scholarly journals An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs)

2008 ◽  
Vol 18 (9) ◽  
pp. 1518-1529 ◽  
Author(s):  
V. K. Rakyan ◽  
T. A. Down ◽  
N. P. Thorne ◽  
P. Flicek ◽  
E. Kulesha ◽  
...  
Keyword(s):  
Human Tissue ◽  
Differentially Methylated Regions ◽  
Tissue Specific ◽  
Genome Wide

scholarly journals Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics

2013 ◽  
Vol 13 (2) ◽  
pp. 397-406 ◽  
Author(s):  
Linn Fagerberg ◽  
Björn M. Hallström ◽  
Per Oksvold ◽  
Caroline Kampf ◽  
Dijana Djureinovic ◽  
...  
Keyword(s):  
Human Tissue ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression ◽  
Genome Wide

scholarly journals A human tissue map of 5-hydroxymethylcytosines exhibits tissue specificity through gene and enhancer modulation

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao-Long Cui ◽  
Ji Nie ◽  
Jeremy Ku ◽  
Urszula Dougherty ◽  
Diana C. West-Szymanski ◽  
...  
Keyword(s):  
Human Tissue ◽  
Tissue Specificity ◽  
Dna Demethylation ◽  
Tissue Type ◽  
Specific Gene ◽  
Mammalian Development ◽  
Tissue Specific ◽  
Genome Wide ◽  
Organ Systems

AbstractDNA 5-hydroxymethylcytosine (5hmC) modification is known to be associated with gene transcription and frequently used as a mark to investigate dynamic DNA methylation conversion during mammalian development and in human diseases. However, the lack of genome-wide 5hmC profiles in different human tissue types impedes drawing generalized conclusions about how 5hmC is implicated in transcription activity and tissue specificity. To meet this need, we describe the development of a 5hmC tissue map by characterizing the genomic distributions of 5hmC in 19 human tissues derived from ten organ systems. Subsequent sequencing results enabled the identification of genome-wide 5hmC distributions that uniquely separates samples by tissue type. Further comparison of the 5hmC profiles with transcriptomes and histone modifications revealed that 5hmC is preferentially enriched on tissue-specific gene bodies and enhancers. Taken together, the results provide an extensive 5hmC map across diverse human tissue types that suggests a potential role of 5hmC in tissue-specific development; as well as a resource to facilitate future studies of DNA demethylation in pathogenesis and the development of 5hmC as biomarkers.

scholarly journals ExtRamp Online: Enabling ramp sequence calculations via an intuitive web interface.

2021 ◽  
Author(s):  
Justin B. Miller ◽  
Matthew W. Hodgman ◽  
Kyle N. Miller ◽  
Taylor E. Meurs ◽  
Mark T. W. Ebbert ◽  
...  
Keyword(s):  
Codon Usage ◽  
Human Tissue ◽  
Translational Efficiency ◽  
Web Interface ◽  
Cell Type ◽  
Web Browser ◽  
Tissue Specific ◽  
Genome Wide ◽  
Evolutionarily Conserved ◽  
Cell Type Specific

Abstract Motivation: Ramp sequences are an understudied evolutionarily-conserved mechanism for regulating protein translational efficiency. Slowly-translated codons concentrated at the 5' end of genes form ramp sequences that counterintuitively increase overall translational efficiency by evenly spacing ribosomes at initiation, which limits downstream ribosomal collisions. We previously developed ExtRamp, which is the only algorithm to identify translational ramp sequences in single genes. ExtRamp currently lacks a web interface to facilitate wider adoption and application for non-programmers. Additionally, ExtRamp currently identifies ramp sequences using only species-wide codon efficiencies that may lack the specificity of tissue and cell type-specific codon usage biases.Results: We present an online interface for ExtRamp to facilitate wider adoption and application for non-programmers, along with a significant improvement to the underlying algorithm to calculate tissue and cell type-specific ramp sequences (https://ramps.byu.edu/ExtRampOnline). ExtRamp Online contains all options available in the original ExtRamp algorithm with additional pre-set default values to enable researchers to calculate human tissue-specific or genome-wide ramp sequences on any web browser. Human tissue and cell type-specific codon usage biases have been precomputed and can be applied with a simple drop-down menu. Hover-over hints provide users with detailed information on all available options, which will help facilitate future creative analyses using ramp sequences. Availability: ExtRamp Online is publicly available at https://ramps.byu.edu/ExtRampOnline. All associated scripts are publicly available at https://github.com/ridgelab/ExtRampOnline.

scholarly journals E-MAGMA: an eQTL-informed method to identify risk genes using genome-wide association study summary statistics

2021 ◽  
Author(s):  
Zachary F Gerring ◽  
Angela Mina-Vargas ◽  
Eric R Gamazon ◽  
Eske M Derks
Keyword(s):  
Genome Wide Association ◽  
Chromosome 1 ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Risk Variants ◽  
Genome Wide ◽  
Causal Genes

