Transcriptome Sequencing on Treatment of Kidney Deficiency and Blood Stasis-thin Endometrium in Rats with Bushen Huoxue Prescription Through Enema / 中国实验方剂学杂志

ObjectiveTo explore the mechanism of Bushen Huoxue enema in treating the rat model of kidney deficiency and blood stasis-thin endometrium （KDBS-TE） by transcriptome sequencing. MethodThe rat model of KDBS-TE was established by administration of tripterygium polyglycosides tablets combined with subcutaneous injection of adrenaline. The pathological changes of rat endometrium in each group were then observed. Three uterine tissue specimens from each of the blank group， model group， and Bushen Huoxue enema group were randomly selected for transcriptome sequencing. The differentially expressed circRNAs， lncRNAs， and miRNAs were screened， and the disease-related specific competitive endogenous RNA （ceRNA） regulatory network was constructed. Furthermore， the gene ontology （GO） functional annotation and the Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment were performed for the mRNAs in the network. ResultCompared with the blank group， the model group showed endometrial dysplasia， decreased endometrial thickness and endometrial/total uterine wall thickness ratio （P<0.01）， and differential expression of 18 circRNAs， 410 lncRNAs， and 7 miRNAs. Compared with the model group， the enema and estradiol valerate groups showed improved endometrial morphology and increased endometrial thickness and ratio of endometrial to total uterine wall thickness （P<0.05）. In addition， 21 circRNAs， 518 lncRNAs， and 17 miRNAs were differentially expressed in the enema group. The disease-related specific circRNA-miRNA-mRNA regulatory network composed of 629 nodes and 664 edges contained 2 circRNAs， 34 miRNAs， and 593 mRNAs. The lncRNA-miRNA-mRNA regulatory network composed of 180 nodes and 212 edges contained 5 lncRNAs， 10 miRNAs， and 164 mRNAs. The mNRAs were mainly enriched in Hippo signaling pathway， autophagy-animal， axon guidance， etc. ConclusionBushen Huoxue enema can treat KDBS-TE in rats by regulating specific circRNAs， lncRNAs， and miRNAs in the uterus and the ceRNA network.

Spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium

Molecular knowledge of human gastric corpus epithelium remains incomplete. Here, by integrated analyses using single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) techniques, we uncovered the spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium. Specifically, we identified a stem/progenitor cell population in the isthmus of human gastric corpus, where EGF and WNT signaling pathways were activated. Meanwhile, LGR4, but not LGR5, was responsible for the activation of WNT signaling pathway. Importantly, FABP5 and NME1 were identified and validated as crucial for both normal gastric stem/progenitor cells and gastric cancer cells. Finally, we explored the epigenetic regulation of critical genes for gastric corpus epithelium at chromatin state level, and identified several important cell-type-specific transcription factors. In summary, our work provides novel insights to systematically understand the cellular diversity and homeostasis of human gastric corpus epithelium in vivo.

Exploring the miRNA-mRNA regulatory network in schizophrenia based on GEO database / 四川精神卫生

ObjectiveTo provide a new idea for exploring the molecular genetic approach to the pathogenesis of schizophrenia via construction of microRNA-messenger RNA （miRNA-mRNA） regulatory network in schizophrenia. MethodsThe microarray datasets of GSE54578 miRNA expression profiles in peripheral blood and GSE145554 mRNA expression in the anterior cingulate in postmortem brain of schizophrenic subjects were downloaded from Gene Expression Omnibus （GEO） database since July 2021. The GEO2R was used to identify the differentially expressed miRNAs and mRNAs， screen the miRNA with target differentially expressed mRNA， and predict their potential upstream transcription factors. The overlapping genes from the mRNA targeted by the differentially expressed miRNA and the mRNA differentially expressed in GSE145554 dataset were collected. Then the biological features of hub genes were analyzed via Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis， and the protein-protein interaction （PPI） network and miRNA-mRNA regulatory network of hub genes were constructed. ResultsA total of 8 up-regulated differentially expressed miRNAs with targeted mRNA were screened out in GSE54578 datasets regarding schizophrenia， which involved in the regulation of 10 transcription factors， 247 down-regulated differentially expressed mRNAs were screened out in GSE145554 datasets， and 17 overlapping mRNAs were obtained. GO analysis showed that the target mRNAs were mainly involved in astrocyte differentiation and development. KEGG pathway enrichment analysis showed that the target mRNAs were mainly involved in Rap1 and Ras signaling pathways. PPI network analysis showed that the mRNAs （KRAS and CD28） might be key genes in schizophrenia. ConclusionThe integrated bioinformatics analysis based on GEO database can identify potential susceptibility genes in schizophrenia， and it also contributes to the construction of miRNA-mRNA regulatory network in schizophrenia.

