Transcription Factor microRNA Research Articles

Bioinformatics Research and qRT-PCR Verify Hub Genes and a Transcription Factor-MicroRNA Feedback Network in Intervertebral Disc Degeneration.

The present study explores the potentials of bioinformatics analysis to identify hub genes linked to intervertebral disc degeneration (IDD) and explored the potential molecular mechanism of transcription factor-microRNA regulatory network. Furthermore, the hub genes were identified through quantitative reverse transcriptase PCR (qRT-PCR). GEO database expression profile datasets for candidate genes (GSE124272) were downloaded. Genes that were differentially expressed (DEGs) were detected utilizing limma technique in the R programming language. Search Tool for the Retrieval of Interacting Genes/Proteins and NetworkAnalyst software identified hub genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis as well as Gene Ontology annotation of the DEGs were performed using Metascape. Using Bioinformatics data from the TRRUST, StarBase, and TransmiR databases, a TF-miRNA-hub genes network was constructed. qRT-PCR was utilized to confirm the result. As compared to healthy persons, 521 DEGs, comprising 203 down-regulated and 318 up-regulated genes, as well as 7 core genes, were found in people with IDD. Analysis revealed that all seven essential genes were under-expressed. qRT-PCR further confirmed the low expression of these seven important genes. Based on the TRRUST database, 16 TFs that could target five junction genes were then predicted. According to the StarBase database, four miRNAs were linked to crucial genes, while the TransmiR database predicted regulatory connections between four miRNAs and five TFs. The expression of the TP53-(hsa-miR-183-5p)-CCNB1 TF-miRNA-mRNA interaction network was discovered to be correlated with IDD. Throughout this investigation, a network of TF-miRNA-mRNA connections was built for investigation of the probable molecular mechanisms responsible for IDD. The identification of hub genes associated with IDD may reveal promising IDD treatment strategies.

Identification of hsa-miR-365b-5p’s role in Alzheimer’s disease: A combined analysis of miRNA and mRNA microarrays

BackgroundAlzheimer’s disease is a prevalent health problem with a heavy global burden. Definitely diagnosed by autopsy, the clear mechanism of Alzheimer’s disease pathogenesis process needs to be illustrated. MicroRNAs are suggested to be involved in many diseases. We aimed to investigate the role of microRNA in Alzheimer’s disease. MethodsWe attempted to discover the role of microRNA in Alzheimer’s disease by microarray bioinformatics analysis using autopsy sample data from the GEO database. Temporal cortex samples were included in this study. Bioinformatics analyses and visualization were processed based on R. ResultsAfter filtering out significantly differential expressed microRNAs and genes, enrichment analyses of both microRNAs and genes were conducted, respectively. Then, we constructed a transcription factor–microRNA–mRNA network and a protein–protein interaction network. In parallel, we used the receiver operating characteristic curve to evaluate the diagnostic value of microRNA. Based on the evidence, we finally identified hsa-miR-365b-5p as a key target in Alzheimer’s disease. ConclusionsHsa-miR-365b-5p act as a key target in Alzheimer’s disease. It regulates Alzheimer’s disease pathogenesis process via neuroinflammation, Wnt and oxidative stress pathway which provides a potential target for Alzheimer’s disease treatment.

Identification of the hub genes and transcription factor-miRNA axes involved in Helicobacter pylori-associated gastric cancer.

