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Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants.

Authors :
Gallegos, Jenna E.
Adames, Neil R.
Rogers, Mark F.
Kraikivski, Pavel
Ibele, Aubrey
Nurzynski-Loth, Kevin
Kudlow, Eric
Murali, T. M.
Tyson, John J.
Peccoud, Jean
Source :
NPJ Systems Biology & Applications; 5/6/2020, Vol. 6 Issue 1, p1-15, 15p
Publication Year :
2020

Abstract

Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues. Here, we describe a hybrid approach in which the 630 genetic interactions between 36 cell-cycle genes are quantitatively estimated by high-throughput phenotyping with an unprecedented number of biological replicates. Using this approach, we identify a subset of high-confidence genetic interactions, which we use to refine a previously published mathematical model of the cell cycle. We also present a quantitative dataset of the growth rate of these mutants under six different media conditions in order to inform future cell cycle models. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20567189
Volume :
6
Issue :
1
Database :
Complementary Index
Journal :
NPJ Systems Biology & Applications
Publication Type :
Academic Journal
Accession number :
143074417
Full Text :
https://doi.org/10.1038/s41540-020-0134-z