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 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 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 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.

scholarly journals A simplified high-throughput method for pyrethroid knock-down resistance (kdr) detection in Anopheles gambiae

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Amy Lynd ◽  
Hilary Ranson ◽  
P J McCall ◽  
Nadine P Randle ◽  
William C Black ◽  
...  
Keyword(s):  
Anopheles Gambiae ◽  
High Throughput ◽  
Knock Down ◽  
High Throughput Method

scholarly journals 192 Pooled T cell receptor screening (POTS) provides unbiased, high-throughput method for TCR discovery

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A204-A204
Author(s):  
Jack Reid ◽  
Shihong Zhang ◽  
Ariunaa Munkhbat ◽  
Matyas Ecsedi ◽  
Megan McAfee ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
T Cell Receptor ◽  
High Throughput ◽  
Ex Vivo ◽  
Cell Receptor ◽  
High Avidity ◽  
Reporter System ◽  
High Throughput Method

BackgroundT Cell Receptor (TCR)-T cell therapies have shown some promising results in cancer clinical trials, however the efficacy of treatment remains suboptimal. Outcomes could potentially be improved by utilizing highly functional TCRs for future trials. Current TCR discovery methods are relatively low throughput and rely on synthesis and screening of individual TCRs based on tetramer binding and peptide specificity, which is costly and labor intensive. We have developed and validated a pooled approach relying on directly cloned TCRs transduced into a fluorescent Jurkat reporter system (figure 1). This approach provides an unbiased, high-throughput method for TCR discovery.MethodsAs a model for POTS, T cells specific for a peptide derived adenovirus structural protein were sorted on tetramer and subjected to 10x single cell VDJ analysis. Pools of randomly paired TCR alpha and beta chains were cloned from the 10x cDNA into a lentiviral vector and transduced into a Jurkat reporter cells. Consecutive stimulations with cognate antigen followed by cell sorts were performed to enrich for functional TCRs. Full length TCRab pools were sequenced by Oxford Nanopore Technologies (ONT) and compared to a 10x dataset to find naturally paired TCRs.ResultsComparison between the ex vivo single cell VDJ sequencing and ONT sequencing of the transduced antigen specific TCRs showed more than 99% of the TCR pairs found in reporter positive Jurkat cells were naturally paired TCRs. The functionality of 8 TCR clonotypes discovered using POTS were compared and clone #2 showed the strongest response. Of the selected clonotypes, clone #2 showed a low frequency of 0.9% in the ex vivo single cell VDJ sequencing. After the first round of stimulation and sequencing, clone #2 takes up of 5% of all reporter-positive clones. The abundance of clone #2 further increased to 17% after another round of stimulation, sorting and sequencing, suggesting this method can retrieve and enrich for highly functional antigen specific TCRs.Abstract 192 Figure 1Outline of the POTS workflow.ConclusionsPOTS provides a high-throughput method for discovery of naturally paired, high-avidity T cell receptors. This method mitigates bias introduced by T cell differentiation state by screening TCRs in a clonal reporter system. Additionally, POTS allows for screening of low abundance clones when compared with traditional TCR discovery techniques. Pooled TCRs could also be screened in vivo with primary T cells in a mouse model to screen for the most functional and physiologically fit TCR for cancer treatment.

scholarly journals A high‐throughput method to identify trans‐activation domains within transcription factor sequences

2018 ◽  
Vol 37 (16) ◽  
Author(s):  
Cosmas D Arnold ◽  
Filip Nemčko ◽  
Ashley R Woodfin ◽  
Sebastian Wienerroither ◽  
Anna Vlasova ◽  
...  
Keyword(s):  
Transcription Factor ◽  
High Throughput ◽  
Activation Domains ◽  
High Throughput Method

scholarly journals ATAC-seq with unique molecular identifiers improves quantification and footprinting

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Tao Zhu ◽  
Keyan Liao ◽  
Rongfang Zhou ◽  
Chunjiao Xia ◽  
Weibo Xie
Keyword(s):  
Transcription Factor ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Pcr Amplification ◽  
Chromatin Accessibility ◽  
Link Type ◽  
Pcr Duplicates ◽  
Identify Transcription Factor ◽  
Accessible Chromatin ◽  
Accurate Quantification

AbstractATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) provides an efficient way to analyze nucleosome-free regions and has been applied widely to identify transcription factor footprints. Both applications rely on the accurate quantification of insertion events of the hyperactive transposase Tn5. However, due to the presence of the PCR amplification, it is impossible to accurately distinguish independently generated identical Tn5 insertion events from PCR duplicates using the standard ATAC-seq technique. Removing PCR duplicates based on mapping coordinates introduces increasing bias towards highly accessible chromatin regions. To overcome this limitation, we establish a UMI-ATAC-seq technique by incorporating unique molecular identifiers (UMIs) into standard ATAC-seq procedures. UMI-ATAC-seq can rescue about 20% of reads that are mistaken as PCR duplicates in standard ATAC-seq in our study. We demonstrate that UMI-ATAC-seq could more accurately quantify chromatin accessibility and significantly improve the sensitivity of identifying transcription factor footprints. An analytic pipeline is developed to facilitate the application of UMI-ATAC-seq, and it is available at https://github.com/tzhu-bio/UMI-ATAC-seq.

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