clusters by cluster analysis. “limma” and “DEseq2” package in R were used to identify differentially expressed genes (DEGs). The weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules related to inflammation in IgAN. R software package “clusterProfiler” was used for enrichment analysis, whereas Short Time-Series Expression Miner (STEM) analysis was used to identify the trend of gene expression. Machine-learn (ML) was performed using the shiny app. Finally, Drug Signatures Database (DSigDB) was used to identify potential molecules for treating IgAN.ResultsThe infiltration of macrophages in IgAN glomeruli was increased, whereas CD4+ T cells, especially inducedregulatory T cells (iTregs) were decreased. A total of 1,104 common DEGs were identified from the merged data and GSE141295. Brown module was identified to have the highest inflammatory correlation with IgAN using WGCNA, and 15 hub genes were screened from this module. Among these 15 hub genes, 14 increased with the severity of IgAN inflammation based on STEM analysis. Neural network (nnet) is considered as the best model to predict the severity of IgAN. Fucose identified from DSigDB has a potential biological activity to treat IgAN.ConclusionThe increase of macrophages and the decrease of iTregs in glomeruli represent the immune-mediated inflammation of IgAN, and fucose may be a potential therapeutic molecule against IgAN because it affects genes involved in the severe inflammation of IgAN.

Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data

Critical functions of the blood–brain barrier (BBB), including cerebral blood flow, energy metabolism, and immunomodulation, are regulated by insulin signaling pathways. Therefore, endothelial insulin resistance could lead to BBB dysfunction, which is associated with neurodegenerative diseases such as Alzheimer’s disease (AD). The current study aims to map the dynamics of insulin-responsive pathways in polarized human cerebral microvascular endothelial cell (hCMEC/D3) monolayers. RNA-Sequencing was performed on hCMEC/D3 monolayers with and without insulin treatment at various time points. The Short Time-series Expression Miner (STEM) method was used to identify gene clusters with distinct and representative expression patterns. Functional annotation and pathway analysis of genes from selected clusters were conducted using Webgestalt and Ingenuity Pathway Analysis (IPA) software. Quantitative expression differences of 16,570 genes between insulin-treated and control monolayers were determined at five-time points. The STEM software identified 12 significant clusters with 6880 genes that displayed distinct temporal patterns upon insulin exposure, and the clusters were further divided into three groups. Gene ontology (GO) enrichment analysis demonstrated that biological processes protecting BBB functions such as regulation of vascular development and actin cytoskeleton reorganization were upregulated after insulin treatment (Group 1 and 2). In contrast, GO pathways related to inflammation, such as response to interferon-gamma, were downregulated (Group 3). The IPA analyses further identified insulin-responsive cellular and molecular pathways that are associated with AD pathology. These findings unravel the dynamics of insulin action on the BBB endothelium and inform about downstream signaling cascades that are potentially disrupted due to brain insulin resistance prevalent in AD.

Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19.

Renal injury secondary to COVID-19 is an important factor for the poor prognosis of COVID-19 patients. The pathogenesis of renal injury caused by aberrant immune inflammatory of COVID-19 remains unclear. In this study, a total of 166 samples from 4 peripheral blood transcriptomic datasets of COVID-19 patients were integrated. By using the weighted gene co-expression network (WGCNA) algorithm, we identified key genes for mild, moderate, and severe COVID-19. Subsequently, taking these genes as input genes, we performed Short Time-series Expression Miner (STEM) analysis in a time consecutive ischemia-reperfusion injury (IRI) -kidney dataset to identify genes associated with renal injury in COVID-19. The results showed that only in severe COVID-19 there exist a small group of genes associated with the progression of renal injury. Gene enrichment analysis revealed that these genes are involved in extensive immune inflammation and cell death-related pathways. A further protein-protein interaction (PPI) network analysis screened 15 PPI-hub genes: ALOX5, CD38, GSF3R, LGR, RPR1, HCK, ITGAX, LYN, MAPK3, NCF4, SELP, SPI1, WAS, TLR2 and TLR4. Single-cell sequencing analysis indicated that PPI-hub genes were mainly distributed in neutrophils, macrophages, and dendritic cells. Intercellular ligand-receptor analysis characterized the activated ligand-receptors between these immune cells and parenchyma cells in depth. And KEGG enrichment analysis revealed that viral protein interaction with cytokine and cytokine receptor, necroptosis, and Toll-like receptor signaling pathway may be potentially essential for immune cell infiltration leading to COVID-19 renal injury. Finally, we validated the expression pattern of PPI-hub genes in an independent data set by random forest. In addition, we found that the high expression of these genes was correlated with a low glomerular filtration rate. Including them as risk genes in lasso regression, we constructed a Nomogram model for predicting severe COVID-19. In conclusion, our study explores the pathogenesis of renal injury promoted by immunoinflammatory in severe COVID-19 and extends the clinical utility of its key genes.