An integrated analysis of mRNA-miRNA transcriptome data revealed hub regulatory networks in three genitourinary cancers

BIOCELL ◽  
2018 ◽  
Vol 41 (1) ◽  
pp. 19-26 ◽  
Author(s):  
M. Liu ◽  
X. Zhang
Keyword(s):  
Regulatory Networks ◽  
Integrated Analysis ◽  
Transcriptome Data ◽  
Genitourinary Cancers

scholarly journals Integrated Analysis of lncRNAs, mRNAs, and TFs to Identify Regulatory Networks Underlying MAP Infection in Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Maryam Heidari ◽  
Abbas Pakdel ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Fariba Dehghanian
Keyword(s):  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Johne's Disease ◽  
Johne’S Disease ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Complex Nature ◽  
Hub Genes ◽  
Cis And Trans

Johne’s disease is a chronic infection of ruminants that burdens dairy herds with a significant economic loss. The pathogenesis of the disease has not been revealed clearly due to its complex nature. In order to achieve deeper biological insights into molecular mechanisms involved in MAP infection resulting in Johne’s disease, a system biology approach was used. As far as is known, this is the first study that considers lncRNAs, TFs, and mRNAs, simultaneously, to construct an integrated gene regulatory network involved in MAP infection. Weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis were conducted to explore coexpression modules from which nonpreserved modules had altered connectivity patterns. After identification of hub and hub-hub genes as well as TFs and lncRNAs in the nonpreserved modules, integrated networks of lncRNA-mRNA-TF were constructed, and cis and trans targets of lncRNAs were identified. Both cis and trans targets of lncRNAs were found in eight nonpreserved modules. Twenty-one of 47 nonpreserved modules showed significant biological processes related to the immune system and MAP infection. Some of the MAP infection’s related pathways in the most important nonpreserved modules comprise “positive regulation of cytokine-mediated signaling pathway,” “negative regulation of leukocyte migration,” “T-cell differentiation,” “neutrophil activation,” and “defense response.” Furthermore, several genes were identified in these modules, including SLC11A1, MAPK8IP1, HMGCR, IFNGR1, CMPK2, CORO1A, IRF1, LDLR, BOLA-DMB, and BOLA-DMA, which are potentially associated with MAP pathogenesis. This study not only enhanced our knowledge of molecular mechanisms behind MAP infection but also highlighted several promising hub and hub-hub genes involved in macrophage-pathogen interaction.

Integrated analysis and reconstruction of microbial transcriptional gene regulatory networks using CoryneRegNet

2009 ◽  
Vol 4 (6) ◽  
pp. 992-1005 ◽  
Author(s):  
Jan Baumbach ◽  
Tobias Wittkop ◽  
Christiane Katja Kleindt ◽  
Andreas Tauch
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Integrated Analysis ◽  
Gene Regulatory

scholarly journals Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data

2017 ◽  
Vol 13 (5) ◽  
pp. 3177-3185 ◽  
Author(s):  
Xiaomei Li ◽  
Weiwei Dong ◽  
Xueling Qu ◽  
Huixia Zhao ◽  
Shuo Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Integrated Analysis ◽  
Transcriptome Data

scholarly journals Integrated metabolomic and transcriptomic analysis of the anthocyanin regulatory networks in Salvia miltiorrhiza Bge. flowers

2020 ◽  
Author(s):  
Tao Jiang ◽  
Meide Zhang ◽  
Chunxiu Wen ◽  
Xiaoliang Xie ◽  
Wei Tian ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Regulatory Networks ◽  
Anthocyanin Biosynthesis ◽  
Salvia Miltiorrhiza ◽  
Flower Color ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Anthocyanin Content ◽  
Transcriptomics Data

Abstract Background: The study objectives were to reveal the anthocyanin biosynthesis metabolic pathway in white and purple flowers of Salvia miltiorrhiza using metabolomics and transcriptomics, to identify different anthocyanin metabolites, and to analyze the differentially expressed genes involved in anthocyanin biosynthesis . Results: We analyzed the metabolomics and transcriptomics data of Salvia miltiorrhiza flowers. A total of 1994 differentially expressed genes and 84 flavonoid metabolites were identified between the white and purple flowers of Salvia miltiorrhiza . Integrated analysis of transcriptomic and metabolomics showed that cyanidin 3,5-O-diglucoside, malvidin 3,5-diglucoside, and cyanidin 3-O-galactoside were mainly responsible for the purple flower color of Salvia miltiorrhiza. A total of 100 unigenes encoding 10 enzymes were identified as candidate genes involved in anthocyanin biosynthesis in Salvia miltiorrhiza flowers. The low expression of the ANS gene decreased the anthocyanin content but enhanced the accumulation of flavonoids in Salvia miltiorrhiza flowers. Conclusions: Our results provide valuable information on the anthocyanin metabolites and the candidate genes involved in the anthocyanin biosynthesis pathways in Salvia miltiorrhiza .

scholarly journals Genome-wide identification and comparison of differentially expressed profiles of miRNAs and lncRNAs with associated ceRNA networks in the gonads of Chinese soft-shelled turtle, Pelodiscus sinensis

2019 ◽  
Author(s):  
Xiao Ma ◽  
Shuangshuang Cen ◽  
Luming Wang ◽  
Chao Zhang ◽  
Limin Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Regulatory Networks ◽  
Target Genes ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Regulation Mechanism ◽  
Pelodiscus Sinensis ◽  
Specific Expression ◽  
Protein Coding ◽  
Protein Coding Genes

