Generation and network analysis of an RNA-seq transcriptional atlas for the rat. Issue 1 (7th March 2022)

• Record Type: Journal Article
• Authors: Summers, Kim M; Bush, Stephen J; Wu, Chunlei; Hume, David A
• Is Part Of: NAR genomics and bioinformatics. Volume 4:Issue 1(2022)
• Publication Date: 2022-03-07
• Subjects: Genomics -- Periodicals; Bioinformatics -- Periodicals; 572.8
• DOI: 10.1093/nargab/lqac017
• Languages: English
• ISSNs: 2631-9268

Abstract

Abstract: The laboratory rat is an important model for biomedical research. To generate a comprehensive rat transcriptomic atlas, we curated and downloaded 7700 rat RNA-seq datasets from public repositories, downsampled them to a common depth and quantified expression. Data from 585 rat tissues and cells, averaged from each BioProject, can be visualized and queried at http://biogps.org/ratatlas . Gene co-expression network (GCN) analysis revealed clusters of transcripts that were tissue or cell type restricted and contained transcription factors implicated in lineage determination. Other clusters were enriched for transcripts associated with biological processes. Many of these clusters overlap with previous data from analysis of other species, while some (e.g. expressed specifically in immune cells, retina/pineal gland, pituitary and germ cells) are unique to these data. GCN analysis on large subsets of the data related specifically to liver, nervous system, kidney, musculoskeletal system and cardiovascular system enabled deconvolution of cell type-specific signatures. The approach is extensible and the dataset can be used as a point of reference from which to analyse the transcriptomes of cell types and tissues that have not yet been sampled. Sets of strictly co-expressed transcripts provide a resource for critical interpretation of single-cell RNA-seq data.