Literature DB >> 32659782

PsychENCODE and beyond: transcriptomics and epigenomics of brain development and organoids.

Alexandre Jourdon1, Soraya Scuderi1, Davide Capauto1, Alexej Abyzov2, Flora M Vaccarino3,4,5.   

Abstract

Crucial decisions involving cell fate and connectivity that shape the distinctive development of the human brain occur in the embryonic and fetal stages-stages that are difficult to access and investigate in humans. The last decade has seen an impressive increase in resources-from atlases and databases to biological models-that is progressively lifting the curtain on this critical period. In this review, we describe the current state of genomic, transcriptomic, and epigenomic datasets charting the development of normal human brain with a particular focus on recent single-cell technologies. We discuss the emergence of brain organoids generated from pluripotent stem cells as a model to compensate for the limited availability of fetal tissue. Indeed, comparisons of neural lineages, transcriptional dynamics, and noncoding element activity between fetal brain and organoids have helped identify gene regulatory networks functioning at early stages of brain development. Altogether, we argue that large multi-omics investigations have pushed brain development into the "big data" era, and that current and future transversal approaches needed to leverage both fetal brain and organoid resources promise to answer major questions of brain biology and psychiatry.

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Mesh:

Year:  2020        PMID: 32659782      PMCID: PMC7689467          DOI: 10.1038/s41386-020-0763-3

Source DB:  PubMed          Journal:  Neuropsychopharmacology        ISSN: 0893-133X            Impact factor:   8.294


  4 in total

Review 1.  The Long Non-Coding RNA GOMAFU in Schizophrenia: Function, Disease Risk, and Beyond.

Authors:  Paul M Zakutansky; Yue Feng
Journal:  Cells       Date:  2022-06-17       Impact factor: 7.666

2.  Big data in psychiatry: multiomics, neuroimaging, computational modeling, and digital phenotyping.

Authors:  Kerry J Ressler; Leanne M Williams
Journal:  Neuropsychopharmacology       Date:  2020-09-12       Impact factor: 8.294

3.  Editorial: Decoding Brain Function Through Genetics.

Authors:  Kazuya Toriumi; Guang-Zhong Wang; Stefano Berto; Noriyoshi Usui
Journal:  Front Genet       Date:  2022-04-11       Impact factor: 4.599

Review 4.  Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases.

Authors:  Chirag Gupta; Pramod Chandrashekar; Ting Jin; Chenfeng He; Saniya Khullar; Qiang Chang; Daifeng Wang
Journal:  J Neurodev Disord       Date:  2022-05-02       Impact factor: 4.074

  4 in total

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