Chromatin accessibility dynamics and single cell RNA-Seq reveal new regulators of regeneration in neural progenitors

Vertebrate appendage regeneration requires precisely coordinated remodeling of the transcriptional landscape to enable the growth and differentiation of new tissue, a process executed over multiple days and across dozens of cell types. The heterogeneity of tissues and temporally-sensitive fate decisions involved has made it difficult to articulate the gene regulatory programs enabling regeneration of individual cell types. To better understand how a regenerative program is fulfilled by neural progenitor cells (NPCs) of the spinal cord, we analyzed pax6-expressing NPCs isolated from regenerating Xenopus tropicalis tails. By intersecting chromatin accessibility data with single-cell transcriptomics, we find that NPCs place an early priority on neuronal differentiation. Late in regeneration, the priority returns to proliferation. Our analyses identify Pbx3 and Meis1 as critical regulators of tail regeneration and axon organization. Overall, we use transcriptional regulatory dynamics to present a new model for cell fate decisions and their regulators in NPCs during regeneration.

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The Roles of Chromatin Accessibility in Regulating the Candida albicans White-Opaque Phenotypic Switch

Journal of Fungi ◽

10.3390/jof7010037 ◽

2021 ◽

Vol 7 (1) ◽

pp. 37

Author(s):

Mohammad N. Qasim ◽

Ashley Valle Arevalo ◽

Clarissa J. Nobile ◽

Aaron D. Hernday

Keyword(s):

Candida Albicans ◽

Cell Fate ◽

Cell Types ◽

Chromatin Accessibility ◽

Phenotypic Switching ◽

Phenotypic Switch ◽

Chromatin Remodelers ◽

Environmental Signals ◽

Cell Fate Decisions ◽

Simple Model System

Candida albicans, a diploid polymorphic fungus, has evolved a unique heritable epigenetic program that enables reversible phenotypic switching between two cell types, referred to as “white” and “opaque”. These cell types are established and maintained by distinct transcriptional programs that lead to differences in metabolic preferences, mating competencies, cellular morphologies, responses to environmental signals, interactions with the host innate immune system, and expression of approximately 20% of genes in the genome. Transcription factors (defined as sequence specific DNA-binding proteins) that regulate the establishment and heritable maintenance of the white and opaque cell types have been a primary focus of investigation in the field; however, other factors that impact chromatin accessibility, such as histone modifying enzymes, chromatin remodelers, and histone chaperone complexes, also modulate the dynamics of the white-opaque switch and have been much less studied to date. Overall, the white-opaque switch represents an attractive and relatively “simple” model system for understanding the logic and regulatory mechanisms by which heritable cell fate decisions are determined in higher eukaryotes. Here we review recent discoveries on the roles of chromatin accessibility in regulating the C. albicans white-opaque phenotypic switch.

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SAT-298 Integrative Single-Cell Transcriptomic and Epigenomic Landscape of Mouse Anterior Pituitary Cell Types

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.593 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Frederique Murielle Ruf-Zamojski ◽

Michel A Zamojski ◽

German Nudelman ◽

Yongchao Ge ◽

Natalia Mendelev ◽

...

Keyword(s):

Single Cell ◽

Cell Line ◽

Anterior Pituitary ◽

Cell Types ◽

Chromatin Accessibility ◽

Pituitary Cell ◽

Integrated Analysis ◽

Pituitary Cells ◽

Rna Seq ◽

Cell Type

Abstract The pituitary gland is a critical regulator of the neuroendocrine system. To further our understanding of the classification, cellular heterogeneity, and regulatory landscape of pituitary cell types, we performed and computationally integrated single cell (SC)/single nucleus (SN) resolution experiments capturing RNA expression, chromatin accessibility, and DNA methylation state from mouse dissociated whole pituitaries. Both SC and SN transcriptome analysis and promoter accessibility identified the five classical hormone-producing cell types (somatotropes, gonadotropes (GT), lactotropes, thyrotropes, and corticotropes). GT cells distinctively expressed transcripts for Cga, Fshb, Lhb, Nr5a1, and Gnrhr in SC RNA-seq and SN RNA-seq. This was matched in SN ATAC-seq with GTs specifically showing open chromatin at the promoter regions for the same genes. Similarly, the other classically defined anterior pituitary cells displayed transcript expression and chromatin accessibility patterns characteristic of their own cell type. This integrated analysis identified additional cell-types, such as a stem cell cluster expressing transcripts for Sox2, Sox9, Mia, and Rbpms, and a broadly accessible chromatin state. In addition, we performed bulk ATAC-seq in the LβT2b gonadotrope-like cell line. While the FSHB promoter region was closed in the cell line, we identified a region upstream of Fshb that became accessible by the synergistic actions of GnRH and activin A, and that corresponded to a conserved region identified by a polycystic ovary syndrome (PCOS) single nucleotide polymorphism (SNP). Although this locus appears closed in deep sequencing bulk ATAC-seq of dissociated mouse pituitary cells, SN ATAC-seq of the same preparation showed that this site was specifically open in mouse GT, but closed in 14 other pituitary cell type clusters. This discrepancy highlighted the detection limit of a bulk ATAC-seq experiment in a subpopulation, as GT represented ~5% of this dissociated anterior pituitary sample. These results identified this locus as a candidate for explaining the dual dependence of Fshb expression on GnRH and activin/TGFβ signaling, and potential new evidence for upstream regulation of Fshb. The pituitary epigenetic landscape provides a resource for improved cell type identification and for the investigation of the regulatory mechanisms driving cell-to-cell heterogeneity. Additional authors not listed due to abstract submission restrictions: N. Seenarine, M. Amper, N. Jain (ISMMS).

