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Related Concept Videos

In-vitro Mutagenesis01:16

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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
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Identifying DNA Mutations in Purified Hematopoietic Stem/Progenitor Cells
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Genomic Mutation Identification in Mice Using Illumina Sequencing and Linux-Based Computational Methods.

John A Williams1,2,3, George Powell1,4, Ann-Marie Mallon1

  • 1MRC Harwell Institute, Mammalian Genetics Unit, Harwell Campus, Oxfordshire, United Kingdom.

Current Protocols in Mouse Biology
|September 19, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a computational platform for detecting genetic variants in mice from whole-genome and exome sequencing data. The protocols guide variant discovery and annotation, aiding researchers in understanding gene function and disease mechanisms.

Keywords:
mouse genomicsmouse mutagenesis screensmutation detectionsingle-nucleotide detectionvariant annotationwhole genome sequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Mouse models

Background:

  • Genetically modified mice are crucial for disease modeling and gene function discovery.
  • Traditional SNP genotyping has limitations in identifying novel genetic variants.
  • Whole-genome and exome sequencing offer deeper insights but require robust analytical tools.

Purpose of the Study:

  • To present a computational platform for variant detection in mouse sequencing data.
  • To guide researchers through the process of analyzing mouse genetic variants.
  • To facilitate the prediction of mutation consequences on protein function.

Main Methods:

  • Development of computational protocols for read alignment to the mouse genome.
  • Implementation of quality assurance strategies for sequencing data.
  • Mutation discovery, comparison with existing mouse SNPs, and variant annotation.
  • Utilizing self-contained containers for version control and adaptability.

Main Results:

  • A comprehensive platform enabling variant detection from whole-genome and exome sequencing.
  • Step-by-step guidance for non-bioinformatics specialists.
  • Protocols adaptable to new techniques via container upgrades.
  • Discussion of challenges specific to mouse genome analysis.

Conclusions:

  • The presented platform empowers researchers to effectively identify and analyze genetic variants in mice.
  • This tool enhances the utility of mouse models for genetic research and disease mechanism studies.
  • The protocols are accessible and designed for broad usability in research settings.