It has been previously reported that transcription factor-microRNA (TF-miRNA) axes play a significant role in the carcinogenesis of several types of malignant tumor. However, there is a lack of research into the differences in the mechanism of Helicobacter pylori (HP)-positive [HP(+)] and HP-negative [HP(−)] gastric cancer. The aim of the present study was to identify the hub genes and TF-miRNA axes, and to determine the potential mechanisms involved in HP-associated gastric cancer. HP-associated mRNA and miRNA data, as well as the corresponding clinical information, was downloaded from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) and DE miRNAs (DEMs) were then identified from the HP(+) and HP(−) cancer mRNA and miRNA datasets, respectively. Subsequently, gene set enrichment analysis and the protein-protein interaction (PPI) networks were investigated using the ClusterProfiler packages. Lastly, TF-miRNA-DEG networks were constructed using the miRWalk online tool. A total of 1,050 DEGs and 13 DEMs were identified from the normalized mRNA and miRNA expression datasets, respectively. In addition, 180 Gene Ontology terms and 30 Kyoto Encyclopedia of Genes and Genomes pathways were found to be enriched, while 6 hub genes were identified from the PPI analysis. Furthermore, 7 TF-miRNA interactions and 181 TF-miRNA-DEG axes were constructed using an integrated bioinformatics approach, while 2 TF-miRNA interactions (ZEB1-miRNA-144-3p and PAX2-miRNA-592) were confirmed using reverse transcription-quantitative PCR in samples from enrolled patients. Moreover, the ZEB1-miRNA-144-3p axis was further validated based on dual luciferase reporter assay results. In summary, an integrated bioinformatics approach was used to screen the significant molecular and regulatory axes, which may provide a novel direction to investigate the pathogenesis of gastric cancer associated with HP.

Uncovering the differentially expressed genes and pathways involved in the progression of stable coronary artery disease to acute myocardial infarction using bioinformatics analysis.

Coronary artery disease (CAD) is the main cause of mortality worldwide. How stable coronary artery disease (SCAD) progresses to acute myocardial infarction (AMI) is not known. This study was aimed to explore the differentially expressed genes (DEGs) and pathways involved in the progression of SCAD to AMI. Publicly available gene-expression profiles (GSE71226, GSE97320, GSE66360) were downloaded from the Gene Expression Omnibus (GEO) database and integrated to identify DEGs. The GSE59867 dataset was further used to verify the result of screened DEGs. Functional-enrichment analyses, protein-protein interaction network, microRNA-transcription factor (TF)-mRNA regulatory network, and drug-gene network were visualized. Sixty common DEGs (CDEGs) were screened between the SCAD-Control group and AMI-Control group in the integrated dataset. Four upregulated DEGs were selected from GSE59867. Twenty hub genes were discovered, and three significant modules were constructed in the PPI network. The intersection of functional and pathway-enrichment analyses of 60 CDEGs and the module DEGs indicated that they were mainly involved in "inflammatory response", "immune response", and "cytokine-cytokine receptor interaction". A miRNA-TF-mRNA regulatory network comprised 87 miRNAs, 16 upregulated target DEGs and 7 TFs. We identified several important genes and miRNAs involved in the progression of SCAD to AMI: platelet activating factor receptor (PTAFR), aquaoporin-9 (AQP9), toll-like receptor-4 (TLR4), human constitutive androstane receptor-3 (HCAR3), leucine-rich-α2 glycoprotein-1 (LRG1), mothers Against Decapentaplegic Homolog 4 (SMAD4) and miRNA-149-5p, miRNA-6778-3p, and miRNA-520a-3p. Inflammation and the immune response had important roles in the progression from SCAD to AMI.

DNA methylation within genes of microRNA MIR-10B and transcription factor TWIST1 in atherosclerosis

Background and Aims: MiR-10b plays a significant role in atherosclerotic plaque formation and is regulated by TWIST transcription factor. Inhibition of miR-10b led to development of atherosclerosis-resistant phenotype and stabilized advanced lesions in mice. We analyzed DNA methylation within MIR10B and TWIST1 genes in tissue samples of patients and healthy individuals to assess epigenetic state of these loci in atherosclerosis.

