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

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.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf

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.


2020 ◽  
Vol 126 (7) ◽  
pp. 875-888 ◽  
Author(s):  
Samir Sissaoui ◽  
Jun Yu ◽  
Aimin Yan ◽  
Rui Li ◽  
Onur Yukselen ◽  
...  

Rationale: Significant progress has revealed transcriptional inputs that underlie regulation of artery and vein endothelial cell fates. However, little is known concerning genome-wide regulation of this process. Therefore, such studies are warranted to address this gap. Objective: To identify and characterize artery- and vein-specific endothelial enhancers in the human genome, thereby gaining insights into mechanisms by which blood vessel identity is regulated. Methods and Results: Using chromatin immunoprecipitation and deep sequencing for markers of active chromatin in human arterial and venous endothelial cells, we identified several thousand artery- and vein-specific regulatory elements. Computational analysis revealed that NR2F2 (nuclear receptor subfamily 2, group F, member 2) sites were overrepresented in vein-specific enhancers, suggesting a direct role in promoting vein identity. Subsequent integration of chromatin immunoprecipitation and deep sequencing data sets with RNA sequencing revealed that NR2F2 regulated 3 distinct aspects related to arteriovenous identity. First, consistent with previous genetic observations, NR2F2 directly activated enhancer elements flanking cell cycle genes to drive their expression. Second, NR2F2 was essential to directly activate vein-specific enhancers and their associated genes. Our genomic approach further revealed that NR2F2 acts with ERG (ETS-related gene) at many of these sites to drive vein-specific gene expression. Finally, NR2F2 directly repressed only a small number of artery enhancers in venous cells to prevent their activation, including a distal element upstream of the artery-specific transcription factor, HEY2 (hes related family bHLH transcription factor with YRPW motif 2). In arterial endothelial cells, this enhancer was normally bound by ERG, which was also required for arterial HEY2 expression. By contrast, in venous endothelial cells, NR2F2 was bound to this site, together with ERG, and prevented its activation. Conclusions: By leveraging a genome-wide approach, we revealed mechanistic insights into how NR2F2 functions in multiple roles to maintain venous identity. Importantly, characterization of its role at a crucial artery enhancer upstream of HEY2 established a novel mechanism by which artery-specific expression can be achieved.


2016 ◽  
Author(s):  
Esben Eickhardt ◽  
Thomas Damm Als ◽  
Jakob Grove ◽  
Anders Dupont Boerglum ◽  
Francesco Lescai

AbstractBackgroundVariants in transcription factor binding sites (TFBSs) may have important regulatory effects, as they have the potential to alter transcription factor (TF) binding affinities and thereby affecting gene expression. With recent advances in sequencing technologies the number of variants identified in TFBSs has increased, hence understanding their role is of significant interest when interpreting next generation sequencing data. Current methods have two major limitations: they are limited to predicting the functional impact of single nucleotide variants (SNVs) and often rely on additional experimental data, laborious and expensive to acquire. We propose a purely bioinformatic method that addresses these two limitations while providing comparable results.ResultsOur method uses position weight matrices and a sliding window approach, in order to account for the sequence context of variants, and scores the consequences of both SNVs and INDELs in TFBSs. We tested the accuracy of our method in two different ways. Firstly, we compared it to a recent method based on DNase I hypersensitive sites sequencing (DHS-seq) data designed to predict the effects of SNVs: we found a significant correlation of our score both with their DHS-seq data and their prediction model. Secondly, we called INDELs on publicly available DHS-seq data from ENCODE, and found our score to represent well the experimental data. We concluded that our method is reliable and we used it to describe the landscape of variation in TFBSs in the human genome, by scoring all variants in the 1000 Genomes Project Phase 3. Surprisingly, we found that most insertions have neutral effects on binding sites, while deletions, as expected, were found to have the most severe TFBS-scores. We identified four categories of variants based on their TFBS-scores and tested them for enrichment of variants classified as pathogenic, benign and protective in ClinVar: we found that the variants with the most negative TFBS-scores have the most significant enrichment for pathogenic variants.ConclusionsOur method addresses key shortcomings of currently available bioinformatic tools in predicting the effects of INDELs in TFBSs, and provides an unprecedented window into the genome-wide landscape of INDELs, their predicted influences on TF binding, and potential relevance for human diseases. We thus offer an additional tool to help prioritising non-coding variants in sequencing studies.


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