scholarly journals Expression quantitative trait methylation analysis reveals methylomic associations with gene expression in childhood asthma

2020 ◽  
Author(s):  
Soyeon Kim ◽  
Erick Forno ◽  
Rong Zhang ◽  
Qi Yan ◽  
Nadia Boutaoui ◽  
...  
Keyword(s):  
Gene Expression ◽  
Puerto Rican ◽  
Childhood Asthma ◽  
Quantitative Trait ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Atopic Asthma ◽  
Nasal Airway ◽  
Airway Epithelial ◽  
Methylation Analysis

AbstractNasal airway epithelial methylation profiles have been associated with asthma, but the effects of such profiles on expression of distant cis-genes are largely unknown. We identified 16,867 significant methylation-gene expression pairs in nasal epithelium from Puerto Rican children and adolescents (with and without asthma) in an expression quantitative trait methylation (eQTM) analysis of cis-genes located within 1 Mb of the methylation probes tested. Most eQTM methylation probes were distant from their target genes, and more likely located in enhancer regions of their target genes in lung tissue than control probes. The top 500 eQTM genes were enriched in pathways for immune processes and epithelial integrity, and also more likely to be differentially expressed in atopic asthma. Moreover, we identified 5,934 paths through which methylation probes could affect atopic asthma through gene expression. Our findings suggest that distant epigenetic regulation of gene expression in airway epithelium plays a role in atopic asthma.

scholarly journals Expression Quantitative Trait Methylation Analysis Reveals Methylomic Associations With Gene Expression in Childhood Asthma

CHEST Journal ◽  
2020 ◽  
Vol 158 (5) ◽  
pp. 1841-1856 ◽  
Author(s):  
Soyeon Kim ◽  
Erick Forno ◽  
Rong Zhang ◽  
Hyun Jung Park ◽  
Zhongli Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Childhood Asthma ◽  
Quantitative Trait ◽  
Methylation Analysis

A TRIPARTITE CLUSTERING ANALYSIS ON MICRORNA, GENE AND DISEASE MODEL

2012 ◽  
Vol 10 (01) ◽  
pp. 1240007 ◽  
Author(s):  
CHENGCHENG SHEN ◽  
YING LIU
Keyword(s):  
Gene Expression ◽  
Clustering Algorithm ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Disease Model ◽  
Relational Information ◽  
Microrna Gene ◽  
Research Findings ◽  
Family Based

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

scholarly journals Gene Expression Networks in the Drosophila Genetic Reference Panel

2019 ◽  
Author(s):  
Logan J. Everett ◽  
Wen Huang ◽  
Shanshan Zhou ◽  
Mary Anna Carbone ◽  
Richard F. Lyman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transposable Elements ◽  
Dna Sequences ◽  
Quantitative Trait ◽  
Regulatory Networks ◽  
Target Genes ◽  
Reference Panel ◽  
Modern Biology ◽  
Specific Expression ◽  
Drosophila Genetic Reference Panel

SummaryA major challenge in modern biology is to understand how naturally occurring variation in DNA sequences affects complex organismal traits through networks of intermediate molecular phenotypes. Here, we performed deep RNA sequencing of 200 Drosophila Genetic Reference Panel inbred lines with complete genome sequences, and mapped expression quantitative trait loci for annotated genes, novel transcribed regions (most of which are long noncoding RNAs), transposable elements and microbial species. We identified host variants that affect expression of transposable elements, independent of their copy number, as well as microbiome composition. We constructed sex-specific expression quantitative trait locus regulatory networks. These networks are enriched for novel transcribed regions and target genes in heterochromatin and euchromatic regions of reduced recombination, and genes regulating transposable element expression. This study provides new insights regarding the role of natural genetic variation in regulating gene expression and generates testable hypotheses for future functional analyses.

scholarly journals Cell-type Specific Expression Quantitative Trait Loci Associated with Alzheimer Disease in Blood and Brain Tissue

2020 ◽  
Author(s):  
Devanshi Patel ◽  
Xiaoling Zhang ◽  
John J. Farrell ◽  
Jaeyoon Chung ◽  
Thor D. Stein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Cell Types ◽  
Eqtl Analysis ◽  
Cell Type ◽  
Specific Expression ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

ABSTRACTBecause regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell-types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5,257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1Mb of genes was evaluated using linear regression models for unrelated subjects and linear mixed models for related subjects. Cell type-specific eQTL (ct-eQTL) models included an interaction term for expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2,533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell-types is supported by the observation that a large portion of GWS ct-eQTLs map within 1Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type specific analysis.

scholarly journals A compendium of uniformly processed human gene expression and splicing quantitative trait loci

2021 ◽  
Vol 53 (9) ◽  
pp. 1290-1299
Author(s):  
Nurlan Kerimov ◽  
James D. Hayhurst ◽  
Kateryna Peikova ◽  
Jonathan R. Manning ◽  
Peter Walter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Target Genes ◽  
Genome Wide Association Study ◽  
Cell Types ◽  
Summary Statistics ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Trait Locus ◽  
Complex Human Traits

AbstractMany gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals ETO-2 Associates with SCL in Erythroid Cells and Megakaryocytes and Provides Repressor Functions in Erythropoiesis

2005 ◽  
Vol 25 (23) ◽  
pp. 10235-10250 ◽  
Author(s):  
Anna H. Schuh ◽  
Alex J. Tipping ◽  
Allison J. Clark ◽  
Isla Hamlett ◽  
Boris Guyot ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Protein Complexes ◽  
Fetal Liver ◽  
Regulation Of Gene Expression ◽  
Erythroid Differentiation ◽  
Cell Types ◽  
Erythroid Cells ◽  
Proteomic Approach ◽  
Endogenous Proteins