The Transcription Factor-microRNA Regulatory Network during hESC-chondrogenesis

Human embryonic stem cells (ESCs) offer a promising therapeutic approach for osteoarthritis (OA). The unlimited source of cells capable of differentiating to chondrocytes has potential for repairing damaged cartilage or to generate disease models via gene editing. However their use is limited by the efficiency of chondrogenic differentiation. An improved understanding of the transcriptional and post-transcriptional regulation of chondrogenesis will enable us to improve hESC chondrogenic differentiation protocols. Small RNA-seq and whole transcriptome sequencing was performed on distinct stages of hESC-directed chondrogenesis. This revealed significant changes in the expression of several microRNAs including upregulation of known cartilage associated microRNAs and those transcribed from the Hox complexes, and the downregulation of pluripotency associated microRNAs. Integration of miRomes and transcriptomes generated during hESC-directed chondrogenesis identified key functionally related clusters of co-expressed microRNAs and protein coding genes, associated with pluripotency, primitive streak, limb development and extracellular matrix. Analysis identified regulators of hESC-directed chondrogenesis such as miR-29c-3p with 10 of its established targets identified as co-regulated ‘ECM organisation’ genes and miR-22-3p which is highly co-expressed with ECM genes and may regulate these genes indirectly by targeting the chondrogenic regulators SP1 and HDAC4. We identified several upregulated transcription factors including HOXA9/A10/D13 involved in limb patterning and RELA, JUN and NFAT5, which have targets enriched with ECM associated genes. We have developed an unbiased approach for integrating transcriptome and miRome using protein-protein interactions, transcription factor regulation and miRNA target interactions and identified key regulatory networks prominent in hESC chondrogenesis.

A developmental stage-specific network approach for studying dynamic co-regulation of transcription factors and microRNAs during craniofacial development.

Craniofacial development is regulated through dynamic and complex mechanisms that involve various signaling cascades and gene regulations. Disruption of such regulations can result in craniofacial birth defects. Here, we propose the first developmental stage-specific network approach by integrating two crucial regulators, transcription factors (TFs) and microRNAs (miRNAs), to study their co-regulation during craniofacial development. Specifically, we used TFs, miRNAs and non-TF genes to form feed-forward loops (FFLs) using genomic data covering mouse embryonic days E10.5 to E14.5. We identified key novel regulators (TFs Foxm1, Hif1a, Zbtb16, Myog, Myod1 and Tcf7, and miRNAs miR-340-5p and miR-129-5p) and target genes (Col1a1, Sgms2 and Slc8a3) expression of which changed in a developmental stage-dependent manner. We found that the Wnt-FoxO-Hippo pathway (from E10.5 to E11.5), tissue remodeling (from E12.5 to E13.5) and miR-129-5p-mediated Col1a1 regulation (from E10.5 to E14.5) might play crucial roles in craniofacial development. Enrichment analyses further suggested their functions. Our experiments validated the regulatory roles of miR-340-5p and Foxm1 in the Wnt-FoxO-Hippo subnetwork, as well as the role of miR-129-5p in the miR-129-5p-Col1a1 subnetwork. Thus, our study helps understand the comprehensive regulatory mechanisms for craniofacial development.

Identification and expression analysis of critical microRNA-transcription factor regulatory modules related to seed development and oil accumulation in developing Hippophae rhamnoides seeds

Sea buckthorn (Hippophae rhamnoides) seed oil is rich in omega fatty acids and various other bioactive compounds, which not only have high antioxidant activity but may also prevent cardiovascular diseases. However, the molecular mechanisms of oil biosynthesis and fatty acid accumulation in developing sea buckthorn seeds remain unknown. Altering the levels of certain miRNAs and transcription factors can affect the expression of multiple genes involved in seed development and fatty acid biosynthesis, resulting in changed seed oil contents. Considering that previous studies have focused mainly on these two regulators separately, we attempted to combine the study of miRNAs and transcription factors to construct a coregulatory network. In the present study, we generated cDNA libraries and small RNA libraries from the seeds of high-oil-content and low-oil-content sea buckthorn cultivars at four developmental stages, and then used high-throughput sequencing technology and bioinformatics methods to identify 140 differentially expressed transcription factors, 137 known miRNAs, and 250 novel miRNAs. Through target relationship prediction, 31 potential transcription factors were found to be associated with 27 miRNAs in 18 independent networks, showing the multiplicity of the regulators. In particular, 9 miRNAs and 5 transcription factors were found as hubs in the network. Furthermore, we hypothesized that 12 regulatory modules might play combinatory regulatory roles in seed development and oil accumulation. In developing seeds, the expression levels of these miRNAs and transcription factors were significantly different between the two cultivars. Taken together, these data describe the first miRNA-transcription factor coregulatory network in developing seeds of sea buckthorn. These findings will be helpful for understanding seed development and oil accumulation at the molecular level in sea buckthorn.

MiR-431-5p Knockdown Protects Against Angiotensin II-Induced Hypertension and Vascular Injury.

