Regulatory Mechanisms
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2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Shi-jin Liu ◽  
Ya-bing Yang ◽  
Jia-xin Zhou ◽  
Yu-jian Lin ◽  
Yun-long Pan ◽  
...  

Background. Gastric cancer (GC) is the third leading cause of cancer death worldwide with complicated molecular and cellular heterogeneity. Iron metabolism and ferroptosis play crucial roles in the pathogenesis of GC. However, the prognostic role and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in GC still remains to be clarified. Methods. We comprehensively analyzed the prognosis of different expression FRGs, based on gastric carcinoma patients in the TCGA cohort. The functional enrichment and immune microenvironment associated with these genes in gastric cancer were investigated. The prognostic model was constructed to clarify the relation between FRGs and the prognosis of GC. Meanwhile, the ceRNA network of FRGs in the prognostic model was performed to explore the regulatory mechanisms. Results. Gastric carcinoma patients were classified into the A, B, and C FRGClusters with different features based on 19 prognostic ferroptosis-related differentially expressed genes in the TCGA database. To quantify the FRG characteristics of individual patients, FRGScore was constructed. And the research shows the GC patients with higher FRGScore had worse survival outcome. Moreover, thirteen prognostic ferroptosis-related differentially expressed genes (DEGs) were selected to construct a prognostic model for GC survival outcome with a superior accuracy in this research. And we also found that FRG RiskScore can be an independent biomarker for the prognosis of GC patients. Interestingly, GC patients with lower RiskScore had less immune dysfunction and were more likely to respond to immunotherapy according to TIDE value analysis. Finally, a ceRNA network based on FRGs in the prognostic model was analyzed to show the concrete regulation mechanisms. Conclusions. The ferroptosis-related gene risk signature has a superior potent in predicting GC prognosis and acts as the biomarkers for immunotherapy, which may provide a reference in clinic.


2021 ◽  
Vol 65 (4) ◽  
Author(s):  
Huyi Liu ◽  
Xiangdao Cai ◽  
Jia Liu ◽  
Fengxiang Zhang ◽  
Andong He ◽  
...  

Preeclampsia (PE) is one of the leading causes of maternal morbidity and mortality in pregnant women. This study aimed to investigate the potential impact and regulatory mechanisms of bone morphogenetic protein receptor 2 (BMPR2) on the progression of PE. We obtained placental tissues from pregnant women with PE and normal pregnant women, and the results showed that BMPR2 was expressed at low levels in the tissue from PE women. Genetic knockdown of BMPR2 increased the proliferation and invasion of cultured trophoblast cells, whereas its overexpression reduced these characteristics. Bioinformatics analysis and luciferase reporter gene assays confirmed that BMPR2 is a direct target of miR-21. Overexpression of a miR-21 inhibitor promoted the growth and invasiveness of trophoblast cells, whereas the opposite results were observed for the miR-21 mimic. Furthermore, miR-21 was sponged by the lncRNA MEG3, and shRNA inhibition of MEG3 reduced trophoblast cell growth and invasiveness. miR-21 was upregulated in the tissues from PE women, whereas MEG3 was downregulated, and the two were negatively correlated. Collectively, this study demonstrates that the lncRNA MEG3 acts as a sponge for miR-21, which regulates BMPR2 expression and promotes trophoblast cell proliferation and invasiveness, thereby preventing the development of PE. These findings provide novel insight into a targeted therapy that could be used to treat or prevent the development of PE.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthew A. Scott ◽  
Amelia R. Woolums ◽  
Cyprianna E. Swiderski ◽  
Andy D. Perkins ◽  
Bindu Nanduri

AbstractBovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms. Our objective was to apply ML models to lung and immunological tissue datasets acquired from previous clinical BRD experiments to identify genes that classify disease with high accuracy. Raw mRNA sequencing reads from 151 bovine datasets (n = 123 BRD, n = 28 control) were downloaded from NCBI-GEO. Quality filtered reads were assembled in a HISAT2/Stringtie2 pipeline. Raw gene counts for ML analysis were normalized, transformed, and analyzed with MLSeq, utilizing six ML models. Cross-validation parameters (fivefold, repeated 10 times) were applied to 70% of the compiled datasets for ML model training and parameter tuning; optimized ML models were tested with the remaining 30%. Downstream analysis of significant genes identified by the top ML models, based on classification accuracy for each etiological association, was performed within WebGestalt and Reactome (FDR ≤ 0.05). Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation models identified 154 and 195 significant genes for IBR and BRSV, respectively; from these genes, the two ML models discriminated IBR and BRSV with 100% accuracy compared to sham controls. Significant genes classified by the top ML models in IBR (154) and BRSV (195), but not BVDV (74), were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not homogenized lung tissue. Genes identified in Mannheimia haemolytica infections (97) were involved in activating classical and alternative pathways of complement. Novel findings, including expression of genes related to reduced mitochondrial oxygenation and ATP synthesis in consolidated lung tissue, were discovered. Genes identified in each analysis represent distinct genomic events relevant to understanding and predicting clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support the prediction and understanding of clinical BRD.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mayuko Kawamoto ◽  
Yuu Ishii ◽  
Masakado Kawata

