Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

Genes

John L. Hartman³  Chandler Stisher³  Darryl A. Outlaw³  Jingyu Guo³  Najaf A. Shah³  Dehua Tian³  Sean M. Santos³  John W. Rodgers³  Richard A. White¹  Karen E. Nelson²  John Burn²  Nicholas J. Schork²  James R. Lupski² 

[1] Department of Statistics and Michael Smith Laboratories, University of British Columbia, 3182 Earth Sciences Building, 2207 Main Mall, Vancouver, BC V6T-1Z4, Canada; E-Mail:Department of Genetics, University of Alabama at Birmingham, 730 Hugh Kaul Human Genetics Building, 720 20th Street South, Birmingham, AL 35294, USA;;Department of Genetics, University of Alabama at Birmingham, 730 Hugh Kaul Human Genetics Building, 720 20th Street South, Birmingham, AL 35294, USA; E-Mails:

关键词: yeast phenomics;    yeast models of human disease;    cell proliferation phenotypes or cell proliferation parameters (CPPs);    gene interaction networks;    quantitative high throughput cell array phenotyping (Q-HTCP);    genetic buffering;    cystic fibrosis (CF);    human-like (HL) yeast media;    ammonium toxicity;    recursive expectation-maximization clustering (REMc);   

DOI  :  10.3390/genes6010024

来源: mdpi

【 摘 要 】

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.