Vascular injury is an early manifestation in hypertension and a cause of end-organ damage. MicroRNAs play an important role in cardiovascular disease, but their implication in vascular injury in hypertension remains unclear. This study revealed using an unbiased approach, microRNA and mRNA sequencing with molecular interaction analysis, a microRNA-transcription factor coregulatory network involved in vascular injury in mice made hypertensive by 14-day Ang II (angiotensin II) infusion. A candidate gene approach identified upregulated miR-431-5p encoded in the conserved 12qF1 (14q32 in humans) microRNA cluster, whose expression correlated with blood pressure, and which has been shown to be upregulated in human atherosclerosis, as a potential key regulator in Ang II-induced vascular injury. Gain- and loss-of-function in human vascular smooth muscle cells demonstrated that miR-431-5p regulates in part gene expression by targeting ETS homologous factor. In vivo miR-431-5p knockdown delayed Ang II-induced blood pressure elevation and reduced vascular injury in mice, which demonstrated its potential as a target for treatment of hypertension and vascular injury.

Identification of a transcription factor-microRNA network in esophageal adenocarcinoma through bioinformatics analysis and validation through qRT-PCR.

Purpose: The rapidly rising incidence of esophageal adenocarcinoma (EAC), which is usually diagnosed late with a poor prognosis, has become a growing problem. This study investigated the potential transcription factor (TF)-related molecular mechanisms of EAC by using bioinformatics analysis and qRT-PCR validation.Methods: Expression profile datasets for mRNAs (GSE92396, GSE13898, GSE26886 and GSE1420) and miRNAs (GSE16456) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. Then, a TF-miRNA-mRNA network was constructed based on bioinformatics data from the TRRUST, TRED and miRTarBase database. Furthermore, overall survival analysis for the mRNAs and miRNAs in the TF-miRNA-mRNA network was performed with data from TCGA, and qRT-PCR was used to validate the results.Results: A total of 294 overlapping DEGs were identified in EAC tissues compared to normal tissues, including 181 downregulated and 113 upregulated genes. Then, 16 TFs that could target the DEGs and were related to cancer were predicted based on public databases, and 41 DEGs that could be targeted were identified as key genes. Additionally, 12 DEMs were predicted through miRTarBase to be associated with the key genes, and TP53-(miR-125b)-ID2 and JUN-(miR-30a)-IL1A from the TF-miRNA-mRNA network were identified to potentially play significant roles in EAC. Furthermore, CCL20, IL1A, ABCC3, hsa-miR-23b, and hsa-miR-191, which are involved in the TF-miRNA-mRNA network, were found to be significantly associated with patient survival in EAC. Finally, the expression of a miRNA-mRNA pair (hsa-miR-30a-5p and IL1A) was revealed to be correlated with prognosis.Conclusion: In this study, a TF-miRNA-mRNA network was constructed to analyze the potential molecular mechanisms of EAC. Key genes and miRNAs associated with patient survival were identified, which may reveal promising approaches for EAC diagnosis and therapy.

Potential biomarkers for heart failure.

In this study, we identified candidate biomarkers for heart failure (HF). The gene expression profile GSE57338, containing 117 ischemic cardiomyopathic HF and 136 control samples, was downloaded and analyzed using various bioinformatics approaches. In total, 376 differentially expressed genes (DEGs) were identified, and four modules were explored in protein-protein interaction networks. DEGs (including ankyrin repeat and SOCS box-containing 14 [ASB14]) in the modules were mainly categorized by the function. Several relationships including interferon regulatory factor 1 (IRF1)-C-C motif chemokine ligand 5 (CCL5) were revealed in the transcription factor microRNA target gene regulatory network. Gene-drug analysis revealed 11 DEGs (such as the cluster of differentiation 163 [CD163]) for the target drugs. Data verification analysis identified 118 overlapping DEGs including ASB14, CD163, and CCL5. ASB14 may be involved in HF progression via protein ubiquitination and CCL5 may be involved in HF via the IRF1-CCL5 interaction. Genes including CD163 are potential biomarkers for HF.

