https://www.biorxiv.org/content/early/2018/12/05/487157

Nick Jacobs, Ji Woong Park, Tim Peterson

bioRxiv 487157; doi: https://doi.org/10.1101/487157

Genotype-phenotype relationships are at the heart of biology and medicine. Numerous advances in genotyping and phenotyping have accelerated the pace of disease gene and drug discovery. Though now that there are so many genes and drugs to study, it makes prioritizing them difficult. Also, disease model assays are getting more complex and this is reflected in the growing complexity of research papers and the cost of drug development. Herein we propose a way out of this arms race. We argue for synthetic interaction testing in mammalian cells using cell growth - changes in cell number that could be due to a number of factors - as a readout to judge the potential of a genetic or environmental variable of interest (e.g., a gene or drug). That is, if a gene or drug of interest is combined with a known perturbation and causes a strong cell growth phenotype relative to that caused by the known perturbation alone, this justifies proceeding with the gene/drug in more complex models like mouse models where the known perturbation is already validated. This recommendation is backed by the following: 1) Genes required for cell growth involve nearly all classifications of cellular and molecular processes; 2) Nearly all genes important in cancer - a disease defined by altered cell number - are also important in other complex diseases; 3) Patient condition and patient cell growth responses to many drugs are comparable. Taken together, these findings suggest cell growth could be broadly applicable phenotype for understanding gene and drug function. Measuring cell growth is robust, and requires little time and money. These are features that have long been capitalized on by pioneers using model organisms that we hope more mammalian biologists will recognize.