Rare genetic variation at transcription factor binding site modulates local DNA methylation profiles
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE159930 | GEO | 2020/10/24
REPOSITORIES: GEO
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Project description:A detailed map of genomic locations where TFs bind DNA and modulate transcription is essential to model mechanisms of gene regulation on a systems-scale. Chromatin immunoprecipitation of transcription complexes coupled to microarray (ChIP-chip (Ren et al, 2000)) or sequencing (ChIP-seq (Robertson et al, 2007)) is a commonly used approach to construct such maps. In ChIP-chip, the resolution to which the protein-DNA binding sites (TFBSs) can be identified is often limited by the genomic spacing of the probes in the array. We utilized the MeDiChI algorithm (Reiss et al, 2008) to estimate precise TFBS locations and their corresponding local false discovery rates (LFDRs) from high-resolution arrays for TFBa, TFBd and TFBf. This regression-based method deconvolves the ChIP-chip enrichment ratios along the genome by fitting them with a 'peak profile' model of binding events, assuming a distribution in enriched DNA fragment lengthsÂ. A comparison of the peak intensities derived from MeDiChI for all three TFs (TFBd, TFBf and TFBa) for which there were biological replicate measurements using 2 different microarray platforms (500 nt resolution spotted arrays, see series GSE7045 vs. 13 nt resolution Nimblegen arrays) provided strong validation (with R2 of 0.66, 0.52, and 0.81, respectively) of most TFBSs. Visualizations comparing the two microarray platforms are available at: http://baliga.systemsbiology.net/regulatory_logic/ IP sample of Cmyc tagged TFBs expressed in Halobacterium NRC-1 cells transformed with pMTFcmyc gene expressing TFBf in standard growth media with 20microgram/ml mevinolin versus a whole cell extract from the same sample. Three biological replicates for TFBd are available.
2010-05-17 | E-GEOD-15786 | biostudies-arrayexpress
Project description:Accurate interpretation of genetic variation is a critical step towards realizing the potential of precision medicine. Sequencing-based genetic tests have uncovered a vast array ofBRCA2sequence variants. Due to limited clinical, familial and/or epidemiological data, thousands of variants are considered to be variants of uncertain significance (VUS). Here we have utilized CRISPR-Cas9-based saturation genome editing (SGE) in a humanized-mouse embryonic stem cell line. We have categorized nearly all possible missense single nucleotide variants (SNVs) encompassing the C-terminal DNA binding domain ofBRCA2.We have generated the function scores for 6270 SNVs, covering 95.5% of possible SNVs in exons 15-26 spanning residues 2479-3216, including 1069 unique missense VUS, with 81% functional and 14% found to be nonfunctional. Our classification aligns strongly with pathogenicity data from ClinVar, orthogonal functional assays and computational meta predictors. Our statistical classifier exhibits 92.2% sensitivity and 96% specificity in distinguishing clinically benign and pathogenic variants recorded in ClinVar. Furthermore, we offer proactive evidence for 617 SNVs being non-functional and 3396 SNVs being functional demonstrated by impact on cell growth and response to DNA-damaging drugs like cisplatin and olaparib. This classification serves as a valuable resource for interpreting unidentified variants in the population and for physicians and genetic counselors assessingBRCA2VUSs in patients.
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Project description:A detailed map of genomic locations where TFs bind DNA and modulate transcription is essential to model mechanisms of gene regulation on a systems-scale. Chromatin immunoprecipitation of transcription complexes coupled to microarray (ChIP-chip (Ren et al, 2000)) or sequencing (ChIP-seq (Robertson et al, 2007)) is a commonly used approach to construct such maps. In ChIP-chip, the resolution to which the protein-DNA binding sites (TFBSs) can be identified is often limited by the genomic spacing of the probes in the array. We utilized the MeDiChI algorithm (Reiss et al, 2008) to estimate precise TFBS locations and their corresponding local false discovery rates (LFDRs) from high-resolution arrays for TFBa, TFBd and TFBf. This regression-based method deconvolves the ChIP-chip enrichment ratios along the genome by fitting them with a 'peak profile' model of binding events, assuming a distribution in enriched DNA fragment lengths. A comparison of the peak intensities derived from MeDiChI for all three TFs (TFBd, TFBf and TFBa) for which there were biological replicate measurements using 2 different microarray platforms (500 nt resolution spotted arrays, see series GSE7045 vs. 13 nt resolution Nimblegen arrays) provided strong validation (with R2 of 0.66, 0.52, and 0.81, respectively) of most TFBSs. Visualizations comparing the two microarray platforms are available at: http://baliga.systemsbiology.net/regulatory_logic/
2009-06-25 | GSE15786 | GEO