MicroRNA-transcription factor network analysis reveals miRNAs cooperatively suppress RORA in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) represents over 90% of oral cancer incidence, while its mechanisms of tumorigenesis remain poorly characterized. In this study, we applied RNA-seq and microRNA-seq methodologies in four pairs of cancer and adjacent normal tissues to profile the contribution of miRNAs to tumorigenesis-altered functional pathways by constructing a comprehensive miRNA-mediated mRNA regulatory network. There were 213 differentially expressed (DE) miRNAs and 2172 DE mRNAs with the involvement of negative miRNA-mRNA interactions identified by at least two pairs of cancerous tissues. GO analysis revealed that the upregulated microRNAs significantly contributed to a global down-regulation of a number of transcription factors (TFs) in OSCC. Among the negative regulatory networks between the selected miRNAs (133) and TFs (167), circadian rhythm genes (RORA, RORB, RORC, and CLOCK) simultaneously regulated by multiple microRNAs were of particular interest. For instance, RORA transcript was predicted to be targeted by 25 co-upregulated miRNAs, of which, miR-503-5p, miR-450b-5p, miR-27a-3p, miR-181a-5p and miR-183-5p were further validated to directly target RORA, resulting in a stronger effect on RORA suppression together. In addition, we showed that the mRNA and protein expression levels of RORα were significantly decreased in most OSCC samples, associated with advanced clinical stage and poor prognosis. RORα significantly suppressed the proliferation of OSCC cells in vitro and in vivo. Attenuated RORα decreased p53 protein expression and suppressed p53 phosphorylation activity. Altogether, our results strongly suggest the importance of the role of miRNAs in regulating the activity of circadian rhythm-related TFs network during OSCC tumorigenesis, and provide further clues to understand the clinical link between circadian rhythm and cancer therapy.

Identification of genes and signaling pathways associated with the pathogenesis of juvenile spondyloarthritis.

The aim of the present study was to identify key genes and signaling pathways associated with the pathogenesis of juvenile spondyloarthritis (JSA). The gene expression profile dataset GSE58667, including data from 15 human whole blood samples collected from 11 patients with JSA and four healthy controls, was analyzed to identify differentially expressed genes (DEGs) associated with disease characteristics. Additionally, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed. Protein-protein, microRNA-transcription factor and chemical-gene interaction networks were constructed. A total of 326 DEGs, 196 upregulated and 130 downregulated, were identified. DEGs, including C-X-C motif chemokine ligand 5 (CXCL5), BCL2 interacting protein 3 like (BNIP3L), dual specificity phosphatase 5 (DUSP5) and tumor protein p53 (TP53) were enriched in functions associated with apoptosis, the cell cycle and immune responses. KEGG pathway enrichment analysis revealed that pathways associated with inflammation and the mitogen-activated protein kinase 1 (MAPK) signaling pathway were the most enriched by DEGs. The results of the present study indicated that the MAPK signaling pathway and four genes, including CXCL5, BNIP3L, DUSP5 and TP53, may be implicated in the pathogenesis of JSA.

Biological networks in Parkinson\u2019s disease: an insight into the epigenetic mechanisms associated with this disease

BackgroundParkinson’s disease (PD) is the second most prevalent neurodegenerative disorders in the world. Studying PD from systems biology perspective involving genes and their regulators might provide deeper insights into the complex molecular interactions associated with this disease.ResultWe have studied gene co-expression network obtained from a PD-specific microarray data. The co-expression network identified 11 hub genes, of which eight genes are not previously known to be associated with PD. Further study on the functionality of these eight novel hub genes revealed that these genes play important roles in several neurodegenerative diseases. Furthermore, we have studied the tissue-specific expression and histone modification patterns of the novel hub genes. Most of these genes possess several histone modification sites those are already known to be associated with neurodegenerative diseases. Regulatory network namely mTF-miRNA-gene-gTF involves microRNA Transcription Factor (mTF), microRNA (miRNA), gene and gene Transcription Factor (gTF). Whereas long noncoding RNA (lncRNA) mediated regulatory network involves miRNA, gene, mTF and lncRNA. mTF-miRNA-gene-gTF regulatory network identified a novel feed-forward loop. lncRNA-mediated regulatory network identified novel lncRNAs of PD and revealed the two-way regulatory pattern of PD-specific miRNAs where miRNAs can be regulated by both the TFs and lncRNAs. SNP analysis of the most significant genes of the co-expression network identified 20 SNPs. These SNPs are present in the 3′ UTR of known PD genes and are controlled by those miRNAs which are also involved in PD.ConclusionOur study identified eight novel hub genes which can be considered as possible candidates for future biomarker identification studies for PD. The two regulatory networks studied in our work provide a detailed overview of the cellular regulatory mechanisms where the non-coding RNAs namely miRNA and lncRNA, can act as epigenetic regulators of PD. SNPs identified in our study can be helpful for identifying PD at an earlier stage. Overall, this study may impart a better comprehension of the complex molecular interactions associated with PD from systems biology perspective.

