ABSTRACT The genome provides a precise, biological blueprint of life. To implement this blueprint correctly, the genome must be read with great precision;; however, due to the constraints of biological fidelity, it is impossible for this process to be completely error-free. As a result, transcription errors can occur at any time, in any transcript, and how these random errors affect cellular health is completely unknown. To fill this gap in our knowledge, we recently monitored yeast cells that were genetically engineered to display error-prone transcription. We discovered that transcription errors give rise to misfolded proteins that induce proteotoxic stress. Ultimately, this stress can overload the protein quality control machinery and allow proteins associated with Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease or prion disease to escape degradation, which promotes their aggregation and enhances their toxicity. Thus, transcription errors represent a new molecular mechanism by which cells can acquire disease. As a result, it will be important to learn more about the mechanisms that induce or suppress transcription errors, because these mechanisms could either delay or accelerate the progression of proteotoxic diseases. To this end, we recently developed the first next-gen sequencing assay that is capable of measuring the fidelity of transcription in a genome-wide fashion. We now propose to use this technology on yeast and mice to identify the parameters that control the fidelity of transcription in eukaryotic cells. These experiments will exploit the genetic flexibility of yeast to dissect how specific alleles, genes and pathways affect the fidelity of transcription, and make use of the biological complexity of mice to determine how aging, tissue specificity and cell types influence the transcriptional error rate. Together, these experiments will provide the first comprehensive, genome wide analysis of transcriptional fidelity in eukaryotic cells. In addition, we propose to use newly developed mouse models of transcriptional mutagenesis, as well as precise experiments in yeast, to discover how transcription errors affect the aging process as a whole, and Alzheimer’s disease in particular. These experiments could reveal novel, mechanistic links between some of the most important forces in human aging and help explain why normal aging contributes to disease.