GEO series

Bulk RNA sequencing of murine pancreatic ductal adenocarcinoma cell lines with and without C1galt1c1 knockout

GSE309741 Mus musculus (mouse) RNA-seq (gene expression) 8 samples Submitted 2026/07/01 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 8 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Mus musculus (mouse)
Samples: 8 samples: 8 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.

Summary (written by the submitters)

Pancreatic ductal adenocarcinoma (PDAC) frequently displays aberrant O-glycosylation that contributes to tumor progression and immune evasion. To investigate the transcriptional consequences of altered O-glycosylation, we performed bulk RNA sequencing of murine PDAC (mPDAC) cell lines derived from the KPC model (Kras^LSL-G12D/+; Trp53^LSL-R172H/+; Pdx1-Cre) and their isogenic C1galt1c1 knockout (KO) counterparts.

Read the full summary ↓

C1galt1c1 encodes Cosmc, an essential chaperone for core 1 O-glycan synthesis, and its loss leads to expression of the Tn antigen. Cells were harvested under standard culture conditions, RNA was extracted, and libraries were prepared and sequenced on an Illumina HiSeq platform (20–30 million reads per sample). Reads were processed and mapped to the mouse reference genome (mm39), and gene-level counts were generated. This dataset provides a resource for understanding how truncated O-glycosylation reshapes the transcriptome of PDAC cells and may influence tumor biology and immune interactions.

This dataset

Open GSE309741 in finder → Find more mouse 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 GSE309741_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1336834 and SRA study SRP630169. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 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 8 sample titles: 8 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

GSM9278155 6694c2 mPDAC cells
GSM9278156 6694c2-Tn mPDAC cells
GSM9278157 2838c3 mPDAC cells
GSM9278158 2838c3-Tn mPDAC cells
GSM9278159 6499c4 mPDAC cells
GSM9278160 6499c4-Tn mPDAC cells
GSM9278161 6419c5 mPDAC cells
GSM9278162 6419c5-Tn mPDAC cells

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GSE264171 Effects at the transcriptomic level after knockout of Eed, Ezh2, Brd8 or Nr6a1 in spinal cord neural progenitor differentiation [bulkRNAseq] 41 samples shares knockout, bulk
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Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.