scholarly journals High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Cancer Cells ◽  
High Throughput ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Chromatin Accessibility ◽  
Regulatory Regions ◽  
Factor Binding ◽  
Genome Wide

AbstractChromatin accessibility profiling can identify putative regulatory regions genome wide; however, pooled single-cell methods for assessing the effects of regulatory perturbations on accessibility are limited. Here, we report a modified droplet-based single-cell ATAC-seq protocol for perturbing and evaluating dynamic single-cell epigenetic states. This method (Spear-ATAC) enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at once. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations reveals the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles.

scholarly journals High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

2020 ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Cancer Cells ◽  
High Throughput ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Chromatin Accessibility ◽  
Factor Binding ◽  
Knock Down ◽  
High Throughput Method

AbstractSpear-ATAC is a modified droplet-based single-cell ATAC-seq (scATAC-seq) protocol that enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at a time. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations revealed the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles, demonstrating a high-throughput method for perturbing and evaluating dynamic single-cell epigenetic states.

scholarly journals Single-Nucleus Chromatin Accessibility Landscape Reveals Diversity in Regulatory Regions Across Distinct Adult Rat Cortex

2021 ◽  
Vol 14 ◽  
Author(s):  
Yeya Yu ◽  
Xiaoyu Wei ◽  
Qiuting Deng ◽  
Qing Lan ◽  
Yiping Guo ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Chromatin Accessibility ◽  
Autism Spectrum ◽  
Regulatory Mechanisms ◽  
Sprague Dawley ◽  
Regulatory Regions ◽  
Rat Cortex ◽  
Single Nucleus

Rats have been widely used as an experimental organism in psychological, pharmacological, and behavioral studies by modeling human diseases such as neurological disorders. It is critical to identify and characterize cell fate determinants and their regulatory mechanisms in single-cell resolutions across rat brain regions. Here, we applied droplet-based single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) to systematically profile the single-cell chromatin accessibility across four dissected brain areas in adult Sprague–Dawley (SD) rats with a total of 59,023 single nuclei and identified 16 distinct cell types. Interestingly, we found that different cortex regions exhibit diversity in both cellular compositions and gene regulatory regions. Several cell-type-specific transcription factors (TFs), including SPI1, KLF4, KLF6, and NEUROD2, have been shown to play important roles during the pathogenesis of various neurological diseases, such as Alzheimer’s disease (AD), astrocytic gliomas, autism spectrum disorder (ASD), and intellectual disabilities. Therefore, our single-nucleus atlas of rat cortex could serve as an invaluable resource for dissecting the regulatory mechanisms underlying diverse cortex cell fates and further revealing the regulatory networks of neuropathogenesis.

scholarly journals Global Prediction of Chromatin Accessibility Using RNA-seq from Small Number of Cells

2016 ◽  
Author(s):  
Weiqiang Zhou ◽  
Zhicheng Ji ◽  
Hongkai Ji
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Regulatory Element ◽  
Cell Number ◽  
Chromatin Accessibility ◽  
Small Cell ◽  
Rna Seq ◽  
Genome Wide ◽  
Gene Regulatory ◽  
Number Of Cells

Conventional high-throughput technologies for mapping regulatory element activities such as ChIP-seq, DNase-seq and FAIRE-seq cannot analyze samples with small number of cells. The recently developed ATAC-seq allows regulome mapping in small-cell-number samples, but its signal in single cell or samples with ≤500 cells remains discrete or noisy. Compared to these technologies, measuring transcriptome by RNA-seq in single-cell and small-cell-number samples is more mature. Here we show that one can globally predict chromatin accessibility and infer regulome using RNA-seq. Genome-wide chromatin accessibility predicted by RNA-seq from 30 cells is comparable with ATAC-seq from 500 cells. Predictions based on single-cell RNA-seq can more accurately reconstruct bulk chromatin accessibility than using single-cell ATAC-seq by pooling the same number of cells. Integrating ATAC-seq with predictions from RNA-seq increases power of both methods. Thus, transcriptome-based prediction can provide a new tool for decoding gene regulatory programs in small-cell-number samples.

scholarly journals Constructing Gene Regulatory Networks using Epigenetic Data

2020 ◽  
Author(s):  
Abhijeet Rajendra Sonawane ◽  
Dawn L. DeMeo ◽  
John Quackenbush ◽  
Kimberly Glass
Keyword(s):  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Message Passing ◽  
Regulatory Networks ◽  
Transcription Factor Binding ◽  
Chromatin Accessibility ◽  
Sequence Motif ◽  
Epigenetic Information ◽  
Factor Binding ◽  
Gene Regulatory

AbstractThe biological processes that drive cellular function can be represented by a complex network of interactions between regulators (transcription factors) and their targets (genes). A cell’s epigenetic state plays an important role in mediating these interactions, primarily by influencing chromatin accessibility. However, effectively leveraging epigenetic information when constructing regulatory networks remains a challenge. We developed SPIDER, which incorporates epigenetic information (DNase-Seq) into a message passing framework in order to estimate gene regulatory networks. We validated SPIDER’s predictions using ChlP-Seq data from ENCODE and found that SPIDER networks were more accurate than other publicly available, epigenetically informed regulatory networks as well as networks based on methods that leverage epigenetic data to predict transcription factor binding sites. SPIDER was also able to improve the detection of cell line specific regulatory interactions. Notably, SPIDER can recover ChlP-seq verified transcription factor binding events in the regulatory regions of genes that do not have a corresponding sequence motif. Constructing biologically interpretable, epigenetically informed networks using SPIDER will allow us to better understand gene regulation as well as aid in the identification of cell-specific drivers and biomarkers of cellular phenotypes.

