scholarly journals Chromatin accessibility landscape and regulatory network of high-altitude hypoxia adaptation

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingxue Xin ◽  
Hui Zhang ◽  
Yaoxi He ◽  
Zhana Duren ◽  
Caijuan Bai ◽  
...  
Keyword(s):  
High Altitude ◽  
Regulatory Network ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Remarkable Case ◽  
Genome Wide ◽  
Altitude Adaptation ◽  
Time Courses ◽  
Coding Variants

Abstract High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution. Previous genome-wide scans found many non-coding variants under selection, suggesting a pressing need to understand the functional role of non-coding regulatory elements (REs). Here, we generate time courses of paired ATAC-seq and RNA-seq data on cultured HUVECs under hypoxic and normoxic conditions. We further develop a variant interpretation methodology (vPECA) to identify active selected REs (ASREs) and associated regulatory network. We discover three causal SNPs of EPAS1, the key adaptive gene for Tibetans. These SNPs decrease the accessibility of ASREs with weakened binding strength of relevant TFs, and cooperatively down-regulate EPAS1 expression. We further construct the downstream network of EPAS1, elucidating its roles in hypoxic response and angiogenesis. Collectively, we provide a systematic approach to interpret phenotype-associated noncoding variants in proper cell types and relevant dynamic conditions, to model their impact on gene regulation.

scholarly journals Single-Cell Epigenomics and Functional Fine-Mapping of Atherosclerosis GWAS Loci

2021 ◽  
Author(s):  
Tiit Örd ◽  
Kadri Õunap ◽  
Lindsey Stolze ◽  
Rédouane Aherrahrou ◽  
Valtteri Nurminen ◽  
...  
Keyword(s):  
Smooth Muscle ◽  
Smooth Muscle Cells ◽  
Muscle Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Atherosclerotic Lesions ◽  
Genome Wide ◽  
Single Nucleus

Rationale: Genome-wide association studies (GWAS) have identified hundreds of loci associated with coronary artery disease (CAD). Many of these loci are enriched in cis-regulatory elements (CREs) but not linked to cardiometabolic risk factors nor to candidate causal genes, complicating their functional interpretation. Objective: Single nucleus chromatin accessibility profiling of the human atherosclerotic lesions was used to investigate cell type-specific patterns of CREs, to understand transcription factors establishing cell identity and to interpret CAD-relevant, non-coding genetic variation. Methods and Results: We used single nucleus ATAC-seq to generate DNA accessibility maps in > 7,000 cells derived from human atherosclerotic lesions. We identified five major lesional cell types including endothelial cells, smooth muscle cells, monocyte/macrophages, NK/T-cells and B-cells and further investigated subtype characteristics of macrophages and smooth muscle cells transitioning into fibromyocytes. We demonstrated that CAD associated genetic variants are particularly enriched in endothelial and smooth muscle cell-specific open chromatin. Using single cell co-accessibility and cis-eQTL information, we prioritized putative target genes and candidate regulatory elements for ~30% of all known CAD loci. Finally, we performed genome-wide experimental fine-mapping of the CAD GWAS variants using epigenetic QTL analysis in primary human aortic endothelial cells and STARR-Seq massively parallel reporter assay in smooth muscle cells. This analysis identified potential causal SNP(s) and the associated target gene for over 30 CAD loci. We present several examples where the chromatin accessibility and gene expression could be assigned to one cell type predicting the cell type of action for CAD loci. Conclusions: These findings highlight the potential of applying snATAC-seq to human tissues in revealing relative contributions of distinct cell types to diseases and in identifying genes likely to be influenced by non-coding GWAS variants.

scholarly journals Integrative analysis of epigenetics data identifies gene-specific regulatory elements

2019 ◽  
Author(s):  
Florian Schmidt ◽  
Alexander Marx ◽  
Marie Hebel ◽  
Martin Wegner ◽  
Nina Baumgarten ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Genome Wide ◽  
A Genome ◽  
Gene Level ◽  
Regulatory Landscape ◽  
Regulatory Sites ◽  
Validation Experiments

AbstractUnderstanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIToutperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.

scholarly journals ALTRE: workflow for defining ALTered Regulatory Elements using chromatin accessibility data

2016 ◽  
Author(s):  
Elizabeth Baskin ◽  
Rick Farouni ◽  
Ewy A. Mathe
Keyword(s):  
Cell Types ◽  
R Package ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Differential Analysis ◽  
Genome Wide ◽  
Wide Range ◽  
R Shiny ◽  
Cell Type Specific ◽  
Different Cell Types

AbstractSummaryRegulatory elements regulate gene transcription, and their location and accessibility is cell-type specific, particularly for enhancers. Mapping and comparing chromatin accessibility between different cell types may identify mechanisms involved in cellular development and disease progression. To streamline and simplify differential analysis of regulatory elements genome-wide using chromatin accessibility data, such as DNase-seq, ATAC-seq, we developed ALTRE (ALTered Regulatory Elements), an R package and associated R Shiny web app. ALTRE makes such analysis accessible to a wide range of users – from novice to practiced computational biologists.Availabilityhttps://github.com/Mathelab/[email protected]

scholarly journals Simultaneous profiling of multiple chromatin proteins in the same cells

