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A Circult Mechanism for Differentiating Positive and Negative Associations

GSE66345 Mus musculus (mouse) RNA-seq (gene expression) 17 samples Submitted 2015/02/27 Platform GPL17021Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 17 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
17 samples: 9 × CeM vs 8 × NAcGroups 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)
The ability to differentiate stimuli predicting positive or negative outcomes is critical for survival, and perturbations of emotional processing underlie many psychiatric disease states. Different neuronal populations of the basolateral amygdala complex (BLA) encode fearful or rewarding associations, but the molecular identity of these functionally distinct populations of BLA neurons remained unknown.
Read the full summary ↓
Here, we show that BLA neurons projecting to the nucleus accumbens (NAc-projectors) or the centromedial amygdala (CeM-projectors) underwent opposing synaptic changes following fear or reward conditioning. The photostimulation of NAc projectors supported positive reinforcement while photostimulation of CeM projectors mediated negative reinforcement. In search of defining molecular characteristics of these functionally-distinct BLA neuronal populations, we compared gene expression profiles of NAc- and CeM-projectors.
This dataset
Open GSE66345 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 GSE66345_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 PRJNA276574 and SRA study SRP055558. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25925480) ↗
Study design
9 × CeM vs 8 × NAc

Supports a between-group comparison across 17 samples.

How we read this: 2 replicated groups read from 17 sample titles; they account for 17 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

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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.