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Resolving Cell Fate Decisions during Somatic Cell Reprogramming by Single-Cell RNA-Seq

Molecular Cell ◽

10.1016/j.molcel.2019.01.042 ◽

2019 ◽

Vol 73 (4) ◽

pp. 815-829.e7 ◽

Cited By ~ 29

Author(s):

Lin Guo ◽

Lihui Lin ◽

Xiaoshan Wang ◽

Mingwei Gao ◽

Shangtao Cao ◽

...

Keyword(s):

Somatic Cell ◽

Single Cell ◽

Cell Fate ◽

Cell Reprogramming ◽

Rna Seq ◽

Cell Fate Decisions ◽

Somatic Cell Reprogramming

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Single Cell RNA seq for Analysis of Cell Fate Decisions

Blood ◽

10.1182/blood.v126.23.sci-20.sci-20 ◽

2015 ◽

Vol 126 (23) ◽

pp. SCI-20-SCI-20

Author(s):

H. Leighton Grimes ◽

Singh Harinder ◽

Andre Olsson ◽

Nathan Salomonis ◽

Bruce J. Aronow ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Clustering Analysis ◽

Conflicts Of Interest ◽

Regulatory Gene ◽

Rna Seq ◽

Regulatory State ◽

Cell Fate Decisions ◽

General Utility ◽

Developmental Hierarchy

Abstract Single-cell RNA-Seq has the potential to become a dominant approach in probing diverse and complex developmental compartments. Its unbiased and comprehensive nature could enable developmental ordering of cellular and regulatory gene hierarchies without prior knowledge. To test general utility we performed single-cell RNA-seq of murine hematopoietic progenitors focusing on the myeloid developmental hierarchy. Using novel unsupervised clustering analysis, ICDS, we correctly ordered known hierarchical states as well as revealed rare intermediates. Regulatory state analysis suggested that the transcription factors Gfi1 and Irf8 function antagonistically to control homeostatic neutrophil and macrophage production, respectively. This prediction was validated by complementary genetic and genomic experiments in granulocyte-macrophage progenitors. Using knock-in reporters for Gfi1 and Irf8 and clonogenic analyses coupled with single-cell RNA-seq we distinguished regulatory states of bi-potential progenitors from their lineage specifying or committed progeny. Thus single-cell RNA-Seq is a powerful developmental tool to characterize hierarchical and rare cellular states along with the regulators that control their dynamics. Disclosures No relevant conflicts of interest to declare.

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Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

10.1101/2020.09.15.299123 ◽

2020 ◽

Author(s):

Timothy J. Durham ◽

Riza M. Daza ◽

Louis Gevirtzman ◽

Darren A. Cusanovich ◽

William Stafford Noble ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Expression Patterns ◽

Cell Types ◽

Chromatin Accessibility ◽

Gene Expression Patterns ◽

Rna Seq ◽

Cell Type ◽

Tissue Specific ◽

C Elegans

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.

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Single cell multi-omics profiling reveals a hierarchical epigenetic landscape during mammalian germ layer specification

10.1101/519207 ◽

2019 ◽

Cited By ~ 5

Author(s):

Ricard Argelaguet ◽

Hisham Mohammed ◽

Stephen J Clark ◽

L Carine Stapel ◽

Christel Krueger ◽

...

