Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

Funk, Cory C.; Casella, Alex M.; Jung, Su-Young; Richards, Matthew A.; Rodríguez, Álex; Shannon, Paul; Donovan-Maiye, Rory; Heavner, Benjamin D.; Chard, Kyle; Xiao, Yukai; Glusman, Gustavo; Ertekin-Taner, Nilüfer; Golde, Todd E.; Toga, Arthur W.; Hood, Leroy; Horn, John D. Van; Kesselman, Carl; Foster, Ian; Madduri, Ravi; Price, Nathan D.; Ament, Seth A.

doi:10.1016/j.celrep.2020.108029

Cited by 31 publications

(35 citation statements)

References 57 publications

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“…The transcriptional regulatory network analysis (TReNA) package ( https://rdrr.io/bioc/TReNA/ ) was used for identifying transcription factors (TFs) that are part of the co-expression modules of interest. Brain-specific transcriptional regulatory network was constructed 78 using information from ENCODE. We downloaded the DNase Hypersensitivity (DHS) fastq files from ENCODE for all available brain samples and aligned the sequences using the SNAP method.…”

Section: Methodsmentioning

confidence: 99%

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Baloni

Funk

Yan

et al. 2020

Cell Reports Medicine

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Summary Increasing evidence suggests Alzheimer's disease (AD) pathophysiology is influenced by primary and secondary bile acids, the end product of cholesterol metabolism. We analyze 2,114 post-mortem brain transcriptomes and identify genes in the alternative bile acid synthesis pathway to be expressed in the brain. A targeted metabolomic analysis of primary and secondary bile acids measured from post-mortem brain samples of 111 individuals supports these results. Our metabolic network analysis suggests that taurine transport, bile acid synthesis, and cholesterol metabolism differ in AD and cognitively normal individuals. We also identify putative transcription factors regulating metabolic genes and influencing altered metabolism in AD. Intriguingly, some bile acids measured in brain tissue cannot be explained by the presence of enzymes responsible for their synthesis, suggesting that they may originate from the gut microbiome and are transported to the brain. These findings motivate further research into bile acid metabolism in AD to elucidate their possible connection to cognitive decline.

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Section: Methodsmentioning

confidence: 99%

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Baloni

Funk

Yan

et al. 2020

Cell Reports Medicine

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120

137

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“…Probes and corresponding multi-supported genes with three or more CpGs with support in a region in the DMR analysis three regions have shown DNase I hypersensitivity and presence of H3K27Ac mark, which identifies them as active regions in determined cell contexts 63,64 (Figure 3).…”

Section: Ta B L Ementioning

confidence: 99%

“…CpG islands: CpG island annotation according to the Gardiner-Garden criteria. DNase I hypersensitivity clusters show DNase hypersensitive areas assayed in a large collection of cell types by the ENCODE project 63. This track shows the levels of enrichment of the H3K27Ac histone mark across the genome as determined by a ChIP-seq assay often found near active regulatory elements 64.…”

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confidence: 99%

ZNF718, HOXA4, and ZFP57 are differentially methylated in periodontitis in comparison with periodontal health: Epigenome‐wide DNA methylation pilot study

Hernández

Hernández-Castañeda

Pieschacón

et al. 2021

J of Periodontal Research

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Objective: To investigate the differences in the epigenomic patterns of DNA methylation in peripheral leukocytes between patients with periodontitis and gingivally healthy controls evaluating its functional meaning by functional enrichment analysis. Background:The DNA methylation profiling of peripheral leukocytes as immunerelated tissue potentially relevant as a source of biomarkers between periodontitis patients and gingivally healthy subjects has not been investigated.Methods: A DNA methylation epigenome-wide study of peripheral leukocytes was conducted using the Illumina MethylationEPIC platform in sixteen subjects, eight diagnosed with periodontitis patients and eight age-matched and sex-matched periodontally healthy controls. A trained periodontist performed the clinical evaluation.Global DNA methylation was estimated using methylation-sensitive high-resolution melting in LINE1. Routine cell count cytometry and metabolic laboratory tests were also performed. The analysis of differentially methylated positions (DMPs) and differentially methylated regions (DMRs) was made using R/Bioconductor environment considering leukocyte populations assessed in both routine cell counts and using the FlowSorted.Blood.EPIC package. Finally, a DMP and DMR intersection analysis was performed. Functional enrichment analysis was carried out with the differentially methylated genes found in DMP.Results: DMP analysis identified 81 differentially hypermethylated genes and 21 differentially hypomethylated genes. Importantly, the intersection analysis showed that zinc finger protein 718 (ZNF718) and homeobox A4 (HOXA4) were differentially hypermethylated and zinc finger protein 57 (ZFP57) was differentially hypomethylated in periodontitis. The functional enrichment analysis found clearly immune-related ontologies such as "detection of bacterium" and "antigen processing and presentation." Conclusion:The results of this study propose three new periodontitis-related genes: ZNF718, HOXA4, and ZFP57 but also evidence the suitability and relevance of studying leukocytes' DNA methylome for biological interpretation of systemic immunerelated epigenetic patterns in periodontitis. | 711 HERNÁNDEZ Et al.

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“…To test this, we performed an RWAS testing for association between SCZ risk and binding sites for individual TFs. We used tissue-specific TF binding site predictions for 503 TFs, derived from integration of DNase-seq footprinting analysis in the human brain with JASPAR2016 vertebrate sequence motifs [33]. There was a strong association between the AT-richness of a given TF binding site motif and the effect size in our model (p= 2.0E-15 in female fetal brain).…”

Section: Resultsmentioning

confidence: 99%

“…Stratified LD score regression (LDSC version 1.0.1) was applied to GWAS summary statistics to evaluate the enrichment of trait heritability across the 127 enhancer sets [33]. These associations were adjusted for 52 annotations from version 1.2 of the LDSC baseline model (including genic regions, enhancer regions and conserved regions).…”

Section: Methodsmentioning

confidence: 99%

Regulome-wide association study identifies enhancer properties associated with risk for schizophrenia

Colantuoni

2021

Preprint

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Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new framework to identify the characteristics of enhancers that contribute to genetic risk for disease. Applying our technique to interrogate genetic risk for schizophrenia, we found that risk-associated enhancers in this disease are predominantly active in the brain, evolutionarily conserved, and AT-rich. The association between AT percentage and risk corresponds to an overrepresentation in risk-associated enhancers for the binding sites of transcription factors that recognize AT-rich cis-regulatory motifs. Several of the TFs identified in our model as being overrepresented in risk-associated enhancers, including MEF2C, are master regulators of neuronal development. The genes that encode several of these TFs are themselves located at genetic risk loci for schizophrenia. This list also includes brain-expressed TFs that have not previously been linked to schizophrenia. In summary, we developed a generalizable approach that integrates GWAS summary statistics with enhancer characteristics to identify risk factors in tissue-specific regulatory regions.

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Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

Abstract: Highlights d Comprehensive map of TF occupancy in human tissues from DNase-seq footprints d Footprints contain genetic variants associated with changes in gene expression d Tissue-specific associations of footprints with genetic risk for complex traits

Cited by 31 publications

References 57 publications

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

ZNF718, HOXA4, and ZFP57 are differentially methylated in periodontitis in comparison with periodontal health: Epigenome‐wide DNA methylation pilot study

Regulome-wide association study identifies enhancer properties associated with risk for schizophrenia

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