2021 ◽  
Author(s):  
Sneha Gopalan ◽  
Yuqing Wang ◽  
Nicholas W. Harper ◽  
Manuel Garber ◽  
Thomas G Fazzio
Keyword(s):  
Rna Polymerase Ii ◽  
Direct Analysis ◽  
Cell Types ◽  
Regulatory Elements ◽  
Genome Wide ◽  
Distinct Cell ◽  
Direct Measurements ◽  
Cell Type Specific ◽  
Chromatin Proteins

Methods derived from CUT&RUN and CUT&Tag enable genome-wide mapping of the localization of proteins on chromatin from as few as one cell. These and other mapping approaches focus on one protein at a time, preventing direct measurements of co-localization of different chromatin proteins in the same cells and requiring prioritization of targets where samples are limiting. Here we describe multi-CUT&Tag, an adaptation of CUT&Tag that overcomes these hurdles by using antibody-specific barcodes to simultaneously map multiple proteins in the same cells. Highly specific multi-CUT&Tag maps of histone marks and RNA Polymerase II uncovered sites of co-localization in the same cells, active and repressed genes, and candidate cis-regulatory elements. Single-cell multi-CUT&Tag profiling facilitated identification of distinct cell types from a mixed population and characterization of cell type-specific chromatin architecture. In sum, multi-CUT&Tag increases the information content per cell of epigenomic maps, facilitating direct analysis of the interplay of different proteins on chromatin.

scholarly journals HCR-FlowFISH: A flexible CRISPR screening method to identify cis-regulatory elements and their target genes

2020 ◽  
Author(s):  
SK Reilly ◽  
SJ Gosai ◽  
A Gutierrez ◽  
JC Ulirsch ◽  
M Kanai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Screening Method ◽  
Cell Types ◽  
Regulatory Elements ◽  
Hybridization Chain Reaction ◽  
Genome Wide ◽  
Wide Range ◽  
Causal Variants ◽  
Endogenous Loci

AbstractCRISPR screens for cis-regulatory elements (CREs) have shown unprecedented power to endogenously characterize the non-coding genome. To characterize CREs we developed HCR-FlowFISH (Hybridization Chain Reaction Fluorescent In-Situ Hybridization coupled with Flow Cytometry), which directly quantifies native transcripts within their endogenous loci following CRISPR perturbations of regulatory elements, eliminating the need for restrictive phenotypic assays such as growth or transcript-tagging. HCR-FlowFISH accurately quantifies gene expression across a wide range of transcript levels and cell types. We also developed CASA (CRISPR Activity Screen Analysis), a hierarchical Bayesian model to identify and quantify CRE activity. Using >270,000 perturbations, we identified CREs for GATA1, HDAC6, ERP29, LMO2, MEF2C, CD164, NMU, FEN1 and the FADS gene cluster. Our methods detect subtle gene expression changes and identify CREs regulating multiple genes, sometimes at different magnitudes and directions. We demonstrate the power of HCR-FlowFISH to parse genome-wide association signals by nominating causal variants and target genes.

scholarly journals Genetic signatures of high-altitude adaptation in Tibetans

2017 ◽  
Vol 114 (16) ◽  
pp. 4189-4194 ◽  
Author(s):  
Jian Yang ◽  
Zi-Bing Jin ◽  
Jie Chen ◽  
Xiu-Feng Huang ◽  
Xiao-Man Li ◽  
...  
Keyword(s):  
High Altitude ◽  
Methylenetetrahydrofolate Reductase ◽  
The Tibetan Plateau ◽  
High Altitude Adaptation ◽  
Drift Model ◽  
Genome Wide ◽  
A Genome ◽  
Altitude Adaptation ◽  
Genetic Signatures ◽  
Genome Wide Study

Indigenous Tibetan people have lived on the Tibetan Plateau for millennia. There is a long-standing question about the genetic basis of high-altitude adaptation in Tibetans. We conduct a genome-wide study of 7.3 million genotyped and imputed SNPs of 3,008 Tibetans and 7,287 non-Tibetan individuals of Eastern Asian ancestry. Using this large dataset, we detect signals of high-altitude adaptation at nine genomic loci, of which seven are unique. The alleles under natural selection at two of these loci [methylenetetrahydrofolate reductase (MTHFR) and EPAS1] are strongly associated with blood-related phenotypes, such as hemoglobin, homocysteine, and folate in Tibetans. The folate-increasing allele of rs1801133 at the MTHFR locus has an increased frequency in Tibetans more than expected under a drift model, which is probably a consequence of adaptation to high UV radiation. These findings provide important insights into understanding the genomic consequences of high-altitude adaptation in Tibetans.

