Align human interactome with phenome to identify causative genes and networks underlying disease families.
BACKGROUND
Understanding the complexity in gene-phenotype relationship is vital for revealing the genetic basis of common diseases. Recent studies on the basis of human interactome and phenome not only uncovers prevalent phenotypic overlap and genetic overlap between diseases, but also reveals a modular organization of the genetic landscape of human diseases, providing new opportunities to reduce the complexity in dissecting the gene-phenotype association.


RESULTS
We provide systematic and quantitative evidence that phenotypic overlap implies genetic overlap. With these results, we perform the first heterogeneous alignment of human interactome and phenome via a network alignment technique and identify 39 disease families with corresponding causative gene networks. Finally, we propose AlignPI, an alignment-based framework to predict disease genes, and identify plausible candidates for 70 diseases. Our method scales well to the whole genome, as demonstrated by prioritizing 6154 genes across 37 chromosome regions for Crohn's disease (CD). Results are consistent with a recent meta-analysis of genome-wide association studies for CD.


BACKGROUND
Bi-modules and disease gene predictions are freely available at the URL http://bioinfo.au.tsinghua.edu.cn/alignpi/
Wu
Xuebing
X
MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
Liu
Qifang
Q
Jiang
Rui
R
D019295:Computational Biology; D003424:Crohn Disease / Q000235:genetics; D004194:Disease / Q000235:genetics*; D053263:Gene Regulatory Networks; D015894:Genome, Human; D006801:Humans; D010641:Phenotype