Dataset Information

Single-Cell Landscape of Transcriptional Heterogeneity and Cell Fate Decisions during Mouse Early Gastrulation.

ABSTRACT: The mouse inner cell mass (ICM) segregates into the epiblast and primitive endoderm (PrE) lineages coincident with implantation of the embryo. The epiblast subsequently undergoes considerable expansion of cell numbers prior to gastrulation. To investigate underlying regulatory principles, we performed systematic single-cell RNA sequencing (seq) of conceptuses from E3.5 to E6.5. The epiblast shows reactivation and subsequent inactivation of the X chromosome, with Zfp57 expression associated with reactivation and inactivation together with other candidate regulators. At E6.5, the transition from epiblast to primitive streak is linked with decreased expression of polycomb subunits, suggesting a key regulatory role. Notably, our analyses suggest elevated transcriptional noise at E3.5 and within the non-committed epiblast at E6.5, coinciding with exit from pluripotency. By contrast, E6.5 primitive streak cells became highly synchronized and exhibit a shortened G1 cell-cycle phase, consistent with accelerated proliferation. Our study systematically charts transcriptional noise and uncovers molecular processes associated with early lineage decisions.

SUBMITTER: Mohammed H

PROVIDER: S-EPMC5554778 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Single-Cell Landscape of Transcriptional Heterogeneity and Cell Fate Decisions during Mouse Early Gastrulation.

Mohammed Hisham H Hernando-Herraez Irene I Savino Aurora A Scialdone Antonio A Macaulay Iain I Mulas Carla C Chandra Tamir T Voet Thierry T Dean Wendy W Nichols Jennifer J Marioni John C JC Reik Wolf W

Cell reports 20170801 5

The mouse inner cell mass (ICM) segregates into the epiblast and primitive endoderm (PrE) lineages coincident with implantation of the embryo. The epiblast subsequently undergoes considerable expansion of cell numbers prior to gastrulation. To investigate underlying regulatory principles, we performed systematic single-cell RNA sequencing (seq) of conceptuses from E3.5 to E6.5. The epiblast shows reactivation and subsequent inactivation of the X chromosome, with Zfp57 expression associated with ...[more]

PMID: 28768204

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Project description:The cell fate decisions between plasmablasts (PBs), germinal center B cells (GCBCs) and non-GC-derived early memory B cells (eMBCs) during early B cell activation determine the outcome of the immune responses to pathogens and vaccines. To characterize these poorly understood lineage choices, we dissected the early B cell responses to T-dependent antigen in mice by single-cell RNA-sequencing. Early after immunization, a homogenous population of activated precursors (APs) gave rise to a transient wave of PBs, followed a day later by the emergence of the first GCBCs, with the transcriptomes of both rapidly diverging from that of APs. The majority of APs started to withdraw from the cell cycle very early on and gave rise to eMBCs, a developmental transition that involved limited transcriptional changes. These events were controlled by antigen availability that rapidly declined soon after immunization, and provision of antigen excess interfered with the cell cycle exit of APs and induced a new wave of PBs. Fate mapping experiments revealed a prominent contribution of eMBCs to the overall MBC pool. Generation of the earliest GCBCs was tightly controlled by the transcriptional repressor Bhlhe40 in the absence of which this population was increased in numbers. Bhlhe40 also restrained in a cell intrinsic fashion the response of T follicular helper (TFH) cells, a specialized T helper cell subset required to mount the GC response. In B cells, Bhlhe40 executed its function in the first days after immunization by selectively restricting the generation of the earliest GCBCs but not of eMBCs or PBs. Conditional Bhlhe40 inactivation confirmed cell-autonomous functions of Bhlhe40 in both GCBCs and TFH cells, while the GC phenotype was further enhanced upon loss of Bhlhe40 in both cell types. This negative regulation of the GC reaction by Bhlhe40 was of crucial importance, as Bhlhe40-deficient mice with progressing age succumbed to a B cell lymphoma characterized by the accumulation of monoclonal GCBCs-like cells and polyclonal TFH cells in various tissues.

Project description:Molecular mechanisms employed by individual multipotent cells at the point of lineage commitment remain largely uncharacterized. Current paradigms span from instructive to noise-driven mechanisms. Of considerable interest is also whether commitment involves a limited set of genes or the entire transcriptional program, and to what extent gene expression configures multiple trajectories into commitment. Importantly, the transient nature of the commitment transition confounds the experimental capture of committing cells. We develop a computational framework that simulates stochastic commitment events, and affords mechanistic exploration of the fate transition. We use a combined modeling approach guided by gene expression classifier methods that infers a time-series of stochastic commitment events from experimental growth characteristics and gene expression profiling of individual hematopoietic cells captured immediately before and after commitment. We define putative regulators of commitment and probabilistic rules of transition through machine learning methods, and employ clustering and correlation analyses to interrogate gene regulatory interactions in multipotent cells. Against this background, we develop a Monte Carlo time-series stochastic model of transcription where the parameters governing promoter status, mRNA production and mRNA decay in multipotent cells are fitted to experimental static gene expression distributions. Monte Carlo time is converted to physical time using cell culture kinetic data. Probability of commitment in time is a function of gene expression as defined by a logistic regression model obtained from experimental single-cell expression data. Our approach should be applicable to similar differentiating systems where single cell data is available. Within our system, we identify robust model solutions for the multipotent population within physiologically reasonable values and explore model predictions with regard to molecular scenarios of entry into commitment. The model suggests distinct dependencies of different commitment-associated genes on mRNA dynamics and promoter activity, which globally influence the probability of lineage commitment.

Dataset Information

Single-Cell Landscape of Transcriptional Heterogeneity and Cell Fate Decisions during Mouse Early Gastrulation.

Publications

Single-Cell Landscape of Transcriptional Heterogeneity and Cell Fate Decisions during Mouse Early Gastrulation.

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