scholarly journals BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Dengwei Zhang ◽  
Si Zhou ◽  
Ziheng Zhou ◽  
Xiaosen Jiang ◽  
Dongsheng Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Birth Defects ◽  
Birth Defect ◽  
Infant Health ◽  
Expression Patterns ◽  
Gene Expression Omnibus ◽  
Omics Data ◽  
Chromatin Immunoprecipitation Sequencing ◽  
Underlying Mechanisms ◽  
User Friendly

Abstract Background Birth defects pose a major challenge to infant health. Thus far, however, the causes of most birth defects remain cryptic. Over the past few decades, considerable effort has been expended on disclosing the underlying mechanisms related to birth defects, yielding myriad treatises and data. To meet the increasing requirements for data resources, we developed a freely accessible birth defect multi-omics database (BDdb, http://t21omics.cngb.org) consisting of multi-omics data and potential disease biomarkers. Results In total, omics datasets from 136 Gene Expression Omnibus (GEO) Series records, including 5245 samples, as well as 869 biomarkers of 22 birth defects in six different species, were integrated into the BDdb. The database provides a user-friendly interface for searching, browsing, and downloading data of interest. The BDdb also enables users to explore the correlations among different sequencing methods, such as chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq) from different studies, to obtain the information on gene expression patterns from diverse aspects. Conclusion To the best of our knowledge, the BDdb is the first comprehensive database associated with birth defects, which should benefit the diagnosis and prevention of birth defects.

scholarly journals BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data

2020 ◽  
Author(s):  
Dengwei Zhang ◽  
Hai-Xi Sun ◽  
Ziheng Zhou ◽  
Xiaosen Jiang ◽  
Dongsheng Chen ◽  
...  
Keyword(s):  
Birth Defects ◽  
Birth Defect ◽  
High Throughput Sequencing ◽  
Infant Health ◽  
Data Sets ◽  
Omics Data ◽  
Related Data ◽  
Circulating Free Dna ◽  
The World ◽  
Next Generation Sequencing Ngs

ABSTRACTBirth defect, not only poses a major challenge for infant health but also attracts the attention of countless people in the world. Chromosome abnormality directly results in diverse birth defects which are generally deleterious and even lethal. Therefore, gaining molecular regulatory insights into these diseases is important and necessary for effective prenatal screening. Recently, with the advance of next-generation sequencing (NGS) techniques, a myriad of treatises and data associated with these diseases are now constantly produced from different laboratories across the world. To meet the increasing requirements for birth-related data resources, we developed a birth defect multi-omics database (BDdb), freely accessible at http://t21omics.cngb.org and consisting of multi-omics data, circulating free DNA (cfDNA) data, as well as diseases biomarkers. Omics data sets from 138 GSE samples, 5271 GSM samples and 328 entries, and more than 2000 biomarkers of 22 birth-defect diseases in 5 different species were integrated into BDdb, which provides a user-friendly interface for searching, browsing and downloading selected data. Additionally, we re-analyzed and normalized the raw data so that users can also customize the analysis using the data generated from different sources or different High-Throughput Sequencing (HTS) methods. To our knowledge, BDdb is the first comprehensive database associated with birth-defect-related diseases. which would benefit the diagnosis and prevention of birth defects.

scholarly journals Biochat: a database for natural language processing of Gene Expression Omnibus data

2018 ◽  
Author(s):  
Bohdan B. Khomtchouk ◽  
Vsevolod Dyomkin ◽  
Kasra A. Vand ◽  
Themistocles Assimes ◽  
Or Gozani
Keyword(s):  
Gene Expression ◽  
Language Processing ◽  
Web Application ◽  
Gene Expression Omnibus ◽  
Omics Data ◽  
Textual Information ◽  
Link Type ◽  
Different Types ◽  
User Friendly ◽  
Omics Data Integration

AbstractA biological dataset’s metadata profile (e.g., study description, organism name, sequencing type, etc.) typically contains terse but descriptive textual information that can be used to link it with other similar biological datasets for the purpose of integrating omics data of different types to inform hypotheses and biological questions. Here we present Biochat, a database containing a multi-omics data integration support system to aid in cross-linking Gene Expression Omnibus (GEO) records to each other by metadata similarity through a user-friendly web application. Biochat is publicly available at: http://www.biochat.ai. Biochat source code is hosted at: https://github.com/Bohdan-Khomtchouk/Bio-chat.Database URLhttps://github.com/Bohdan-Khomtchouk/Bio-chat

scholarly journals CircFAM13B promotes the proliferation of hepatocellular carcinoma by sponging miR-212, upregulating E2F5 expression and activating the P53 pathway