Keyword(s):

Dna Methylation ◽

Single Cell ◽

Cell Fate ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

List Type ◽

Germ Layer ◽

Epigenetic Landscape ◽

Germ Layers ◽

Cell Fate Decisions

AbstractFormation of the three primary germ layers during gastrulation is an essential step in the establishment of the vertebrate body plan. Recent studies employing single cell RNA-sequencing have identified major transcriptional changes associated with germ layer specification. Global epigenetic reprogramming accompanies these changes, but the role of the epigenome in regulating early cell fate choice remains unresolved, and the coordination between different epigenetic layers is unclear. Here we describe the first single cell triple-omics map of chromatin accessibility, DNA methylation and RNA expression during the exit from pluripotency and the onset of gastrulation in mouse embryos. We find dynamic dependencies between the different molecular layers, with evidence for distinct modes of epigenetic regulation. The initial exit from pluripotency coincides with the establishment of a global repressive epigenetic landscape, followed by the emergence of local lineage-specific epigenetic patterns during gastrulation. Notably, cells committed to mesoderm and endoderm undergo widespread coordinated epigenetic rearrangements, driven by loss of methylation in enhancer marks and a concomitant increase of chromatin accessibility. In striking contrast, the epigenetic landscape of ectodermal cells is already established in the early epiblast. Hence, regulatory elements associated with each germ layer are either epigenetically primed or epigenetically remodelled prior to overt cell fate decisions during gastrulation, providing the molecular logic for a hierarchical emergence of the primary germ layers.HighlightsFirst map of mouse gastrulation using comprehensive single cell triple-omic analysis.Exit from pluripotency is associated with a global repressive epigenetic landscape, driven by a sharp gain of DNA methylation and a gradual decrease of chromatin accessibility.DNA methylation and chromatin accessibility changes in enhancers, but not in promoters, are associated with germ layer formation.Mesoderm and endoderm enhancers become open and demethylated upon lineage commitment.Ectoderm enhancers are primed in the early epiblast and protected from the global repressive dynamics, supporting a default model of ectoderm commitment in vivo.

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Inference of cell state transitions and cell fate plasticity from single-cell with MARGARET

10.1101/2021.10.22.465455 ◽

2021 ◽

Author(s):

Kushagra Pandey ◽

Hamim Zafar

Keyword(s):

Single Cell ◽

Cell Fate ◽

Markov Chain Model ◽

Metric Learning ◽

Transitional Cell ◽

Cell Types ◽

State Transitions ◽

Chain Model ◽

Rna Seq ◽

Cell State

Despite recent advances in inferring cellular dynamics using single-cell RNA-seq data, existing trajectory inference (TI) methods face difficulty in accurately reconstructing cell-state manifold and inferring trajectory and cell fate plasticity for complex topologies. We present MARGARET, a novel TI method that utilizes a deep unsupervised metric learning-based approach for inferring the cellular embeddings and employs a novel measure of connectivity between cell clusters and a graph-partitioning approach to reconstruct complex trajectory topologies. MARGARET utilizes the inferred trajectory for determining terminal states and inferring cell-fate plasticity using a scalable absorbing Markov Chain model. On a diverse simulated benchmark, MARGARET outperformed state-of-the-art methods in recovering global topology and cell pseudotime ordering. When applied to experimental datasets from hematopoiesis, embryogenesis, and colon differentiation, MARGARET reconstructed major lineages and associated gene expression trends, better characterized key branching events and transitional cell types, and identified novel cell types, and branching events that were previously uncharacterized.

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SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions

10.1101/046110 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ning Leng ◽

Li-Fang Chu ◽

Jeea Choi ◽

Christina Kendziorski ◽

James A. Thomson ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Empirical Bayes ◽

Time Course ◽

Expression Patterns ◽

R Package ◽

Embryonic Cell ◽

Rna Seq ◽

Cell Fate Decisions ◽

Probability Estimates

AbstractMotivationWith the development of single cell RNA-seq (scRNA-seq) technology, scRNA-seq experiments with ordered conditions (e.g. time-course) are becoming common. Methods developed for analyzing ordered bulk RNA-seq experiments are not applicable to scRNA-seq, since their distributional assumptions are often violated by additional heterogeneities prevalent in scRNA-seq. Here we present SC-Pattern - an empirical Bayes model to characterize genes with expression changes in ordered scRNA-seq experiments. SCPattern utilizes the non-parametrical Kolmogorov-Smirnov statistic, thus it has the flexibility to identify genes with a wide variety of types of changes. Additionally, the Bayes framework allows SCPattern to classify genes into expression patterns with probability estimates.ResultsSimulation results show that SCPattern is well powered for identifying genes with expression changes while the false discovery rate is well controlled. SCPattern is also able to accurately classify these dynamic genes into directional expression patterns. Applied to a scRNA-seq time course dataset studying human embryonic cell differentiation, SCPattern detected a group of important genes that are involved in mesendoderm and definitive endoderm cell fate decisions, positional patterning, and cell cycle.Availability and ImplementationThe SCPattern is implemented as an R package along with a user-friendly graphical interface, which are available at:https://github.com/lengning/SCPatternContact:[email protected]

