@article{cca471b572f441bd8d8d15c897bf7199,
title = "Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia",
abstract = "Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions presents a difficult signal-to-noise problem. Using a machine-learning method (RetroSom) and deep whole-genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains. We characterized two brain-specific L1 insertions in neurons and glia from a donor with schizophrenia. There was anatomical distribution of the L1 insertions in neurons and glia across both hemispheres, indicating retrotransposition occurred during early embryogenesis. Both insertions were within the introns of genes (CNNM2 and FRMD4A) inside genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate that RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.",
author = "{Brain Somatic Mosaicism Network} and Xiaowei Zhu and Bo Zhou and Reenal Pattni and Kelly Gleason and Chunfeng Tan and Agnieszka Kalinowski and Steven Sloan and Fiston-Lavier, {Anna Sophie} and Jessica Mariani and Dmitri Petrov and Barres, {Ben A.} and Laramie Duncan and Alexej Abyzov and Hannes Vogel and Xiaowei Zhu and Bo Zhou and Alexander Urban and Christopher Walsh and Javier Ganz and Mollie Woodworth and Pengpeng Li and Rachel Rodin and Robert Hill and Sara Bizzotto and Zinan Zhou and Alice Lee and Alissa D{\textquoteright}Gama and Alon Galor and Craig Bohrson and Daniel Kwon and Doga Gulhan and Elaine Lim and Isidro Cortes and Joe Luquette and Maxwell Sherman and Michael Coulter and Michael Lodato and Peter Park and Rebeca Monroy and Sonia Kim and Yanmei Dou and Andrew Chess and Attila Jones and Chaggai Rosenbluh and Schahram Akbarian and Ben Langmead and Jeremy Thorpe and Jonathan Pevsner and Rob Scharpf and Tamminga, {Carol A.}",
note = "Funding Information: We thank W. H. Wong, J. Chao, A. Z. Wang and N. Bosch for constructive comments on the manuscript. We thank J. E. Kleinman, T. H. Hyde and D.W. from Lieber Institute for Brain Development for providing the BSMN common brain tissue and L. Fasching from Yale University for extracting the BSMN common brain DNA. This work utilized computing resources provided by the Stanford Genetics Bioinformatics Service Center. Funding: this work was supported by Eureka Grant R01MH094740 from the NIMH and the Stanford Schizophrenia Genetics Research Fund. The mixing-genome DNA sequencing and BSMN common brain sequencing data were generated as part of the BSMN Consortium and supported by: U01MH106874, U01MH106876, U01MG106882, U01MH106883, U01MH106883, U01MH106884, U01MH106891, U01MH106891, U01MH106891, U01MH106892, U01MH106893, and U01MH108898 awarded to N.S., F.M.V., F.G., C.W., P.P., J.P., A.C., J.V.M., D.W. and J.G. B.Z. is funded by the National Heart, Lung, and Blood Institute grant T32 HL110952. A.E.U. was a Tashia and John Morgridge Faculty Fellow of the Stanford Child Health Research Institute. The Urban laboratory receives funding through the Jaswa Innovator Award and from B. Blackie and W. Mclvor. We acknowledge helpful discussions with B. Blackie and W. Mclvor. Flow cytometry sorting was performed on an instrument in the Stanford shared fluorescence-activated cell sorting facility obtained under an NIH S10 Shared Instrument Grant (S10RR025518-01). Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.",
year = "2021",
month = feb,
doi = "10.1038/s41593-020-00767-4",
language = "English (US)",
volume = "24",
pages = "186--196",
journal = "Nature Neuroscience",
issn = "1097-6256",
publisher = "Nature Publishing Group",
number = "2",
}