Identification of Mutations in Zebrafish Using Next‐Generation Sequencing. Issue 1 (16th February 2018)

• Record Type: Journal Article
• Authors: Henke, Katrin; Bowen, Margot E.; Harris, Matthew P.
• Editors: Ausubel, Frederick M.; Brent, Roger; Kingston, Robert E.; Moore, David D.; Seidman, J.G.; Smith, John A.; Struhl, Kevin
• Is Part Of: Current protocols in molecular biology. Volume 104:Issue 1(2013)
• Page Start: 7.13.1
• Page End: 7.13.33
• Publication Date: 2018-02-16
• Subjects: whole‐genome sequencing -- WGS -- mutation mapping -- zebrafish -- next‐generation sequencing; Molecular biology -- Technique -- Periodicals; Molecular biology -- Laboratory manuals; Molecular Biology -- methods; Biologie moléculaire -- Technique; Biologie moléculaire -- Manuels de laboratoire; Molecular biology; Molecular biology -- Technique; Laboratory Manual; Electronic reference sources; Laboratory manuals; 572.8028
• DOI: 10.1002/0471142727.mb0713s104
• Languages: English
• ISSNs: 1934-3639

Abstract

Abstract: Whole‐genome sequencing (WGS) has been used in many invertebrate model organisms as an efficient tool for mapping and identification of mutations affecting particular morphological or physiological processes. However, the application of WGS in highly polymorphic, larger genomes of vertebrates has required new experimental and analytical approaches. As a consequence, a wealth of different analytical tools has been developed. As the generation and analysis of data stemming from WGS can be unwieldy and daunting to researchers not accustomed to many common bioinformatic analyses and Unix‐based computational tools, we focus on how to manage and analyze next‐generation sequencing datasets without an extensive computational infrastructure and in‐depth bioinformatic knowledge. Here we describe methods for the analysis of WGS for use in mapping and identification of mutations in the zebrafish. We stress key elements of the experimental design and the analytical approach that allow the use of this method across different sequencing platforms and in different model organisms with annotated genomes. Curr. Protoc. Mol. Biol . 104:7.13.1‐7.13.33. © 2013 by John Wiley & Sons, Inc.