scholarly journals Chromatin potential identified by shared single cell profiling of RNA and chromatin

2020 ◽  
Author(s):  
Sai Ma ◽  
Bing Zhang ◽  
Lindsay LaFave ◽  
Zachary Chiang ◽  
Yan Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Mouse Skin ◽  
Chromatin Accessibility ◽  
Lineage Commitment ◽  
Single Cell Profiling ◽  
Lineage Priming ◽  
And Function ◽  
Computational Strategy

SummaryCell differentiation and function are regulated across multiple layers of gene regulation, including the modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of the regulatory events leading to cell fate commitment. Here, we developed SHARE-seq, a highly scalable approach for measurement of chromatin accessibility and gene expression within the same single cell. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define Domains of Regulatory Chromatin (DORCs), which significantly overlap with super-enhancers. We show that during lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting changes in chromatin accessibility may prime cells for lineage commitment. We therefore develop a computational strategy (chromatin potential) to quantify chromatin lineage-priming and predict cell fate outcomes. Together, SHARE-seq provides an extensible platform to study regulatory circuitry across diverse cells within tissues.

scholarly journals SIS-seq, a molecular ‘time machine’, connects single cell fate with gene programs

2018 ◽  
Author(s):  
Luyi Tian ◽  
Jaring Schreuder ◽  
Daniela Zalcenstein ◽  
Jessica Tran ◽  
Nikolce Kocovski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Single Cells ◽  
Cell Subset ◽  
Dendritic Cell Subset ◽  
Rna Seq ◽  
Time Machine ◽  
Clonal Heterogeneity ◽  
And Function

AbstractConventional single cell RNA-seq methods are destructive, such that a given cell cannot also then be tested for fate and function, without a time machine. Here, we develop a clonal method SIS-seq, whereby single cells are allowed to divide, and progeny cells are assayed separately in SISter conditions; some for fate, others by RNA-seq. By cross-correlating progenitor gene expression with mature cell fate within a clone, and doing this for many clones, we can identify the earliest gene expression signatures of dendritic cell subset development. SIS-seq could be used to study other populations harboring clonal heterogeneity, including stem, reprogrammed and cancer cells to reveal the transcriptional origins of fate decisions.

scholarly journals The cis-regulatory dynamics of embryonic development at single cell resolution

2017 ◽  
Author(s):  
Darren A. Cusanovich ◽  
James P. Reddington ◽  
David A. Garfield ◽  
Riza Daza ◽  
Raquel Marco-Ferreres ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Germ Layer ◽  
Regulatory Changes ◽  
Single Cell Profiling ◽  
Transgenic Embryos ◽  
Cell Trajectories

ABSTRACTSingle cell measurements of gene expression are providing new insights into lineage commitment, yet the regulatory changes underlying individual cell trajectories remain elusive. Here, we profiled chromatin accessibility in over 20,000 single nuclei across multiple stages of Drosophila embryogenesis. Our data reveal heterogeneity in the regulatory landscape prior to gastrulation that reflects anatomical position, a feature that aligns with future cell fate. During mid embryogenesis, tissue granularity emerges such that cell types can be inferred by their chromatin accessibility, while maintaining a signature of their germ layer of origin. We identify over 30,000 distal elements with tissue-specific accessibility. Using transgenic embryos, we tested the germ layer specificity of a subset of predicted enhancers, achieving near-perfect accuracy. Overall, these data demonstrate the power of shotgun single cell profiling of embryos to resolve dynamic changes in open chromatin during development, and to uncover the cis-regulatory programs of germ layers and cell types.

scholarly journals Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rohit Singh ◽  
Brian L. Hie ◽  
Ashwin Narayan ◽  
Bonnie Berger
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Metric Learning ◽  
Disease Status ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Multiple Modalities ◽  
Technological Advances ◽  
Single Cell Profiling ◽  
Or Gene

AbstractA complete understanding of biological processes requires synthesizing information across heterogeneous modalities, such as age, disease status, or gene expression. Technological advances in single-cell profiling have enabled researchers to assay multiple modalities simultaneously. We present Schema, which uses a principled metric learning strategy that identifies informative features in a modality to synthesize disparate modalities into a single coherent interpretation. We use Schema to infer cell types by integrating gene expression and chromatin accessibility data; demonstrate informative data visualizations that synthesize multiple modalities; perform differential gene expression analysis in the context of spatial variability; and estimate evolutionary pressure on peptide sequences.

scholarly journals Single-cell multi-omic velocity infers dynamic and decoupled gene regulation

2021 ◽  
Author(s):  
Chen Li ◽  
Maria Virgilio ◽  
Kathleen Collins ◽  
Joshua D Welch
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Latent Variable ◽  
Mechanistic Model ◽  
Chromatin Accessibility ◽  
Time Lags ◽  
Variable Model ◽  
Switch Time ◽  
Transcriptomic Changes

