← BioTransfer GEO Dataset Finder
GEO series

Next Generation Sequencing Facilitates Quantitative Analysis of mRNA expression prolifes in placentas from wild Type,early-onset and later-onset PE mouse models

GSE168702 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2024/03/11 Platform GPL21273
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples: 4 × LO-PE vs 4 × EO-PE vs 2 × ControlGroups 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)
Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare transcriptome profiling (RNA-seq) of E17.5 placentas from control, early-onset (EO) and later-onset (LO) preeclampsia (PE) mice. Methods: E17.5 placental mRNA profiles of offspring from control, EO and LO PE mice were generated by deep sequencing, using Illumina GAIIx.
Read the full summary ↓
The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the E17.5 placentas from control EO and LO PE mice with BWA workflow and 34,115 transcripts with TopHat workflow. R Conclusions: Our study represents the first detailed analysis of E17.5 placentas transcriptomes, with biologic replicates, generated by mRNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within tissue. We conclude that mRNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
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 GSE168702_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 PRJNA713561 and SRA study SRP310236. Searching any of these in the dataset finder brings you back here.

Study design
4 × LO-PE vs 4 × EO-PE vs 2 × Control

Supports a between-group comparison across 10 samples.

How we read this: 3 replicated groups read from 10 sample titles; they account for 10 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.