Gene Essentiality Analyzed by <i>In Vivo</i> Transposon Mutagenesis and Machine Learning in a Stable Haploid Isolate of <i>Candida albicans</i>.

ABSTRACT: Knowing the full set of essential genes for a given organism provides important information about ways to promote, and to limit, its growth and survival. For many non-model organisms, the lack of a stable haploid state and low transformation efficiencies impede the use of conventional approaches to generate a genome-wide comprehensive set of mutant strains and the identification of the genes essential for growth. Here we report on the isolation and utilization of a highly stable haploid derivative of the human pathogenic fungus Candida albicans, together with a modified heterologous transposon and machine learning (ML) analysis method, to predict the degree to which all of the open reading frames are required for growth under standard laboratory conditions. We identified 1,610 C.

SUBMITTER: Segal ES 

PROVIDER: S-EPMC6212825 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature