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Cell-type specific effects of genetic variation on chromatin accessibility during human neuronal differentiation

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood how these variants influence gene regulation. To model the functional impact of common genetic variation on the non-coding genome during hu...

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Detalles Bibliográficos
Autores principales: Liang, Dan, Elwell, Angela L., Aygün, Nil, Krupa, Oleh, Wolter, Justin M., Kyere, Felix A., Lafferty, Michael J., Cheek, Kerry E., Courtney, Kenan P., Yusupova, Marianna, Garrett, Melanie E., Ashley-Koch, Allison, Crawford, Gregory E., Love, Michael I., de la Torre-Ubieta, Luis, Geschwind, Daniel H., Stein, Jason L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254789/
https://www.ncbi.nlm.nih.gov/pubmed/34017130
http://dx.doi.org/10.1038/s41593-021-00858-w
Descripción
Sumario:Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood how these variants influence gene regulation. To model the functional impact of common genetic variation on the non-coding genome during human cortical development, we performed ATAC-seq and analyzed chromatin accessibility quantitative trait loci in cultured human neural progenitor cells and their differentiated neuronal progeny from 92 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (~30%) of caQTLs were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type specific caQTLs and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying non-coding neuropsychiatric disorder risk loci.