1. Computational and Systems Biology
  2. Genetics and Genomics
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Downregulation of glial genes involved in synaptic function mitigates Huntington's Disease pathogenesis

  1. Tarik Seref Onur
  2. Andrew Laitman
  3. He Zhao
  4. Ryan Keyho
  5. Hyemin Kim
  6. Jennifer Wang
  7. Megan Mair
  8. Huilan Wang
  9. Lifang Li
  10. Alma Perez
  11. Maria de Haro
  12. Ying-Wooi Wan
  13. Genevera Allen
  14. Boxun Lu
  15. Ismael Al-Ramahi
  16. Zhandong Liu
  17. Juan Botas  Is a corresponding author
  1. Baylor College of Medicine, United States
  2. Balor College of Medicine, United States
  3. Texas Children's Hospital, United States
  4. Fudan University, China
  5. Rice University, United States
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Cite this article as: eLife 2021;10:e64564 doi: 10.7554/eLife.64564

Abstract

Most research on neurodegenerative diseases has focused on neurons, yet glia help form and maintain the synapses whose loss is so prominent in these conditions. To investigate the contributions of glia to Huntington's disease (HD), we profiled the gene expression alterations of Drosophila expressing human mutant Huntingtin (mHTT) in either glia or neurons and compared these changes to what is observed in HD human and HD mice striata. A large portion of conserved genes are concordantly dysregulated across the three species; we tested these genes in a high-throughput behavioral assay and found that downregulation of genes involved in synapse assembly mitigated pathogenesis and behavioral deficits. To our surprise, reducing dNRXN3 function in glia was sufficient to improve the phenotype of flies expressing mHTT in neurons, suggesting that mHTT's toxic effects in glia ramify throughout the brain. This supports a model in which dampening synaptic function is protective because it attenuates the excitotoxicity that characterizes HD.

Data availability

RNA-sequencing data produced by this study has been deposited in GEO under accession code GSE157287. We have provided source data for all main figures 2, 3,4,5, and 6 as well as for supplemental figures 4,5, and 6. Codes for analyzing gene expression, networks, and Drosophila behavior are provided.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Tarik Seref Onur

    Genetics and Genomics Graduate Program, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Andrew Laitman

    Quantitative & Computational Biosciences, Balor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. He Zhao

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Ryan Keyho

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Hyemin Kim

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Jennifer Wang

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Megan Mair

    Genetics & Genomics Graduate Program, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Huilan Wang

    State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Lifang Li

    Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Alma Perez

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Maria de Haro

    Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Ying-Wooi Wan

    Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Genevera Allen

    Departments of Electrical & Computer Engineering, Statistics and Computer Science, Rice University, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Boxun Lu

    State Key Laboratory of Genetic Engineering, Department of Biophysics, School of Life Sciences, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  15. Ismael Al-Ramahi

    Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Zhandong Liu

    Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  17. Juan Botas

    Molecular and Human Genetics, Baylor College of Medicine, Houston, United States
    For correspondence
    jbotas@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5476-5955

Funding

This work was supported by grants to J.B. from NIH/ NIA (R01AG057339) and CHDI. B.L. is sponsored by Natural Science Foundation of China (31970747, 31601105, 81870990, 81925012). T.O. and M.M. were supported by the NIGMS Ruth L. Kirschstein National Research Service Award (NRSA) Predoctoral Institutional Research Training Grant (T32 GM008307) provided to the Genetics & Genomics Graduate Program at Baylor College of Medicine. A.L. was supported by Baylor College of Medicine Medical Scientist Training Program and the NLM Training Program in Biomedical Informatics and Data Science (T15 LM007093) at the Gulf Coast Consortium. The High Throughput Behavioral Screening core at the Jan and Dan Duncan Neurological Research Institute was supported by generous philanthropy from the Hildebrand family foundation. The project was also supported by a shared Instrumentation grant from the NIH (S10 OD016167) and Baylor College of Medicine IDDRC Grant Number P50HD103555 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development for use of the Microscopy Core facilities, the Cell and Tissue Pathogenesis Core and the RNA In Situ Hybridization Core facility with the expert assistance of Dr. Cecilia Ljungberg. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health & Human Development or the National Institutes of Health.

Reviewing Editor

  1. Michael B Eisen, University of California, Berkeley, United States

Publication history

  1. Received: November 3, 2020
  2. Accepted: April 19, 2021
  3. Accepted Manuscript published: April 19, 2021 (version 1)

Copyright

© 2021, Onur et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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