Project description:Germline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to breast, ovarian, prostate and pancreatic cancer. However, variants of uncertain significance (VUS) (n>5000) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants. Here we report on comprehensive saturation genome editing-based functional characterization of 99% of all possible single nucleotide variants (SNVs) in the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants that is encoded by exons 15 to 26. The assay was based on deep sequence analysis of HAP1 haploid cells endogenously targeted using a CRISPR/cas9 knockin approach. A total of 6959 SNVs were characterized for effects on cell survival. The assay was validated relative to nonsense and synonymous variants, ClinVar pathogenic/likely pathogenic and benign/likely benign variants and homology directed repair cell based DNA repair assay results, all of which showed >94% sensitivity and specificity. Variants were assigned posterior probabilities of pathogenicity using a VarCall two component Bayesian mixture model and were further grouped according to ACMG strength of evidence under the PS3/BS3 rule resulting in Benign Strong (n=5430), Benign Moderate (n=190), Benign Supporting (n=61), VUS (122), Pathogenic Strong (n=1021), Pathogenic Moderate (n=88), and Pathogenic Supporting (n=47). Breast cancer case-control association studies showed that pooled SNVs encoding functionally pathogenic missense variants were associated with increased risks of breast (odds ratio (OR)3.81, 95%CI: 2.88-5.07) and ovarian cancer (OR 5.93, 95%CI: 4.12-8.52). The functional data were also combined with other sources of information in the ClinGen BRCA1/2 VCEP ACMG/AMP-classification model. A total of 785 SNVs, including 261 missense SNVs, were classified as pathogenic or likely pathogenic, while 5566 SNVs, including 3786 missense SNVs, were classified as benign or likely benign. These classified variants can now be used for risk assessment and clinical care of variant carriers.
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Project description:Truncated forms of CGGBP1 with (N-term) or without (C-term) the DNA-binding domain (DBD) have been used to to assay global cytosine methylation. HEK293T cells with endogenous CGGBP1 knocked down were used to over-express truncated forms of CGGBP1 followed by MeDIP-Seq analysis. Genome-wide analyses of cytosine methylation and binding of CGGBP1 DBD show that CGGBP1 restricts cytosine methylation in a manner that depends on its DBD and its DNA-binding. Our findings suggest that CGGBP1 protects transcription factor binding sites (TFBS) from cytosine methylation-associated loss. A superimposition of our results and evolution of CGGBP1 suggests that mitigation of cytosine methylation is majorly achieved by its N-terminal DBD. Our results position CGGBP1 DNA-binding as a major evolutionarily acquired mechanism through which it keeps cytosine methylation under check and regulates TFBS retention.
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2016-05-25 | GSE60142 | GEO
Project description:A number of genetic studies have identified rare protein-coding DNA variations associated with autism spectrum disorder (ASD), a neurodevelopmental disorder with significant genetic etiology and heterogeneity. In contrast, the contributions of functional, regulatory genetic variations that occur in the extensive non-protein-coding regions of the genome remain poorly understood. Here we developed a genome-wide analysis to identify rare single nucleotide variants (SNVs) that occur in non-coding regions and determined regulatory function and evolutionary conservation of these variants. Using publicly available datasets and computational predictions, we identified SNVs within putative regulatory regions in promoters, transcription factor binding sites, microRNA genes and their target sites. Overall, we found regulatory variants in the ASD cases were enriched in autism-risk genes and genes involved in fetal neurodevelopment. As with previously reported coding mutations, we found an enrichment of regulatory variants associated with dysregulation of neurodevelopmental and synaptic signaling pathways. Among these were rare inherited non-coding SNVs found in the mature sequence of a number of microRNAs predicted to affect the regulation of autism-risk genes. We show a paternally inherited miR-873-5p variant, with reduced NRXN2 binding affinity, overlays a maternally inherited NRXN1 putative loss-of-function coding variation to likely increase genetic liability in an idiopathic ASD case. Our analysis pipeline provides a new resource for identifying loss-of-function regulatory DNA variations that may contribute to the genetic etiology of complex disorders.
2017-04-25 | GSE98088 | GEO
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2019-12-01 | GSE137527 | GEO
Project description:Data from multiple high throughput technologies such as RNA sequencing (RNA-Seq) and protein mass spectrometry (MS/MS) are often used to assist in predicting eukaryote genome features such as genes, splice variants, and single nucleotide variants (SNVs). The genomes of parasitic nematodes causing neglected tropical diseases are often poorly annotated. Angiostrongylus costaricensis, a nematode that causes an intestinal inflammatory disease known as abdominal angiostrongyliasis (AA), is one example. Currently, no drugs or treatments are available for AA, a public health problem in Latin America, especially in Costa Rica and Brazil. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction supplemented the reference annotation with a) novel coding and non-coding genes; b) pieces of evidence of alternative splicing generating new proteoforms; c) a list of SNVs specific to the Brazilian strain (Crissiumal). To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of a parasitic nematode. We hope this supplemented genome annotation can assist the future development of drugs to treat AA caused by either Brazil strain (Crissiumal) or Costa Rica strain.
2023-03-11 | PXD034605 | Pride