Whole transcriptome analysis and critical gene regulatory network analysis during Schistosoma japonicum infection and praziquantel treatment in mice / 中国血吸虫病防治杂志

Objective To investigate long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) interactions and identify the critical gene regulatory network during Schistosoma japonicum infections and praziquantel treatment using whole transcriptome sequencing. Methods A total of 110 male C57BL/6 mice were randomly divided into the control group, the infection group and the treatment group. Mice in the infection treatment and the control group were infected with S. japonicum cercariae via the abdomen, and liver specimens were sampled from 10 mice 3, 6, 8 weeks post-infection. Praziquantel treatment was given to mice in the treatment group 8 weeks post-infection, and liver specimens were sampled from 10 mice 2, 4, 6, 8, 10 weeks post-treatment. Total RNA was isolated from mouse liver specimens, and the transcriptome library was constructed for highthroughput whole transcriptome sequencing. The significant differentially expressed genes were subjected to functional annotations, Gene Ontology (GO) terms enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Correlation analysis of liver specimens was performed using R Corrplot and Himsc functions, and the lncRNAmiRNA-mRNA interaction network analysis was performed using R MixOmics and Himsc functions. Results There were 1 176 differentially expressed miRNAs, 5 270 differentially expressed mRNAs, and 2 682 differentially expressed lncRNAs between the infection group and the control group, 1 289 differentially expressed miRNAs, 7 differentially expressed mRNAs, and 69 differentially expressed lncRNAs between the treatment group and the infection group, and 1 210 differentially expressed miRNAs, 4 456 differentially expressed mRNAs, and 2 016 differentially expressed lncRNAs between the treatment group and the control group. Correlation analysis showed a higher correlation of gene expression between the treatment group and the control group. Principal component analysis showed obvious separate clustering between the infection group and the treatment group. The differentially expressed genes with significant relevance were significantly enriched in 24 GO terms, including arachidonic acid metabolic process, xenobiotic catabolic process, unsaturated fatty acid metabolic process, xenobiotic metabolic process, long-chain fatty acid metabolic process, and 8 KEGG metabolic pathways, including cholesterol metabolism, tyrosine metabolism, linoleic acid metabolism, retinol metabolism, and steroid hormone biometabolism. Conclusions There were 23 mRNAs including Cyp2b9 and 14 lncRNAs including Rmrpr in the core position of the gene regulatory network, which may play a critical role in S. japonicum infections and praziquantel treatment, and 9 miRNAs including miR-8105 may serve as potential molecular markers for diagnosis of S. japonicum infections.

Identification of onco-miRNAs in hepatocellular carcinoma and analysis of their regulatory network / 南方医科大学学报

