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Comprehensive identification of somatic nucleotide variants in human brain tissue

Authors :
Schahram Akbarian
Jonathan Pevsner
Joseph G. Gleeson
Reenal Pattni
Matthew T. Oetjens
Ryan E. Mills
Kenneth Daily
Alexander E. Urban
Yifan Wang
Irene Lobon
David Juan
John V. Moran
Taejeong Bae
Shobana Sekar
Christopher A. Walsh
Sara Bizzotto
Mette A. Peters
Yeongjun Jang
Attila G. Jones
Maxwell A. Sherman
Sean Cho
Liana Fasching
Rujuta Narurkar
Chaggai Rosenbluh
Yanmei Dou
Andrew Chess
Alon Galor
Jeremy Thorpe
Esther Lizano
Tomas Marques-Bonet
John B. Moldovan
Livia Tomasini
Laurel L. Ball
Javier Ganz
Weichen Zhou
Daniel R. Weinberger
Richard E. Straub
Ryan N. Doan
Xiaoxu Yang
Flora M. Vaccarino
Jeffrey M. Kidd
S. Emery
Alexej Abyzov
Bo Zhou
Simone Tomasi
Joo Heon Shin
Peter J. Park
Eduardo Soriano
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

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. Here, the Brain Somatic Mosaicism Network conducted a coordinated, multi-institutional study to: (i) examine the ability of existing methods to detect simulated somatic single nucleotide variants (SNVs) in DNA mixing experiments; (ii) 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; (iii) devise strategies to discover somatic SNVs; and (iv) apply various approaches to validate somatic SNVs. These efforts led to the identification of 43 bona fide somatic SNVs that ranged in variant allele fractions from ~0.005 to ~0.28. Guided by these results, we devised best practices for calling mosaic SNVs from 250X whole genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrated that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Thus, 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

Database :
OpenAIRE
Accession number :
edsair.doi...........064859c9ad7c33119f048584d41f4e12
Full Text :
https://doi.org/10.1101/2020.10.10.332213