scholarly journals Combined analysis of single cell RNA-Seq and ATAC-Seq data reveals putative regulatory toggles operating in native and iPS-derived retina

2020 ◽  
Author(s):  
Anouk Georges ◽  
Haruko Takeda ◽  
Arnaud Lavergne ◽  
Michiko Mandai ◽  
Fanny Lepiemme ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Retinal Development ◽  
Amacrine Cells ◽  
Regulatory Elements ◽  
Precursor Cells ◽  
Retinal Cell ◽  
Rna Seq ◽  
Combined Analysis ◽  
Temporal Sampling

AbstractBackgroundIt has recently become possible to recapitulate retinal development from induced pluripotent stem cells, opening new investigative and therapeutic opportunities. Single cell RNA sequencing allows comparison of transcriptome unfolding during in vivo and in vitro development at single cell resolution, which can be integrated with information about accessible regulatory elements identified by ATAC-Seq.ResultsWe report the generation and analysis of single-cell RNA-Seq data (> 38,000 cells) from native and iPSC-derived murine retina at four matched developmental stages spanning the emergence of the major retinal cell types. We combine information from temporal sampling, visualization of 3D UMAP manifolds, and RNA velocity to show that iPSC-derived 3D retinal aggregates broadly recapitulate the native developmental trajectories with evidence supporting re-specification from amacrine cells to horizontal and photoreceptor precursor cells, as well as a direct differentiation of Tbr1+ retinal ganglion cells from neuro-epithelium cells. We show relaxation of spatial and temporal transcriptome control, premature emergence and dominance of photoreceptor precursor cells, and susceptibility of dynamically regulated pathways and transcription factors to culture conditions in iPSC-derived retina. We generate bulk ATAC-Seq data for native and iPSC-derived murine retina identifying ∼125,000 peaks. We combine single-cell RNA-Seq with ATAC-Seq information and obtain evidence that approximately halve the transcription factors that are dynamically regulated during retinal development may act as repressors rather than activators. We propose that sets of activators and repressors with cell-type specific expression control “regulatory toggles” that lock cells in distinct transcriptome states underlying differentiation, with subtle but noteworthy differences between native and iPSC-derived retina.ConclusionsCombined analysis of single-cell RNA-Seq and ATAC-Seq information has refined the comparison of native and iPS-derived retinal development.

scholarly journals Molecular identification of sixty-three amacrine cell types completes a mouse retinal cell atlas

2020 ◽  
Author(s):  
Wenjun Yan ◽  
Mallory A. Laboulaye ◽  
Nicholas M. Tran ◽  
Irene E. Whitney ◽  
Inbal Benhar ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
High Throughput ◽  
Amacrine Cells ◽  
Cell Types ◽  
Retinal Cell ◽  
Mouse Retina ◽  
Single Cell Rna Sequencing ◽  
Neuronal Types ◽  
The Brain

ABSTRACTAmacrine cells (ACs) are a diverse class of interneurons that modulate input from photoreceptors to retinal ganglion cells (RGCs), rendering each RGC type selectively sensitive to particular visual features, which are then relayed to the brain. While many AC types have been identified morphologically and physiologically, they have not been comprehensively classified or molecularly characterized. We used high-throughput single-cell RNA sequencing (scRNA-seq) to profile >32,000 ACs from mouse retina, and applied computational methods to identify 63 AC types. We identified molecular markers for each type, and used them to characterize the morphology of multiple types. We show that they include nearly all previously known AC types as well as many that had not been described. Consistent with previous studies, most of the AC types express markers for the canonical inhibitory neurotransmitters GABA or glycine, but several express neither or both. In addition, many express one or more neuropeptides, and two express glutamatergic markers. We also explored transcriptomic relationships among AC types and identified transcription factors expressed by individual or multiple closely related types. Noteworthy among these were Meis2 and Tcf4, expressed by most GABAergic and most glycinergic types, respectively. Together, these results provide a foundation for developmental and functional studies of ACs, as well as means for genetically accessing them. Along with previous molecular, physiological and morphological analyses, they establish the existence of at least 130 neuronal types and nearly 140 cell types in mouse retina.SIGNIFICANCE STATEMENTThe mouse retina is a leading model for analyzing the development, structure, function and pathology of neural circuits. A complete molecular atlas of retinal cell types provides an important foundation for these studies. We used high-throughput single-cell RNA sequencing (scRNA-seq) to characterize the most heterogeneous class of retinal interneurons, amacrine cells, identifying 63 distinct types. The atlas includes types identified previously as well as many novel types. We provide evidence for use of multiple neurotransmitters and neuropeptides and identify transcription factors expressed by groups of closely related types. Combining these results with those obtained previously, we proposed that the mouse retina contains 130 neuronal types, and is therefore comparable in complexity to other regions of the brain.