OBJECTIVE@#To construct the regulatory network of survival-related onco-miRNAs and their target genes in hepatocellular carcinoma (HCC) and verify the interactions between the key miRNAs and their targets.@*METHODS@#We screened survival-related miRNAs in HCC in OncomiR and Oncolnc databases, predicted their target genes using miRNet, and conducted survival and expression analysis using GEPIA2 and Ualcan, respectively. The miRNA-target gene co-expression analysis was performed and the miRNA-target network was constructed. Enrichment analysis was performed in Enrichr and protein-protein interaction analysis in STRING database. We tested the effects of transfection with the mimic or inhibitor of hsa-miR-1226-3p or hsa-miR-221-5p on proliferation of HepG2 cells using CCK8 assay and examined the changes in the expressions of the target genes using RT-qPCR. The effect of transfection with hsa-miR-221-5p mimic or inhibitor on protein expressions of the target genes was examined using Western blotting in. A dual luciferase reporter assay was used to test the interaction between hsa-miR-221-5p and its potential target gene GCDH. We further examined the effect of transfection with hsa-miR-221-5p mimic and pEGFP N1-GCDH, alone or in combination, on proliferation, migration and invasion of HepG2 cells.@*RESULTS@#We identified 223 survival-related miRNAs in HCC from OncomiR and 146 miRNAs from Oncolnc with an intersection of 131 miRNAs, and 48 miRNAs were identified as onco-miRNAs in HCC after survival and expression analysis. Twenty-seven eligible target genes were identified after miRNA-mRNA co-expression analysis. The constructed miRNA-target gene network consisted of 25 miRNAs and 27 target genes. The most enriched term was fatty acid metabolism for the target genes. In HepG2 cells, transfection with the mimic or inhibitor of hsa-miR-1226-3p or hsa-miR-221-5p caused significant changes of the mRNA and protein levels of their respective target genes (P < 0.05). The results of dual luciferase reporter assay confirmed the targeting relationship between hsa-miR-221-5p and GCDH gene (P < 0.05). Transfection with hsa-miR-221-5p mimic significantly suppressed the proliferation, migration and invasion of HepG2 cells, but this effect was obviously relieved by co-transformation with pEGFP N1-GCDH (P < 0.05).@*CONCLUSION@#Fatty acid metabolism might be one of the most crucial pathways that mediate the effect of the oncomiRNAs in HCC, and the hsa-miR-221-5p/GCDH axis is an important molecular mechanism for HCC progression.

An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851

BACKGROUND Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. OBJECTIVES In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. METHODS We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. FINDINGS Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. MAIN CONCLUSIONS Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.

Expression profile of circRNA and construction of ceRNA regulatory network in tuberous sclerosis related renal angiomyolipoma (TSC-RAML) / 中华泌尿外科杂志

Objective:To comprehensively analyze the expression profile of circular RNA (circRNA) and construct competing endogenous RNA (ceRNA) regulatory networks in tuberous sclerosis complex related renal angiomyolipoma (TSC-RAML).Methods:According to the diagnostic criteria of TSC determined by the international consensus group on tuberous sclerosis in 2012, tumor tissues and paired normal renal tissues of 3 patients with TSC-RAML who were diagnosed in our hospital from January 2017 to January 2019 were collected. The circRNA, miRNA and mRNA of 3 paired samples were detected by circRNA, miRNA chip technology and next generation sequencing respectively, and the differential molecules were determined. Gene Ontology(GO) functional enrichment analysis and Kyoto Encyclopedia of genes and genomes(KEGG) pathway enrichment analysis were performed based on differential mRNA molecules and host genes of circRNA. Based on differential circRNA, miRNA and mRNA, up-regulated and down-regulated ceRNA regulatory networks were established.Results:A total of 330 up-regulated and 336 down-regulated differential circRNA, 8 up-regulated and 7 down-regulated miRNA, 800 up-regulated and 1130 down-regulated mRNA were screened. Through GO and KEGG enrichment analysis, many pathways including lipid metabolism, focal adhesion and mineral absorption were abnormally altered. Finally, the up-regualted ceRNA network led by hsa_circ_0092022, hsa_circ_0076859 and hsa_circ_0033388 and down-regulated network led by hsa_circ_0000374, hsa_circ_0000141, hsa_circ_0072665, hsa_circ_0009503 and hsa_circ_0000009 were constructed.Conclusions:There were many differentially expressed circRNA between TSC-RAML and paired normal renal tissues. ceRNA regulatory networks may be involved in the occurrence and development of TSC-RAML.

