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Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia

Xiaowei Zhu, View ORCID ProfileBo Zhou, Reenal Pattni, Kelly Gleason, Chunfeng Tan, Agnieszka Kalinowski, Steven Sloan, Anna-Sophie Fiston-Lavier, Jessica Mariani, Brain Somatic Mosaicism Network, Alexej Abyzov, Dimitri Petrov, Ben A. Barres, Hannes Vogel, John V. Moran, Flora M. Vaccarino, Carol A. Tamminga, Douglas F. Levinson, Alexander E. Urban
doi: https://doi.org/10.1101/660779
Xiaowei Zhu
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
2Department of Genetics, Stanford University, Palo Alto, CA
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Bo Zhou
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
2Department of Genetics, Stanford University, Palo Alto, CA
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  • ORCID record for Bo Zhou
Reenal Pattni
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
2Department of Genetics, Stanford University, Palo Alto, CA
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Kelly Gleason
3Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
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Chunfeng Tan
3Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
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Agnieszka Kalinowski
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
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Steven Sloan
4Department of Human Genetics, Emory University, Atlanta, GA
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Anna-Sophie Fiston-Lavier
5Institut des Sciences de l’Evolution de Montpellier (UMR 5554, CNRS-UM-IRD-EPHE), Université de Montpellier, Place Eugène Bataillon, Montpellier, France
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Jessica Mariani
6Child Study Center, Yale University, New Haven, CT
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Alexej Abyzov
7Department of Health Sciences Research, Mayo Clinic, Rochester, MN
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Dimitri Petrov
8Department of Biology, Stanford University, Palo Alto, CA
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Ben A. Barres
9Department of Neurobiology, Stanford University, Palo Alto, CA
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Hannes Vogel
10Department of Pathology, Stanford University, Palo Alto, CA
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John V. Moran
11Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI
12Department of Internal Medicine, University of Michigan, Ann Arbor, MI
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Flora M. Vaccarino
6Child Study Center, Yale University, New Haven, CT
13Department of Neuroscience, Yale School of Medicine, New Haven, CT
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Carol A. Tamminga
3Division of Translational Research in Schizophrenia, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
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Douglas F. Levinson
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
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Alexander E. Urban
1Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA
2Department of Genetics, Stanford University, Palo Alto, CA
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  • For correspondence: aeurban@stanford.edu
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Abstract

Active retrotransposons in the human genome (L1, Alu and SVA elements) can create genomic mobile element insertions (MEIs) in both germline and somatic tissue1. Specific somatic MEIs have been detected at high levels in human cancers2, and at lower to medium levels in human brains3. Dysregulation of somatic retrotransposition in the human brain has been hypothesized to contribute to neuropsychiatric diseases4,5. However, individual somatic MEIs are present in small proportions of cells at a given anatomical location, and thus standard whole-genome sequencing (WGS) presents a difficult signal-to-noise problem, while single-cell approaches suffer from limited scalability and experimental artifacts introduced by enzymatic whole-genome amplification6. Previous studies produced widely differing estimates for the somatic retrotransposition rates in human brain3,6–8. Here, we present a highly precise machine learning method (RetroSom) to directly identify somatic L1 and Alu insertions in <1% cells from 200× deep WGS, which allows circumventing the restrictions of whole-genome amplification. Using RetroSom we confirmed a lower rate of retrotransposition for individual somatic L1 insertions in human neurons. We discovered that anatomical distribution of somatic L1 insertion is as widespread in glia as in neurons, and across both hemispheres of the brain, indicating retrotransposition occurs during early embryogenesis. We characterized two of the detected brain-specific L1 insertions in great detail in neurons and glia from a donor with schizophrenia. Both insertions are within introns of genes active in brain (CNNM2, FRMD4A) in regions with multiple genetic associations with neuropsychiatric disorders9–11. Gene expression was significantly reduced by both somatic insertions in a reporter assay. Our results provide novel insights into the potential for pathological effects of somatic retrotransposition in the human brain, now including the large glial fraction. RetroSom has broad applicability in all disease states where somatic retrotransposition is expected to play a role, such as autoimmune disorders and cancer.

Footnotes

  • ↵‡ Full list of the members of the Brain Somatic Mosaicism Network is included after the acknowledgements

  • Changed the subject area from “bioinformatics” to “genomics” Separated the manuscript into “main text” and “supplementary materials”

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 10, 2019.
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Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Xiaowei Zhu, Bo Zhou, Reenal Pattni, Kelly Gleason, Chunfeng Tan, Agnieszka Kalinowski, Steven Sloan, Anna-Sophie Fiston-Lavier, Jessica Mariani, Brain Somatic Mosaicism Network, Alexej Abyzov, Dimitri Petrov, Ben A. Barres, Hannes Vogel, John V. Moran, Flora M. Vaccarino, Carol A. Tamminga, Douglas F. Levinson, Alexander E. Urban
bioRxiv 660779; doi: https://doi.org/10.1101/660779
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Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Xiaowei Zhu, Bo Zhou, Reenal Pattni, Kelly Gleason, Chunfeng Tan, Agnieszka Kalinowski, Steven Sloan, Anna-Sophie Fiston-Lavier, Jessica Mariani, Brain Somatic Mosaicism Network, Alexej Abyzov, Dimitri Petrov, Ben A. Barres, Hannes Vogel, John V. Moran, Flora M. Vaccarino, Carol A. Tamminga, Douglas F. Levinson, Alexander E. Urban
bioRxiv 660779; doi: https://doi.org/10.1101/660779

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