scholarly journals Systematic clustering algorithm for chromatin accessibility data and its application to hematopoietic cells

2020 ◽  
Vol 16 (11) ◽  
pp. e1008422
Author(s):  
Azusa Tanaka ◽  
Yasuhiro Ishitsuka ◽  
Hiroki Ohta ◽  
Akihiro Fujimoto ◽  
Jun-ichirou Yasunaga ◽  
...  
Keyword(s):  
Data Reduction ◽  
Clustering Algorithm ◽  
High Throughput Sequencing ◽  
Hematopoietic Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Genome Wide ◽  
Data Reduction Method ◽  
Effective Analysis

The huge amount of data acquired by high-throughput sequencing requires data reduction for effective analysis. Here we give a clustering algorithm for genome-wide open chromatin data using a new data reduction method. This method regards the genome as a string of 1s and 0s based on a set of peaks and calculates the Hamming distances between the strings. This algorithm with the systematically optimized set of peaks enables us to quantitatively evaluate differences between samples of hematopoietic cells and classify cell types, potentially leading to a better understanding of leukemia pathogenesis.

scholarly journals Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhe Cui ◽  
Ya Cui ◽  
Yan Gao ◽  
Tao Jiang ◽  
Tianyi Zang ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Support Vector ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Copy Numbers ◽  
Genome Wide ◽  
Accessible Chromatin

Single-cell Assay Transposase Accessible Chromatin sequencing (scATAC-seq) has been widely used in profiling genome-wide chromatin accessibility in thousands of individual cells. However, compared with single-cell RNA-seq, the peaks of scATAC-seq are much sparser due to the lower copy numbers (diploid in humans) and the inherent missing signals, which makes it more challenging to classify cell type based on specific expressed gene or other canonical markers. Here, we present svmATAC, a support vector machine (SVM)-based method for accurately identifying cell types in scATAC-seq datasets by enhancing peak signal strength and imputing signals through patterns of co-accessibility. We applied svmATAC to several scATAC-seq data from human immune cells, human hematopoietic system cells, and peripheral blood mononuclear cells. The benchmark results showed that svmATAC is free of literature-based markers and robust across datasets in different libraries and platforms. The source code of svmATAC is available at https://github.com/mrcuizhe/svmATAC under the MIT license.

scholarly journals Methylation studies in Peromyscus: aging, altitude adaptation, and monogamy

GeroScience ◽  
2021 ◽  
Author(s):  
Steve Horvath ◽  
Amin Haghani ◽  
Joseph A. Zoller ◽  
Asieh Naderi ◽  
Elham Soltanmohammadi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Altitude ◽  
Extreme Environments ◽  
Stress Factors ◽  
Deer Mice ◽  
Epigenetic Clock ◽  
Age Cohorts ◽  
Biomarkers Of Aging ◽  
Genome Wide ◽  
Altitude Adaptation

AbstractDNA methylation-based biomarkers of aging have been developed for humans and many other mammals and could be used to assess how stress factors impact aging. Deer mice (Peromyscus) are long-living rodents that have emerged as an informative model to study aging, adaptation to extreme environments, and monogamous behavior. In the present study, we have undertaken an exhaustive, genome-wide analysis of DNA methylation in Peromyscus, spanning different species, stocks, sexes, tissues, and age cohorts. We describe DNA methylation-based estimators of age for different species of deer mice based on novel DNA methylation data generated on highly conserved mammalian CpGs measured with a custom array. The multi-tissue epigenetic clock for deer mice was trained on 3 tissues (tail, liver, and brain). Two human-Peromyscus clocks accurately measure age and relative age, respectively. We present CpGs and enriched pathways that relate to different conditions such as chronological age, high altitude, and monogamous behavior. Overall, this study provides a first step towards studying the epigenetic correlates of monogamous behavior and adaptation to high altitude in Peromyscus. The human-Peromyscus epigenetic clocks are expected to provide a significant boost to the attractiveness of Peromyscus as a biological model.

scholarly journals Functional Inference of Gene Regulation using Single-Cell Multi-Omics

2021 ◽  
Author(s):  
Vinay K Kartha ◽  
Fabiana M Duarte ◽  
Yan Hu ◽  
Sai Ma ◽  
Jennifer G Chew ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Regulatory Networks ◽  
Immunological Response ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Human Blood Cells ◽  
Functional Inference ◽  
Omic Data

Cells require coordinated control over gene expression when responding to environmental stimuli. Here, we apply scATAC-seq and scRNA-seq in resting and stimulated human blood cells. Collectively, we generate ~91,000 single-cell profiles, allowing us to probe the cis -regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multi-omic data, we develop FigR - a framework to computationally pair scATAC-seq with scRNA-seq cells, connect distal cis -regulatory elements to genes, and infer gene regulatory networks (GRNs) to identify candidate TF regulators. Utilizing these paired multi-omic data, we define Domains of Regulatory Chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility prior to production of gene expression at time scales of minutes. Further, the construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables the elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

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