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Çelik, M.H.* ; Gagneur, J. ; Lim, R.G.* ; Wu, J.* ; Thompson, L.M.* ; Xie, X.*

Identifying dysregulated regions in amyotrophic lateral sclerosis through chromatin accessibility outliers.

HGG Advances 5:100318 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The high heritability of ALS contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone ChIP-seq and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Aberrant Gene Expression ; Amyotrophic Lateral Sclerosis (als) ; Chromatin Accessibility ; Epigenetics ; Motor Neuron Disease ; Multiomics ; Outlier Detection ; Post-transcriptional Regulation ; Rare Disease ; Transcriptional Regulation; Model; Bcl-2; Distinct; Genome; Gene
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 2666-2477
e-ISSN 2666-2477
Zeitschrift Human Genetics and Genomics Advances
Quellenangaben Band: 5, Heft: 3, Seiten: , Artikelnummer: 100318 Supplement: ,
Verlag Cell Press
Verlagsort Radarweg 29, 1043 Nx Amsterdam, Netherlands
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503800-001
Förderungen UCI IPH Pilot Award
National Science Foundation
Robert Packard Center for ALS Research at Johns Hopkins
DOI 10.1016/j.xhgg.2024.100318
WOS ID 001262083000001
Scopus ID 85196956532
PubMed ID 38872308
Erfassungsdatum 2024-07-19
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