scholarly journals Genomic analyses identify significant processes in BCL11B-deficient aorta

2021 ◽  
Author(s):  
Tingting Zhang ◽  
Jing Wang ◽  
Mengyao Wang ◽  
Min Zhang ◽  
Hanming Gu
Keyword(s):  
Blood Pressure ◽  
Transcription Factor ◽  
Calcium Signaling ◽  
Signaling Pathways ◽  
Mus Musculus ◽  
Contractile Properties ◽  
Rna Seq ◽  
Resistance Vessels ◽  
Genomic Analyses

BCL11B is a transcription factor, which contains profound effects on the aorta, contractile properties of resistance vessels, and blood pressure. However, the mechanism of how BCL11B regulates the aorta function is not fully understood. In this study, our study is to identify the key molecules and signaling pathways by analyzing the RNA-seq data. The GSE163551 was produced by the Illumina NextSeq 500 (Mus musculus). The KEGG and GO analyses showed the ribosome and calcium signaling pathways are the main processes during the BCL11B knockout. Moreover, we determined ten key molecules including RPS11, GATA4, RPS13, RPL9, RPL27A, RPS24, RPL23A, RPL37A, BMP4, RPS7. Thus, our study may provide novel knowledge of the BCL11B regulated aorta.

scholarly journals Synergistic Network Pharmacology for Traditional Chinese Medicine Liangxue Tongyu Formula in Acute Intracerebral Hemorrhagic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Yang Chen ◽  
Ju Dong ◽  
Dongqing Yang ◽  
Qin Qian ◽  
Pengcheng Wang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Rna Seq ◽  
Anti Inflammatory

Background. Nowadays, acute intracerebral hemorrhage stroke (AICH) still causes higher mortality. Liangxue Tongyu Formula (LXTYF), originating from a traditional Chinese medicine (TCM) prescription, is widely used as auxiliary treatment for AICH. Objective. To dig into the multicomponent, multitarget, and multipathway mechanism of LXTYF on treating AICH via network pharmacology and RNA-seq. Methods. Network pharmacology analysis was used by ingredient collection, target exploration and prediction, network construction, and Gene Ontology (GO) and KEGG analysis, with the Cytoscape software and ClusterProfiler package in R. The RNA-seq data of the AICH-rats were analyzed for differential expression and functional enrichments. Herb-Compound-Target-Pathway (H-C-T-P) network was shown to clarify the mechanism of LXTYF for AICH. Results. 76 active ingredients (quercetin, Alanine, kaempferol, etc.) of LXTYF and 376 putative targets to alleviate AICH (PTGS2, PTGS1, ESR1, etc.) were successfully identified. The protein-protein interaction (PPI) network indicated the important role of STAT3. The functional enrichment of GO and KEGG pathway showed that LXTYF is most likely to influence MAPK and PI3K-Akt signaling pathways for AICH treatment. From the RNA-seq of AICH-rats, 583 differential mRNAs were identified and 14 of them were consistent with the putative targets of LXTYF for AICH treatment. The KEGG pathway enrichment also implied that the MAPK signaling pathway was the most correlated one among all the related signaling pathways. Many important targets with expression changes of LXTYF for AICH treatment and their related pathways are great markers of antioxidation, anti-inflammatory, antiapoptosis, and lowering blood pressure, which indicated that LXTYF may play mutiroles in the mechanisms for AICH treatment. Conclusion. The LXTYF attenuates AICH partially by antioxidation, anti-inflammatory, and antiapoptosis and lowers blood pressure roles through regulating the targets involved MAPK, calcium, apoptosis, and TNF signaling pathway, which provide notable clues for further experimental validation.

Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Signaling Pathways ◽  
Underlying Mechanism ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Gastrointestinal Cancers ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

scholarly journals Transcriptome profiling of developing leaf and shoot apices to reveal the molecular mechanism and co-expression genes responsible for the wheat heading date

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuxin Yang ◽  
Xueying Zhang ◽  
Lifen Wu ◽  
Lichao Zhang ◽  
Guoxiang Liu ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Flowering Time ◽  
Heading Date ◽  
Yield Component ◽  
Potential Candidate ◽  
Rna Seq ◽  
Nucleotide Synthesis ◽  
Light Reaction ◽  
Grain Number Per Spike ◽  
Double Ridge

Abstract Background Wheat is one of the most widely planted crops worldwide. The heading date is important for wheat environmental adaptability, as it not only controls flowering time but also determines the yield component in terms of grain number per spike. Results In this research, homozygous genotypes with early and late heading dates derived from backcrossed progeny were selected to conduct RNA-Seq analysis at the double ridge stage (W2.0) and androgynous primordium differentiation stage (W3.5) of the leaf and apical meristem, respectively. In total, 18,352 differentially expressed genes (DEGs) were identified, many of which are strongly associated with wheat heading date genes. Gene Ontology (GO) enrichment analysis revealed that carbohydrate metabolism, trehalose metabolic process, photosynthesis, and light reaction are closely related to the flowering time regulation pathway. Based on MapMan metabolic analysis, the DEGs are mainly involved in the light reaction, hormone signaling, lipid metabolism, secondary metabolism, and nucleotide synthesis. In addition, 1,225 DEGs were annotated to 45 transcription factor gene families, including LFY, SBP, and MADS-box transcription factors closely related to flowering time. Weighted gene co-expression network analysis (WGCNA) showed that 16, 336, 446, and 124 DEGs have biological connections with Vrn1-5 A, Vrn3-7B, Ppd-1D, and WSOC1, respectively. Furthermore, TraesCS2D02G181400 encodes a MADS-MIKC transcription factor and is co-expressed with Vrn1-5 A, which indicates that this gene may be related to flowering time. Conclusions RNA-Seq analysis provided transcriptome data for the wheat heading date at key flower development stages of double ridge (W2.0) and androgynous primordium differentiation (W3.5). Based on the DEGs identified, co-expression networks of key flowering time genes in Vrn1-5 A, Vrn3-7B, WSOC1, and Ppd-1D were established. Moreover, we discovered a potential candidate flowering time gene, TraesCS2D02G181400. Taken together, these results serve as a foundation for further study on the regulatory mechanism of the wheat heading date.

scholarly journals Challenges with Methods for Detecting and Studying the Transcription Factor Nuclear Factor Kappa B (NF-κB) in the Central Nervous System

Cells ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1335
Author(s):  
Marina Mostafizar ◽  
Claudia Cortes-Pérez ◽  
Wanda Snow ◽  
Jelena Djordjevic ◽  
Aida Adlimoghaddam ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Signaling Pathways ◽  
Quantitative Methods ◽  
Nuclear Factor Kappa B ◽  
Inflammatory Responses ◽  
Nuclear Factor ◽  
Nuclear Factor Kappa ◽  
Regulated Gene Expression ◽  
Transcription Factor Nuclear Factor

The transcription factor nuclear factor kappa B (NF-κB) is highly expressed in almost all types of cells. NF-κB is involved in many complex biological processes, in particular in immunity. The activation of the NF-κB signaling pathways is also associated with cancer, diabetes, neurological disorders and even memory. Hence, NF-κB is a central factor for understanding not only fundamental biological presence but also pathogenesis, and has been the subject of intense study in these contexts. Under healthy physiological conditions, the NF-κB pathway promotes synapse growth and synaptic plasticity in neurons, while in glia, NF-κB signaling can promote pro-inflammatory responses to injury. In addition, NF-κB promotes the maintenance and maturation of B cells regulating gene expression in a majority of diverse signaling pathways. Given this, the protein plays a predominant role in activating the mammalian immune system, where NF-κB-regulated gene expression targets processes of inflammation and host defense. Thus, an understanding of the methodological issues around its detection for localization, quantification, and mechanistic insights should have a broad interest across the molecular neuroscience community. In this review, we summarize the available methods for the proper detection and analysis of NF-κB among various brain tissues, cell types, and subcellular compartments, using both qualitative and quantitative methods. We also summarize the flexibility and performance of these experimental methods for the detection of the protein, accurate quantification in different samples, and the experimental challenges in this regard, as well as suggestions to overcome common challenges.

