Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Single-cell replication profiling reveals stochastic regulation of the mammalian replication-timing program

Vishnu Dileep, David M. Gilbert
doi: https://doi.org/10.1101/158352
Vishnu Dileep
1Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, FL 32306, USA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David M. Gilbert
1Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, FL 32306, USA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: gilbert@bio.fsu.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

In mammalian cells, distinct replication domains (RDs) corresponding to structural units of chromosomes called topologically-associating domains (TADs) replicate at different times during S-phase1–4. Further, early/late replication of RDs corresponds to active/inactive chromatin interaction compartments5,6. Although replication origins are selected stochastically, such that each cell is using a different cohort of origins to replicate their genomes7–12, replication-timing is regulated independently and upstream of origin selection13. Moreover, cytogenetic evidence suggests that the same cohorts of RDs can replicate synchronously in consecutive cell cycles14. Hence, measuring the extent of cell-to-cell variation in replication timing is central to studies of chromosome structure and function. Here we devise a strategy to measure variation in single-cell replication timing using copy number variation. Our results detect a similar degree of stochastic variation in the temporal order of domain replication from cell-to-cell as within individual cells and between early vs. late replicating compartments. Finally, borders between replicated and un-replicated DNA were highly conserved between cells with domains replicating at similar times demarcating active and inactive compartments of the nucleus. These results demonstrate that the precise environment within each cell does not influence the extent of stochastic variation in replication timing.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted June 30, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Single-cell replication profiling reveals stochastic regulation of the mammalian replication-timing program
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Single-cell replication profiling reveals stochastic regulation of the mammalian replication-timing program
Vishnu Dileep, David M. Gilbert
bioRxiv 158352; doi: https://doi.org/10.1101/158352
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Single-cell replication profiling reveals stochastic regulation of the mammalian replication-timing program
Vishnu Dileep, David M. Gilbert
bioRxiv 158352; doi: https://doi.org/10.1101/158352

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3513)
  • Biochemistry (7358)
  • Bioengineering (5334)
  • Bioinformatics (20290)
  • Biophysics (10032)
  • Cancer Biology (7753)
  • Cell Biology (11323)
  • Clinical Trials (138)
  • Developmental Biology (6442)
  • Ecology (9962)
  • Epidemiology (2065)
  • Evolutionary Biology (13340)
  • Genetics (9363)
  • Genomics (12594)
  • Immunology (7717)
  • Microbiology (19055)
  • Molecular Biology (7452)
  • Neuroscience (41085)
  • Paleontology (300)
  • Pathology (1232)
  • Pharmacology and Toxicology (2140)
  • Physiology (3169)
  • Plant Biology (6867)
  • Scientific Communication and Education (1275)
  • Synthetic Biology (1899)
  • Systems Biology (5320)
  • Zoology (1089)