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Reconstructing regulative progenitor behaviors in synthetic embryos

GSE220949 synthetic construct; Mus musculus Single-cell RNA-seq 29 samples Submitted 2024/03/05 Platform GPL17769Platform GPL24247Platform GPL26526
At a glance

Single-cell RNA-seq · synthetic construct; Mus musculus · 29 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
synthetic construct; Mus musculus
Samples
29 samples: 19 distinct titles, 2 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Advanced stem cell-based in vitro models of embryogenesis offer great promise to decipher developmental programs with high-throughput and resolution. However, the rapid changes in morphology and cell state that underly these models mask multiple higher order parameters, including the regulative balance between differentiation and self-renewal that govern transient progenitor cell populations.
Read the full summary ↓
Here, we apply a continuous single-cell Cas9-based molecular recorder to mouse embryonic stem cells, which enables the recovery of can reproducibly recovere and high-content information regarding the historical relationship between individual cells. We apply our system to Trunk-Like Structures (TLS), a complex in vitro model of embryogenesis that captures differentiation and morphological dynamics from pluripotency exit to the specification of the somitic and neural lineages. By recording cell lineages alongside the transcriptional identities of extant cells, we are able to build high-resolution phylogenetic trees, identify clonal subpopulations, and reveal recover the step-wisestepwise series of events that govern germ layer specification. Moreover, we examine are able to functionally characterize the specification and maintenance of multipotent neuro-mesodermal progenitor (NMP) populations as they coordinate self-renewal and commitment into more specialized cell types, including how thehow highly disparateplastic individual nature of individual branches trajectories ultimately aggregateultimately aggregate to ensure to generate the generation of highly consistent embryonic structures. Finally, we demonstrate the potential of this technology for high-throughput perturbation screening by combining small molecule treatment with individual structure labeling, allowing us to we demonstrate that these parameters can be independently tuned to modulate TLS morphology, including in reversible ways that extend the duration through which NMPs can contribute to both lineages of the embryonic trunkconnect perturbation of early differentiation pathways to progenitor cell behavior and structure morphology. Our work represents the first continuous molecular recording approach applied to dynamic in vitro models, a toolkit that can be combined with inhibitor libraries or other screening modalities to uncover the genetic and epigenetic mechanisms that enable highly orchestrated and robust changes in cell state composition during critical windows of morphogenesis.
This dataset
Open GSE220949 in finder → Find more RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE220949_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA912143 and SRA study SRP413034. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
19 distinct titles, 2 of them repeated
gDNA - Tracer mESC - Day ×6 cDNA - Tracer mESC - Day ×6

How we read this: Read from 29 sample titles: 19 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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