scholarly journals EPEN-30. C11ORF95-RELA FUSION PROTEIN ENGAGES NOVEL GENOMIC LOCI TO DRIVE MURINE EPENDYMOMA GROWTH

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii314-iii314
Author(s):  
Amir Arabzade ◽  
Yanhua Zhao ◽  
Srinidhi Varadharajan ◽  
Hsiao-Chi Chen ◽  
Austin Stuckert ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Molecular Targets ◽  
Lead Target ◽  
Open Chromatin ◽  
Rna Seq ◽  
In Utero Electroporation ◽  
Pathway Activation ◽  
Mouse Cells ◽  
Shed Light

Abstract RATIONALE Over 70% of supratentorial (ST) ependymoma are characterized by an oncogenic fusion between C11ORF95 and RELA. C11ORF95-RELA fusion is frequently the sole genetic driver detected in ST ependymoma, thus ranking this genomic event as a lead target for therapeutic investigation. RELA is a transcription factor (TF) central to mediating NF-kB pathway activation in processes such as inflammation, cellular metabolism, and chemotaxis. HYPOTHESIS: We posited that C11ORF95-RELA acts as an oncogenic TF that aberrantly shapes the tumor epigenome to drive aberrant transcription. Approach: To this end we developed an in utero electroporation (IUE) mouse model of ependymoma to express C11ORF95-RELA during embryonic development. Our IUE approach allowed us to develop C11ORF95-RELA driven tumor models and cell lines. We comprehensively characterized the epigenome and transcriptome of C11ORF95-RELA fusion driven mouse cells by H3K27ac ChIP-seq, ATAC-seq, and RNA-seq. RESULTS This data revealed that: 1) C11ORF95-RELA directly engages ‘open’ chromatin and is enriched at regions with known RELA TF binding sites as well as novel genomic loci/motifs, 2) C11ORF95-RELA preferentially binds to both H3K27ac (active) enhancers and promoters, and 3) Bound C11ORF95-RELA promoter loci are associated with increased transcription of genes shared with human ependymoma. CONCLUSION Our findings shed light on the transcriptional mechanisms of C11ORF95-RELA, and reveal downstream targets that may represent cancer dependency genes and molecular targets.

scholarly journals Identification of Potential Key lncRNAs in the Context of Mouse Myeloid Differentiation by Systematic Transcriptomics Analysis

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 630
Author(s):  
Yongqing Lan ◽  
Meng Li ◽  
Shuangli Mi
Keyword(s):  
Transcription Factor ◽  
Cell Model ◽  
Myeloid Differentiation ◽  
Rna Seq ◽  
Hematopoietic Differentiation ◽  
Granulocytic Differentiation ◽  
Expression Of Genes ◽  
Non Coding Rnas

Hematopoietic differentiation is a well-orchestrated process by many regulators such as transcription factor and long non-coding RNAs (lncRNAs). However, due to the large number of lncRNAs and the difficulty in determining their roles, the study of lncRNAs is a considerable challenge in hematopoietic differentiation. Here, through gene co-expression network analysis over RNA-seq data generated from representative types of mouse myeloid cells, we obtained a catalog of potential key lncRNAs in the context of mouse myeloid differentiation. Then, employing a widely used in vitro cell model, we screened a novel lncRNA, named Gdal1 (Granulocytic differentiation associated lncRNA 1), from this list and demonstrated that Gdal1 was required for granulocytic differentiation. Furthermore, knockdown of Cebpe, a principal transcription factor of granulocytic differentiation regulation, led to down-regulation of Gdal1, but not vice versa. In addition, expression of genes involved in myeloid differentiation and its regulation, such as Cebpa, were influenced in Gdal1 knockdown cells with differentiation blockage. We thus systematically identified myeloid differentiation associated lncRNAs and substantiated the identification by investigation of one of these lncRNAs on cellular phenotype and gene regulation levels. This study promotes our understanding of the regulation of myeloid differentiation and the characterization of roles of lncRNAs in hematopoietic system.

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