Abstract Background To understand the evolutionary significance of female mate choice for colorful male ornamentation, the underlying regulatory mechanisms of such ornamentation must be understood for examining how the ornaments are associated with “male qualities” that increase the fitness or sexual attractiveness of offspring. In the guppy (Poecilia reticulata), an established model system for research on sexual selection, females prefer males possessing larger and more highly saturated orange spots as potential mates. Although previous studies have identified some chromosome regions and genes associated with orange spot formation, the regulation and involvement of these genetic elements in orange spot formation have not been elucidated. In this study, the expression patterns of genes specific to orange spots and certain color developmental stages were investigated using RNA-seq to reveal the genetic basis of orange spot formation. Results Comparing the gene expression levels of male guppy skin with orange spots (orange skin) with those without any color spots (dull skin) from the same individuals identified 1102 differentially expressed genes (DEGs), including 630 upregulated genes and 472 downregulated genes in the orange skin. Additionally, the gene expression levels of the whole trunk skin were compared among the three developmental stages and 2247 genes were identified as DEGs according to color development. These analyses indicated that secondary differentiation of xanthophores may affect orange spot formation. Conclusions The results suggested that orange spots might be formed by secondary differentiation, rather than de novo generation, of xanthophores, which is induced by Csf1 and thyroid hormone signaling pathways. Furthermore, we suggested candidate genes associated with the areas and saturation levels of orange spots, which are both believed to be important for female mate choice and independently regulated. This study provides insights into the genetic and cellular regulatory mechanisms underlying orange spot formation, which would help to elucidate how these processes are evolutionarily maintained as ornamental traits relevant to sexual selection.


2021 ◽  
Author(s):  
Jibo Zhang ◽  
Aakanksha Gundu ◽  
Brian D. Strahl

How transcription programs rapidly adjust to changing metabolic and cellular cues remains poorly defined. Here, we reveal a function for the Yaf9 component of the SWR1-C and NuA4 chromatin regulatory complexes in maintaining timely transcription of metabolic genes across the yeast metabolic cycle (YMC). By reading histone acetylation during the oxidative and respiratory phase of the YMC, Yaf9 recruits SWR1-C and NuA4 complexes to deposit H2A.Z and acetylate H4, respectively. Increased H2A.Z and H4 acetylation during the oxidative phase promotes transcriptional initiation and chromatin machinery occupancy and is associated with reduced RNA polymerase II levels at genes—a pattern reversed during transition from oxidative to reductive metabolism. Prevention of Yaf9-H3 acetyl reading disrupted this pattern of transcriptional and chromatin regulator recruitment and impaired the timely transcription of metabolic genes. Together, these findings reveal that Yaf9 contributes to a dynamic chromatin and transcription initiation factor signature that is necessary for the proper regulation of metabolic gene transcription during the YMC. They also suggest that unique regulatory mechanisms of transcription exist at distinct metabolic states.


2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ya-bing Yang ◽  
Jia-xin Zhou ◽  
Sheng-hui Qiu ◽  
Jia-shuai He ◽  
Jing-hua Pan ◽  
...  

