Using Cloning to Amplify Neuronal Genomes for Whole-Genome Sequencing and Comprehensive Mutation Detection and Validation

  • Jennifer L. Hazen
  • Michael A. Duran
  • Ryan P. Smith
  • Alberto R. Rodriguez
  • Greg S. Martin
  • Sergey Kupriyanov
  • Ira M. Hall
  • Kristin K. BaldwinEmail author
Part of the Neuromethods book series (NM, volume 131)


Recent studies of somatic mutation in neurons and other cell types suggest that somatic cells can acquire hundreds to thousands of new mutations over their lifetimes. Each individual mutation can have extremely low prevalence, with many mutations restricted to a single cell. Because of their rarity, somatic mutations can be challenging to detect and reliably distinguish from false-positive calls arising from amplification, sequencing, or bioinformatic methods. In these scenarios, a variety of methods are required to compensate for the limited applicability and technical artifacts inherent in any single approach. In the method we describe, somatic cell nuclear transfer (SCNT, also known as cloning) is used to reprogram single neurons to blastocysts from which we derive embryonic stem cells. Division of these cells faithfully amplifies the neuronal genome for next-generation sequencing and genome-wide mutation detection. This approach allows the detection of false positives due to amplification artifacts and is applicable to all classes of mutations. While it is both sensitive and reliable, our method is lower throughput than single-cell sequencing-based approaches and may also fail to amplify the most severely compromised neuronal genomes. In this chapter, we outline current methods for generating neuron-derived SCNT embryonic cell lines, discuss best practices for genome-wide mutation detection, and address the advantages and limitations of this approach.

Key words

Somatic mutation Postmitotic neuron Somatic cell nuclear transfer Whole-genome sequencing Mobile element insertion Structural variant mutation Copy number variants Indel mutation Single-nucleotide variant mutation 


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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Jennifer L. Hazen
    • 1
  • Michael A. Duran
    • 1
  • Ryan P. Smith
    • 1
  • Alberto R. Rodriguez
    • 1
  • Greg S. Martin
    • 1
  • Sergey Kupriyanov
    • 1
  • Ira M. Hall
    • 1
  • Kristin K. Baldwin
    • 2
    Email author
  1. 1.Dorris Neuroscience CenterScripps Research InstituteSan DiegoUSA
  2. 2.Department of Neuroscience, Dorris Neuroscience CenterScripps Research Institute—California CampusSan DiegoUSA

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