scholarly journals Comprehensive Benchmarking of CITE-seq versus DOGMA-seq Single Cell Multimodal Omics

2021 ◽  
Author(s):  
Zhongli Xu ◽  
Elisa Heidrich-OHare ◽  
Wei Chen ◽  
Richard H. Duerr
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Human Peripheral Blood ◽  
Surface Protein ◽  
Chromatin Accessibility ◽  
Low Loss ◽  
Cell Permeabilization ◽  
Pros And Cons ◽  
Additional Value ◽  
Optimal Incubation

The recently developed transcription, epitopes, and chromatin accessibility by sequencing (TEA-seq) and similar DOGMA-seq single-cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent optimization, benchmarking and evaluation are lacking. We explored the utility, pros and cons of DOGMA-seq compared to the bimodal cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) assay in activated and stimulated human peripheral blood T cells. We identified an optimal incubation time and concentration of digitonin (DIG) for cell permeabilization and found that single-cell trimodal omics measurements after DIG permeabilization were generally better than after an alternative low-loss lysis (LLL) permeabilization condition. Next, we found that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, even though its mRNA and cell surface protein antibody-derived tag (ADT) libraries have slightly inferior quality, compared to CITE-seq. Finally, we recognized the additional value of DOGMA-seq for studying lineage-specific T helper cells.

scholarly journals Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Elliott Swanson ◽  
Cara Lord ◽  
Julian Reading ◽  
Alexander T Heubeck ◽  
Palak C Genge ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Single Cell ◽  
Human Peripheral Blood ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Specific Gene ◽  
Test Case ◽  
Cell Assays ◽  
Paired Measurement

Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

scholarly journals TEA-seq: a trimodal assay for integrated single cell measurement of transcription, epitopes, and chromatin accessibility

2020 ◽  
Author(s):  
Elliott Swanson ◽  
Cara Lord ◽  
Julian Reading ◽  
Alexander T. Heubeck ◽  
Adam K. Savage ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cell ◽  
Human Peripheral Blood ◽  
Signal To Noise Ratio ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Specific Gene ◽  
Test Case ◽  
Cell Assays

AbstractSingle-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to extracellular signals, and human disease states. scATAC-seq has been particularly challenging due to the large size of the human genome and processing artefacts resulting from DNA damage that are an inherent source of background signal. Downstream analysis and integration of scATAC-seq with other single-cell assays is complicated by the lack of clear phenotypic information linking chromatin state and cell type. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases the signal-to-noise ratio and allows simultaneous measurement of cell surface markers: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). We extended this approach using a droplet-based multiomics platform to develop a trimodal assay to simultaneously measure Transcriptomic state (scRNA-seq), cell surface Epitopes, and chromatin Accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

scholarly journals Smart3-ATAC: a highly sensitive method for joint accessibility and full-length transcriptome analysis in single cells

2021 ◽  
Author(s):  
Huaitao Cheng ◽  
Han-pin Pui ◽  
Antonio Lentini ◽  
Solrún Kolbeinsdóttir ◽  
Nathanael Andrews ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Element ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Great Promise ◽  
Low Loss ◽  
Genome Wide ◽  
Highly Sensitive ◽  
Element Activity ◽  
Sensitive Method

AbstractJoint single-cell measurements of gene expression and DNA regulatory element activity holds great promise as a tool to understand transcriptional regulation. Towards this goal we have developed Smart3-ATAC, a highly sensitive method which allows joint mRNA and chromatin accessibility analysis genome wide in single cells. With Smart3-ATAC, we are able to obtain the highest possible quality measurements per cell. The method combines transcriptomic profiling based on the highly sensitive Smart-seq3 protocol on cytosolic mRNA, with a novel low-loss single-cell ATAC (scATAC) protocol to measure chromatin accessibility. Compared to current droplet multiome methods, the yield of both the scATAC protocol and mRNA-seq protocol is markedly higher.

scholarly journals MultiMAP: dimensionality reduction and integration of multimodal data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mika Sarkin Jain ◽  
Krzysztof Polanski ◽  
Cecilia Dominguez Conde ◽  
Xi Chen ◽  
Jongeun Park ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Single Cell ◽  
Binding Site ◽  
Spatial Data ◽  
Cell Biology ◽  
Chromatin Accessibility ◽  
Linear Mapping ◽  
Multimodal Data ◽  
Transcription Factor Expression ◽  
Temporal Trajectory