Role of IL-23/IL-17 pathway and regulatory network in the pathogenesis of uveitis / 中华实验眼科杂志

Uveitis is an inflammatory disease, a leading cause of blindness, the pathogenesis of which is not fully understood.In recent years, it has been found that interleukin (IL)-23/IL-17 pathway plays an important role in the occurrence of uveitis.The IL-23/IL-17 pathway mainly acts on target cells through activating the T helper 17 cells, resulting in the production of inflammatory factors and chemokines as well as the damage of retinal pigment epithelium, which can cause uveitis.The IL-23/IL-17 pathway is regulated by a giant network, and the regulation of it by its positive and negative factors can lead to immune disorders and participate in the occurrence of uveitis.The polymorphism of genes in IL-23/IL-17 pathway and regulatory network is closely related to uveitis, which provides an important basis for the genetic pathogenesis of uveitis.In addition, clinical trials have confirmed the efficacy of biological agents targeting IL-23/IL-17 pathway, which provides a new research direction for the treatment of uveitis.The IL-23/IL-17 pathway and its physiological function, the positive and negative factors and gene polymorphism of IL-23/IL-17 pathway and its regulatory network in uveitis were summarized, and the research progress of biological agents of IL-23/IL-17 pathway in uveitis were reviewed in this article in order to deepen the understanding of the pathogenesis of uveitis and guide clinical practice.

Bioinformatics analysis of differential expression genes and microRNA-messenger RNA regulatory network in biliary atresia / 中华实用儿科临床杂志

Objective:To mining differential expression genes (DEGs) and establish a regulatory network of dysregulated microRNAs (miRNAs) and messenger RNAs (mRNAs) in biliary atresia (BA) spectrum via bioinforma-tics analysis, and to explore the pathogenesis of BA.Methods:GSE46960 dataset was download from gene expression omnibus (GEO). DEGs between normal liver tissues and BA tissues were analyzed using the GEO2R analysis tool.The functional and pathway enrichment analyses of DEGs were performed utilizing the Database for Annotation, Visualization and Integrated Discovery (DAVID6.8). A protein-protein interaction (PPI) network was constructed using the PPI database (STRING11.0) and Cytoscape_v3.7.1 software, and thus key genes were analyzed.BA-related miRNAs were obtained using the human miRNA disease database (HMDD_V3.0) and target mRNAs were predicted by the miRNA target prediction database (miRDB). The intersection between the predicted target mRNAs and DEGs from the GSE46960 dataset was selected.The regulatory network of miRNA-mRNA was constructed using Cytoscape software.Results:A total of 565 DEGs, including 352 up-regulated ones and 213 down-regulated ones were identified.Among them, up-regulated DEGs were enriched in extracellular matrix(ECM)-receptor interaction, focal adhesion kinase (FAK), Amoebiasis, and the phosphoinositide 3 kinase/protein kinase B(PI3K/Akt) pathway.Down-regulated DEGs were enriched in metabolic signaling, biosynthesis of antibiotics and steroid biosynthesis pathway.From the PPI network, 10 key genes were screened out.A complex miRNA-mRNA regulatory network was constructed based on screened DEGs.Conclusions:Identified DEGs and miRNA-mRNA regulatory network constructed in this study may help clarify the molecular mechanisms of BA.This study provides a new direction to explore promising molecular targets for the diagnosis and treatment of BA.

Differential mRNA expression profile and competitive endogenous RNA regulatory network in osteoarthritis / 中国组织工程研究

