IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0148744.html
   My bibliography  Save this article

MENGA: A New Comprehensive Tool for the Integration of Neuroimaging Data and the Allen Human Brain Transcriptome Atlas

Author

Listed:
  • Gaia Rizzo
  • Mattia Veronese
  • Paul Expert
  • Federico E Turkheimer
  • Alessandra Bertoldo

Abstract

Introduction: Brain-wide mRNA mappings offer a great potential for neuroscience research as they can provide information about system proteomics. In a previous work we have correlated mRNA maps with the binding patterns of radioligands targeting specific molecular systems and imaged with positron emission tomography (PET) in unrelated control groups. This approach is potentially applicable to any imaging modality as long as an efficient procedure of imaging-genomic matching is provided. In the original work we considered mRNA brain maps of the whole human genome derived from the Allen human brain database (ABA) and we performed the analysis with a specific region-based segmentation with a resolution that was limited by the PET data parcellation. There we identified the need for a platform for imaging-genomic integration that should be usable with any imaging modalities and fully exploit the high resolution mapping of ABA dataset. Aim: In this work we present MENGA (Multimodal Environment for Neuroimaging and Genomic Analysis), a software platform that allows the investigation of the correlation patterns between neuroimaging data of any sort (both functional and structural) with mRNA gene expression profiles derived from the ABA database at high resolution. Results: We applied MENGA to six different imaging datasets from three modalities (PET, single photon emission tomography and magnetic resonance imaging) targeting the dopamine and serotonin receptor systems and the myelin molecular structure. We further investigated imaging-genomic correlations in the case of mismatch between selected proteins and imaging targets.

Suggested Citation

  • Gaia Rizzo & Mattia Veronese & Paul Expert & Federico E Turkheimer & Alessandra Bertoldo, 2016. "MENGA: A New Comprehensive Tool for the Integration of Neuroimaging Data and the Allen Human Brain Transcriptome Atlas," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-20, February.
    • Handle: RePEc:plo:pone00:0148744
    DOI: 10.1371/journal.pone.0148744
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148744
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0148744&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0148744?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Colleen M. Burns & Hsin Chu & Susan M. Rueter & Linda K. Hutchinson & Hervé Canton & Elaine Sanders-Bush & Ronald B. Emeson, 1997. "Regulation of serotonin-2C receptor G-protein coupling by RNA editing," Nature, Nature, vol. 387(6630), pages 303-308, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marlon S. Zambrano-Mila & Monika Witzenberger & Zohar Rosenwasser & Anna Uzonyi & Ronit Nir & Shay Ben-Aroya & Erez Y. Levanon & Schraga Schwartz, 2023. "Dissecting the basis for differential substrate specificity of ADAR1 and ADAR2," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Liran Carmel & Eugene V Koonin & Stella Dracheva, 2012. "Dependencies among Editing Sites in Serotonin 2C Receptor mRNA," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-13, September.
    3. Suba Rajendren & Xiang Ye & William Dunker & Antiana Richardson & John Karijolich, 2023. "The cellular and KSHV A-to-I RNA editome in primary effusion lymphoma and its role in the viral lifecycle," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0148744. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.