NEAT-seq: Simultaneous profiling of intra-nuclear proteins, chromatin accessibility, and gene expression in single cells

Chen, Amy F.; Parks, Benjamin; Kathiria, Arwa S.; Ober-Reynolds, Benjamin; Goronzy, Jörg J.; Greenleaf, William J.

doi:10.1101/2021.07.29.454078

Cited by 13 publications

(12 citation statements)

References 61 publications

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“…This approach remains comprehensive while enabling deeper sequencing coverage of biologically relevant genomic regions. Furthermore, integrated approaches have recently been described that combine measurements of chromatin accessibility with analysis of transcription and other epigenomic features from a single population of cells (Kelly et al 2012;Clark et al 2018;Barnett et al 2020;Chen et al 2022). Similarly, ATAC-STARR-seq has the potential to reveal multiple levels of gene regulatory information simultaneously, but this potential has not been explored.…”

Section: Introductionmentioning

confidence: 99%

ATAC-STARR-seq reveals transcription factor–bound activators and silencers within chromatin-accessible regions of the human genome

Hansen

Hodges

2022

Genome Res.

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Massively parallel reporter assays (MPRAs) test the capacity of putative gene regulatory elements to drive transcription on a genome-wide scale. Most gene regulatory activity occurs within accessible chromatin, and recently described methods have combined assays that capture these regions, such as assay for transposase-accessible chromatin using sequencing (ATAC-seq), with self-transcribing active regulatory region sequencing (STARR-seq) to selectively assay the regulatory potential of accessible DNA (ATAC-STARR-seq). Here, we report an integrated approach that quantifies activating and silencing regulatory activity, chromatin accessibility, and transcription factor (TF) occupancy with one assay using ATAC-STARR-seq. Our strategy, including important updates to the ATAC-STARR-seq assay and workflow, enabled high-resolution testing of ~50 million unique DNA fragments tiling ~101,000 accessible chromatin regions in human lymphoblastoid cells. We discovered that 30% of all accessible regions contain an activator, a silencer or both. Although few MPRA studies have explored silencing activity, we demonstrate silencers occur at similar frequencies to activators, and they represent a distinct functional group enriched for unique TF motifs and repressive histone modifications. We further show that Tn5 cut-site frequencies are retained in the ATAC-STARR plasmid library compared to standard ATAC-seq, enabling TF occupancy to be ascertained from ATAC-STARR data. With this approach, we found that activators and silencers cluster by distinct TF footprint combinations and these groups of activity represent different gene regulatory networks of immune cell function. Altogether, these data highlight the multi-layered capabilities of ATAC-STARR-seq to comprehensively investigate the regulatory landscape of the human genome all from a single DNA fragment source.

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Section: Introductionmentioning

confidence: 99%

ATAC-STARR-seq reveals transcription factor–bound activators and silencers within chromatin-accessible regions of the human genome

Hansen

Hodges

2022

Genome Res.

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“…auto encoders that fit TF activities as latent variables informed by prior knowledge of TFgene relations 45 and mechanism-based deep learning models 34 . There is also development of sequencing based methods that simultaneously profile chromatin accessibility, intra-nuclear proteins, and gene expression 46 , which could aid in acquiring more accurate TF activity estimates. There are presently several methods that strive to infer signaling patterns from transcriptomics data and prior knowledge of the signaling-and regulatory networks, e.g.…”

Section: Discussionmentioning

confidence: 99%

Artificial neural networks enable genome-scale simulations of intracellular signaling

Nilsson

Peters

Bryson

et al. 2021

Preprint

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Mammalian cells adapt their functional state in response to external signals in form of ligands that bind receptors on the cell-surface. Mechanistically, this involves signal-processing through a complex network of molecular interactions that govern transcription factor (TF) activity patterns. Computer simulations of the information flow through this network could help predict cellular responses in health and disease. Here we develop a recurrent neural network constrained by prior knowledge of the signaling network with ligand concentrations as input, TF activity as output and signaling molecules as hidden nodes. Simulations are assumed to reach steady state, and we regularize the parameters to enforce this. Using synthetic data, we train models that generalize to unseen data and predict the effects of gene knockouts. We also fit models to a small experimental data set from literature and confirm the predictions using cross validation. This demonstrates the feasibility of simulating intracellular signaling at the genome-scale.

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“…1 and 2 ), which does not require custom sequencing primers or recipes. Furthermore, with the recent development of multi-omics methods that utilize antibody-oligo conjugates, such as TEA-seq 28 , DOGMA-seq 27 and NEAT-seq 47 , it is possible to capture ATAC, RNA and protein information from the same cell. Similar design can also be applied in the ISSAAC-seq method to collect additional information (see Supplementary Note 4 ).…”

Section: Main Textmentioning

confidence: 99%

ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells

Yang

Zhang

et al. 2022

Preprint

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Joint profiling of chromatin accessibility and gene expression from the same single cell/nucleus provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms. However, many methods are currently limited by low sensitivity, low throughput or complex workflow. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single nucleus. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from over 10,000 nuclei from the mouse cerebral cortex, we uncovered major and rare cell types and cell-type specific regulatory elements and identified heterogeneity at the chromatin level within established cell types defined by gene expression. Finally, we revealed distinct dynamics and relationships of gene expression and chromatin accessibility during an oligodendrocyte maturation trajectory.

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NEAT-seq: Simultaneous profiling of intra-nuclear proteins, chromatin accessibility, and gene expression in single cells

Cited by 13 publications

References 61 publications

ATAC-STARR-seq reveals transcription factor–bound activators and silencers within chromatin-accessible regions of the human genome

ATAC-STARR-seq reveals transcription factor–bound activators and silencers within chromatin-accessible regions of the human genome

Artificial neural networks enable genome-scale simulations of intracellular signaling

ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells

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