Single-cell multi-omic datasets, in which multiple molecular modalities are profiled within the same cell, provide a unique opportunity to discover the relationships between cellular epigenomic and transcriptomic changes. To realize this potential, we developed MultiVelo, a mechanistic model of gene expression that extends the RNA velocity framework to incorporate epigenomic data. MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression from single-cell data, providing a quantitative summary of the temporal relationship between epigenomic and transcriptomic changes. Incorporating chromatin accessibility data significantly improves the accuracy of cell fate prediction compared to velocity estimates from RNA only. Fitting MultiVelo on single-cell multi-omic datasets from brain, skin, and blood cells reveals two distinct classes of genes distinguished by whether chromatin closes before or after transcription ceases. Our model also identifies four types of cell states--two states in which epigenome and transcriptome are coupled and two distinct decoupled states. The parameters inferred by MultiVelo quantify the length of time for which genes occupy each of the four states, ranking genes by the degree of coupling between transcriptome and epigenome. Finally, we identify time lags between transcription factor expression and binding site accessibility and between disease-associated SNP accessibility and expression of the linked genes. We provide an open-source Python implementation of MultiVelo on PyPI and GitHub (https://github.com/welch-lab/MultiVelo).

scholarly journals Resolution of Cell Fate Decisions Revealed by Single-Cell Gene Expression Analysis from Zygote to Blastocyst

2010 ◽  
Vol 18 (4) ◽  
pp. 675-685 ◽  
Author(s):  
Guoji Guo ◽  
Mikael Huss ◽  
Guo Qing Tong ◽  
Chaoyang Wang ◽  
Li Li Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Cell Fate Decisions ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals Joint profiling of gene expression and chromatin accessibility of amphioxus development at single cell resolution

2021 ◽  
Author(s):  
Pengcheng Ma ◽  
Xingyan Liu ◽  
Huimin Liu ◽  
Zaoxu Xu ◽  
Xiangning Ding ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Functional Divergence ◽  
Expression Patterns ◽  
Genetic Regulatory Networks ◽  
Public Access ◽  
Origin And Evolution ◽  
Key Species

Abstract Vertebrate evolution was accompanied with two rounds of whole genome duplication followed by functional divergence in terms of regulatory circuits and gene expression patterns. As a basal and slow-evolving chordate species, amphioxus is an ideal paradigm for exploring the origin and evolution of vertebrates. Single cell sequencing has been widely employed to construct the developmental cell atlas of several key species of vertebrates (human, mouse, zebrafish and frog) and tunicate (sea squirts). Here, we performed single-nucleus RNA sequencing (snRNA-seq) and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) for different stages of amphioxus (covering embryogenesis and adult tissues). With the datasets generated we constructed the developmental tree for amphioxus cell fate commitment and lineage specification, and revealed the underlying key regulators and genetic regulatory networks. The generated data were integrated into an online platform, AmphioxusAtlas, for public access at http://120.79.46.200:81/AmphioxusAtlas.

scholarly journals Generative modeling of single-cell population time series for inferring cell differentiation landscapes

2020 ◽  
Author(s):  
Grace H.T. Yeo ◽  
Sachit D. Saksena ◽  
David K. Gifford
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Cell Differentiation ◽  
Single Cell ◽  
Cell Fate ◽  
Lineage Tracing ◽  
Model Framework ◽  
Modeling Framework ◽  
Generative Modeling ◽  
Model Complex

SummaryExisting computational methods that use single-cell RNA-sequencing for cell fate prediction either summarize observations of cell states and their couplings without modeling the underlying differentiation process, or are limited in their capacity to model complex differentiation landscapes. Thus, contemporary methods cannot predict how cells evolve stochastically and in physical time from an arbitrary starting expression state, nor can they model the cell fate consequences of gene expression perturbations. We introduce PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative modeling framework that learns an underlying differentiation landscape from single-cell time-series gene expression data. Our generative model framework provides insight into the process of differentiation and can simulate differentiation trajectories for arbitrary gene expression progenitor states. We validate our method on a recently published experimental lineage tracing dataset that provides observed trajectories. We show that this model is able to predict the fate biases of progenitor cells in neutrophil/macrophage lineages when accounting for cell proliferation, improving upon the best-performing existing method. We also show how a model can predict trajectories for cells not found in the model’s training set, including cells in which genes or sets of genes have been perturbed. PRESCIENT is able to accommodate complex perturbations of multiple genes, at different time points and from different starting cell populations. PRESCIENT models are able to recover the expected effects of known modulators of cell fate in hematopoiesis and pancreatic β cell differentiation.

