A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE162387 | GEO | 2022/02/08
REPOSITORIES: GEO
Similar Datasets
Project description:Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. We named these molecularly coordinated regions “variable chromatin modules” (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect an uncharacterized VCM-modulating non-coding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a big change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with long-range chromatin compaction and AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.
2022-04-21 | PXD029313 | Pride
Project description:The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.
| EGAS00001002073 | EGA
Project description:Multiplexed assays of variant effects (MAVEs) guide clinical variant interpretation and reveal disease mechanisms. To date, MAVEs have focussed on a single mutation type - amino acid (AA) substitutions - despite the diversity of coding variants that cause disease. Here we use Deep Indel Mutagenesis (DIM) to generate the first comprehensive atlas of diverse variant effects for a disease protein, amyloid beta (Aß) that aggregates in Alzheimer’s disease (AD) and is mutated in familial AD (fAD). The atlas identifies known fAD variants and many mutations beyond substitutions that accelerate Aß aggregation. Truncations, substitutions, insertions, single- and multi-AA deletions differ in their propensity to enhance or impair aggregation, but likely pathogenic variants from all classes are strongly enriched in the polar N-terminus of Aß. This first comparative atlas for any disease gene highlights the importance of including diverse mutation types in MAVEs and provides important mechanistic insights into amyloid nucleation.
2022-10-27 | GSE193837 | GEO
Project description:Aberrant chromatin features and epigenetic signaling emerge as an important part of the tumor disease state in chronic lymphocytic leukemia (CLL). However, an integrative analysis of the malignant chromatin landscape is currently missing. Here, we mapped DNA-methylation, nucleosome position, 7 histone modifications, ATAC-seq and the transcriptome in primary CD19+ sorted B-cells from the peripheral blood of CLL patients in comparison to non-malignant lymphocytes of healthy donor reference samples. On the > 50 kb scale we identified global differences with respect to DNA methylation, nucleosome positioning and histone modifications in CLL. Furthermore, a chromatin state annotation was developed to identify deregulated chromatin features of promoters and enhancers in CLL. By integrating these findings with an ATAC-seq based transcription factor binding analysis we identified a set of promoters and enhancers specific to CLL that were enriched in certain transcription factors binding motifs and genes of the BCR signaling pathway. Thus, our study provides an in-depth map of the CLL chromatin landscape and links chromatin state changes at promoters and enhancers to deregulated pathways.
| EGAS00001002518 | EGA
Project description:CENP-A, a variant of histone H3, is incorporated into centromeric chromatin and plays a role during kinetochore establishment. In fission yeast, the localization of CENP-A is limited to a region spanning 10 to 20 kb of the core domain of the centromere. Here, we report a mutant (rpt3-1) in which this region is expanded to 40 to 70 kb. Likely due to abnormal distribution of CENP-A, this mutant exhibits chromosome instability and enhanced gene silencing. Interestingly, the rpt3+ gene encodes a subunit of the 19S proteasome, which localizes to the nuclear membrane. While Rpt3 associates with centromeric chromatin, the mutant protein has lost this localization. A loss of the cut8+ gene encoding an anchor of the proteasome to the nuclear membrane causes similar phenotypes as observed in the rpt3-1 mutant. Thus, we propose that the proteasome (or its subcomplex) associates with centromeric chromatin and regulates distribution of CENP-A. Chromosomal distributions of differentially expressed centromere protein A in wild-type and a proteasome mutant.
2014-04-07 | E-GEOD-44594 | biostudies-arrayexpress
Project description:One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as M-bM-^@M-^\active enhancersM-bM-^@M-^]. 201 samples were analyzed - 57 transcription factors were knocked down in triplicate in the same cell line, 2 factors were knocked down in 6 replicates each and an additional 18 control knockdowns (siRNA not targeting any known gene) were analyzed
2014-02-05 | E-GEOD-50588 | biostudies-arrayexpress
Project description:This model is from the article:
A regulatory role for repeated decoy transcription factor binding sites in target gene expression.
Lee TH, Maheshri N. Mol Syst Biol.
2012 Mar 27;8:576. 22453733
,
Abstract:
Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding.
Note:
This model corresponds to the basic model for gene expression in the presence of decoys, described in the paper.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1202270000 | BioModels
Project description:This model is from the article:
A regulatory role for repeated decoy transcription factor binding sites in target gene expression.
Lee TH, Maheshri N. Mol Syst Biol.
2012 Mar 27;8:576. 22453733
,
Abstract:
Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding.
Note:
This model corresponds to the comprehensive model encompassing the basic model (MODEL1202270000) as well as the tTA/dox (tet-transcriptional activator/doxycycline) interaction, described in the paper.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1202270001 | BioModels
Project description:CENP-A, a variant of histone H3, is incorporated into centromeric chromatin and plays a role during kinetochore establishment. In fission yeast, the localization of CENP-A is limited to a region spanning 10 to 20 kb of the core domain of the centromere. Here, we report a mutant (rpt3-1) in which this region is expanded to 40 to 70 kb. Likely due to abnormal distribution of CENP-A, this mutant exhibits chromosome instability and enhanced gene silencing. Interestingly, the rpt3+ gene encodes a subunit of the 19S proteasome, which localizes to the nuclear membrane. While Rpt3 associates with centromeric chromatin, the mutant protein has lost this localization. A loss of the cut8+ gene encoding an anchor of the proteasome to the nuclear membrane causes similar phenotypes as observed in the rpt3-1 mutant. Thus, we propose that the proteasome (or its subcomplex) associates with centromeric chromatin and regulates distribution of CENP-A.
2014-04-07 | GSE44594 | GEO
Project description:DNA methylation is an important epigenetic regulator of gene expression. Recent studies have revealed widespread associations between genetic variation and methylation levels. However, the mechanistic links between genetic variation and methylation remain unclear. To begin addressing this gap, we collected methylation data at ~300,000 loci in lymphoblastoid cell lines (LCLs) from 64 HapMap Yoruba individuals, and genome-wide bisulfite sequence data in ten of these individuals. We identified 11,752 methylation QTLs (meQTLs)—i.e., loci in which genetic variation is significantly associated with changes in DNA methylation. We found that meQTLs are frequently associated with changes in methylation at multiple CpGs across regions of up to 3 kb. Interestingly, meQTLs are also frequently associated with variation in other properties of gene regulation, including histone modifications, DNaseI accessibility, chromatin accessibility, and expression levels of nearby genes. These observations suggest a shared and coordinated molecular variation in all of these regulatory phenotypes. One plausible driver of coordinated changes in different regulatory mechanisms is variation in transcription factor (TF) binding. Indeed, we found that both changes in putative TF binding affinity and changes in the strength of TF binding footprints are associated with variation in DNA methylation near the TF binding sites. Considered together, our observations are consistent with a model whereby changes in TF binding may frequently drive coordinated changes in DNA methylation, histone modification, and gene expression levels. Bisulfite converted DNA from 64 individuals was hybridized to the Illumina Infinium HumanMethylation450 BeadChip
2014-05-09 | E-GEOD-57481 | biostudies-arrayexpress