Intricate SUMO-based control of the homologous recombination machinery Review


Authors: Dhingra, N.; Zhao, X.
Review Title: Intricate SUMO-based control of the homologous recombination machinery
Abstract: The homologous recombination (HR) machinery plays multiple roles in genome maintenance. Best studied in the context of DNA double-stranded break (DSB) repair, recombination enzymes can cleave, pair, and unwind DNA molecules, and collaborate with regulatory proteins to execute multiple DNA processing steps before generating specific repair products. HR proteins also help to cope with problems arising from DNA replication, modulating impaired replication forks or filling DNA gaps. Given these important roles, it is not surprising that each HR step is subject to complex regulation to adjust repair efficiency and outcomes as well as to limit toxic intermediates. Recent studies have revealed intricate regulation of all steps of HR by the protein modifier SUMO, which has been increasingly recognized for its broad influence in nuclear functions. This review aims to connect established roles of SUMO with its newly identified effects on recombinational repair and stimulate further thought on many unanswered questions. © 2019 Dhingra and Zhao This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genesdev.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
Keywords: homologous recombination; sumoylation; double-strand break repair; genome maintenance
Journal Title: Genes and Development
Volume: 33
Issue: 19-20
ISSN: 0890-9369
Publisher: Cold Spring Harbor Laboratory Press  
Date Published: 2019-10-01
Start Page: 1346
End Page: 1354
Language: English
DOI: 10.1101/gad.328534.119
PUBMED: 31575678
PROVIDER: scopus
PMCID: PMC6771382
DOI/URL:
Notes: Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Xiaolan Zhao
    77 Zhao
  2. Nalini Dhingra
    10 Dhingra