High-throughput chromatin accessibility profiling at single-cell resolution

Mezger, Anja; Klemm, Sandy; Mann, Ishminder; Brower, Kara; Mir, Alain; Bostick, Magnolia; Farmer, Andrew; Linnarsson, Sten; Greenleaf, William J.

doi:10.1038/s41467-018-05887-x

Cited by 134 publications

(92 citation statements)

References 21 publications

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“…We have shown that CUT&Tag provides high-quality single-cell profiles using the ICELL8 nanodispensation system 12 , which allows for imaging prior to reagent addition and PCR. Likewise, CUT&Tag should be suitable for the 10X Genomics encapsulation system 13 by adaptation of their recently announced ATAC-seq single-cell protocol 28 .…”

Section: Discussionmentioning

confidence: 99%

“…Although CUT&RUN can generate high-quality data from as few as 100-1000 cells, it must be followed by DNA end polishing and adapter ligation to prepare sequencing libraries, which increases the time, cost and effort of the overall procedure. Moreover, the release of MNase-cleaved fragments into the supernatant with CUT&RUN is not well-suited for application to single-cell platforms 12,13 .…”

Section: Introductionmentioning

confidence: 99%

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CUT&Tag for efficient epigenomic profiling of small samples and single cells

Kaya-Okur

Codomo

et al. 2019

Preprint

220

439

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Many chromatin features play critical roles in regulating gene expression. A complete understanding of gene regulation will require the mapping of specific chromatin features in small samples of cells at high resolution. Here we describe Cleavage Under Targets and Tagmentation (CUT&Tag), an enzyme-tethering strategy that provides efficient high-resolution sequencing libraries for profiling diverse chromatin components. In CUT&Tag, a chromatin protein is bound in situ by a specific antibody, which then tethers a protein A-Tn5 transposase fusion protein. Activation of the transposase efficiently generates fragment libraries with high resolution and exceptionally low background. All steps from live cells to sequencing-ready libraries can be performed in a single tube on the benchtop or a microwell in a high-throughput pipeline, and the entire procedure can be performed in one day. We demonstrate the utility of CUT&Tag by profiling histone modifications, RNA Polymerase II and transcription factors on low cell numbers and single cells.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CUT&Tag for efficient epigenomic profiling of small samples and single cells

Kaya-Okur

Codomo

et al. 2019

Preprint

220

439

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“…Generally, the number of samples appears more important than read depth, and results using the full set were consistent for a coverage as low as 1-5 million processed reads per sample (see Methods). Although the subsampling results are dataset-specific and difficult to generalize they provide guidelines for the applicability of diffTF and are in line with single-cell ATAC-Seq data analysis that also show robustness for low coverage at the level of genome-wide summary statistics (Mezger et al, 2018) .…”

Section: Case-study I: Quantify Differential Tf Activity In a Large Amentioning

confidence: 67%

Quantification of differential transcription factor activity and multiomics-based classification into activators and repressors:diffTF

Berest

Arnold²,

Reyes-Palomares³

et al. 2018

Preprint

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Transcription factor (TF) activity constitutes an important readout of cellular signalling pathways and thus for assessing regulatory differences across conditions. However, current technologies lack the ability to simultaneously assess activity changes for multiple TFs and in particular to determine whether a specific TF acts as repressor or activator. To this end, we introduce a widely applicable genome-wide method diffTF to assess differential TF binding activity and classifying TFs as activator or repressor by integrating any type of genome-wide chromatin with RNA-Seq data and in-silico predicted TF binding sites (available at https://git.embl.de/grp-zaugg/diffTF). We apply diffTF to a large ATAC-Seq dataset of mutated and unmutated chronic lymphocytic leukemia and identify dozens of TFs that are differentially active. Around 40% of them have a previously described association with CLL while~60% constitute potentially novel TFs driving the different CLL subtypes. Finally, we validated the method experimentally using the well studied system of hematopoietic differentiation in mouse.

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“…This is most evident in situations where RNA is prepared from complex mixtures of cells, such as healthy tissues samples and cancer biopsies. Single-cell strategies that can both resolve cell heterogeneity and infer RE activity have been developed, but they still provide a relatively shallow (discontinuous) and noisy view of RE activity per cell (e.g., Buenrostro et al, 2015;Cusanovich et al, 2015;Chen et al, 2018;Cusanovich et al, 2018a;Cusanovich et al, 2018bMezger et al, 2018Kuono et al, 2019). These properties limit the usefulness of single-cell strategies for VEnCode determination, which requires very stringent RE activity criteria, especially for negative RE activity calls.…”

Section: Vencodes Using Single-cell Sequencing Datamentioning

confidence: 99%

The intersectional genetics landscape for human

Macedo

Gontijo

2019

Preprint

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The human body is made up of hundreds, perhaps thousands of cell types and states, most of which are currently inaccessible genetically. Genetic accessibility carries significant diagnostic and therapeutic potential by allowing the selective delivery of genetic messages or cures to cells. Research in model organisms has shown that single regulatory element (RE) activities are seldom cell type specific, limiting their usage in genetic systems designed to restrict gene expression posteriorly to their delivery to cells. Intersectional genetic approaches can theoretically increase the number of genetically accessible cells, but the scope and safety of these approaches to human have not been systematically assessed due primarily to the lack of suitable thorough RE activity databases and methods to explore them. A typical intersectional method acts like an AND logic gate by converting the input of two or more active REs into a single synthetic output, which becomes unique for that cell. Here, we systematically assessed the intersectional genetics landscape of human using a curated subset of cells from a large RE usage atlas obtained by Cap Analysis of Gene Expression sequencing (CAGE-seq) of thousands of primary and cancer cells (the FANTOM5 consortium atlas). We developed the heuristics and algorithms to retrieve AND gate intersections and quality-rank them intra-and interindividually.We find that >90% of the 154 primary cell types surveyed can be distinguished from each other with as little as 3 to 4 active REs, with quantifiable safety and robustness. We call these minimal intersections of active REs with cell-type diagnostic potential "Versatile Entry Codes" (VEnCodes). Each of the 158 cancer cell types surveyed could also be distinguished from the healthy primary cell types with small VEnCodes, most of which were highly robust to intra-and interindividual variation. Finally, we provide methods for the cross-validation of CAGE-seq-derived VEnCodes and for the extraction of VEnCodes from pooled single cell sequencing data. Our work provides a systematic view of the intersectional genetics landscape in human and demonstrates the potential of these approaches for future gene delivery technologies in human.

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High-throughput chromatin accessibility profiling at single-cell resolution

Cited by 134 publications

References 21 publications

CUT&Tag for efficient epigenomic profiling of small samples and single cells

CUT&Tag for efficient epigenomic profiling of small samples and single cells

Quantification of differential transcription factor activity and multiomics-based classification into activators and repressors:diffTF

The intersectional genetics landscape for human

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