AbstractMultimodal data is rapidly growing in many fields of science and engineering, including single-cell biology. We introduce MultiMAP, a novel algorithm for dimensionality reduction and integration. MultiMAP can integrate any number of datasets, leverages features not present in all datasets, is not restricted to a linear mapping, allows the user to specify the influence of each dataset, and is extremely scalable to large datasets. We apply MultiMAP to single-cell transcriptomics, chromatin accessibility, methylation, and spatial data and show that it outperforms current approaches. On a new thymus dataset, we use MultiMAP to integrate cells along a temporal trajectory. This enables quantitative comparison of transcription factor expression and binding site accessibility over the course of T cell differentiation, revealing patterns of expression versus binding site opening kinetics.

scholarly journals BABEL enables cross-modality translation between multiomic profiles at single-cell resolution

2021 ◽  
Vol 118 (15) ◽  
pp. e2023070118
Author(s):  
Kevin E. Wu ◽  
Kathryn E. Yost ◽  
Howard Y. Chang ◽  
James Zou
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Training Data ◽  
Grand Challenge ◽  
Widespread Application ◽  
Fine Grained ◽  
Cell Transcriptome ◽  
Cell Expression

Simultaneous profiling of multiomic modalities within a single cell is a grand challenge for single-cell biology. While there have been impressive technical innovations demonstrating feasibility—for example, generating paired measurements of single-cell transcriptome (single-cell RNA sequencing [scRNA-seq]) and chromatin accessibility (single-cell assay for transposase-accessible chromatin using sequencing [scATAC-seq])—widespread application of joint profiling is challenging due to its experimental complexity, noise, and cost. Here, we introduce BABEL, a deep learning method that translates between the transcriptome and chromatin profiles of a single cell. Leveraging an interoperable neural network model, BABEL can predict single-cell expression directly from a cell’s scATAC-seq and vice versa after training on relevant data. This makes it possible to computationally synthesize paired multiomic measurements when only one modality is experimentally available. Across several paired single-cell ATAC and gene expression datasets in human and mouse, we validate that BABEL accurately translates between these modalities for individual cells. BABEL also generalizes well to cell types within new biological contexts not seen during training. Starting from scATAC-seq of patient-derived basal cell carcinoma (BCC), BABEL generated single-cell expression that enabled fine-grained classification of complex cell states, despite having never seen BCC data. These predictions are comparable to analyses of experimental BCC scRNA-seq data for diverse cell types related to BABEL’s training data. We further show that BABEL can incorporate additional single-cell data modalities, such as protein epitope profiling, thus enabling translation across chromatin, RNA, and protein. BABEL offers a powerful approach for data exploration and hypothesis generation.

Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens

2021 ◽  
Author(s):  
Noa Liscovitch-Brauer ◽  
Antonino Montalbano ◽  
Jiale Deng ◽  
Alejandro Méndez-Mancilla ◽  
Hans-Hermann Wessels ◽  
...  
Keyword(s):  
Single Cell ◽  
Chromatin Accessibility ◽  
Genetic Determinants

scholarly journals High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Cancer Cells ◽  
High Throughput ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Chromatin Accessibility ◽  
Regulatory Regions ◽  
Factor Binding ◽  
Genome Wide

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.

scholarly journals Single cell transcriptome atlas of mouse mammary epithelial cells across development

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Bhupinder Pal ◽  
Yunshun Chen ◽  
Michael J. G. Milevskiy ◽  
François Vaillant ◽  
Lexie Prokopuk ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Single Cell ◽  
Developmental Stages ◽  
Mammary Epithelial Cells ◽  
Expression Profiles ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Mammary Epithelial ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Background Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. Methods The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. Results The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. Conclusions This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

scholarly journals SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  
Keyword(s):  
Single Cell ◽  
Posttranslational Modification ◽  
Cellular Differentiation ◽  
Single Cells ◽  
Simultaneous Detection ◽  
Surface Protein ◽  
Rna Seq ◽  
Cell Level ◽  
Simultaneous Integration ◽  
Unique Surface

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.

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