BACKGROUND: The possible causes of osteochondroarthritis have been identified as cartilage degeneration, autophagy, mechanical changes, cartilage hypertrophy, internal immunity, oxidative stress, and pain. OBJECTIVE: To explore the pathogenesis of osteoarthritis that is a degenerative disease of articular cartilage caused by a variety of factors. METHODS: GSE51588 and GSE19060, the chip data sets related to osteoarthritis in GEO database, were retrieved, and differential genes were analyzed with the help of R language. miRDB, miRTarbase and starBase databases were used to predict the targeted miRNAs of osteoarthritis related mRNAs respectively, and miRNA-mRNA regulatory network was constructed. GeneMANIA and FUNRICH were used to analyze the mRNAs mentioned in the regulatory network. lncRNA-miRNA-mRNA ceRNA regulatory network was constructed by retrieving LncRNADisease database and osteoarthiritis related IncRNA, using Starbase database to predict their miRNAs. RESULTS AND CONCLUSION: A total of 11 significantly differentially expressed mRNAs were screened by R language analysis. Through the cross-mapping of miRDB, miRTarbase and starBase and the predicted targeted miRNAs and the above 11 differentially expressed mRNAs, 290 miRNAs were identified to be involved in the construction of the miRNA-mRNA regulatory network related to osteoarthritis. Fifteen incRNAs related to the pathogenesis of osteoarthritis were retrieved in the LncRNADisease database, 270 miRNAs were predicted using Starbase database, and the lncRNA-miRNA-mRNA ceRNA regulatory network consisting of 5 IncRNAs, 106 miRNAs and 8 mRNAs was constructed. Seven major biological processes and two major signaling pathways were obtained through FUNRICH. Finding from our further analysis indicate that differentially expressed mRNA is mainly related to the biological processes of protein metabolism, cell communication, signal transduction, immune response, metabolism, energy pathway and cell growth. By participating in the pathogenesis of osteoarthritis, it provides ideas for the determination of therapeutic targets for osteoarthritis.

Utilizing benchmarked dataset and gene regulatory network to investigate hub genes in postmenopausal osteoporosis

Objective: The objective of this paper was to investigate hub genes of postmenopausal osteoporosis (PO) utilizing benchmarked dataset and gene regulatory network (GRN). Materials and Methods: To achieve this goal, the first step was to benchmark the dataset downloaded from the ArrayExpress database by adding local noise and global noise. Second, differentially expressed genes (DEGs) between PO and normal controls were identified using the Linear Models for Microarray Data package based on benchmarked dataset. Third, five kinds of GRN inference methods, which comprised Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT), and GEne Network Inference with Ensemble of trees (Genie3), were described and evaluated by receiver operating characteristic (ROC) and precision and recall (PR) curves. Finally, GRN constructed according to the method with best performance was implemented to conduct topological centrality (closeness) for the purpose of investigate hub genes of PO. Results:A total of 236 DEGs were obtained based on benchmarked dataset of 20,554 genes. By assessing Zscore, GeneNet, CLR, PCIT, and Genie3 on the basis of ROC and PR curves, Genie3 had a clear advantage than others and was applied to construct the GRN which was composed of 236 nodes and 27,730 edges. Closeness centrality analysis of GRN was carried out, and we identified 14 hub genes (such as TTN, ACTA1, and MYBPC1) for PO. Conclusion: In conclusion, we have identified 14 hub genes (such as TN, ACTA1, and MYBPC1) based on benchmarked dataset and GRN. These genes might be potential biomarkers and give insights for diagnose and treatment of PO

Identification of potential traumatic spinal cord injury related circular RNA-microRNA networks by sequence analysis / 中国修复重建外科杂志

Objective: To systematically profile and characterize the circular RNA (circRNA) and microRNA (miRNA) expression pattern in the lesion epicenter of spinal tissues after traumatic spinal cord injury (TSCI) and predict the structure and potential functions of the regulatory network. Methods: Forty-eight adult male C57BL/6 mice (weighing, 18-22 g) were randomly divided into the TSCI ( n=24) and sham ( n=24) groups. Mice in the TSCI group underwent T 8-10 vertebral laminectomy and Allen's weight-drop spinal cord injury. Mice in the sham group underwent the same laminectomy without TSCI. The spinal tissues were harvested after 3 days. Some tissues were stained with HE staining to observe the structure. The others were used for sequencing. The RNA-Seq, gene ontology (GO) analysis, and circRNA-miRNA network analyses (TargetScan and miRanda) were used to profile the expression and regulation patterns of network of mice models after TSCI. Results: HE staining showed the severe damage to the spinal cord in TSCI group compared with sham group. A total of 17 440 circRNAs and 1 228 miRNAs were identified. The host gene of significant differentially expressed circRNA enriched in the cytoplasm, associated with positive regulation of transcription and protein phosphorylation. mmu-miR-21-5p was the most significant differentially expressed miRNA after TSCI, and circRNA6730 was predicted to be its targeted circRNA. Then a potential regulatory circRNA-miRNA network was constructed. Conclusion: The significant differentially expressed circRNAs and miRNAs may play important roles after TSCI. A targeted interaction network with mmu-miR-21-5p at the core of circRNA6730 could provide basis of pathophysiological mechanism, as well as help guide therapeutic strategies for TSCI.

