Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility

Xing, Q.; Farran, Chadi A. El; Zeng, Ying Ying; Yao, Yi; Warrier, Tushar; Gautam, Pradeep; Collins, James J.; Xu, Jian; Dröge, Peter; Koh, Cheng-Gee; Li, Hu; Zhang, Li Feng; Loh, Yuin-Han

doi:10.1101/gr.257840.119

Cited by 63 publications

(24 citation statements)

References 91 publications

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“…This is followed by bisulfite sequencing of nonmethylated cytosine to obtain information on regions that are not protected by the nucleosomes [ 25 , 26 ]. Recent advancements in single-cell chromatin accessibility assays involve combinations of multiple readouts to maximize information extracted from the same cell [ 27 – 29 ]. Each method comes with its own bias in enrichment or loss of signals.…”

Section: Single-cell and Low-input Techniquesmentioning

confidence: 99%

Chromatin Regulation in Development: Current Understanding and Approaches

Zheng

Sam

Zeng

et al. 2021

Stem Cells International

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The regulation of mammalian stem cell fate during differentiation is complex and can be delineated across many levels. At the chromatin level, the replacement of histone variants by chromatin-modifying proteins, enrichment of specific active and repressive histone modifications, long-range gene interactions, and topological changes all play crucial roles in the determination of cell fate. These processes control regulatory elements of critical transcriptional factors, thereby establishing the networks unique to different cell fates and initiate waves of distinctive transcription events. Due to the technical challenges posed by previous methods, it was difficult to decipher the mechanism of cell fate determination at early embryogenesis through chromatin regulation. Recently, single-cell approaches have revolutionised the field of developmental biology, allowing unprecedented insights into chromatin structure and interactions in early lineage segregation events during differentiation. Here, we review the recent technological advancements and how they have furthered our understanding of chromatin regulation during early differentiation events.

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Section: Single-cell and Low-input Techniquesmentioning

confidence: 99%

Chromatin Regulation in Development: Current Understanding and Approaches

Zheng

Sam

Zeng

et al. 2021

Stem Cells International

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“…Furthermore, new technologies now enable the co-assay of multiple cellular modalities in single cells, including DNA accessibility alongside mRNA abundance [Cao et al, 2018, Clark et al, 2018, Ludwig et al, 2019, Zhu et al, 2019, Xing et al, 2020, Liu et al, 2019, Ma et al, 2020, protein abundance , Fiskin et al, 2020, Swanson et al, 2020, CRISPR guide RNAs [Rubin et al, 2019, or spatial position [Thornton et al, 2019]. These datasets present unique opportunities to learn the relationships between cellular modalities , and will be especially powerful in deciphering the regulatory roles of noncoding DNA sequences.…”

Section: Introductionmentioning

confidence: 99%

Multimodal single-cell chromatin analysis with Signac

Stuart

Srivastava

Lareau

et al. 2020

Preprint

149

172

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The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a framework for the analysis of single-cell chromatin data, as an extension of the Seurat R toolkit for single-cell multimodal analysis. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis, and interactive visualization. Furthermore, Signac facilitates the analysis of multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance, and mitochondrial genotype. We demonstrate scaling of the Signac framework to datasets containing over 700,000 cells.AvailabilityInstallation instructions, documentation, and tutorials are available at: https://satijalab.org/signac/

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“…Thus, it is now possible to access almost all types of omic data at single-cell resolution. Currently, multimodal single-cell omics, where two omic profiles (e.g., proteomics and transcriptomics) are captured for the same cell [ 14 ], and spatially resolved techniques are pushing the frontier of possibility [ 15 ]. The breadth of single-cell omics available underlines the importance of innovative strategies for advanced data analysis.…”

Section: Introductionmentioning

confidence: 99%

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches

Weiskittel

Correia

et al. 2021

Genes

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Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has revolutionized biomedical imaging analysis, drug discovery, and systems biology, is an ideal strategy to fill these gaps in single-cell studies. Machine learning additionally has proven to be remarkably synergistic with single-cell data because it remedies unique challenges while capitalizing on the positive aspects of single-cell data. In this review, we describe how systems-biology algorithms have layered machine learning with biological components to provide systems level analyses of single-cell omics data, thus elucidating complex biological mechanisms. Accordingly, we highlight the trifecta of single-cell, systems-biology, and machine-learning approaches and illustrate how this trifecta can significantly contribute to five key areas of scientific research: cell trajectory and identity, individualized medicine, pharmacology, spatial omics, and multi-omics. Given its success to date, the systems-biology, single-cell omics, and machine-learning trifecta has proven to be a potent combination that will further advance biomedical research.

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Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility

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Cited by 63 publications

References 91 publications

Chromatin Regulation in Development: Current Understanding and Approaches

Chromatin Regulation in Development: Current Understanding and Approaches

Multimodal single-cell chromatin analysis with Signac

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches

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