Identification of Genes Which Affect Chromosomal Instability (CIN) in a Dosage-Sensitive Manner in Saccharomyces cerevisiae

Heinecke, Dominic (2014). Identification of Genes Which Affect Chromosomal Instability (CIN) in a Dosage-Sensitive Manner in Saccharomyces cerevisiae. MPhil thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.0000eff2

Abstract

Chromosomal instability (CIN) refers to circumstances which can alter the chromosomal content of a cell during its division. Aneuploidy is known to be a direct result of CIN but importantly has recently been shown to affect CIN itself. A possible reason as to why aneuploidy could influence CIN is by gene copy-number-variation (CNV) of dosage sensitive genes that are present on the chromosome which was lost or gained by the aneuploid cell. To test this hypothesis, our lab developed a novel form of CIN assay in budding yeast, termed Improved GFP-based Chromosome Transmission Fidelity (iCTF) assay, which allows us to determine the effects that slight copy number changes of individual genes have on CIN in a high-throughput manner. We utilized this assay to systematically screen for genes which can affect the loss rate of a yeast artificial chromosome (YAC) when (1) their copy number was increased by a gene containing plasmid (Over-Dosage CIN) or (2) decreased due to haploid insufficiency (HI-CIN). We identified and validated 36 CIN genes in the Over-Dosage CIN screen as well as 139 CIN genes in the HI-CIN screen. From these 175 CIN genes, in total, only 25 known CIN genes were identified by previous screens, which leave 150 novel CIN genes. Most interestingly, 9 out of 175 CIN gene candidates decrease CIN. To our knowledge this is the first reported case of this phenotype.

CIN and aneuploidy are widely known to frequently co-exist in tumorigenic tissues and that they can be caused by loss or gain of certain genes, often involved in maintenance of genomic integrity. The spectrum of such genes is only partially known and it is so far impossible to predict the effects that individual mutations could have on chromosomal instability, especially in such a complex and diverse background as cancer cells. To address this issue we present here a fast and reliable method to determine the effects of single copy number variations in CIN in a quantitative manner.

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