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Next-Generation Sequencing to compare RNA transcripts between Adam19 wildtype and knockout mice

GSE183318 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/05/10 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 2 × heart_WT_ATR234 vs 2 × lung_WT_ATR234 vs 2 × heart_Mut_ATR237 vs 2 × lung_Mut_ATR237Groups 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
Adam19 Deficiency Impacts Pulmonary Function: Human GWAS Follow-up in MouseResearch square · 2024
Summary (written by the submitters)
ADAM19 has been associated with pulmonary function traits in a number of genome wide association analyses by our group and others. We want to use a mouse model to examine the role Adam19 in lung function to clarify whether ADAM19 is truly the causal gene at this locus. We created a whole body Adam19 knockout mouse model targeting exon6 and 7 to disrupt the transcript expression from exon 8 through the end of gene sequences.
Read the full summary ↓
In previous publications, mice lacking Adam19 exon 11, which harbor a catalytic site, were not postnatal viable. Contradictory to the previous publications, our Adam19 knockout survived postnatally. Our objectives were to determine if this novel mouse model is truly Adam19-deficient rather than a hypomorph or neomorph rescuing the previously published lethal phenotype of Adam19-deficient mice.
Published in
Adam19 Deficiency Impacts Pulmonary Function: Human GWAS Follow-up in Mouse
Li H, House J, Nichols C et al. · Research square 2024 · PMID 38659817 · doi:10.21203/rs.3.rs-4207678/v1
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 GSE183318_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: 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 PRJNA759920 and SRA study SRP335436. Searching any of these in the dataset finder brings you back here.

Study design
2 × heart_WT_ATR234 vs 2 × lung_WT_ATR234 vs 2 × heart_Mut_ATR237 vs 2 × lung_Mut_ATR237

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 8 of them. 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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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.