1. Genetics and Genomics
  2. Neuroscience

MicroRNA-eQTLs in the developing human neocortex link miR-4707-3p expression to brain size

  1. Michael J Lafferty
  2. Nil Aygün
  3. Niyanta K Patel
  4. Oleh Krupa
  5. Dan Liang
  6. Justin M Wolter
  7. Daniel H Geschwind
  8. Luis de la Torre-Ubieta
  9. Jason L Stein  Is a corresponding author
  1. University of North Carolina at Chapel Hill, United States
  2. University of California, Los Angeles, United States
https://doi.org/10.7554/eLife.79488
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Cite this article
  1. Michael J Lafferty
  2. Nil Aygün
  3. Niyanta K Patel
  4. Oleh Krupa
  5. Dan Liang
  6. Justin M Wolter
  7. Daniel H Geschwind
  8. Luis de la Torre-Ubieta
  9. Jason L Stein
(2023)
MicroRNA-eQTLs in the developing human neocortex link miR-4707-3p expression to brain size
eLife 12:e79488.
https://doi.org/10.7554/eLife.79488
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  3. Download .RIS

Abstract

Expression quantitative trait loci (eQTL) data have proven important for linking non-coding loci to protein-coding genes. But eQTL studies rarely measure microRNAs (miRNAs), small non-coding RNAs known to play a role in human brain development and neurogenesis. Here, we performed small-RNA sequencing across 212 mid-gestation human neocortical tissue samples, measured 907 expressed miRNAs, discovering 111 of which were novel, and identified 85 local-miRNA-eQTLs. Colocalization of miRNA-eQTLs with GWAS summary statistics yielded one robust colocalization of miR-4707-3p expression with educational attainment and brain size phenotypes, where the miRNA expression increasing allele was associated with decreased brain size. Exogenous expression of miR-4707-3p in primary human neural progenitor cells decreased expression of predicted targets and increased cell proliferation, indicating miR-4707-3p modulates progenitor gene regulation and cell fate decisions. Integrating miRNA-eQTLs with existing GWAS yielded evidence of a miRNA that may influence human brain size and function via modulation of neocortical brain development.

Data availability

Small RNA-sequencing data and sample genotypes will be available via dbGaP with study accession number phs003106.v1.p1. Total RNA-sequencing data can be found under the dbGaP study phs001900.v1.p1. Scripts used to reproduce the analyses presented here are available via bitbucket code repository at https://bitbucket.org/steinlabunc/mirna-eqtl-manuscript/.

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

Article and author information

Author details

  1. Michael J Lafferty

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Nil Aygün

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Niyanta K Patel

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Oleh Krupa

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Dan Liang

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Justin M Wolter

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Daniel H Geschwind

    Department of Neurology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2896-3450

  8. Luis de la Torre-Ubieta

    Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Jason L Stein

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    For correspondence
    jason_stein@med.unc.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4829-0513

Funding

National Institutes of Health (R01MH120125,R01MH118349,U54EB020403,R00MH102357)

  • Jason L Stein

National Institute of General Medical Sciences (5T32GM067553-13)

  • Michael J Lafferty

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

Reviewing Editor

  1. Joseph G Gleeson, University of California, San Diego, United States

Ethics

Human subjects: Human fetal brain tissue was obtained from the UCLA Gene and Cell Therapy Core following institutional review board regulations. This study was declared Exempt by the UNC Institutional Review Board (16-0054).

Version history

  1. Preprint posted: April 1, 2022 (view preprint)
  2. Received: April 14, 2022
  3. Accepted: January 10, 2023
  4. Accepted Manuscript published: January 11, 2023 (version 1)
  5. Version of Record published: January 20, 2023 (version 2)

Copyright

© 2023, Lafferty 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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  1. Michael J Lafferty
  2. Nil Aygün
  3. Niyanta K Patel
  4. Oleh Krupa
  5. Dan Liang
  6. Justin M Wolter
  7. Daniel H Geschwind
  8. Luis de la Torre-Ubieta
  9. Jason L Stein
(2023)
MicroRNA-eQTLs in the developing human neocortex link miR-4707-3p expression to brain size
eLife 12:e79488.
https://doi.org/10.7554/eLife.79488

Share this article

https://doi.org/10.7554/eLife.79488

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