Rat Retina RNA-Seq Data for Diabetic Retinopathy ceRNA Network Analysis

RNA-seq data from retinal tissues of 3 streptozotocin-induced type-1 diabetic retinopathy rats and 3 normal controls. Ming Yang published this 1.1 GB dataset on figshare in 2026, containing small RNA and whole-transcriptome sequencing files. These data support the construction of a circRNA-miRNA-mRNA ceRNA regulatory network.

Use Cases

• Constructing competing endogenous RNA (ceRNA) regulatory networks based on circRNA, miRNA, and mRNA expression data.
• Identifying differentially expressed non-coding RNAs in diabetic retinopathy based on RNA-seq data from rat retina.
• Validating computational predictions of miRNA-mRNA interactions based on paired small RNA and whole-transcriptome sequencing.
• Benchmarking network analysis algorithms for multi-omics integration based on the provided circRNA-miRNA-mRNA data.

Strengths

• Includes raw FASTQ files and processed expression data, providing flexibility for re-analysis.
• Contains matched small RNA and whole-transcriptome sequencing from the same samples, enabling integrated analysis.
• Data is shared under a permissive CC-BY-4.0 license, allowing for broad reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• The sample size is limited to 3 diabetic and 3 control rats, which may affect statistical power for some analyses.

Provenance

Source

figshare

Collection Method

RNA sequencing of retinal tissues from a streptozotocin-induced rat model.

Freshness

Last updated 2026-05-06.