Linking Hematopoietic Differentiation to Co-Expressed Sets of Pluripotency-Associated and Imprinted Genes and to Regulatory microRNA-Transcription Factor Motifs.

Maintenance of cell pluripotency, differentiation, and reprogramming are regulated by complex gene regulatory networks (GRNs) including monoallelically-expressed imprinted genes. Besides transcriptional control, epigenetic modifications and microRNAs contribute to cellular differentiation. As a model system for studying the capacity of cells to preserve their pluripotency state and the onset of differentiation and subsequent specialization, murine hematopoiesis was used and compared to embryonic stem cells (ESCs) as a control. Using published microarray data, the expression profiles of two sets of genes, pluripotent and imprinted, were compared to a third set of known hematopoietic genes. We found that more than half of the pluripotent and imprinted genes are clearly upregulated in ESCs but subsequently repressed during hematopoiesis. The remaining genes were either upregulated in hematopoietic progenitors or in differentiated blood cells. The three gene sets each consist of three similarly behaving gene groups with similar expression profiles in various lineages of the hematopoietic system as well as in ESCs. To explain this co-regulation behavior, we explored the transcriptional and post-transcriptional mechanisms of pluripotent and imprinted genes and their regulator/target miRNAs in six different hematopoietic lineages. Therewith, lineage-specific transcription factor (TF)-miRNA regulatory networks were generated and their topologies and functional impacts during hematopoiesis were analyzed. This led to the identification of TF-miRNA co-regulatory motifs, for which we validated the contribution to the cellular development of the corresponding lineage in terms of statistical significance and relevance to biological evidence. This analysis also identified key miRNAs and TFs/genes that might play important roles in the derived lineage networks. These molecular associations suggest new aspects of the cellular regulation of the onset of cellular differentiation and during hematopoiesis involving, on one hand, pluripotent genes that were previously not discussed in the context of hematopoiesis and, on the other hand, involve genes that are related to genomic imprinting. These are new links between hematopoiesis and cellular differentiation and the important field of epigenetic modifications.

Methods of MicroRNA Promoter Prediction and Transcription Factor Mediated Regulatory Network.

MicroRNAs (miRNAs) are short (~22 nucleotides) noncoding RNAs and disseminated throughout the genome, either in the intergenic regions or in the intronic sequences of protein-coding genes. MiRNAs have been proved to play important roles in regulating gene expression. Hence, understanding the transcriptional mechanism of miRNA genes is a very critical step to uncover the whole regulatory network. A number of miRNA promoter prediction models have been proposed in the past decade. This review summarized several most popular miRNA promoter prediction models which used genome sequence features, or other features, for example, histone markers, RNA Pol II binding sites, and nucleosome-free regions, achieved by high-throughput sequencing data. Some databases were described as resources for miRNA promoter information. We then performed comprehensive discussion on prediction and identification of transcription factor mediated microRNA regulatory networks.

Principles of microRNA Regulation Revealed Through Modeling microRNA Expression Quantitative Trait Loci.