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Xie ◽  
Xiaofeng Hang ◽  
Wensheng Xu ◽  
Jing Gu ◽  
Yuanjing Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
In Vivo Studies ◽  
Circular Rnas ◽  
Novel Target ◽  
Underlying Mechanisms

Abstract Background Most of the biological functions of circular RNAs (circRNAs) and the potential underlying mechanisms in hepatocellular carcinoma (HCC) have not yet been discovered. Methods In this study, using circRNA expression data from HCC tumor tissues and adjacent tissues from the Gene Expression Omnibus database, we identified out differentially expressed circRNAs and verified them by qRT-PCT. Functional experiments were performed to evaluate the effects of circFAM13B in HCC in vitro and in vivo. Results We found that circFAM13B was the most significantly differentially expressed circRNA in HCC tissue. Subsequently, in vitro and in vivo studies also demonstrated that circFAM13B promoted the proliferation of HCC. Further studies revealed that circFAM13B, a sponge of miR-212, is involved in the regulation of E2F5 gene expression by competitively binding to miR-212, inhibits the activation of the P53 signalling pathway, and promotes the proliferation of HCC cells. Conclusions Our findings revealed the mechanism underlying the regulatory role played by circFAM13B, miR-212 and E2F5 in HCC. This study provides a new theoretical basis and novel target for the clinical prevention and treatment of HCC.

A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Submandibular Salivary Gland ◽  
Data Sets ◽  
Control Mechanisms ◽  
Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

scholarly journals Mechanisms driving endosperm-based hybrid incompatibilities: insights from hybrid monkeyflowers

2018 ◽  
Author(s):  
Taliesin J. Kinser ◽  
Ronald D. Smith ◽  
Amelia H. Lawrence ◽  
Arielle M. Cooley ◽  
Mario Vallejo-Marin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genomic Imprinting ◽  
Parental Species ◽  
Expression Patterns ◽  
Naturally Occurring ◽  
Epigenetic Phenomenon ◽  
Underlying Mechanisms ◽  
Methylation Patterns ◽  
Regulatory Landscapes ◽  
Interspecies Hybrid

ABSTRACTAngiosperm endosperm requires genomic and epigenomic interactions between maternal and paternal genomes for proper seed development. Genomic imprinting, an epigenetic phenomenon where the expression of certain genes is predominantly contributed by one parent, is an essential part of this process and unique to endosperm. Perturbation of imprinting can be fatal to developing seeds, and can be caused by interspecific or interploidy hybridization. However, underlying mechanisms driving these endosperm-based hybridization barriers are not well understood or described. Here we investigate the consequences of genomic imprinting in a naturally occurring interploidy and interspecies hybrid between the diploid, Mimulus guttatus, and the allotetraploid (with two subgenomes), M. luteus (Phrymaceae). We find that the two parental species differ in patterns of DNA methylation, gene expression, and imprinting. Hybrid crosses in both directions, which suffer from endosperm abnormalities and decreased germination rates, display altered methylation patterns compared to parent endosperm. Furthermore, imprinting and expression patterns appear perturbed in hybrid endosperm, where we observe global expression dominance of each of the two M. luteus subgenomes, which share similar expression patterns, over the M. guttatus genome, regardless of crossing direction. We suggest that epigenetic repatterning within the hybrid may drive global shifts in expression patterns and be the result of diverged epigenetic/regulatory landscapes between parental genomes. This may either establish or exacerbate dosage-based epistatic incompatibilities between the specific imprinting patterns that have diverged between parental species, thus driving potentially rapid endosperm-based hybridization barriers.

scholarly journals hTFtarget: a comprehensive database for regulations of human transcription factors and their targets

2019 ◽  
Author(s):  
Qiong Zhang
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Dna Sequences ◽  
Chromatin Immunoprecipitation ◽  
Target Genes ◽  
Gene Expression Regulation ◽  
Epigenetic Modification ◽  
Wide Range ◽  
Chromatin Immunoprecipitation Sequencing ◽  
User Friendly

Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of Chromatin immunoprecipitation sequencing (ChIP-Seq) provides great opportunities to discover the TF-target regulations across different conditions. In this study, we constructed a database named hTFtarget, which integrated huge human TF target resources (7,190 ChIP-Seq samples of 659 TFs and high confident TF binding sites of 699 TFs) and epigenetic modification information to predict accurate TF-target regulations. hTFtarget offers the following functions for users to explore TF-target regulations: 1) Browse or search general targets of a query TF across datasets; 2) Browse TF-target regulations for a query TF in a specific dataset or tissue; 3) Search potential TFs for a given target gene or ncRNA; 4) Investigate co-association between TFs in cell lines; 5) Explore potential co-regulations for given target genes or TFs; 6) Predict candidate TFBSs on given DNA sequences; 7) View ChIP-Seq peaks for different TFs and conditions in genome browser. hTFtarget provides a comprehensive, reliable and user-friendly resource for exploring human TF-target regulations, which will be very useful for a wide range of users in the TF and gene expression regulation community. hTFtarget is available at http://bioinfo.life.hust.edu.cn/hTFtarget.

scholarly journals Bioinformatics Analysis Reveals Most Prominent Gene Candidates to Distinguish Colorectal Adenoma from Adenocarcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Nina Hauptman ◽  
Emanuela Boštjančič ◽  
Margareta Žlajpah ◽  
Branislava Ranković ◽  
Nina Zidar
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Colorectal Adenoma ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Normal Mucosa ◽  
Gene Expression Omnibus ◽  
Colorectal Adenomas ◽  
Screening Programs

Colorectal cancer (CRC) is one of the leading causes of death by cancer worldwide. Bowel cancer screening programs enable us to detect early lesions and improve the prognosis of patients with CRC. However, they also generate a significant number of problematic polyps, e.g., adenomas with epithelial misplacement (pseudoinvasion) which can mimic early adenocarcinoma. Therefore, biomarkers that would enable us to distinguish between adenoma with epithelial misplacement (pseudoinvasion) and adenoma with early adenocarcinomas (true invasion) are needed. We hypothesized that the former are genetically similar to adenoma and the latter to adenocarcinoma and we used bioinformatics approach to search for candidate genes that might be potentially used to distinguish between the two lesions. We used publicly available data from Gene Expression Omnibus database and we analyzed gene expression profiles of 252 samples of normal mucosa, colorectal adenoma, and carcinoma. In total, we analyzed 122 colorectal adenomas, 59 colorectal carcinomas, and 62 normal mucosa samples. We have identified 16 genes with differential expression in carcinoma compared to adenoma:COL12A1,COL1A2,COL3A1, DCN, PLAU, SPARC, SPON2, SPP1,SULF1,FADS1, G0S2, EPHA4, KIAA1324,L1TD1, PCKS1, andC11orf96. In conclusion, ourin silicoanalysis revealed 16 candidate genes with different expression patterns in adenoma compared to carcinoma, which might be used to discriminate between these two lesions.

scholarly journals Regulatory T Cell-Related Gene Biomarkers in the Deterioration of Atherosclerosis

2021 ◽  
Vol 8 ◽  
Author(s):  
Meng Xia ◽  
Qingmeng Wu ◽  
Pengfei Chen ◽  
Cheng Qian
Keyword(s):  
Gene Expression ◽  
Cardiovascular Events ◽  
Molecular Mechanisms ◽  
Inflammatory Responses ◽  
Expression Patterns ◽  
Interaction Network ◽  
Gene Signature ◽  
Smooth Muscle Contraction ◽  
Gene Expression Omnibus ◽  
Scoring Method

