Similar Datasets
Project description:Identification of cellular context sensitive regulatory variation in mouse genomes
| PRJNA658784 | ENA
Project description:In mammals, the circadian clock controls behavioral, physiological and cellular rhythms. Part of this daily variation is controlled by transcription-translation feedback loops in sync with the light-dark phase. On the other hand, daily rhythms in expression of a multitude of genes are related to nutrient-response cycles. Time-resolved mapping of DNase I hypersensitive sites (DHS) throughout the day can identify details of the regulatory interplay between metabolism and the internal clock at a molecular level. Here, we report a genome-wide analysis of mammalian DHS using high‐throughput sequencing of DNase tags from mouse liver with a resolution of 4 h (12 h light/12 h dark). Among the 65’000 DHS sites identified, a significant proportion of distal DHS showed a diurnal cycle, suggesting a fine regulation of oscillating genes by enhancers, which we seek to understand better. Using PolII and H3K27ac ChIP-seq, we characterize the DHS and study the dynamics of each mark in wild-type and Bmal1-KO mice. We use the sequence motif content of each DHS and a linear regression model to explain DHS temporal behaviour in terms of phase and amplitude. We monitor the temporal expression of target genes in order to understand the phase-specific regulation in the circadian context. Interestingly, DHS associated with circadian genes tend to be time-correlated with expression, Pol II and H3K27ac marks. The Bmal1-KO phenotype in light-dark conditions show a proportion of DHS with circadian rhythms associated with transcription factors related to metabolism, due to food entrainment and systemic cues.
2016-12-31 | GSE60577 | GEO
Project description:Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.
| S-EPMC8121920 | biostudies-literature
Project description:DNase-seq mapping in engineered mesendodermal cells differentiated from mouse embryonic stem cells (mESCs) using CHIR.
2024-03-13 | GSE254963 | GEO
Project description:Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profiled open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We define key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrated that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells followed a more complex differentiation, where Hfn4a was associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease identified critical cell types, developmental stages, genes, and regulatory mechanisms. We provide a global single cell resolution view of chromatin accessibility of kidney development. The dataset is available via interactive public websites.
2020-08-29 | GSE157079 | GEO
Project description:Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.
| S-EPMC3141000 | biostudies-literature
Project description:<p>International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not been identified by conventional epidemiology yet potentially make a substantial contribution to cancer burden1. This pertains to clear cell renal cell carcinoma (ccRCC), for which obesity, hypertension, and tobacco smoking are risk factors but do not explain its geographical variation in incidence2. Some carcinogens generate somatic mutations and a complementary strategy for detecting past exposures is to sequence the genomes of cancers from populations with different incidence rates and infer underlying causes from differences in patterns of somatic mutations. Here, we sequenced 962 ccRCC from 11 countries of varying incidence. Somatic mutation profiles differed between countries. In Romania, Serbia and Thailand, mutational signatures likely caused by extracts of Aristolochia plants were present in most cases and rare elsewhere. In Japan, a mutational signature of unknown cause was found in >70% cases and <2% elsewhere. A further mutational signature of unknown cause was ubiquitous but exhibited higher mutation loads in countries with higher kidney cancer incidence rates (p-value <6 × 10−18). Known signatures of tobacco smoking correlated with tobacco consumption, but no signature was associated with obesity or hypertension suggesting non-mutagenic mechanisms of action underlying these risk factors. The results indicate the existence of multiple, geographically variable, mutagenic exposures potentially affecting 10s of millions of people and illustrate the opportunities for new insights into cancer causation through large-scale global cancer genomics.</p><p><br></p><p><strong>Linked cross omic data sets:</strong></p><p>Geographic variation of mutagenic exposures in kidney cancer genomes – patient metadata files (<strong>Mutographs</strong>) associated with this study are available in the <strong>European Genome-Phenome Archive</strong>: https://ega-archive.org/datasets/EGAD00001012223.</p>
2024-03-26 | MTBLS9394 | MetaboLights
Project description:Interventions: Patients with spleen deficiency and qi stagnation syndrome SDQSS:NA;Patients with DHS with damp-heat accumulation syndrome:NA;Patients with SPOS with stasis and internal resistance syndrome:NA;Patients with SKYDS of Spleen and Kidney Yang Deficiency Syndrome:NA;Patients with liver-kidney yin deficiency syndrome LKYDS:NA;QBDS patients with deficiency of both qi and blood syndrome:NA
Primary outcome(s): Serum metabolites;Fecal microbiome;lipidomics
Study Design: Diagnostic test for accuracy
| 105810 | ecrin-mdr-crc
Project description:MicroRNAs (miRNAs) are short non-coding RNAs that regulate expression of target messenger RNAs (mRNAs) post-transcriptionally. Understanding the precise regulatory role of miRNAs is of great interest since miRNAs have been shown to play an important role in development, diseases, and other biological processes. Early work on miRNA target prediction has focused on static sequence-driven miRNA-mRNA complementarity. However, recent research also utilizes expression-level data to study context-dependent regulation effects in a more dynamic, physiologically-relevant setting. Methods: We propose a novel artificial neural network (ANN) based method, named Tiresias, to predict such targets in a context-dependent manner by combining sequence and expression data. In order to predict the interacting pairs among miRNAs and mRNAs and their regulatory weights, we develop a two-stage ANN and present how to train it appropriately. Tiresias is designed to study various regulation models, ranging from a simple linear model to a complex non-linear model. Tiresias has a single hyper-parameter to control the sparsity of miRNA-mRNA interactions, which we optimize using Bayesian optimization. Results: Tiresias performs better than existing computational methods such as GenMiR++, Elastic Net, and PIMiM, achieving an F1 score of >0.8 for a certain level of regulation strength. For the TCGA breast invasive carcinoma dataset, Tiresias results in the rate of up to 82% in detecting the experimentally-validated interactions between miRNAs and mRNAs, even if we assume that true regulations may result in a low level of regulation strength. Conclusion: Tiresias is a two-stage ANN, computational method that deciphers context-dependent microRNA regulatory interactions. Experiment results demonstrate that Tiresias outperforms existing solutions and can achieve a high F1 score. Source code of Tiresias is available at https://bitbucket.org/cellsandmachines/.
| S-EPMC5743474 | biostudies-literature
Project description:Hypusination is a unique post-translational modification of the eukaryotic translation factor 5A (eIF5A) that is essential for overcoming ribosome stalling at polyproline sequence stretches. The initial step of hypusination, the formation of deoxyhypusine, is catalyzed by deoxyhypusine synthase (DHS), however, the molecular details of the DHS-mediated reaction remained elusive. Recently, patient-derived variants of DHS and eIF5A have been linked to rare neurodevelopmental disorders. Here, we present the cryo-EM structure of the human eIF5A-DHS complex at 2.8Å resolution and a crystal structure of DHS trapped in the key reaction transition state. Furthermore, we show that disease-associated DHS variants influence the complex formation and hypusination efficiency. Hence, our work dissects the molecular details of the deoxyhypusine synthesis reaction and reveals how clinically-relevant mutations affect this crucial cellular process.
2023-05-10 | PXD040460 | Pride