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 EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species

2019 ◽  
Author(s):  
Tianshun Gao ◽  
Jiang Qian
Keyword(s):  
Large Scale ◽  
Target Gene ◽  
Target Genes ◽  
Cell Types ◽  
Regulatory Elements ◽  
Tissue Cell ◽  
Normal Tissues ◽  
Genome Wide ◽  
Wide Range ◽  
User Friendly

Abstract Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer–target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer–target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

scholarly journals A compendium of uniformly processed human gene expression and splicing quantitative trait loci

2021 ◽  
Vol 53 (9) ◽  
pp. 1290-1299
Author(s):  
Nurlan Kerimov ◽  
James D. Hayhurst ◽  
Kateryna Peikova ◽  
Jonathan R. Manning ◽  
Peter Walter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Target Genes ◽  
Genome Wide Association Study ◽  
Cell Types ◽  
Summary Statistics ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Trait Locus ◽  
Complex Human Traits

AbstractMany gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

scholarly journals Beyond the ENCODE project: using genomics and epigenomics strategies to study enhancer evolution

2013 ◽  
Vol 368 (1632) ◽  
pp. 20130022 ◽  
Author(s):  
Noboru Jo Sakabe ◽  
Marcelo A. Nobrega
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Patterns ◽  
Dna Interaction ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Genome Wide ◽  
Identify Transcription Factor ◽  
Specific Proteins ◽  
Species Specific

The complex expression patterns observed for many genes are often regulated by distal transcription enhancers. Changes in the nucleotide sequences of enhancers may therefore lead to changes in gene expression, representing a central mechanism by which organisms evolve. With the development of the experimental technique of chromatin immunoprecipitation (ChIP), in which discrete regions of the genome bound by specific proteins can be identified, it is now possible to identify transcription factor binding events (putative cis -regulatory elements) in entire genomes. Comparing protein–DNA binding maps allows us, for the first time, to attempt to identify regulatory differences and infer global patterns of change in gene expression across species. Here, we review studies that used genome-wide ChIP to study the evolution of enhancers. The trend is one of high divergence of cis -regulatory elements between species, possibly compensated by extensive creation and loss of regulatory elements and rewiring of their target genes. We speculate on the meaning of the differences observed and discuss that although ChIP experiments identify the biochemical event of protein–DNA interaction, it cannot determine whether the event results in a biological function, and therefore more studies are required to establish the effect of divergence of binding events on species-specific gene expression.

scholarly journals A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods

2019 ◽  
Author(s):  
Jill E. Moore ◽  
Henry Pratt ◽  
Michael Purcaro ◽  
Zhiping Weng
Keyword(s):  
Computational Methods ◽  
Method Development ◽  
Target Genes ◽  
Gene Prediction ◽  
Cell Types ◽  
Regulatory Elements ◽  
Distance Method ◽  
Genome Wide ◽  
Benchmark Datasets ◽  
Better Than

ABSTRACTMany genome-wide collections of candidate cis-regulatory elements (cCREs) have been defined using genomic and epigenomic data, but it remains a major challenge to connect these elements to their target genes. To facilitate the development of computational methods for predicting target genes, we developed a Benchmark of candidate Enhancer-Gene Interactions (BENGI) by integrating the Registry of cCREs we developed recently with experimentally-derived genomic interactions. We used BENGI to test several published computational methods for linking enhancers with genes, including signal correlation and the supervised learning methods TargetFinder and PEP. We found that while TargetFinder was the best performing method, it was modestly better than a baseline distance method for most benchmark datasets while trained and tested within the same cell type and that TargetFinder often did not outperform the distance method when applied across cell types. Our results suggest that current computational methods need to be improved and that BENGI presents a useful framework for method development and testing.

scholarly journals EpiRegio: analysis and retrieval of regulatory elements linked to genes

2020 ◽  
Vol 48 (W1) ◽  
pp. W193-W199 ◽  
Author(s):  
Nina Baumgarten ◽  
Dennis Hecker ◽  
Sivarajan Karunanithi ◽  
Florian Schmidt ◽  
Markus List ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Association Studies ◽  
Web Server ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Genome Wide Association Studies ◽  
Coding Regions ◽  
Genomic Regions

Abstract A current challenge in genomics is to interpret non-coding regions and their role in transcriptional regulation of possibly distant target genes. Genome-wide association studies show that a large part of genomic variants are found in those non-coding regions, but their mechanisms of gene regulation are often unknown. An additional challenge is to reliably identify the target genes of the regulatory regions, which is an essential step in understanding their impact on gene expression. Here we present the EpiRegio web server, a resource of regulatory elements (REMs). REMs are genomic regions that exhibit variations in their chromatin accessibility profile associated with changes in expression of their target genes. EpiRegio incorporates both epigenomic and gene expression data for various human primary cell types and tissues, providing an integrated view of REMs in the genome. Our web server allows the analysis of genes and their associated REMs, including the REM’s activity and its estimated cell type-specific contribution to its target gene’s expression. Further, it is possible to explore genomic regions for their regulatory potential, investigate overlapping REMs and by that the dissection of regions of large epigenomic complexity. EpiRegio allows programmatic access through a REST API and is freely available at https://epiregio.de/.

scholarly journals GWAS for systemic sclerosis identifies multiple risk loci and highlights fibrotic and vasculopathy pathways

