Science (American Association for the Advancement of Science), 2024-05, Vol.384 (6698), p.eadh0559
2024
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- Autor(en) / Beteiligte
- Titel
- Massively parallel characterization of regulatory elements in the developing human cortex
- Ist Teil von
- Science (American Association for the Advancement of Science), 2024-05, Vol.384 (6698), p.eadh0559
- Ort / Verlag
- United States: The American Association for the Advancement of Science
- Erscheinungsjahr
- 2024
- Quelle
- American Association for the Advancement of Science
- Beschreibungen/Notizen
- Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 0036-8075, 1095-9203eISSN: 1095-9203DOI: 10.1126/science.adh0559Titel-ID: cdi_proquest_miscellaneous_3060384329
- Format
- –
- Schlagworte
- Artificial intelligence, Assaying, Brain, Cerebral Cortex - embryology, Cerebral Cortex - growth & development, Cerebral Cortex - metabolism, Chromatin, Chromatin - genetics, Chromatin - metabolism, Computational neuroscience, Deep Learning, Disorders, Enhancer Elements, Genetic, Etiology, Gene Expression Regulation, Developmental, Gene regulation, Gene sequencing, Genetic diversity, Genetic variance, Gestation, Human performance, Humans, Literary Devices, Machine learning, Mental disorders, Model accuracy, Model testing, Mutagenesis, Neural networks, Neurodevelopmental disorders, Neurogenesis - genetics, Neurons - metabolism, Nucleotides, Organoids, Organoids - metabolism, Pregnancy, Psychiatry, Regulatory sequences, Regulatory Sequences, Nucleic Acid, Repressors, Transcription factors