Genomic Mutation Identification in Mice Using Illumina Sequencing and Linux-Based Computational Methods

Curr Protoc Mouse Biol. 2019 Sep;9(3):e64. doi: 10.1002/cpmo.64.

Abstract

Genetically modified mice are an essential tool for modeling disease-causing mechanisms and discovering gene function. SNP genotyping was traditionally used to associate candidate regions with traits in the mouse, but failed to reveal novel variants without further targeted sequencing. Using a robust set of computational protocols, we present a platform to enable scientists to detect variants arising from whole-genome and exome sequencing experiments. This article guides researchers on aligning reads to the mouse genome, quality-assurance strategies, mutation discovery, comparing mutations to previously discovered mouse SNPs, and the annotation of novel variants, in order to predict mutation consequences on the protein level. Challenges unique to the mouse are discussed, and two protocols use self-contained containers to maintain version control and allow users to adapt our approach to new techniques by upgrading container versions. Our protocols are suited for servers or office workstations and are usable by non-bioinformatics specialists. © 2019 by John Wiley & Sons, Inc.

Keywords: mouse genomics; mouse mutagenesis screens; mutation detection; single-nucleotide detection; variant annotation; whole genome sequencing.

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing / methods*
  • Mice / genetics*
  • Mutation*
  • Sequence Analysis, DNA
  • Whole Genome Sequencing