Differential expression analysis and regulatory network construction of miRNA and genes in osteoporosis / 医学研究生学报

ObjectiveMicroRNAs (miRNA) play an important role in the development and regression of osteoporosis. This study aims to screen for miRNAs and genes closely related to osteoporosis, and to complete the construction of a miRNA-mRNA regulatory network of osteoporosis.MethodsThe gene chip expression profile of osteoporosis was obtained through the GEO database, and the differentially expressed genes (DEGs) and miRNAs were analyzed and screened via GEO2R. We used volcanic maps to display differential genes and miRNAs, and completed the GO and KEGG pathway analysis through the David online database. The String online database is used to complete PPI protein network analysis. The TargetScan, miRTarBase and miRDB were used to predict the targeted genes. Finally, the PPI and miRNA-mRNA regulatory networks were visualized by Cytoscape software.ResultsWe obtained 15 differential miRNAs and 174 differentially expressed genes through screening. The GO enrichment analysis mainly focused on drug response, angiogenesis, ion transport, regulation of small GTPase mediated signal ransduction, adaptive immune response, etc. NF-κB signaling pathway and HIF-1 signal were obtained through KEGG enrichment analysis. We obtained 10 hub genes through the cytohubba plug-in. We also obtained 3065 targeted genes by processing of seven miRNAs, and then intersected them with 174 DEGs to obtain 44 intersection genes. Finally, we successfully constructed a regulation map of miRNA-mRNA network. The miR-194-5p is significantly up-regulated in osteoporosis.ConclusionThe miR-194-5p might play an important role in osteoporosis by regulating its target gene CDH2, which provides candidate targets for the diagnosis and treatment of osteoporosis.

Discovery and molecular analysis of conserved circRNAs from cashmere goat reveal their integrated regulatory network and potential roles in secondary hair follicle

Background: Circular RNAs, a novel class in the eukaryotic transcriptome, are characterized by the 3' and 5' ends that are covalently joined in a covalently closed loop without free ends. Circular RNAs are considerably stable molecules and act as microRNA sponges with regulatory potential to the protein-coding genes. Results: Eight circular RNAs were found to be significantly upregulated at anagen skin tissue of cashmere goat compared with their counterparts at telogen. Rich and complex regulatory patterns were revealed among the eight upregulated circular RNAs at anagen and related miRNAs with their potential regulatory genes. The potential regulatory genes of eight upregulated circular RNAs at anagen were involved in several pathways related to the main physiological process of hair follicle, such as histone acetylation and axon. For chi_circ_1926, chi_circ_3541, chi_circ_0483, chi_circ_3196, and chi_circ_2092, overall, the relative expression in secondary hair follicle exhibited highly similar trends with their corresponding host genes during the different stages of the hair follicle cycle. However, the expression trends of chi_circ_0100, chi_circ_2829, and chi_circ_1967 were found to diverge from their corresponding host genes during the different stages of the hair follicle cycle. Conclusions: A total of eighteen circular RNAs were identified and characterized from skin tissue of cashmere goat. The eight upregulated circular RNAs at anagen might have significant roles in the secondary hair follicle of cashmere goat. Our results would provide a novel regulatory layer to elucidate the molecular mechanisms underlying the development of secondary hair follicle and the growth of cashmere fiber in cashmere goat.