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Elena López-Isac ◽  
◽  
Marialbert Acosta-Herrera ◽  
Martin Kerick ◽  
Shervin Assassi ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Target Genes ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Cell Types ◽  
The Novel ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants ◽  
Work Supports

Abstract Systemic sclerosis (SSc) is an autoimmune disease that shows one of the highest mortality rates among rheumatic diseases. We perform a large genome-wide association study (GWAS), and meta-analysis with previous GWASs, in 26,679 individuals and identify 27 independent genome-wide associated signals, including 13 new risk loci. The novel associations nearly double the number of genome-wide hits reported for SSc thus far. We define 95% credible sets of less than 5 likely causal variants in 12 loci. Additionally, we identify specific SSc subtype-associated signals. Functional analysis of high-priority variants shows the potential function of SSc signals, with the identification of 43 robust target genes through HiChIP. Our results point towards molecular pathways potentially involved in vasculopathy and fibrosis, two main hallmarks in SSc, and highlight the spectrum of critical cell types for the disease. This work supports a better understanding of the genetic basis of SSc and provides directions for future functional experiments.

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 Genome-wide errant targeting by Hairy

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Kurtulus Kok ◽  
Ahmet Ay ◽  
Li M Li ◽  
David N Arnosti
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Regulatory Elements ◽  
Transcriptional Repressors ◽  
Biochemical Activity ◽  
Specific Effects ◽  
Genome Wide ◽  
Context Specific ◽  
Enhancer Of Split ◽  
Drosophila Embryos

Metazoan transcriptional repressors regulate chromatin through diverse histone modifications. Contributions of individual factors to the chromatin landscape in development is difficult to establish, as global surveys reflect multiple changes in regulators. Therefore, we studied the conserved Hairy/Enhancer of Split family repressor Hairy, analyzing histone marks and gene expression in Drosophila embryos. This long-range repressor mediates histone acetylation and methylation in large blocks, with highly context-specific effects on target genes. Most strikingly, Hairy exhibits biochemical activity on many loci that are uncoupled to changes in gene expression. Rather than representing inert binding sites, as suggested for many eukaryotic factors, many regions are targeted errantly by Hairy to modify the chromatin landscape. Our findings emphasize that identification of active cis-regulatory elements must extend beyond the survey of prototypical chromatin marks. We speculate that this errant activity may provide a path for creation of new regulatory elements, facilitating the evolution of novel transcriptional circuits.

scholarly journals Integrating genome-wide association and transcriptome predicted model identify novel target genes with osteoporosis

2019 ◽  
Author(s):  
Peng Yin ◽  
Muchun Zhu ◽  
Fan Hu ◽  
Jiaxin Jiang ◽  
Li Yin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Mineral Density ◽  
Candidate Genes ◽  
Bone Mineral ◽  
Target Genes ◽  
Causal Variant ◽  
Genome Wide Association ◽  
Mineral Density ◽  
Genome Wide ◽  
Causal Variants

AbstractOsteoporosis (OP) is a highly polygenetic disease which is usually characterized by low bone mineral density. Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with bone mineral density. However, the biological mechanisms of these loci remain elusive. To identify potential causal genes of the associated loci, we detected trait-gene expression associations by transcriptome-wide association study (TWAS) method. It directly imputes gene expression effects from GWAS data, using a statistical prediction model trained on GTEx reference transcriptome data, with blood and skeletal tissues data. Then we performed a colocalization analysis to evaluate the posterior probability of biological patterns: association characterized by a single shared causal variant or two distinct causal variants. The ultimate analysis identified 276 candidate genes, including 3 novel loci, 204 novel candidate genes and 69 replicated from GWAS. The 3 novel loci located at chr6: 72417543, chr15: 69601206, chr21: 30530692, mapping to gene RIMS1, SPESP1, MAP3K7CL. The results of colocalization analysis indicated that 142 of them showing strong evidence of a single shared causal variant and 134 of them showing evidence of joint causal variants. Their biological function was directly or indirectly associated with the occurrence of OP validated by VarElect tool. Several important OP-associated pathways were detected by protein-protein interaction and pathway enrichment analysis. Target genes were further enriched for differential expression genes in osteoblasts expression profiles, e.g. IBSP, affecting calcium and hydroxyapatite binding, and CD44, regulating alternative splicing of gene transcription. Transcriptome fine-mapping identifies more disease-related genes and provide additional insight into the development of novel targeted therapeutics to treat OP.

scholarly journals INFERNO - INFERring the molecular mechanisms of NOncoding genetic variants

2017 ◽  
Author(s):  
Alexandre Amlie-Wolf ◽  
Mitchell Tang ◽  
Elisabeth E. Mlynarski ◽  
Pavel P. Kuksa ◽  
Otto Valladares ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Cellular Processes ◽  
Genome Wide ◽  
Causal Variants ◽  
Novel Method

AbstractThe majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, where they affect regulatory elements including transcriptional enhancers. We propose INFERNO (INFERring the molecular mechanisms of NOncoding genetic variants), a novel method which integrates hundreds of diverse functional genomics data sources with GWAS summary statistics to identify putatively causal noncoding variants underlying association signals. INFERNO comprehensively infers the relevant tissue contexts, target genes, and downstream biological processes affected by causal variants. We apply INFERNO to schizophrenia GWAS data, recapitulating known schizophrenia-associated genes including CACNA1C and discovering novel signals related to transmembrane cellular processes.

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