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Inverse genetics tracing the differentiation pathway of human chondrocytes

GSE261806 Homo sapiens (human) Single-cell RNA-seq 10 samples Submitted 2024/06/27 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 10 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
Homo sapiens (human)
Samples
10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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.
Paper
Inverse genetics tracing the differentiation pathway of human chondrocytesOsteoarthritis and cartilage · 2024
Summary (written by the submitters)
Objective: Mammalian somatic cells can be reprogrammed into induced pluripotent stem cells (iPSCs) via the forced expression of Yamanaka reprogramming factors. However, only a limited population of the cells that pass through a particular pathway can metamorphose into iPSCs, while the others do not. This study aimed to clarify the pathways that chondrocytes follow during the reprogramming process.
Read the full summary ↓
Design: The fate of human articular chondrocytes under reprogramming was investigated through a time-coursed single-cell transcriptomic analysis, which we termed an inverse genetic approach. The iPS interference technique was also employed to verify that chondrocytes inversely return to pluripotency following the proper differentiation pathway . Results: We confirmed that human chondrocytes could be converted into cells with an iPSC phenotype. Moreover, it was clarified that a limited population that underwent the silencing of SOX9, a master gene for chondrogenesis, at a specific point during the proper transcriptome transition pathway, could eventually become iPS cells. Interestingly, the other cells, which failed to be reprogrammed, followed a distinct pathway toward cells with a surface zone chondrocyte phenotype. The critical involvement of cellular communication network factors (CCNs) in this process was indicated. The idea that chondrocytes, when reprogrammed into iPSCs, follow the differentiation pathway backward was supported by the successful iPS interference using SOX9. Conclusions: This inverse genetic strategy is expected to be utilized to identify the master genes for the differentiation of various somatic cells. The utility of CCNs in articular cartilage regeneration is also supported.
Published in
Inverse genetics tracing the differentiation pathway of human chondrocytes
Do HT, Ono M, Wang Z et al. · Osteoarthritis and cartilage 2024 · PMID 38925474 · doi:10.1016/j.joca.2024.06.009
This dataset
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.

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 GSE261806_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1089120 and SRA study SRP496068. Searching any of these in the dataset finder brings you back here.

Study design
10 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 10 sample titles: 10 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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