Interaction network analysis of YBX1 for identification of therapeutic targets in adenocarcinomas

Human Y-box binding protein-1 (YBX1) is a member of highly conserved cold-shock domain protein family, which isinvolved in transcriptional as well as translational regulation of many genes. Nuclear localization of YBX1 has beenobserved in various cancer types and it’s overexpression has been linked to adverse clinical outcome and poor therapyresponse, but no diagnostic or therapeutic correlation has been established so far. This study aimed to identify differentiallyexpressed novel genes among the interactors of YBX1 in different cancer types. Analysis of RNA-Seq data for colorectal,lung, prostate and stomach adenocarcinoma identified 39 unique genes, which are differentially expressed in the fouradenocarcinoma types. Gene-enrichment analysis for the differentially expressed genes from individual adenocarcinomawith focus on unique genes resulted in a total of 57 gene sets specific to each adenocarcinoma. Gene ontology forcommonly expressed genes suggested the pathways and possible mechanisms through which they affect each adenocarcinoma type considered in the study. Gene regulatory network constructed for the common genes and network topologywas analyzed for the central nodes. Here 12 genes were found to play important roles in the network formation; amongthem, two genes FOXM1 and TOP2A were found to be in central network formation, which makes them a common targetfor therapeutics. Furthermore, five common differentially expressed genes in all adenocarcinomas were also identified.

Identification of the miRNA-mRNA regulatory network of antler growth centers

Antler growth is a unique event compared to other growth and development processes in mammals. Antlers grow extremelyfast during the rapid growth stage when growth rate peaks at 2 cm per day. Antler growth is driven by a specificendochondral ossification process in the growth center that is in the distal region of the antler tip. In this study, we usedstate-of-art RNA-seq technology to analyze the expression profiles of mRNAs and miRNAs during antler growth. Ourresults indicated that the expression levels of multiple genes involved in chondrogenesis and endochondral ossification,including Fn1, Sox9, Col2a1, Acan, Col9a1, Col11a1, Hapln1, Wwp2, Fgfr3, Comp, Sp7 and Ihh, were significantlyincreased at the rapid growth stage. Our results also indicated that there were multiple differentially expressed miRNAsinteracting with differentially expressed genes with opposite expression patterns. Furthermore, some of the miRNAs,including miR-3072-5p, miR-1600, miR-34-5p, miR-6889-5p and miR-6729-5p, simultaneously interacted with andcontrolled multiple genes involved in the process of chondrogenesis and endochondral ossification. Therefore, we established a miRNA-mRNA regulatory network by identifying miRNAs and their target genes that were differentially expressedin the antler growth centers by comparing the rapid growth stage and the initial growth stage

Transcriptome and Regulatory Network Analyses of CD19-CAR-T Immunotherapy for B-ALL / 基因组蛋白质组与生物信息学报·英文版

Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor efficacy in clinical trials. In this study, we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells, and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations, e.g., CD8 T cells and natural killer (NK) cells, in the bone marrow. Additionally, CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways, including the NK cell mediated cytotoxicity and NOD-like receptor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g., miR-148a-3p and miR-375), acting as oncogenes or tumor suppressors, could regulate the crosstalk between the genes encoding transcription factors (TFs; e.g., JUN and FOS) and histones (e.g., HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore, many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g., FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for further understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.

Differentially expressed microRNA and target gene analysis in patients with postmenopausal osteoporosis / 中华创伤杂志

Objective@#To analyze the differentially expressed microRNA (miRNA) and their target genes in peripheral blood and bone tissue of postmenopausal osteoporosis (PMOP), and provide basis for the study of pathogenesis as well as biomarkers identification of PMOP.@*Methods@#Two miRNA datasets of PMOP from the public platform NCBI-GEO DataSets were obtained, including GSE64433 (the miRNA expression profile of peripheral blood samples, including 23 PMOP patients and 25 controls) and GSE74209 (the miRNA expression profile of the femoral neck bone tissue sample, including six PMOP patients and six controls). R/Bioconductor was performed for data analysis and differentially expressed miRNA screening, and miRNAs with fold change>2 & P<0.05 between osteoporosis and controls were selected as differentially expressed miRNA. The miRNA target gene prediction was performed by combining TargetScan, miRDB and miRTarBase databases. The miRNA-target gene regulatory network was constructed and analyzed by Cytoscape.@*Results@#There were 224 differentially expressed miRNAs (75 up-regulated miRNAs and 149 down-regulated miRNAs) in the peripheral blood samples of PMOP group (GSE64433 dataset) and 132 differentially expressed miRNAs (58 up-regulated miRNAs and 74 down-regulated miRNAs) in the femoral neck bone tissue of PMOP group (GSE74209 dataset). We combined the results from the two datasets and obtained 8 miRNAs down-regulated in both datasets, and the 8 miRNAs regulated a total of 327 target genes, and 10 of these target genes were co-regulated by two miRNAs.@*Conclusions@#The core miRNAs and the target genes regulated by multiple miRNAs in the regulatory network may play important roles in the pathogenesis of PMOP and have potential application values as molecular biomarkers of disease. These findings are meaningful for the studies of PMOP pathogenesis, biomarkers screening and prevention of osteoporotic fractures.

