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Comprehensive identification of somatic nucleotide variants in human brain tissue

Authors :
Yifan Wang
Taejeong Bae
Jeremy Thorpe
Maxwell A. Sherman
Attila G. Jones
Sean Cho
Kenneth Daily
Yanmei Dou
Javier Ganz
Alon Galor
Irene Lobon
Reenal Pattni
Chaggai Rosenbluh
Simone Tomasi
Livia Tomasini
Xiaoxu Yang
Bo Zhou
Schahram Akbarian
Laurel L. Ball
Sara Bizzotto
Sarah B. Emery
Ryan Doan
Liana Fasching
Yeongjun Jang
David Juan
Esther Lizano
Lovelace J. Luquette
John B. Moldovan
Rujuta Narurkar
Matthew T. Oetjens
Rachel E. Rodin
Shobana Sekar
Joo Heon Shin
Eduardo Soriano
Richard E. Straub
Weichen Zhou
Andrew Chess
Joseph G. Gleeson
Tomas Marquès-Bonet
Peter J. Park
Mette A. Peters
Jonathan Pevsner
Christopher A. Walsh
Daniel R. Weinberger
Brain Somatic Mosaicism Network
Flora M. Vaccarino
John V. Moran
Alexander E. Urban
Jeffrey M. Kidd
Ryan E. Mills
Alexej Abyzov
Source :
Genome Biology, Vol 22, Iss 1, Pp 1-32 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Background Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. Results Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Conclusions This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

Details

Language :
English
ISSN :
1474760X
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.8ec2a7cb594e94ba5848bb9fd9be5a
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-021-02285-3