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Beagrie, R.A.* ; Thieme, C.J.* ; Annunziatella, C.* ; Baugher, C.* ; Zhang, Y.* ; Schueler, M.* ; Kukalev, A.* ; Kempfer, R.* ; Chiariello, A.M.* ; Bianco, S.* ; Li, Y.* ; Davis, T.* ; Scialdone, A. ; Welch, L.R.* ; Nicodemi, M.* ; Pombo, A.*

Multiplex-GAM: genome-wide identification of chromatin contacts yields insights overlooked by Hi-C.

Nat. Methods 20, 1037-1047 (2023)
Postprint DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
Technology for measuring 3D genome topology is increasingly important for studying gene regulation, for genome assembly and for mapping of genome rearrangements. Hi-C and other ligation-based methods have become routine but have specific biases. Here, we develop multiplex-GAM, a faster and more affordable version of genome architecture mapping (GAM), a ligation-free technique that maps chromatin contacts genome-wide. We perform a detailed comparison of multiplex-GAM and Hi-C using mouse embryonic stem cells. When examining the strongest contacts detected by either method, we find that only one-third of these are shared. The strongest contacts specifically found in GAM often involve ‘active’ regions, including many transcribed genes and super-enhancers, whereas in Hi-C they more often contain ‘inactive’ regions. Our work shows that active genomic regions are involved in extensive complex contacts that are currently underestimated in ligation-based approaches, and highlights the need for orthogonal advances in genome-wide contact mapping technologies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Rna-polymerase-ii; Organization; Reveals; Principles; Dynamics
ISSN (print) / ISBN 1548-7091
e-ISSN 1548-7105
Zeitschrift Nature Methods
Quellenangaben Band: 20, Heft: 7, Seiten: 1037-1047 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epigenetics and Stem Cells (IES)
Institute of Functional Epigenetics (IFE)
Institute of Computational Biology (ICB)
Förderungen NIDDK NIH HHS
Wellcome Trust