Differentially expressed microRNA and target gene analysis in patients with postmenopausal osteoporosis / 中华创伤杂志

Objective To analyze the differentially expressed microRNA (miRNA) and their target genes in peripheral blood and bone tissue of postmenopausal osteoporosis (PMOP),and provide basis for the study of pathogenesis as well as biomarkers identification of PMOP.Methods Two miRNA datasets of PMOP from the public platform NCBI-GEO DataSets were obtained,including GSE64433 (the miRNA expression profile of peripheral blood samples,including 23 PMOP patients and 25 controls) and GSE74209 (the miRNA expression profile of the femoral neck bone tissue sample,including six PMOP patients and six controls).R/Bioconductor was performed for data analysis and differentially expressed miRNA screening,and miRNAs with fold change ＞ 2 & P ＜ 0.05 between osteoporosis and controls were selected as differentially expressed miRNA.The miRNA target gene prediction was performed by combining TargetScan,miRDB and miRTarBase databases.The miRNA-target gene regulatory network was constructed and analyzed by Cytoscape.Results There were 224 differentially expressed miRNAs (75 up-regulated miRNAs and 149 down-regulated miRNAs) in the peripheral blood samples of PMOP group (GSE64433 dataset) and 132 differentially expressed miRNAs (58 up-regulated miRNAs and 74 down-regulated miRNAs) in the femoral neck bone tissue of PMOP group (GSE74209 dataset).We combined the results from the two datasets and obtained 8 miRNAs down-regulated in both datasets,and the 8 miRNAs regulated a total of 327 target genes,and 10 of these target genes were co-regulated by two miRNAs.Conclusions The core miRNAs and the target genes regulated by multiple miRNAs in the regulatory network may play important roles in the pathogenesis of PMOP and have potential application values as molecular biomarkers of disease.These findings are meaningful for the studies of PMOP pathogenesis,biomarkers screening and prevention of osteoporotic fractures.

Gene regulatory network inference and analysis of multidrug-resistant Pseudomonas aeruginosa

BACKGROUND Healthcare-associated infections caused by bacteria such as Pseudomonas aeruginosa are a major public health problem worldwide. Gene regulatory networks (GRN) computationally represent interactions among regulatory genes and their targets. They are an important approach to help understand bacterial behaviour and to provide novel ways of overcoming scientific challenges, including the identification of potential therapeutic targets and the development of new drugs. OBJECTIVES The goal of this study was to reconstruct the multidrug-resistant (MDR) P. aeruginosa GRN and to analyse its topological properties. METHODS The methodology used in this study was based on gene orthology inference using the reciprocal best hit method. We used the genome of P. aeruginosa CCBH4851 as the basis of the reconstruction process. This MDR strain is representative of the sequence type 277, which was involved in an endemic outbreak in Brazil. FINDINGS We obtained a network with a larger number of regulatory genes, target genes and interactions as compared to the previously reported network. Topological analysis results are in accordance with the complex network representation of biological processes. MAIN CONCLUSIONS The properties of the network were consistent with the biological features of P. aeruginosa. To the best of our knowledge, the P. aeruginosa GRN presented here is the most complete version available to date.