Background. Colorectal cancer (CRC) is the third most common malignancies worldwide. Ferroptosis is a programmed, iron-dependent cell death observed in cancer cells. However, the prognostic potential and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in CRC patients remains to be clarified. Methods. At first, we comprehensively analysed the different expression and prognosis of related FRGs in CRC patients based on TCGA cohort. The relationship between functional enrichment of these genes and immune microenvironment in CRC was investigated using the TCGA database. Prognostic model was constructed to determine the association between FRGs and the prognosis of CRC. Relative verification was done based on the GEO database. Meanwhile, the ceRNA network of FRGs in the model was also performed to explore the regulatory mechanisms. Results. Eight differentially expressed FRGs were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the A, B, and C FRG clusters with different features. And FRG scores were constructed to quantify the FRG pattern of individual patients with colorectal cancer. The CRC patients with higher FRG score showed worse survival outcomes, higher immune dysfunction, and lower response to immunotherapy. The prognostic model showed a high accuracy for predicting the OS of CRC. Finally, a ceRNA network was analysed to show the concrete regulation mechanisms of critical FRGs in CRC. Conclusions. The FRG risk score prognostic model based on 8 FRGs exhibit superior predictive performance, providing a novel prognostic model with a high accuracy for CRC patients. Moreover, FRG score can be the potential biomarker of the response of immunotherapy for CRC.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mehmet Can Uçar ◽  
Dmitrii Kamenev ◽  
Kazunori Sunadome ◽  
Dominik Fachet ◽  
Francois Lallemend ◽  
...  

AbstractBranching morphogenesis governs the formation of many organs such as lung, kidney, and the neurovascular system. Many studies have explored system-specific molecular and cellular regulatory mechanisms, as well as self-organizing rules underlying branching morphogenesis. However, in addition to local cues, branched tissue growth can also be influenced by global guidance. Here, we develop a theoretical framework for a stochastic self-organized branching process in the presence of external cues. Combining analytical theory with numerical simulations, we predict differential signatures of global vs. local regulatory mechanisms on the branching pattern, such as angle distributions, domain size, and space-filling efficiency. We find that branch alignment follows a generic scaling law determined by the strength of global guidance, while local interactions influence the tissue density but not its overall territory. Finally, using zebrafish innervation as a model system, we test these key features of the model experimentally. Our work thus provides quantitative predictions to disentangle the role of different types of cues in shaping branched structures across scales.


2021 ◽  
Author(s):  
junyao jiang ◽  
Seth Blackshaw ◽  
Jiang Qian ◽  
Jie Wang

While single-cell RNA sequencing (scRNA-seq) is widely used to profile gene expression, few methods are available to infer gene regulatory networks using scRNA-seq data. Here, we developed and extended IReNA (Integrated Regulatory Network Analysis) to perform regulatory network analysis using scRNA-seq profiles. Four features are developed for IReNA. First, regulatory networks are divided into different modules which represent distinct biological functions. Second, transcription factors significantly regulating each gene module can be identified. Third, regulatory relationships among modules can be inferred. Fourth, IReNA can integrate ATAC-seq data into regulatory network analysis. If ATAC-seq data is available, both transcription factor footprints and binding motifs are used to refine regulatory relationships among co-expressed genes. Using public datasets, we showed that integrated network analysis of scRNA-seq data with ATAC-seq data identified a higher fraction of known regulators than scRNA-seq data alone. Moreover, IReNA provided a better performance of network analysis than currently available methods. Beyond the reconstruction of regulatory networks, IReNA can modularize regulatory networks, and identify key regulators and significant regulatory relationships for modules, facilitating the systems-level understanding of biological regulatory mechanisms. The R package IReNA is available at https://github.com/jiang-junyao/IReNA.


2021 ◽  
Author(s):  
Shelsa S. Marcel ◽  
Austin L. Quimby ◽  
Melodie P. Noel ◽  
Oscar C. Jaimes ◽  
Marjan Mehrab-Mohseni ◽  
...  

Chromatin accessibility states that influence gene expression and other nuclear processes can be altered in disease. The constellation of transcription factors and chromatin regulatory complexes in cells results in characteristic patterns of chromatin accessibility. The study of these patterns in tissues has been limited because existing chromatin accessibility assays are ineffective for archival formalin-fixed, paraffin-embedded (FFPE) tissues. We have developed a method to efficiently extract intact chromatin from archival tissue via enhanced cavitation with a nanodroplet reagent consisting of a lipid shell with a liquid perfluorocarbon core. Inclusion of nanodroplets during the extraction of chromatin from FFPE tissues enhances the recovery of intact accessible and nucleosome-bound chromatin. We show that the addition of nanodroplets to the chromatin accessibility assay formaldehyde-assisted isolation of regulatory elements (FAIRE), does not affect the accessible chromatin signal. Applying the technique to FFPE human tumor xenografts, we identified tumor-relevant regions of accessible chromatin shared with those identified in primary tumors. Further, we deconvoluted non-tumor signal to identify cellular components of the tumor microenvironment. Incorporation of this method of enhanced cavitation into FAIRE offers the potential for extending chromatin accessibility to clinical diagnosis and personalized medicine, while also enabling the exploration of gene regulatory mechanisms in archival samples.


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