scholarly journals Molecular diversity and lineage commitment of human interneuron progenitors

2021 ◽  
Author(s):  
Dmitry Velmeshev ◽  
Manideep Chavali ◽  
Tomasz Jan Nowakowski ◽  
Mohini Bhade ◽  
Simone Mayer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Autism Spectrum ◽  
Lineage Commitment ◽  
Proper Function ◽  
Specific Gene ◽  
Specific Cell ◽  
Cortical Interneurons ◽  
Human Specific ◽  
Interneuron Development

Cortical interneurons are indispensable for proper function of neocortical circuits. Changes in interneuron development and function are implicated in human disorders, such as autism spectrum disorder and epilepsy. In order to understand human-specific features of cortical development as well as the origins of neurodevelopmental disorders it is crucial to identify the molecular programs underlying human interneuron development and subtype specification. Recent studies have explored gene expression programs underlying mouse interneuron specification and maturation. We applied single-cell RNA sequencing to samples of second trimester human ganglionic eminence and developing cortex to identify molecularly defined subtypes of human interneuron progenitors and immature interneurons. In addition, we integrated this data from the developing human ganglionic eminences and neocortex with single-nucleus RNA-seq of adult cortical interneurons in order to elucidate dynamic molecular changes associated with commitment of progenitors and immature interneurons to mature interneuron subtypes. By comparing our data with published mouse single-cell genomic data, we discover a number of divergent gene expression programs that distinguish human interneuron progenitors from mouse. Moreover, we find that a number of transcription factors expressed during prenatal development become restricted to adult interneuron subtypes in the human but not the mouse, and these adult interneurons express species- and lineage-specific cell adhesion and synaptic genes. Therefore, our study highlights that despite the similarity of main principles of cortical interneuron development and lineage commitment between mouse and human, human interneuron genesis and subtype specification is guided by species-specific gene programs, contributing to human-specific features of cortical inhibitory interneurons.

scholarly journals Dynamic changes in chromatin accessibility, altered adipogenic gene expression, and total versus de novo fatty acid synthesis in subcutaneous adipose stem cells of normal-weight polycystic ovary syndrome (PCOS) women during adipogenesis: evidence of cellular programming

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Karen L. Leung ◽  
Smriti Sanchita ◽  
Catherine T. Pham ◽  
Brett A. Davis ◽  
Mariam Okhovat ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fatty Acid ◽  
De Novo ◽  
Polycystic Ovary ◽  
Total Content ◽  
Chromatin Accessibility ◽  
Normal Weight ◽  
Triacylglycerol Synthesis ◽  
And Function

Abstract Background Normal-weight polycystic ovary syndrome (PCOS) women exhibit adipose resistance in vivo accompanied by enhanced subcutaneous (SC) abdominal adipose stem cell (ASC) development to adipocytes with accelerated lipid accumulation per cell in vitro. The present study examines chromatin accessibility, RNA expression and fatty acid (FA) synthesis during SC abdominal ASC differentiation into adipocytes in vitro of normal-weight PCOS versus age- and body mass index-matched normoandrogenic ovulatory (control) women to study epigenetic/genetic characteristics as well as functional alterations of PCOS and control ASCs during adipogenesis. Results SC abdominal ASCs from PCOS women versus controls exhibited dynamic chromatin accessibility during adipogenesis, from significantly less chromatin accessibility at day 0 to greater chromatin accessibility by day 12, with enrichment of binding motifs for transcription factors (TFs) of the AP-1 subfamily at days 0, 3, and 12. In PCOS versus control cells, expression of genes governing adipocyte differentiation (PPARγ, CEBPα, AGPAT2) and function (ADIPOQ, FABP4, LPL, PLIN1, SLC2A4) was increased two–sixfold at days 3, 7, and 12, while that involving Wnt signaling (FZD1, SFRP1, and WNT10B) was decreased. Differential gene expression in PCOS cells at these time points involved triacylglycerol synthesis, lipid oxidation, free fatty acid beta-oxidation, and oxidative phosphorylation of the TCA cycle, with TGFB1 as a significant upstream regulator. There was a broad correspondence between increased chromatin accessibility and increased RNA expression of those 12 genes involved in adipocyte differentiation and function, Wnt signaling, as well as genes involved in the triacylglycerol synthesis functional group at day 12 of adipogenesis. Total content and de novo synthesis of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1), and oleic (C18:1) acid increased from day 7 to day 12 in all cells, with total content and de novo synthesis of FAs significantly greater in PCOS than controls cells at day 12. Conclusions In normal-weight PCOS women, dynamic chromatin remodeling of SC abdominal ASCs during adipogenesis may enhance adipogenic gene expression as a programmed mechanism to promote greater fat storage.

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