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LTMG: A novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

10.1101/430009 ◽

2018 ◽

Cited By ~ 1

Author(s):

Changlin Wan ◽

Wennan Chang ◽

Yu Zhang ◽

Fenil Shah ◽

Xiaoyu Lu ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Single Cells ◽

Cell Types ◽

R Package ◽

Data Sets ◽

Rna Seq ◽

Cell Functions ◽

Transcriptional Regulatory ◽

A Cell

ABSTRACTA key challenge in modeling single-cell RNA-seq (scRNA-seq) data is to capture the diverse gene expression states regulated by different transcriptional regulatory inputs across single cells, which is further complicated by a large number of observed zero and low expressions. We developed a left truncated mixture Gaussian (LTMG) model that stems from the kinetic relationships between the transcriptional regulatory inputs and metabolism of mRNA and gene expression abundance in a cell. LTMG infers the expression multi-modalities across single cell entities, representing a gene’s diverse expression states; meanwhile the dropouts and low expressions are treated as left truncated, specifically representing an expression state that is under suppression. We demonstrated that LTMG has significantly better goodness of fitting on an extensive number of single-cell data sets, comparing to three other state of the art models. In addition, our systems kinetic approach of handling the low and zero expressions and correctness of the identified multimodality are validated on several independent experimental data sets. Application on data of complex tissues demonstrated the capability of LTMG in extracting varied expression states specific to cell types or cell functions. Based on LTMG, a differential gene expression test and a co-regulation module identification method, namely LTMG-DGE and LTMG-GCR, are further developed. We experimentally validated that LTMG-DGE is equipped with higher sensitivity and specificity in detecting differentially expressed genes, compared with other five popular methods, and that LTMG-GCR is capable to retrieve the gene co-regulation modules corresponding to perturbed transcriptional regulations. A user-friendly R package with all the analysis power is available at https://github.com/zy26/LTMGSCA.

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EPEN-05. MUTATIONAL ANALYSIS OF THE C11ORF95 DOMAIN AND SINGLE-CELL RNA-SEQ PROFILE OF A MOUSE MODEL OF SUPRATENTORIAL EPENDYMOMA

Neuro-Oncology ◽

10.1093/neuonc/noab090.055 ◽

2021 ◽

Vol 23 (Supplement_1) ◽

pp. i14-i14

Author(s):

Kevin Truong ◽

James He ◽

Gavin Birdsall ◽

Ericka Randazzo ◽

Jesse Dunnack ◽

...

Keyword(s):

Mouse Model ◽

Single Cell ◽

Tumor Cells ◽

Cell Fate ◽

Transcriptional Activation ◽

Mutational Analysis ◽

Cell Types ◽

Marker Genes ◽

Rna Seq ◽

Loss Of Function

Abstract We used a recently developed mouse model to better understand the cellular and molecular determinants of tumors driven by the oncogenic fusion protein C11orf95-RELA. Our approach makes use of in utero electroporation and a binary transposase system to introduce human C11orf95-RELA sequence, wild type and mutant forms, into neural progenitors. We used single cell RNA-seq to profile the cellular constituents within the resulting tumors in mice. We find that approximately 70% of the cells in the tumors do not express the oncogene C11orf95-RELA and these non-oncogene expressing cells are a combination of different non-tumor cell cell-types, including significant numbers of T-cells, and macrophages. The C11orf95-RELA expressing tumor cells have a unique transcriptomic profile that includes both astrocytic and neural progenitor marker genes, and is distinct from glioblastoma transcriptomic profiles. Since C11orf95-RELA is believed to function through a combination of both activation of NF-κB response genes by constitutive activation of RELA, and genes not activated by NF-κB, we assessed the expression of NF-κB response genes across the populations of cells in the tumor. Interestingly, when tumor cells highly expressing C11orf95-RELA were analyzed further, the subclusters identified were distinguished by upregulation of non-NF-kB pathways involved in cell proliferation, cell fate determination, and immune activation. We hypothesized that the C11orf95 domain may function to bring RELA transcriptional activation to inappropriate non-NF-κB targets, and we therefore performed a point mutation analysis of the C11orf95 domain. We found that mutations in either of the cysteines or histidines that make up a possible zinc finger domain in C11orf95 eliminate the ability of the fusion to induce tumors. In cell lines, these loss-of-function point mutants still trafficked to nuclei, and activated NF-κB pathways. We are currently using RNAseq and CRISPR loss-of function to identify genes downstream of C11orf95-RELA that are required for tumorigenesis.

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