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Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants

Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS...

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Autores principales: McAfee, Jessica C., Lee, Sool, Lee, Jiseok, Bell, Jessica L., Krupa, Oleh, Davis, Jessica, Insigne, Kimberly, Bond, Marielle L., Zhao, Nanxiang, Boyle, Alan P., Phanstiel, Douglas H., Love, Michael I., Stein, Jason L., Ruzicka, W. Brad, Davila-Velderrain, Jose, Kosuri, Sriram, Won, Hyejung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589626/
https://www.ncbi.nlm.nih.gov/pubmed/37868037
http://dx.doi.org/10.1016/j.xgen.2023.100404
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author McAfee, Jessica C.
Lee, Sool
Lee, Jiseok
Bell, Jessica L.
Krupa, Oleh
Davis, Jessica
Insigne, Kimberly
Bond, Marielle L.
Zhao, Nanxiang
Boyle, Alan P.
Phanstiel, Douglas H.
Love, Michael I.
Stein, Jason L.
Ruzicka, W. Brad
Davila-Velderrain, Jose
Kosuri, Sriram
Won, Hyejung
author_facet McAfee, Jessica C.
Lee, Sool
Lee, Jiseok
Bell, Jessica L.
Krupa, Oleh
Davis, Jessica
Insigne, Kimberly
Bond, Marielle L.
Zhao, Nanxiang
Boyle, Alan P.
Phanstiel, Douglas H.
Love, Michael I.
Stein, Jason L.
Ruzicka, W. Brad
Davila-Velderrain, Jose
Kosuri, Sriram
Won, Hyejung
author_sort McAfee, Jessica C.
collection PubMed
description Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.
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spelling pubmed-105896262023-10-22 Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants McAfee, Jessica C. Lee, Sool Lee, Jiseok Bell, Jessica L. Krupa, Oleh Davis, Jessica Insigne, Kimberly Bond, Marielle L. Zhao, Nanxiang Boyle, Alan P. Phanstiel, Douglas H. Love, Michael I. Stein, Jason L. Ruzicka, W. Brad Davila-Velderrain, Jose Kosuri, Sriram Won, Hyejung Cell Genom Resource Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture. Elsevier 2023-09-15 /pmc/articles/PMC10589626/ /pubmed/37868037 http://dx.doi.org/10.1016/j.xgen.2023.100404 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Resource
McAfee, Jessica C.
Lee, Sool
Lee, Jiseok
Bell, Jessica L.
Krupa, Oleh
Davis, Jessica
Insigne, Kimberly
Bond, Marielle L.
Zhao, Nanxiang
Boyle, Alan P.
Phanstiel, Douglas H.
Love, Michael I.
Stein, Jason L.
Ruzicka, W. Brad
Davila-Velderrain, Jose
Kosuri, Sriram
Won, Hyejung
Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title_full Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title_fullStr Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title_full_unstemmed Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title_short Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
title_sort systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589626/
https://www.ncbi.nlm.nih.gov/pubmed/37868037
http://dx.doi.org/10.1016/j.xgen.2023.100404
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