scholarly journals TRACE: transcription factor footprinting using chromatin accessibility data and DNA sequence

2019 ◽  
Author(s):  
Ningxin Ouyang ◽  
Alan P. Boyle
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Chromatin Accessibility ◽  
Training Data ◽  
Distinct Advantage ◽  
Factor Binding ◽  
Dna Elements

AbstractTranscription is tightly regulated by cis-regulatory DNA elements where transcription factors can bind. Thus, identification of transcription factor binding sites is key to understanding gene expression and whole regulatory networks within a cell. The standard approaches for transcription factor binding sites (TFBSs) prediction such as position weight matrices (PWMs) and chromatin immunoprecipitation followed by sequencing (ChIP-seq) are widely used but have their drawbacks such as high false positive rates and limited antibody availability, respectively. Several computational footprinting algorithms have been developed to detect TFBSs by investigating chromatin accessibility patterns, but also have their limitations. To improve on these methods, we have developed a footprinting method to predict Transcription factor footpRints in Active Chromatin Elements (TRACE). Trace incorporates DNase-seq data and PWMs within a multivariate Hidden Markov Model (HMM) to detect footprint-like regions with matching motifs. Trace is an unsupervised method that accurately annotates binding sites for specific TFs automatically with no requirement on pre-generated candidate binding sites or ChIP-seq training data. Compared to published footprinting algorithms, TRACE has the best overall performance with the distinct advantage of targeting multiple motifs in a single model.

scholarly journals High-Throughput ChIPmentation: freely scalable, single day ChIPseq data generation from very low cell-numbers

2018 ◽  
Author(s):  
Charlotte Gustafsson ◽  
Ayla De Paepe ◽  
Christian Schmidl ◽  
Robert Månsson
Keyword(s):  
Transcription Factor ◽  
Histone Modifications ◽  
High Throughput ◽  
Chromatin Immunoprecipitation ◽  
Dna Purification ◽  
Data Generation ◽  
Cell Numbers ◽  
Factor Binding ◽  
Genome Wide ◽  
A Genome

AbstractChromatin immunoprecipitation coupled to sequencing (ChIP-seq) is widely used to map histone modifications and transcription factor binding on a genome-wide level. Here, we present high-throughput ChIPmentation (HT-ChIPmentation) that eliminates the need for DNA purification prior to library amplification and reduces reverse-crosslinking time from hours to minutes. The resulting workflow is easily established, extremely rapid, and compatible with requirements for very low numbers of FACS sorted cells, high-throughput applications and single day data generation.

scholarly journals Zelda potentiates transcription factor binding to zygotic enhancers by increasing local chromatin accessibility during early Drosophila melanogaster embryogenesis

2018 ◽  
Author(s):  
Xiao-Yong Li ◽  
Michael B. Eisen
Keyword(s):  
Transcription Factor ◽  
Structural Changes ◽  
Temporal Dynamics ◽  
Transcription Factor Binding ◽  
Chromatin Accessibility ◽  
Additional Function ◽  
Factor Binding ◽  
Early Embryos ◽  
Chromatin Structural ◽  
Pioneer Factor

AbstractThe maternally deposited transcription factor Zelda binds to and is required for the activation of a large number of genes in early Drosophila development, and has been suggested to act as a pioneer factor. In this study, we investigated the temporal dynamics of Zelda binding along with the maternal patterning factors Dorsal and Caudal during early embryogenesis. We found in regions bound by Zelda and either Dorsal or Caudal, Zelda binding was detected, and reached maximum levels, earlier than Caudal and Dorsal, providing support of its role as a pioneer factor. We found that Dorsal and Caudal binding correlated strongly with Zelda binding at mitotic cycle 12, suggesting that Zelda is important for early binding by these factors and early onset of their target gene expression. At the same time, we show that among Dorsal target enhancers, the dorsal and ventral ectoderm enhancers are much more strongly associated with Zelda than mesoderm enhancers, revealing an additional function of Zelda in coordinating spatial activity of enhancers. We have also investigated the role of Zelda on chromatin structure. We found that in early embryos, before Dorsal and Caudal are bound at significant levels, Zelda binding is associated with histone acetylation and local histone depletion. These chromatin associated changes accompanied with increased local chromatin accessibility were also detected around Zelda peaks in coding sequences that do not appear to play a role in subsequent transcription factor binding. These findings suggest that Zelda binding itself can lead to chromatin structural changes. Finally, we found that Zelda motifs, both bound and unbound, tend to be associated with positioned nucleosomes, which we suggest may be important for the regulatory specificity of enhancers.

scholarly journals Accurate estimation of intrinsic biases for improved analysis of chromatin accessibility sequencing data using SELMA

2021 ◽  
Author(s):  
Shengen Shawn Hu ◽  
Lin Liu ◽  
Qi Li ◽  
Wenjing Ma ◽  
Michael J Guertin ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Dna Cleavage ◽  
Transcription Factor Binding ◽  
Chromatin Accessibility ◽  
Computational Method ◽  
Accurate Estimation ◽  
Bias Estimation ◽  
Sequencing Data ◽  
Factor Binding

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. We also demonstrate improved cell clustering of single-cell ATAC-seq data by considering the SELMA-estimated bias effect. SELMA can be applied to existing bioinformatics tools to improve the analysis of chromatin accessibility sequencing data.

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