With the initial advent of microarrays and, more recently, RNA-sequencing (RNA-seq), this approach can be applied at a transcriptome-wide level, enabling researchers to gain crucial insights into molecular defects associated with a particular experimental condition ( Smith, 2003 Wang et al., 2009). In most model systems, a common analytical approach is to profile changes in gene expression following a particular experimental manipulation, or in comparison between wild type and mutant siblings. Together, these characteristics of zebrafish life history have contributed to its establishment as a leading model to study developmental biology, while expanding its utility to the modeling of human diseases ( Lam and Peterson, 2019). By 5 days post-fertilization (dpf), most organ systems are fully functional. Moreover, the initial steps of zebrafish development are very rapid, with gastrulation completed by 24 hr post-fertilization (hpf) and a complete circulatory system online just 12 hr later. Most notably, zebrafish embryos are transparent and develop externally, allowing direct observation and facile technical manipulation ( Beis and Stainier, 2006). The power of these applications is enhanced by the unique characteristics of the zebrafish embryo. Due to its hardy nature and fecundity, it is highly amenable to a variety of manipulations, including both forward and reverse genetic approaches ( Lawson and Wolfe, 2011). The zebrafish has become an ideal animal model for studying processes related to developmental biology (e.g. Thus, we demonstrate that our new transcriptome annotation can outperform existing annotations, providing an important resource for zebrafish researchers. 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. Since these discrepancies could compromise downstream analyses and biological reproducibility, we built a more comprehensive zebrafish transcriptome annotation that addresses these deficiencies. These issues were due, in part, to variably annotated 3' untranslated regions and thousands of gene models missing from each annotation. Here, we find discrepancies in analysis from RNA-seq datasets quantified using Ensembl and RefSeq zebrafish annotations. Application of RNA-seq relies on accurate transcript annotation for a genome of interest. In these contexts, RNA-sequencing (RNA-seq) provides mechanistic insights by identifying transcriptome changes between experimental conditions. The zebrafish is ideal for studying embryogenesis and is increasingly applied to model human disease.
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