Abstract Abstract Background: Gonad is the major factor affecting the animal reproduction. The regulation mechanism of protein coding genes expression involved reproduction is still remains to be elucidated. Increasing evidence has shown that ncRNAs play key regulatory roles in gene expression in many life processes. The roles of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in reproduction had been investigated in some species. However, the regulation patterns of miRNA and lncRNA in sex biased expression of protein coding genes remains to be elucidated. In this study, we performed an integrated analysis of miRNA, messenger RNA (mRNA), and lncRNA expression profiles to explore their regulatory patterns in the female ovary and male testis of the soft-shelled turtle, Pelodiscus sinensis. Results: We identified 10 796 mature miRNAs, 44 678 mRNAs, and 58 923 lncRNAs in the testis and ovary. A total of 16 817 target genes were identified for miRNAs. Of these, 11 319 mRNAs, 10 495 lncRNAs, and 633 miRNAs were expressed differently. The predicted target genes of these differential expression (DE) miRNAs and lncRNAs included genes related to reproduction regulation. Furthermore, we found that 5 408 DElncRNAs and 186 DE miRNAs showed sex-specific expression. Of these, 3 miRNAs and 917 lncRNAs were testis specific and 186 DEmiRNAs and 4 491 DElncRNAs were ovary specific. We constructed compete endogenous lncRNA-miRNA-mRNA networks using bioinformatics, including 273 DEmRNAs, 5 730 DEmiRNAs, and 2 945 DElncRNAs. The target genes for the different expressed of miRNAs and lncRNAs included Wt1, Creb3l2, Gata4, Wnt2, Nr5a1, Hsd17, Igf2r, H2afz, Lin52, Trim71, Zar1, and Jazf1, etc. Conclusions: In animals, miRNA and lncRNA regulate the reproduction process, including the regulation of oocyte maturation and spermatogenesis. Considering their importance, the identified miRNAs, lncRNAs, and their targets in P. sinensis might be useful for genome editing to produce higher quality aquaculture animals. A thorough understanding of ncRNA-based cellular regulatory networks will aid in the improvement of P. sinensis reproduction traits for aquaculture.

scholarly journals StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis

BMC Genomics ◽  
2019 ◽  
Vol 20 (S11) ◽  
Author(s):  
Dongwon Kang ◽  
Hongryul Ahn ◽  
Sangseon Lee ◽  
Chai-Jin Lee ◽  
Jihye Hur ◽  
...  
Keyword(s):  
Neural Network ◽  
Gene Expression ◽  
Machine Learning ◽  
Time Series ◽  
Integrated Analysis ◽  
Expression Data ◽  
Transcriptome Data ◽  
Multiple Stress ◽  
Stress Related Genes ◽  
Single Stress

Abstract Background Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the stress response are available in databases. With the data, an integrated analysis of multiple stresses is possible, which identifies stress-responsive genes with higher specificity because considering multiple stress can capture the effect of interference between stresses. To analyze such data, a machine learning model needs to be built. Results In this study, we developed StressGenePred, a neural network-based machine learning method, to integrate time-series transcriptome data of multiple stress types. StressGenePred is designed to detect single stress-specific biomarker genes by using a simple feature embedding method, a twin neural network model, and Confident Multiple Choice Learning (CMCL) loss. The twin neural network model consists of a biomarker gene discovery and a stress type prediction model that share the same logical layer to reduce training complexity. The CMCL loss is used to make the twin model select biomarker genes that respond specifically to a single stress. In experiments using Arabidopsis gene expression data for four major environmental stresses, such as heat, cold, salt, and drought, StressGenePred classified the types of stress more accurately than the limma feature embedding method and the support vector machine and random forest classification methods. In addition, StressGenePred discovered known stress-related genes with higher specificity than the Fisher method. Conclusions StressGenePred is a machine learning method for identifying stress-related genes and predicting stress types for an integrated analysis of multiple stress time-series transcriptome data. This method can be used to other phenotype-gene associated studies.

scholarly journals VariED: the first integrated database of gene annotation and expression profiles for variants related to human diseases

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Chien-Yueh Lee ◽  
Amrita Chattopadhyay ◽  
Li-Mei Chiang ◽  
Jyh-Ming Jimmy Juang ◽  
Liang-Chuan Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Gene Annotation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Analysis ◽  
Free Text ◽  
Functional Prediction ◽  
Annotation Database ◽  
Dna Variants

Abstract Integrated analysis of DNA variants and gene expression profiles may facilitate precise identification of gene regulatory networks involved in disease mechanisms. Despite the widespread availability of public resources, we lack databases that are capable of simultaneously providing gene expression profiles, variant annotations, functional prediction scores and pathogenic analyses. VariED is the first web-based querying system that integrates an annotation database and expression profiles for genetic variants. The database offers a user-friendly platform and locates gene/variant names in the literature by connecting to established online querying tools, biological annotation tools and records from free-text literature. VariED acts as a central hub for organized genome information consisting of gene annotation, variant allele frequency, functional prediction, clinical interpretation and gene expression profiles in three species: human, mouse and zebrafish. VariED also provides a novel scoring scheme to predict the functional impact of a DNA variant. With one single entry, all results regarding queried DNA variants can be downloaded. VariED can potentially serve as an efficient way to obtain comprehensive variant knowledge for clinicians and scientists around the world working on important drug discoveries and precision treatments.

Sign in / Sign up

Export Citation Format

Share Document