scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells

Clark, Stephen J.; Argelaguet, Ricard; Kapourani, Chantriolnt-Andreas; Stubbs, Thomas M.; Lee, Heather; Alda-Catalinas, Celia; Krueger, Felix; Sanguinetti, Guido; Kelsey, Gavin; Marioni, John C.; Stegle, Oliver; Reik, Wolf

doi:10.1101/138685

Cited by 121 publications

(166 citation statements)

References 35 publications

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“…As NMF algorithms have recently been successfully applied to single-cell RNAseq data in order to obtain clusters or subgroups [43,44], our feature extraction methodology could be applied to such factorizations and map features to subgroups. In addition the ability of our method to integrate across multiple omics layers could also benefit the analysis of upcoming datasets with multi-omics measurements in single cells [45][46][47].…”

Section: Discussionmentioning

confidence: 99%

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Huebschmann

Kurzawa

Steinhauser

et al. 2017

Preprint

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Metazoans are crucially dependent on multiple layers of gene regulatory mechanisms which allow them to control gene expression across developmental stages, tissues and cell types.Multiple recent research consortia have aimed to generate comprehensive datasets to profile the activity of these cell type-and condition-specific regulatory landscapes across many different cell lines and primary cells. However, extraction of genes or regulatory elements specific to certain entities from these datasets remains challenging. We here propose a novel method based on non-negative matrix factorization for disentangling and associating peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/199547 doi: bioRxiv preprint first posted online 2 huge multi-assay datasets including chromatin accessibility and gene expression data.Taking advantage of implementations of NMF algorithms in the GPU CUDA environment full datasets composed of tens of thousands of genes as well as hundreds of samples can be processed without the need for prior feature selection to reduce the input size. Applying this framework to multiple layers of genomic data derived from human blood cells we unravel mechanisms of regulation of cell type-specific expression in T-cells and monocytes.

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Section: Discussionmentioning

confidence: 99%

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Huebschmann

Kurzawa

Steinhauser

et al. 2017

Preprint

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“…Similarly, scTrio‐Seq integrates parallel transcriptome analysis and bisulfite sequencing DNA copy number analysis to perform genome, epigenome, and transcriptome analysis of the same cell . Recently, the G&T‐seq method has further been adapted to incorporate NOME‐seq analysis of the same single cell, giving a triple readout of chromatin accessibility, DNA methylation, and gene expression …”

Section: Concepts and Methods For Single‐cell Isolation And Profilingmentioning

confidence: 99%

Defining Cell Identity with Single‐Cell Omics

et al. 2018

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Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation—most notably in the emergence and evolution of tumors. Recent technical advances in single‐cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.

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“…Epigenetic alterations such as DNA and histone modifications, RNA interference, nucleosome positioning, and chromatin remodeling, can regulate the structure of chromatin and control gene expression, therefore interacting and subsequently promoting malignancy‐associated phenotypes, such as cellular differentiation, growth, invasion, metabolism, apoptosis, genomic instability, and modulation of autophagy (Fig ). Therefore, the epigenetic regulation of autophagy‐lyosome system should be given more consideration as potential cancer treatments.…”

Section: Epigenetic Regulation Of Adaptive Autophagy‐lyosome Systemmentioning

confidence: 99%

Transcriptional regulation of autophagy‐lysosomal pathway in cancer

Chang

Dong

2020

Thoracic Cancer

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The transcriptional regulation of autophagy-lysosomal pathway adapts to cellular stress and enables advanced cancer cells survive. This pathway plays an oncopromoting or oncosuppressing role, depending on context-dependent stresses and treatment resistance. It remains controversial whether this pathway represents a target for drugs, although autophagy-lysosomal inducers and inhibitors have been tested in clinical trials for cancer treatment. Therefore, identifying the transcriptional regulators of autophagy-lysosomal pathway may lead to the development of effective cancer treatment and the improvement of the existing targeted cancer therapies. In this review, we summarize findings from several published studies on transcriptional regulation of autophagy-lysosomal pathway in cancer biology, and evaluate its functional role as a therapeutic target.

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scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells

Cited by 121 publications

References 35 publications

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Defining Cell Identity with Single‐Cell Omics

Transcriptional regulation of autophagy‐lysosomal pathway in cancer

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