Abstract Motivation Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with human traits and diseases, but the exact causal genes are largely unknown. Common genetic risk variants are enriched in non-protein-coding regions of the genome and often affect gene expression (expression quantitative trait loci, eQTL) in a tissue-specific manner. To address this challenge, we developed a methodological framework, E-MAGMA, which converts genome-wide association summary statistics into gene-level statistics by assigning risk variants to their putative genes based on tissue-specific eQTL information. Results We compared E-MAGMA to three eQTL informed gene-based approaches using simulated phenotype data. Phenotypes were simulated based on eQTL reference data using GCTA for all genes with at least one eQTL at chromosome 1. We performed 10 simulations per gene. The eQTL-h2 (i.e., the proportion of variation explained by the eQTLs) was set at 1%, 2%, and 5%. We found E-MAGMA outperforms other gene-based approaches across a range of simulated parameters (e.g. the number of identified causal genes). When applied to genome-wide association summary statistics for five neuropsychiatric disorders, E-MAGMA identified more putative candidate causal genes compared to other eQTL-based approaches. By integrating tissue-specific eQTL information, these results show E-MAGMA will help to identify novel candidate causal genes from genome-wide association summary statistics and thereby improve the understanding of the biological basis of complex disorders. Availability A tutorial and input files are made available in a github repository: https://github.com/eskederks/eMAGMA-tutorial. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Understanding multicellular function and disease with human tissue-specific networks

2015 ◽  
Vol 47 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Casey S Greene ◽  
Arjun Krishnan ◽  
Aaron K Wong ◽  
Emanuela Ricciotti ◽  
Rene A Zelaya ◽  
...  
Keyword(s):  
Human Tissue ◽  
Tissue Specific

scholarly journals Nuclear receptor HNF4A transrepresses CLOCK:BMAL1 and modulates tissue-specific circadian networks

2018 ◽  
Vol 115 (52) ◽  
pp. E12305-E12312 ◽  
Author(s):  
Meng Qu ◽  
Tomas Duffy ◽  
Tsuyoshi Hirota ◽  
Steve A. Kay
Keyword(s):  
Nuclear Receptor ◽  
Metabolic Pathways ◽  
Feedback Loop ◽  
Transcriptional Activity ◽  
Transcript Level ◽  
Colon Cells ◽  
Tissue Specific ◽  
Metabolic Genes ◽  
Genome Wide ◽  
Circadian Control

Either expression level or transcriptional activity of various nuclear receptors (NRs) have been demonstrated to be under circadian control. With a few exceptions, little is known about the roles of NRs as direct regulators of the circadian circuitry. Here we show that the nuclear receptor HNF4A strongly transrepresses the transcriptional activity of the CLOCK:BMAL1 heterodimer. We define a central role for HNF4A in maintaining cell-autonomous circadian oscillations in a tissue-specific manner in liver and colon cells. Not only transcript level but also genome-wide chromosome binding of HNF4A is rhythmically regulated in the mouse liver. ChIP-seq analyses revealed cooccupancy of HNF4A and CLOCK:BMAL1 at a wide array of metabolic genes involved in lipid, glucose, and amino acid homeostasis. Taken together, we establish that HNF4A defines a feedback loop in tissue-specific mammalian oscillators and demonstrate its recruitment in the circadian regulation of metabolic pathways.

scholarly journals A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

2019 ◽  
Author(s):  
Tom G Richardson ◽  
Gibran Hemani ◽  
Tom R Gaunt ◽  
Caroline L Relton ◽  
George Davey Smith
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Drug Repositioning ◽  
Association Studies ◽  
Thyroid Tissue ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide

AbstractBackgroundDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. By applying the principles of Mendelian randomization, we have undertaken a systematic analysis to evaluate transcriptome-wide associations between gene expression across 48 different tissue types and 395 complex traits.ResultsOverall, we identified 100,025 gene-trait associations based on conventional genome-wide corrections (P < 5 × 10−08) that also provided evidence of genetic colocalization. These results indicated that genetic variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. We identified many examples of tissue-specific effects, such as genetically-predicted TPO, NR3C2 and SPATA13 expression only associating with thyroid disease in thyroid tissue. Additionally, FBN2 expression was associated with both cardiovascular and lung function traits, but only when analysed in heart and lung tissue respectively.We also demonstrate that conducting phenome-wide evaluations of our results can help flag adverse on-target side effects for therapeutic intervention, as well as propose drug repositioning opportunities. Moreover, we find that exploring the tissue-dependency of associations identified by genome-wide association studies (GWAS) can help elucidate the causal genes and tissues responsible for effects, as well as uncover putative novel associations.ConclusionsThe atlas of tissue-dependent associations we have constructed should prove extremely valuable to future studies investigating the genetic determinants of complex disease. The follow-up analyses we have performed in this study are merely a guide for future research. Conducting similar evaluations can be undertaken systematically at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

scholarly journals Microarray data integration for genome-wide analysis of human tissue-selective gene expression

BMC Genomics ◽  
2010 ◽  
Vol 11 (Suppl 2) ◽  
pp. S15 ◽  
Author(s):  
Liangjiang Wang ◽  
Anand K Srivastava ◽  
Charles E Schwartz
Keyword(s):  
Gene Expression ◽  
Data Integration ◽  
Microarray Data ◽  
Human Tissue ◽  
Genome Wide Analysis ◽  
Genome Wide

Tissue specific expression and serum levels of human tissue factor in patients with urological cancer

2003 ◽  
Vol 193 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Yvonne Förster ◽  
Axel Meye ◽  
Sybille Albrecht ◽  
Matthias Kotzsch ◽  
Susanne Füssel ◽  
...  
Keyword(s):  
Tissue Factor ◽  
Human Tissue ◽  
Serum Levels ◽  
Urological Cancer ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression
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