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Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation

Overview of attention for article published in BMC Biology, July 2015
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Title
Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation
Published in
BMC Biology, July 2015
DOI 10.1186/s12915-015-0148-y
Pubmed ID
Authors

Michael Chiang, Amanda Cinquin, Adrian Paz, Edward Meeds, Christopher A. Price, Max Welling, Olivier Cinquin

Abstract

Stem cells are thought to play a critical role in minimizing the accumulation of mutations, but it is not clear which strategies they follow to fulfill that performance objective. Slow cycling of stem cells provides a simple strategy that can minimize cell pedigree depth and thereby minimize the accumulation of replication-dependent mutations. Although the power of this strategy was recognized early on, a quantitative assessment of whether and how it is employed by biological systems is missing. Here we address this problem using a simple self-renewing organ - the C. elegans gonad - whose overall organization is shared with many self-renewing organs. Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached. This compromise is such that worm germline stem cells should cycle more slowly than their differentiating counterparts, but only by a modest amount. Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions. Our findings shed light both on design principles that underlie the role of stem cells in delaying aging, and on evolutionary forces that shape stem cell gene regulatory networks.

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The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 47%
Student > Master 5 17%
Other 2 7%
Student > Bachelor 2 7%
Student > Ph. D. Student 2 7%
Other 3 10%
Unknown 2 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 33%
Agricultural and Biological Sciences 9 30%
Business, Management and Accounting 1 3%
Mathematics 1 3%
Computer Science 1 3%
Other 4 13%
Unknown 4 13%