Parallel competition analysis of Saccharomyces cerevisiae strains differing by a single base using polymerase colonies.

We describe a strategy to analyze the impact of single nucleotide mutations on protein function. Our method utilizes a combination of yeast functional complementation, growth competition of mutant pools and polyacrylamide gel immobilized PCR. A system was constructed in which the yeast PGK1 gene was expressed from a plasmid-borne copy of the gene in a PGK1 deletion strain of Saccharomyces cerevisiae. Using this system, we demonstrated that the enrichment or depletion of PGK1 point mutants from a mixed culture was consistent with the expected results based on the isolated growth rates of the mutants. Enrichment or depletion of individual point mutants was shown to result from increases or decreases, respectively, in the specific activities of the encoded proteins. Further, we demonstrate the ability to analyze the functional effect of many individual point mutations in parallel. By functional complementation of yeast deletions with human homologs, our technique could be readily applied to the functional analysis of single nucleotide polymorphisms in human genes of medical interest.

Digital quantitative measurements of gene expression.

One of the primary goals of functional genomics is to provide a quantitative understanding of gene function. However, the success of this enterprise is dependent on the accuracy and precision of the functional genomic data. A novel approach, digital analysis of gene expression (DAGE) described herein, is an accurate and precise technology for measuring digital gene expression on a relative or absolute scale by simply counting the number of transcripts of a gene being expressed at a given time. The result is a greatly improved technology sensitive enough for identifying and quantifying small (but biologically important and statistically relevant) changes in gene expression. Fourteen genes involved in galactose metabolism in Saccharomyces cerevisiae were analyzed for their expression levels in glucose and galactose minimal media. The quantitative expression results were characterized in terms of distributional and accuracy attributes; they were also in general agreement (in terms of direction of change) with corresponding results obtained using microarray technology. DAGE is likely to have profound implications in the field of functional genomics because the gene expression measurements are digital in nature and therefore more accurate than any other technologies.