University of Massachusetts Medical School Faculty Publications
UMMS Affiliation
Department of Molecular, Cell, and Cancer Biology; Bioinformatics Core; Program in Molecular Medicine; Program in Bioinformatics and Integrative Biology
Publication Date
2020-08-24
Document Type
Article
Disciplines
Bioinformatics | Developmental Biology
Abstract
The zebrafish is ideal for studying embryogenesis and is increasingly applied to model human disease. In these contexts, RNA-sequencing (RNA-seq) provides mechanistic insights by identifying transcriptome changes between experimental conditions. Application of RNA-seq relies on accurate transcript annotation for a genome of interest. Here, we find discrepancies in analysis from RNA-seq datasets quantified using Ensembl and RefSeq zebrafish annotations. These issues were due, in part, to variably annotated 3' untranslated regions and thousands of gene models missing from each annotation. Since these discrepancies could compromise downstream analyses and biological reproducibility, we built a more comprehensive zebrafish transcriptome annotation that addresses these deficiencies. Our annotation improves detection of cell type-specific genes in both bulk and single cell RNA-seq datasets, where it also improves resolution of cell clustering. Thus, we demonstrate that our new transcriptome annotation can outperform existing annotations, providing an important resource for zebrafish researchers.
Keywords
RNA-seq, annotation, developmental biology, transcriptome, zebrafish
Rights and Permissions
Copyright Lawson et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
DOI of Published Version
10.7554/eLife.55792
Source
Lawson ND, Li R, Shin M, Grosse A, Yukselen O, Stone OA, Kucukural A, Zhu L. An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes. Elife. 2020 Aug 24;9:e55792. doi: 10.7554/eLife.55792. Epub ahead of print. PMID: 32831172. Link to article on publisher's site
Related Resources
Journal/Book/Conference Title
eLife
PubMed ID
32831172
Repository Citation
Lawson ND, Li R, Shin M, Grosse AS, Yukselen O, Stone OA, Kucukural A, Zhu LJ. (2020). An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes. University of Massachusetts Medical School Faculty Publications. https://doi.org/10.7554/eLife.55792. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1790
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.