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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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10589626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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