scholarly journals Single cell RNA-seq reveals cellular diversity and developmental characteristics of human infant retina

2019 ◽  
Author(s):  
Jixing Zhong ◽  
Dongsheng Chen ◽  
Fangyuan Hu ◽  
Fang Chen ◽  
Zaoxu Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
Developmental Process ◽  
Retinal Disease ◽  
Amacrine Cells ◽  
Bipolar Cells ◽  
Human Infant ◽  
Retinal Cell ◽  
Rna Seq ◽  
Human Infants ◽  
Retina Development

AbstractRetina, located in the innermost layer of the eye of human, holds the decisive role in visual perception. Dissecting the heterogeneity of retina is essential for understanding the mechanism of vision formation and even the development of central nervous system (CNS). Here, we performed single cell RNA-seq, analyzed 57,832 cells from human infant donors, resulting in 20 distinct clusters representing major cell types in retina: rod photoreceptors, cone photoreceptors, bipolar cells, horizontal cells, amacrine cells, Muller glia cells and microglia. We next constructed extensive networks of intercellular communication and identified ligand-receptor interactions playing crucial roles in regulating neural cell development and immune homeostasis in retina. Though re-clustering, we identified known subtypes in cone PRs and additional unreported subpopulations and corresponding markers in rod PRs as well as bipolar cells. Additionally, we linked inherited retinal disease to certain cell subtypes or subpopulations through enrichment analysis. Intriguingly, we found that status and functions of photoreceptors changed drastically between early and late retina. Overall, our study offers the first retinal cell atlas in human infants, dissecting the heterogeneity of retina and identifying the key molecules in the developmental process, which provides an important resource that will pave the way for retina development mechanism research and regenerative medicine concerning retinal biology.

scholarly journals Single-cell RNA-seq analysis maps the development of human fetal retina

2018 ◽  
Author(s):  
Yufeng Lu ◽  
Wenyang Yi ◽  
Qian Wu ◽  
Suijuan Zhong ◽  
Zhentao Zuo ◽  
...  
Keyword(s):  
Single Cell ◽  
Visual Information ◽  
Developmental Trajectories ◽  
Retinal Development ◽  
Neuronal Cell ◽  
Cell Types ◽  
Retinal Cell ◽  
Rna Seq ◽  
Fetal Retina ◽  
The Impact

AbstractVision starts with image formation at the retina, which contains diverse neuronal cell types that extract, process, and relay visual information to higher order processing centers in the brain. Though there has been steady progress in defining retinal cell types, very little is known about retinal development in humans, which starts well before birth. In this study, we performed transcriptomic profiling of developing human fetal retina from gestational weeks 12 to 27 using single-cell RNA-seq (scRNA-seq) and used pseudotime analysis to reconstruct the developmental trajectories of retinogenesis. Our analysis reveals transcriptional programs driving differentiation down four different cell types and suggests that Müller glia (MG) can serve as embryonic progenitors in early retinal development. In addition, we also show that transcriptional differences separate retinal progenitor cells (RPCs) into distinct subtypes and use this information to reconstruct RPC developmental trajectories and cell fate. Our results support a hierarchical program of differentiation governing cell-type diversity in the developing human retina. In summary, our work details comprehensive molecular classification of retinal cells, reconstructs their relationships, and paves the way for future mechanistic studies on the impact of gene regulation upon human retinogenesis.

scholarly journals Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

2019 ◽  
Author(s):  
Ning Wang ◽  
Andrew E. Teschendorff
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Dropout Rate ◽  
Rna Seq ◽  
Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

scholarly journals Exploring the Changing Landscape of Cell-to-Cell Variation After CTCF Knockdown via Single Cell RNA-seq

2019 ◽  
Author(s):  
Wei Wang ◽  
Gang Ren ◽  
Ni Hong ◽  
Wenfei Jin
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Cell ◽  
Zinc Finger ◽  
Ctcf Binding ◽  
Rna Seq ◽  
Expression Noise ◽  
Genome Wide ◽  
Cell Variation ◽  
Variable Genes

Abstract Background: CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation is unclear. Results: We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, Zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, indicating tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explain why knockdown of CTCF lead to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions: To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

scholarly journals Improved detection of tumor suppressor events in single-cell RNA-Seq data

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Andrew E. Teschendorff ◽  
Ning Wang
Keyword(s):  
Transcription Factors ◽  
Tumor Suppressor ◽  
Single Cell ◽  
Cancer Cells ◽  
Dropout Rate ◽  
Lung Epithelial Cells ◽  
Rna Seq ◽  
Regulatory Activity ◽  
Tissue Specific ◽  
Early Tumor

