Analysis of Yeast’s ORF Upstream Regions by Parallel Processing, Microarrays, and Computational Methods

Proceedings of the Twentieth International Conference on Machine Learning, 2000

Volume

Proceedings of the Twentieth International Conference on Machine Learning, 2000

Contents

We use a network of workstations to compute all pairwise alignments of the 500 bp upstream regions of 6,225 yeast ORFs (Open Reading Frames). We correlate the alignments with DNA microarray expression data from budding yeast cells over an oxidative stress time course. We confirm on a genomic scale that, in general, genes with extremely similar upstream regions have similar activity levels, even when located on different chromosomes. As the difference in upstream regions increases, the correlation rapidly drops towards zero. Divergent ORFs with overlapping upstream regions do not seem to be correlated in any way. The pairwise alignments coupled with the expression data, together with other computational techniques, suggest a few new putative regulatory binding sites that can be tested experimentally. Finally, we investigate the inherent symmetry present in the two strands of the yeast genome. We show that it extends at least all the way up to 9-mers and is likely to result from different evolutionary pressures operating at different length scales.