Extensive work has been dedicated to study mechanisms of microRNA-mediated gene regulation. However, the transcriptional regulation of microRNAs themselves is far less well understood, due to difficulties determining the transcription start sites of transient primary transcripts. This challenge can be addressed using expression quantitative trait loci (eQTLs) whose regulatory effects represent a natural source of perturbation of cis-regulatory elements. Here we used previously published cis-microRNA-eQTL data for the human GM12878 cell line, promoter predictions, and other functional annotations to determine the relationship between functional elements and microRNA regulation. We built a logistic regression model that classifies microRNA/SNP pairs into eQTLs or non-eQTLs with 85% accuracy; shows microRNA-eQTL enrichment for microRNA precursors, promoters, enhancers, and transcription factor binding sites; and depletion for repressed chromatin. Interestingly, although there is a large overlap between microRNA eQTLs and messenger RNA eQTLs of host genes, 74% of these shared eQTLs affect microRNA and host expression independently. Considering microRNA-only eQTLs we find a significant enrichment for intronic promoters, validating the existence of alternative promoters for intragenic microRNAs. Finally, in line with the GM12878 cell line derived from B cells, we find genome-wide association (GWA) variants associated to blood-related traits more likely to be microRNA eQTLs than random GWA and non-GWA variants, aiding the interpretation of GWA results.

Transcription factor‑microRNA synergistic regulatory network revealing the mechanism of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is the most common type of endocrine disorder, affecting 5–11% of women of reproductive age worldwide. Transcription factors (TFs) and microRNAs are considered to have crucial roles in the developmental process of several diseases and have synergistic regulatory actions. However, the effects of TFs and microRNAs, and the patterns of their cooperation in the synergistic regulatory network of PCOS, remain to be elucidated. The present study aimed to determine the possible mechanism of PCOS, based on a TF-microRNA synergistic regulatory network. Initially, the differentially expressed genes (DEGs) in PCOS were identified using microarray data of the GSE34526 dataset. Subsequently, the TFs and microRNAs which regulated the DEGs of PCOS were identified, and a PCOS-associated TF-microRNA synergistic regulatory network was constructed. This network included 195 DEGs, 136 TFs and 283 microRNAs, and the DEGs were regulated by TFs and microRNAs. Based on topological and functional enrichment analyses, SP1, mir-355-5p and JUN were identified as potentially crucial regulators in the development of PCOS and in characterizing the regulatory mechanism. In conclusion, the TF-microRNA synergistic regulatory network constructed in the present study provides novel insight on the molecular mechanism of PCOS in the form of synergistic regulated model.

On the evolution of developmental mechanisms: Divergent polarities in leaf growth as a case study

ABSTRACTMost model plants used to study leaf growth share a common developmental mechanism, namely basipetal growth polarity, wherein the distal end differentiates first with progressively more proliferative cells toward the base. Therefore, this base-to-tip growth pattern has served as a paradigm to explain leaf growth and also formed the basis for several computational models. However, our recent report in The Plant Cell on the investigation of leaf growth in 75 eudicot species covering a wide range of eudicot families showed that leaves grow with divergent polarities in the proximo-distal axis or without any obvious polarity. This divergence in growth polarity is linked to the expression divergence of a conserved microRNA-transcription factor module. This study raises several questions on the evolutionary origin of leaf growth pattern, such as ‘when and why in evolution did the divergent growth polarities arise?’ and ‘what were the molecular changes that led to this divergence?’. Here, we discuss a few of these questions in some detail.

Construction and analysis of the regulatory network disturbed by the silenced Sp1 transcription factor in HeLa cells.

The objective of our study was to explore the characteristics of the regulatory network after siRNA-Sp1 (Specificity Protein 1) treatment in HeLa cells through the regulation network construction with bioinformatics methods. Using GSE37935 datasets downloaded from Gene Expression Omnibus data, the differentially expressed genes (DEGs) were screened out by the limma package in R software. Combining the DEGs with the data from the microRNA (miRNA) databases and transcription factor databases, an integrated regulatory network was established with Cytoscape. Then the motifs in the network were examined by FANMOD. A total of 708 DEGs were screened, and a regulatory network consisting of 585 nodes and 1070 edges was constructed. By analyzing the two modules extracted from the network, we found that the most significant biological processes were cell cycle and apoptosis, some significant DEGs among them were CDKN1A, CUL5, and EGFR. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis discovered that DEGs, including EGFR, CDKN1A, RRM2B, and GADD45B, were significantly enriched in glioma pathway and p53 signaling pathway. While Sp1 was silenced by siRNA, the regulatory network in HeLa cells changed a lot. Genes related to cell cycle and apoptosis in the cell nucleus were dysregulated and the p53 signaling pathway was disturbed.