Abstract Tissue-specific transcription factors are frequently inactivated in cancer. To fully dissect the heterogeneity of such tumor suppressor events requires single-cell resolution, yet this is challenging because of the high dropout rate. Here we propose a simple yet effective computational strategy called SCIRA to infer regulatory activity of tissue-specific transcription factors at single-cell resolution and use this tool to identify tumor suppressor events in single-cell RNA-Seq cancer studies. We demonstrate that tissue-specific transcription factors are preferentially inactivated in the corresponding cancer cells, suggesting that these are driver events. For many known or suspected tumor suppressors, SCIRA predicts inactivation in single cancer cells where differential expression does not, indicating that SCIRA improves the sensitivity to detect changes in regulatory activity. We identify NKX2-1 and TBX4 inactivation as early tumor suppressor events in normal non-ciliated lung epithelial cells from smokers. In summary, SCIRA can help chart the heterogeneity of tumor suppressor events at single-cell resolution.

scholarly journals Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Qingnan Liang ◽  
Rachayata Dharmat ◽  
Leah Owen ◽  
Akbar Shakoor ◽  
Yumei Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Transcriptome Profiling ◽  
Cell Types ◽  
Retinal Cell ◽  
Peripheral Retina ◽  
Marker Genes ◽  
Rna Seq ◽  
Cell Type ◽  
Retinal Tissue ◽  
The Individual

AbstractSingle-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA-seq (snRNA-seq) transcriptomic study on human retinal tissue, which is composed of multiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models.

scholarly journals Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification

Neuron ◽  
2019 ◽  
Vol 102 (6) ◽  
pp. 1111-1126.e5 ◽  
Author(s):  
Brian S. Clark ◽  
Genevieve L. Stein-O’Brien ◽  
Fion Shiau ◽  
Gabrielle H. Cannon ◽  
Emily Davis-Marcisak ◽  
...  
Keyword(s):  
Single Cell ◽  
Retinal Development ◽  
Mitotic Exit ◽  
Rna Seq ◽  
Cell Specification

scholarly journals CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues

2019 ◽  
Author(s):  
Pawel F. Przytycki ◽  
Katherine S. Pollard
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Labeling ◽  
Open Chromatin ◽  
Specific Cell ◽  
Rna Seq ◽  
Data Types ◽  
Bulk Data ◽  
Cell Type Specific

Single-cell and bulk genomics assays have complementary strengths and weaknesses, and alone neither strategy can fully capture regulatory elements across the diversity of cells in complex tissues. We present CellWalker, a method that integrates single-cell open chromatin (scATAC-seq) data with gene expression (RNA-seq) and other data types using a network model that simultaneously improves cell labeling in noisy scATAC-seq and annotates cell-type specific regulatory elements in bulk data. We demonstrate CellWalker’s robustness to sparse annotations and noise using simulations and combined RNA-seq and ATAC-seq in individual cells. We then apply CellWalker to the developing brain. We identify cells transitioning between transcriptional states, resolve enhancers to specific cell types, and observe that autism and other neurological traits can be mapped to specific cell types through their enhancers.

Tracing the Formation of Haematopoietic Stem Cells in Mouse Embryos By Single-Cell Functional and RNA-Seq Analyses

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5046-5046
Author(s):  
Fuchou Tang
Keyword(s):  
Stem Cells ◽  
Endothelial Cells ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Conflicts Of Interest ◽  
Precursor Cells ◽  
Considerable Proportion ◽  
Rna Seq ◽  
Haematopoietic Stem Cells

Abstract Haematopoietic stem cells (HSCs) are derived early from embryonic precursor cells, such as haemogenic endothelial cells and pre-HSCs. However, the identity of precursor cells remains elusive due to their rareness, transience, and inability to be isolated efficiently. Here we employed potent surface markers to capture the nascent pre-HSCs at 30% purity, as rigorously validated by single-cell-initiated serial transplantation assay. Then we applied single-cell RNA-Seq technique to analyse five populations closely related to HSC formation: endothelial cells, CD45- and CD45+ pre-HSCs in E11 aorta-gonad-mesonephros (AGM) region, and mature HSCs in E12 and E14 foetal liver. In comparison, the pre-HSCs showed unique features in transcriptional machinery, arterial signature, apoptosis, metabolism state, signalling pathway, transcription factor network, and lncRNA expression pattern. Among signalling pathways enriched in pre-HSCs, the mTOR activation was uncovered indispensable for the emergence of HSCs but not haematopoietic progenitors from endothelial cells in vivo. Transcriptome data-based functional analysis revealed de novo the remarkable heterogeneity in cell cycle status of pre-HSCs, with considerable proportion being actively proliferative. By comparing with proximal populations without HSC potential, the core molecular signature of pre-HSCs was identified. Collectively, our work paves the way for dissection of complex molecular mechanisms regulating the step-wise generation of HSCs in vivo, informing future efforts to engineer HSCs for clinical application. Disclosures No relevant conflicts of interest to declare.

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