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Updated: Apr 24, 2026
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
Published on: November 7, 2025
Improved rat genome gene prediction by integration of ESTs with RNA-Seq information
Liping Li1, Enguo Chen2, Chun Yang2
1Department of Gynecologic Oncology, The Affiliated Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Gynecologic Oncology, The Affiliated Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang 310058, China, Division of Respiratory Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China, Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA and Human Molecular and Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Motivation:
RNA-Seq (also called whole-transcriptome sequencing) is an emerging technology that uses the capabilities of next-generation sequencing to detect and quantify entire transcripts. One of its important applications is the improvement of existing genome annotations. RNA-Seq provides rapid, comprehensive and cost-effective tools for the discovery of novel genes and transcripts compared with expressed sequence tag (EST), which is instrumental in gene discovery and gene sequence determination. The rat is widely used as a laboratory disease model, but has a less well-annotated genome as compared with humans and mice. In this study, we incorporated deep RNA-Seq data from three rat tissues-bone marrow, brain and kidney-with EST data to improve the annotation of the rat genome.
Results:
Our analysis identified 32 197 transcripts, including 13 461 known transcripts, 13 934 novel isoforms and 4802 new genes, which almost doubled the numbers of transcripts in the current public rat genome database (rn5). Comparisons of our predicted protein-coding gene sets with those in public datasets suggest that RNA-Seq significantly improves genome annotation and identifies novel genes and isoforms in the rat. Importantly, the large majority of novel genes and isoforms are supported by direct evidence of RNA-Seq experiments. These predicted genes were integrated into the Rat Genome Database (RGD) and can serve as an important resource for functional studies in the research community.
Availability And Implementation:
The predicted genes are available at http://rgd.mcw.edu.
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