ABSTRACT Lineage specification and cellular maturation require coordinated regulation of gene expression programs. In large part, this is dependent on the activator and repressor functions of protein complexes associated with tissue-specific transcriptional regulators. In this study, we have used a proteomic approach to characterize multiprotein complexes containing the key hematopoietic regulator SCL in erythroid and megakaryocytic cell lines. One of the novel SCL-interacting proteins identified in both cell types is the transcriptional corepressor ETO-2. Interaction between endogenous proteins was confirmed in primary cells. We then showed that SCL complexes are shared but also significantly differ in the two cell types. Importantly, SCL/ETO-2 interacts with another corepressor, Gfi-1b, in red cells but not megakaryocytes. The SCL/ETO-2/Gfi-1b association is lost during erythroid differentiation of primary fetal liver cells. Genetic studies of erythroid cells show that ETO-2 exerts a repressor effect on SCL target genes. We suggest that, through its association with SCL, ETO-2 represses gene expression in the early stages of erythroid differentiation and that alleviation/modulation of the repressive state is then required for expression of genes necessary for terminal erythroid maturation to proceed.

scholarly journals Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits

2018 ◽  
Author(s):  
Heather E. Wheeler ◽  
Sally Ploch ◽  
Alvaro N. Barbeira ◽  
Rodrigo Bonazzola ◽  
Angela Andaleon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Complex Traits ◽  
Target Gene ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nucleic Acid Binding ◽  
Expression Of Genes ◽  
Gene Associations ◽  
Made In

AbstractRegulation of gene expression is an important mechanism through which genetic variation can affect complex traits. A substantial portion of gene expression variation can be explained by both local (cis) and distal (trans) genetic variation. Much progress has been made in uncovering cis-acting expression quantitative trait loci (cis-eQTL), but trans-eQTL have been more difficult to identify and replicate. Here we take advantage of our ability to predict the cis component of gene expression coupled with gene mapping methods such as PrediXcan to identify high confidence candidate trans-acting genes and their targets. That is, we correlate the cis component of gene expression with observed expression of genes in different chromosomes. Leveraging the shared cis-acting regulation across tissues, we combine the evidence of association across all available GTEx tissues and find 2356 trans-acting/target gene pairs with high mappability scores. Reassuringly, trans-acting genes are enriched in transcription and nucleic acid binding pathways and target genes are enriched in known transcription factor binding sites. Interestingly, trans-acting genes are more significantly associated with selected complex traits and diseases than target or background genes, consistent with percolating trans effects. Our scripts and summary statistics are publicly available for future studies of trans-acting gene regulation.

scholarly journals Removal of H3K27me3 by JMJ Proteins Controls Plant Development and Environmental Responses in Arabidopsis

2021 ◽  
Vol 12 ◽  
Author(s):  
Nobutoshi Yamaguchi
Keyword(s):  
Gene Expression ◽  
Plant Development ◽  
Transcriptional Repression ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Histone H3 ◽  
Control Of Gene Expression ◽  
Precise Control ◽  
Repressive Histone Modification ◽  
Environmental Responses

Trimethylation of histone H3 lysine 27 (H3K27me3) is a highly conserved repressive histone modification that signifies transcriptional repression in plants and animals. In Arabidopsis thaliana, the demethylation of H3K27 is regulated by a group of JUMONJI DOMAIN-CONTANING PROTEIN (JMJ) genes. Transcription of JMJ genes is spatiotemporally regulated during plant development and in response to the environment. Once JMJ genes are transcribed, recruitment of JMJs to target genes, followed by demethylation of H3K27, is critically important for the precise control of gene expression. JMJs function synergistically and antagonistically with transcription factors and/or other epigenetic regulators on chromatin. This review summarizes the latest advances in our understanding of Arabidopsis H3K27me3 demethylases that provide robust and flexible epigenetic regulation of gene expression to direct appropriate development and environmental responses in plants.

scholarly journals Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in Arabidopsis thaliana using ChIP-Seq peak data

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 372 ◽  
Author(s):  
Delasa Aghamirzaie ◽  
Karthik Raja Velmurugan ◽  
Shuchi Wu ◽  
Doaa Altarawy ◽  
Lenwood S. Heath ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Chromatin Immunoprecipitation ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Data Sets ◽  
Motif Analysis ◽  
Chromatin Immunoprecipitation Sequencing

Motivation: The increasing availability of chromatin immunoprecipitation sequencing (ChIP-Seq) data enables us to learn more about the action of transcription factors in the regulation of gene expression. Even though in vivo transcriptional regulation often involves the concerted action of more than one transcription factor, the format of each individual ChIP-Seq dataset usually represents the action of a single transcription factor. Therefore, a relational database in which available ChIP-Seq datasets are curated is essential. Results: We present Expresso (database and webserver) as a tool for the collection and integration of available Arabidopsis ChIP-Seq peak data, which in turn can be linked to a user’s gene expression data. Known target genes of transcription factors were identified by motif analysis of publicly available GEO ChIP-Seq data sets. Expresso currently provides three services: 1) Identification of target genes of a given transcription factor; 2) Identification of transcription factors that regulate a gene of interest; 3) Computation of correlation between the gene expression of transcription factors and their target genes. Availability: Expresso is freely available at http://bioinformatics.cs.vt.edu/expresso/

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