A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans.

Abstract:

:The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets.

journal_name

Nat Genet

journal_title

Nature genetics

authors

Lee I,Lehner B,Crombie C,Wong W,Fraser AG,Marcotte EM

doi

10.1038/ng.2007.70

subject

Has Abstract

pub_date

2008-02-01 00:00:00

pages

181-8

issue

2

eissn

1061-4036

issn

1546-1718

pii

ng.2007.70

journal_volume

40

pub_type

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