Background: Regulatory T cells (Tregs) have shown to be protective against the development of atherosclerosis, a major pathological cause for cardiovascular events. Here, we aim to explore the roles of Tregs-related genes in atherosclerosis deterioration.Methods and Results: We downloaded the gene expression profile of 29 atherosclerotic samples from the Gene Expression Omnibus database with an accession number of GSE28829. The abundance of Tregs estimated by the CIBERSORT algorithm was negatively correlated with the atherosclerotic stage. Using the limma test and correlation analysis, a total of 159 differentially expressed Tregs-related genes (DETregRGs) between early and advanced atherosclerotic plaques were documented. Functional annotation analysis using the DAVID tool indicated that the DETregRGs were mainly enriched in inflammatory responses, immune-related mechanisms, and pathways such as complement and coagulation cascades, platelet activation, leukocyte trans-endothelial migration, vascular smooth muscle contraction, and so on. A protein-protein interaction network of the DETregRGs was then constructed, and five hub genes (PTPRC, C3AR1, CD53, TLR2, and CCR1) were derived from the network with node degrees ≥20. The expression patterns of these hub DETregRGs were further validated in several independent datasets. Finally, a single sample scoring method was used to build a gene signature for the five DETregRGs, which could distinguish patients with myocardial infarction from those with stable coronary disease.Conclusion: The results of this study will improve our understanding about the Tregs-associated molecular mechanisms in the progression of atherosclerosis and facilitate the discovery of novel biomarkers for acute cardiovascular events.

scholarly journals The Significant Pathways and Genes Underlying the Colon Cancer Treatment by the Traditional Chinese Medicine PHY906

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Ziyuan Su ◽  
Changyu Zhou ◽  
Shaoyou Qin ◽  
Erna Jia ◽  
Zhenting Wu
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Interferon Gamma ◽  
Anticancer Agents ◽  
Steroid Hormone ◽  
Expression Patterns ◽  
Therapeutic Targets ◽  
Gene Expression Omnibus ◽  
Ppi Network ◽  
Cancer Cell Death

Background. We attempted to explore the molecular mechanism underlying PHY906 intervention of colon cancer.Methods. The microarray data of tumors treated by PHY906 and PBS alone were downloaded from the public Gene Expression Omnibus database. The dataset was further analyzed for the differentially expressed genes (DEGs) and their related biological functions were analyzed, followed by function and pathways. Protein-protein interaction (PPI) network was constructed and the significant nodes were screened by network centralities and then the significant modules analysis. Besides, they were clustered and transcriptional factors (TFs) were predicted.Results. The gene expression patterns changed induced by PHY906 treatment, including 414 upregulated and 337 downregulated DEGs. The biological process of response to steroid hormone stimulus and regulation of interferon-gamma production were significantly enriched by DEGs. Ezh2 (enhancer of zeste 2) was found to be the key node in PPI network. There are 12 significant TFs predicted for module 1 genes and 3 TFs for module 2 genes.Conclusions. PHY906 treatment may function in protecting the epithelial barrier against tumor cell invasion by modulating IFN-γlevel and mediating cancer cell death by activating the response to steroid hormone stimulus and activating the response to steroid hormone stimulus. E2f1, Hsfy2, and Nfyb may be therapeutic targets for colon cancer. PHY906 showed treatment efficacy in modulating cell apoptosis by intervening interferon-gamma production and response to steroid hormone stimulus. Ezh2 and its TFs such as E2f1, Hsfy2, and Nfyb may be the potential therapeutic targets for anticancer agents development.

scholarly journals GAIT-GM: Galaxy tools for modeling metabolite changes as a function of gene expression

2020 ◽  
Author(s):  
Lauren M. McIntyre ◽  
Francisco Huertas ◽  
Olexander Moskalenko ◽  
Marta Llansola ◽  
Vicente Felipo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Text Mining ◽  
Kegg Pathway ◽  
Annotation Tool ◽  
Omics Data ◽  
Metabolomics Data ◽  
Pathway Data ◽  
User Friendly ◽  
Omics Data Analysis

AbstractGalaxy is a user-friendly platform with a strong development community and a rich set of tools for omics data analysis. While multi-omics experiments are becoming popular, tools for multi-omics data analysis are poorly represented in this platform. Here we present GAIT-GM, a set of new Galaxy tools for integrative analysis of gene expression and metabolomics data. In the Annotation Tool, features are mapped to KEGG pathway using a text mining approach to increase the number of mapped metabolites. Several interconnected databases are used to maximally map gene IDs across species. In the Integration Tool, changes in metabolite levels are modelled as a function of gene expression in a flexible manner. Both unbiased exploration of relationships between genes and metabolites and biologically informed models based on pathway data are enabled. The GAIT-GM tools are freely available at https://github.com/SECIMTools/gait-gm.

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