Epistasis analysis with global transcriptional phenotypes.
Classical epistasis analysis can determine the order of function of genes in pathways using morphological, biochemical and other phenotypes. It requires knowledge of the pathway's phenotypic output and a variety of experimental expertise and so is unsuitable for genome-scale analysis. Here we used microarray profiles of mutants as phenotypes for epistasis analysis. Considering genes that regulate activity of protein kinase A in Dictyostelium, we identified known and unknown epistatic relationships and reconstructed a genetic network with microarray phenotypes alone. This work shows that microarray data can provide a uniform, quantitative tool for large-scale genetic network analysis.
Van Driessche
Nancy
N
Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA.
Demsar
Janez
J
Booth
Ezgi O
EO
Hill
Paul
P
Juvan
Peter
P
Zupan
Blaz
B
Kuspa
Adam
A
Shaulsky
Gad
G
D000818:Animals; D017868:Cyclic AMP-Dependent Protein Kinases / Q000235:genetics / Q000378:metabolism; D004023:Dictyostelium / Q000201:enzymology / Q000235:genetics*; D004843:Epistasis, Genetic; D009154:Mutation; D011493:Protein Kinase C / Q000235:genetics / Q000378:metabolism; D014158:Transcription, Genetic
D017868:Cyclic AMP-Dependent Protein Kinases; D011493:Protein Kinase C