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dc.contributor.authorWang, Yifan
dc.contributor.authorBae, Taejeong
dc.contributor.authorThorpe, Jeremy
dc.contributor.authorSherman, Maxwell A
dc.contributor.authorJones, Attila G
dc.contributor.authorCho, Sean
dc.contributor.authorDaily, Kenneth
dc.contributor.authorDou, Yanmei
dc.contributor.authorGanz, Javier
dc.contributor.authorGalor, Alon
dc.contributor.authorLobon, Irene
dc.contributor.authorPattni, Reenal
dc.contributor.authorRosenbluh, Chaggai
dc.contributor.authorTomasi, Simone
dc.contributor.authorTomasini, Livia
dc.contributor.authorYang, Xiaoxu
dc.contributor.authorZhou, Bo
dc.contributor.authorAkbarian, Schahram
dc.contributor.authorBall, Laurel L
dc.contributor.authorBizzotto, Sara
dc.date.accessioned2021-09-20T17:41:59Z
dc.date.available2021-09-20T17:41:59Z
dc.date.issued2021-03-29
dc.identifier.urihttps://hdl.handle.net/1721.1/132104
dc.description.abstractAbstract 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.en_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofhttps://doi.org/10.1186/s13059-021-02285-3en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceBioMed Centralen_US
dc.titleComprehensive identification of somatic nucleotide variants in human brain tissueen_US
dc.typeArticleen_US
dc.identifier.citationGenome Biology. 2021 Mar 29;22(1):92en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-04-04T04:16:36Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.date.submission2021-04-04T04:16:36Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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