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Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains

BACKGROUND: The genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it...

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Autores principales: Gamache, Julia, Gingerich, Daniel, Shwab, E. Keats, Barrera, Julio, Garrett, Melanie E., Hume, Cordelia, Crawford, Gregory E., Ashley-Koch, Allison E., Chiba-Falek, Ornit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546724/
https://www.ncbi.nlm.nih.gov/pubmed/37789374
http://dx.doi.org/10.1186/s13578-023-01120-5
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author Gamache, Julia
Gingerich, Daniel
Shwab, E. Keats
Barrera, Julio
Garrett, Melanie E.
Hume, Cordelia
Crawford, Gregory E.
Ashley-Koch, Allison E.
Chiba-Falek, Ornit
author_facet Gamache, Julia
Gingerich, Daniel
Shwab, E. Keats
Barrera, Julio
Garrett, Melanie E.
Hume, Cordelia
Crawford, Gregory E.
Ashley-Koch, Allison E.
Chiba-Falek, Ornit
author_sort Gamache, Julia
collection PubMed
description BACKGROUND: The genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. METHODS: Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). RESULTS: Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. CONCLUSIONS: To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-023-01120-5.
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spelling pubmed-105467242023-10-04 Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains Gamache, Julia Gingerich, Daniel Shwab, E. Keats Barrera, Julio Garrett, Melanie E. Hume, Cordelia Crawford, Gregory E. Ashley-Koch, Allison E. Chiba-Falek, Ornit Cell Biosci Research BACKGROUND: The genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. METHODS: Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). RESULTS: Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. CONCLUSIONS: To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-023-01120-5. BioMed Central 2023-10-03 /pmc/articles/PMC10546724/ /pubmed/37789374 http://dx.doi.org/10.1186/s13578-023-01120-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gamache, Julia
Gingerich, Daniel
Shwab, E. Keats
Barrera, Julio
Garrett, Melanie E.
Hume, Cordelia
Crawford, Gregory E.
Ashley-Koch, Allison E.
Chiba-Falek, Ornit
Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title_full Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title_fullStr Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title_full_unstemmed Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title_short Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains
title_sort integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in alzheimer’s disease brains
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546724/
https://www.ncbi.nlm.nih.gov/pubmed/37789374
http://dx.doi.org/10.1186/s13578-023-01120-5
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