Comprehensive identification of somatic nucleotide variants in human brain tissue

Area of Science:

• Genetics
• Genomics
• Neuroscience

Background:

• Somatic mosaicism, caused by post-zygotic mutations, is linked to diseases like cancer.
• Detecting low-frequency mosaic variants in non-cancerous tissues is challenging.

Purpose of the Study:

• To evaluate methods for detecting simulated somatic single-nucleotide variants (SNVs).
• To establish best practices for identifying and validating somatic SNVs in the brain.
• To reconstruct early developmental cell lineage trees using DNA analysis.

Main Methods:

• Generated whole-genome sequencing data from multiple tissues of a single individual.
• Performed DNA mixing experiments to simulate somatic SNVs.
• Applied various computational and experimental approaches for SNV discovery and validation.

Main Results:

• Identified 43 bona fide somatic SNVs with variant allele fractions from 0.005 to 0.28.
• Developed best practices for calling mosaic SNVs from whole-genome sequencing data with 90% specificity and sensitivity.
• Demonstrated reconstruction of early developmental cell lineage trees.

Conclusions:

• Established a unified set of best practices for detecting somatic SNVs in non-cancerous tissues.
• Provided freely available data and methods to the scientific community.
• Aimed to guide research on the contribution of somatic SNVs to neuropsychiatric diseases.