1. Genetics and Genomics
  2. Neuroscience

Gain-of-function mutations in the UNC-2/CaV2α channel lead to excitation-dominant synaptic transmission in C. elegans

  1. Yung-Chi Huang
  2. Jennifer K Pirri
  3. Diego Rayes
  4. Shangbang Gao
  5. Ben Mulcahy
  6. Jeff Grant
  7. Yasunori Saheki
  8. Michael M Francis
  9. Mei Zhen
  10. Mark J Alkema  Is a corresponding author
  1. University of Massachusetts Medical School, United States
  2. Mount Sinai Hospital, Canada
  3. The Rockefeller University, United States
https://doi.org/10.7554/eLife.45905
Share this article
Cite this article
  1. Yung-Chi Huang
  2. Jennifer K Pirri
  3. Diego Rayes
  4. Shangbang Gao
  5. Ben Mulcahy
  6. Jeff Grant
  7. Yasunori Saheki
  8. Michael M Francis
  9. Mei Zhen
  10. Mark J Alkema
(2019)
Gain-of-function mutations in the UNC-2/CaV2α channel lead to excitation-dominant synaptic transmission in C. elegans
eLife 8:e45905.
https://doi.org/10.7554/eLife.45905
  2. Download BibTeX
  3. Download .RIS

Abstract

Mutations in pre-synaptic voltage gated calcium channels can lead to familial hemiplegic migraine type 1 (FHM1). While mammalian studies indicate that the migraine brain is hyperexcitable due to enhanced excitation or reduced inhibition, the molecular and cellular mechanisms underlying this excitatory/inhibitory (E/I) imbalance are poorly understood. We identified a gain-of-function (gf) mutation in the Caenorhabditis elegans CaV2 channel α1 subunit, UNC-2, which leads to increased calcium currents. unc-2(zf35gf) mutants exhibit hyperactivity and seizure-like motor behaviors. Expression of the unc-2 gene with FHM1 substitutions R192Q and S218L leads to hyperactivity similar to that of unc-2(zf35gf) mutants. unc-2(zf35gf) mutants display increased cholinergic- and decreased GABAergic-transmission. Moreover, increased cholinergic transmission in unc-2(zf35gf) mutants leads to an increase of cholinergic synapses and a TAX-6/calcineurin dependent reduction of GABA synapses. Our studies reveal mechanisms through which CaV2 gain-of-function mutations disrupt excitation-inhibition balance in the nervous system.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

Article and author information

Author details

  1. Yung-Chi Huang

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Jennifer K Pirri

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Diego Rayes

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Shangbang Gao

    Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5431-4628

  5. Ben Mulcahy

    Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3336-245X

  6. Jeff Grant

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Yasunori Saheki

    Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Michael M Francis

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8076-6668

  9. Mei Zhen

    Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0086-9622

  10. Mark J Alkema

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    For correspondence
    mark.alkema@umassmed.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1311-5179

Funding

National Institutes of Health (GM084491)

  • Mark J Alkema

National Institutes of Health (NS107475)

  • Mei Zhen
  • Mark J Alkema

Canadian Institutes of Health Research (154274)

  • Mei Zhen

Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-06738)

  • Mei Zhen

National Natural Science Foundation of China (31671052)

  • Shangbang Gao

National Institutes of Health (NS064263)

  • Michael M Francis

Consejo Nacional de Investigaciones Científicas y Técnicas (Postdoctoral fellowship)

  • Diego Rayes

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2019, Huang 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.

Metrics

  • 3,487
    views
  • 434
    downloads
  • 35
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Yung-Chi Huang
  2. Jennifer K Pirri
  3. Diego Rayes
  4. Shangbang Gao
  5. Ben Mulcahy
  6. Jeff Grant
  7. Yasunori Saheki
  8. Michael M Francis
  9. Mei Zhen
  10. Mark J Alkema
(2019)
Gain-of-function mutations in the UNC-2/CaV2α channel lead to excitation-dominant synaptic transmission in C. elegans
eLife 8:e45905.
https://doi.org/10.7554/eLife.45905

Share this article

https://doi.org/10.7554/eLife.45905

Categories and tags

Research organism

Further reading

    1. Computational and Systems Biology
    2. Genetics and Genomics

    Risk factors affecting polygenic score performance across diverse cohorts

    Daniel Hui, Scott Dudek ... Marylyn D Ritchie
    Research Article

    Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed the effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N = 491,111) and African (N = 21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best- and worst-performing quintiles for certain covariates. Twenty-eight covariates had significant PGSBMI–covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects – across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account nonlinear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge genome-wide association studies effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

    1. Genetics and Genomics

    Dynamics and regulatory roles of RNA m6A methylation in unbalanced genomes

    Shuai Zhang, Ruixue Wang ... Lin Sun
    Research Article

    N6-methyladenosine (m6A) in eukaryotic RNA is an epigenetic modification that is critical for RNA metabolism, gene expression regulation, and the development of organisms. Aberrant expression of m6A components appears in a variety of human diseases. RNA m6A modification in Drosophila has proven to be involved in sex determination regulated by Sxl and may affect X chromosome expression through the MSL complex. The dosage-related effects under the condition of genomic imbalance (i.e. aneuploidy) are related to various epigenetic regulatory mechanisms. Here, we investigated the roles of RNA m6A modification in unbalanced genomes using aneuploid Drosophila. The results showed that the expression of m6A components changed significantly under genomic imbalance, and affected the abundance and genome-wide distribution of m6A, which may be related to the developmental abnormalities of aneuploids. The relationships between methylation status and classical dosage effect, dosage compensation, and inverse dosage effect were also studied. In addition, we demonstrated that RNA m6A methylation may affect dosage-dependent gene regulation through dosage-sensitive modifiers, alternative splicing, the MSL complex, and other processes. More interestingly, there seems to be a close relationship between MSL complex and RNA m6A modification. It is found that ectopically overexpressed MSL complex, especially the levels of H4K16Ac through MOF, could influence the expression levels of m6A modification and genomic imbalance may be involved in this interaction. We found that m6A could affect the levels of H4K16Ac through MOF, a component of the MSL complex, and that genomic imbalance may be involved in this interaction. Altogether, our work reveals the dynamic and regulatory role of RNA m6A modification in unbalanced genomes, and may shed new light on the mechanisms of aneuploidy-related developmental abnormalities and diseases.

    1. Genetics and Genomics

    Down Syndrome: How a gene fuels ear infections

    Sedigheh Delmaghani, Aziz El-Amraoui
    Insight

    The DYRK1A enzyme is a pivotal contributor to frequent and severe episodes of otitis media in Down syndrome, positioning it as a promising target for therapeutic interventions.