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Cellular and genetic drivers of RNA editing variation in the human brain

Author

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  • Winston H. Cuddleston

    (Department of Psychiatry at Mount Sinai
    Department of Genetics and Genomic Sciences at Mount Sinai
    Seaver Autism Center for Research and Treatment at Mount Sinai
    Pamela Sklar Division of Psychiatric Genomics at Mount Sinai)

  • Junhao Li

    (University of California, San Diego)

  • Xuanjia Fan

    (Department of Psychiatry at Mount Sinai
    Department of Genetics and Genomic Sciences at Mount Sinai
    Seaver Autism Center for Research and Treatment at Mount Sinai
    Pamela Sklar Division of Psychiatric Genomics at Mount Sinai)

  • Alexey Kozenkov

    (Department of Psychiatry at Mount Sinai
    James J Peters VA Medical Center)

  • Matthew Lalli

    (Department of Psychiatry at Mount Sinai
    Seaver Autism Center for Research and Treatment at Mount Sinai)

  • Shahrukh Khalique

    (Department of Psychiatry at Mount Sinai
    James J Peters VA Medical Center)

  • Stella Dracheva

    (Department of Psychiatry at Mount Sinai
    James J Peters VA Medical Center)

  • Eran A. Mukamel

    (University of California, San Diego)

  • Michael S. Breen

    (Department of Psychiatry at Mount Sinai
    Department of Genetics and Genomic Sciences at Mount Sinai
    Seaver Autism Center for Research and Treatment at Mount Sinai
    Pamela Sklar Division of Psychiatric Genomics at Mount Sinai)

Abstract

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

Suggested Citation

  • Winston H. Cuddleston & Junhao Li & Xuanjia Fan & Alexey Kozenkov & Matthew Lalli & Shahrukh Khalique & Stella Dracheva & Eran A. Mukamel & Michael S. Breen, 2022. "Cellular and genetic drivers of RNA editing variation in the human brain," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30531-0
    DOI: 10.1038/s41467-022-30531-0
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    References listed on IDEAS

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    1. Miyoko Higuchi & Stefan Maas & Frank N. Single & Jochen Hartner & Andrei Rozov & Nail Burnashev & Dirk Feldmeyer & Rolf Sprengel & Peter H. Seeburg, 2000. "Point mutation in an AMPA receptor gene rescues lethality in mice deficient in the RNA-editing enzyme ADAR2," Nature, Nature, vol. 406(6791), pages 78-81, July.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Adam Kepecs & Gordon Fishell, 2014. "Interneuron cell types are fit to function," Nature, Nature, vol. 505(7483), pages 318-326, January.
    4. Hagit T. Porath & Shai Carmi & Erez Y. Levanon, 2014. "A genome-wide map of hyper-edited RNA reveals numerous new sites," Nature Communications, Nature, vol. 5(1), pages 1-10, December.
    5. Susan M. Rueter & T. Renee Dawson & Ronald B. Emeson, 1999. "Regulation of alternative splicing by RNA editing," Nature, Nature, vol. 399(6731), pages 75-80, May.
    6. Jinhong Wie & Apoorva Bharthur & Morgan Wolfgang & Vinodh Narayanan & Keri Ramsey & Kimberly Aranda & Qi Zhang & Yandong Zhou & Dejian Ren, 2020. "Intellectual disability-associated UNC80 mutations reveal inter-subunit interaction and dendritic function of the NALCN channel complex," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
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    Cited by:

    1. Miguel Rodriguez de los Santos & Brian H. Kopell & Ariela Buxbaum Grice & Gauri Ganesh & Andy Yang & Pardis Amini & Lora E. Liharska & Eric Vornholt & John F. Fullard & Pengfei Dong & Eric Park & Sara, 2024. "Divergent landscapes of A-to-I editing in postmortem and living human brain," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Amir Dailamy & Weiqi Lyu & Sami Nourreddine & Michael Tong & Joseph Rainaldi & Daniella McDonald & Rebecca Panwala & Alysson Muotri & Michael S. Breen & Kun Zhang & Prashant Mali, 2024. "Charting and probing the activity of ADARs in human development and cell-fate specification," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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