Novel approach reveals genomic landscapes of single-strand DNA breaks with nucleotide resolution in human cells

Huifen Cao, Lorena Salazar-García, Fan Gao, Thor Wahlestedt, Chun-Lin Wu, Xueer Han, Ye Cai, Dongyang Xu, Fang Wang, Lu Tang, Natalie Ricciardi, DingDing Cai, Huifang Wang, Mario P. S. Chin, James A. Timmons, Claes Wahlestedt () and Philipp Kapranov ()
Additional contact information
Huifen Cao: Huaqiao University
Lorena Salazar-García: Huaqiao University
Fan Gao: Huaqiao University
Thor Wahlestedt: Huaqiao University
Chun-Lin Wu: Second Affiliated Hospital of Fujian Medical University
Xueer Han: Huaqiao University
Ye Cai: Huaqiao University
Dongyang Xu: Huaqiao University
Fang Wang: Huaqiao University
Lu Tang: Huaqiao University
Natalie Ricciardi: University of Miami Miller School of Medicine
DingDing Cai: Huaqiao University
Huifang Wang: Huaqiao University
Mario P. S. Chin: Huaqiao University
James A. Timmons: Augur Precision Medicine LTD, Scion House, Stirling University Innovation Park
Claes Wahlestedt: University of Miami Miller School of Medicine
Philipp Kapranov: Huaqiao University

Nature Communications, 2019, vol. 10, issue 1, 1-14

Abstract: Abstract Single-strand breaks (SSBs) represent the major form of DNA damage, yet techniques to map these lesions genome-wide with nucleotide-level precision are limited. Here, we present a method, termed SSiNGLe, and demonstrate its utility to explore the distribution and dynamic changes in genome-wide SSBs in response to different biological and environmental stimuli. We validate SSiNGLe using two very distinct sequencing techniques and apply it to derive global profiles of SSBs in different biological states. Strikingly, we show that patterns of SSBs in the genome are non-random, specific to different biological states, enriched in regulatory elements, exons, introns, specific types of repeats and exhibit differential preference for the template strand between exons and introns. Furthermore, we show that breaks likely contribute to naturally occurring sequence variants. Finally, we demonstrate strong links between SSB patterns and age. Overall, SSiNGLe provides access to unexplored realms of cellular biology, not obtainable with current approaches.

Date: 2019
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DOI: 10.1038/s41467-019-13602-7

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