Harnessing natural sequence variation to dissect posttranscriptional regulatory networks in yeast
Mina Fazlollahi1, Eunjee Lee2, Ivor Muroff2
1Department of Biological Sciences, Columbia University, New York, New York 10027 Department of Systems Biology, Columbia University, New York, New York 10032.
Abstract:
Understanding how genomic variation influences phenotypic variation through the molecular networks of the cell is one of the central challenges of biology. Transcriptional regulation has received much attention, but equally important is the posttranscriptional regulation of mRNA stability. Here we applied a systems genetics approach to dissect posttranscriptional regulatory networks in the budding yeast Saccharomyces cerevisiae. Quantitative sequence-to-affinity models were built from high-throughput in vivo RNA binding protein (RBP) binding data for 15 yeast RBPs. Integration of these models with genome-wide mRNA expression data allowed us to estimate protein-level RBP regulatory activity for individual segregants from a genetic cross between two yeast strains. Treating these activities as a quantitative trait, we mapped trans-acting loci (activity quantitative trait loci, or aQTLs) that act via posttranscriptional regulation of transcript stability. We predicted and experimentally confirmed that a coding polymorphism at the IRA2 locus modulates Puf4p activity. Our results also indicate that Puf3p activity is modulated by distinct loci, depending on whether it acts via the 5' or the 3' untranslated region of its target mRNAs. Together, our results validate a general strategy for dissecting the connectivity between posttranscriptional [corrected] regulators and their upstream signaling pathways.
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