Simulation and estimation of gene number in a biological pathway using almost complete saturation mutagenesis screening of haploid mouse cells

Abstract

Background: Genome-wide saturation mutagenesis and subsequent phenotype-driven screening has been central to a comprehensive understanding of complex biological processes in classical model organisms such as flies, nematodes, and plants. The degree of "saturation" (i.e., the fraction of possible target genes identified) has been shown to be a critical parameter in determining all relevant genes involved in a biological function, without prior knowledge of their products. In mammalian model systems, however, the relatively large scale and labor intensity of experiments have hampered the achievement of actual saturation mutagenesis, especially for recessive traits that require biallelic mutations to manifest detectable phenotypes. Results: By exploiting the recently established haploid mouse embryonic stem cells (ESCs), we present an implementation of almost complete saturation mutagenesis in a mammalian system. The haploid ESCs were mutagenized with the chemical mutagen N-ethyl-N-nitrosourea (ENU) and processed for the screening of mutants defective in various steps of the glycosylphosphatidylinositol-anchor biosynthetic pathway. The resulting 114 independent mutant clones were characterized by a functional complementation assay, and were shown to be defective in any of 20 genes among all 22 known genes essential for this well-characterized pathway. Ten mutants were further validated by whole-exome sequencing. The predominant generation of single-nucleotide substitutions by ENU resulted in a gene mutation rate proportional to the length of the coding sequence, which facilitated the experimental design of saturation mutagenesis screening with the aid of computational simulation. Conclusions: Our study enables mammalian saturation mutagenesis to become a realistic proposition. Computational simulation, combined with a pilot mutagenesis experiment, could serve as a tool for the estimation of the number of genes essential for biological processes such as drug target pathways when a positive selection of mutants is available.