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In-depth transcriptomic analyses investigating molecular mechanisms underlying diabetic retinopathy (totalRNA)

GSE160306 Homo sapiens (human) Single-cell RNA-seq 79 samples Submitted 2021/04/19 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 79 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
79 samples
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)
Diabetic Retinopathy (DR) is among the major global causes for vision loss. With the rise in diabetes prevalence, an increase in DR incidence is expected. Current understanding of both the molecular etiology and pathways involved in the initiation and progression of DR is limited. Here we analyzed mRNA and miRNA expression profiles of 80 human post-mortem retinal samples from 80 patients diagnosed with various stages of DR.
Read the full summary ↓
We found differentially expressed transcripts to be predominantly associated with late stage DR and pathways such as hippo and gap junction signaling. A multivariate regression model identified transcripts with progressive changes throughout disease stages, which in turn displayed significant overlap with sphingolipid and cGMP−PKG signaling. Combined analysis of miRNA and mRNA expression further uncovered disease-relevant miRNA/mRNA associations as potential mechanisms of post-transcriptional regulation. Finally, integrating human retinal single cell RNA-Sequencing data revealed a continuous loss of retinal ganglion cells, and Müller cell mediated changes in histidine and β-alanine signaling. Our findings offer an unprecedented insight into the development of DR and provide potential avenues for future therapeutic intervention.
This dataset
Open GSE160306 in finder → Find more human 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 GSE160306_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: 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 PRJNA672928. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 34006945) ↗
Samples in this study

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+ 79 more — browse all 79 samples with per-sample file links →

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