Rooted firmly in his lab suite tucked deep within the core of the Pentagon-esque Medical Sciences Research Building (MSRB) complex on the University of Michigan campus, John Prensner, M.D., Ph.D., is focused on bringing to light an area of genomic investigation involving a hive of “worker bees” called noncanonical ORFs (open reading frames), that play a vital role in the regulation of RNA translation in the human genome.
Unlike traditional mRNA sequencing (mRNA-seq) methods which produce an approximate determination of how many RNA transcripts are present and what their structure is, Prensner’s work relies on a next-generation, deep-sequencing-based tool known as ribosome profiling (Ribo-Seq) which allows Prensner and his team to identify ORFs, which are the select portions of RNA molecules that give rise to proteins – essentially coaxing the cell into giving up many more of its secrets.
Assistant Professor of Pediatrics, and Assistant Professor of Biological Chemistry at Michigan, Prensner hopes that this information will one day lead to improved RNA therapeutics for cancer and other diseases.
However, one obstacle Prensner sees is that ribosome profiling in its current state is the “wild west” of RNA research, where few laws and regulations guide how researchers process their data. “Without clear metrics for this type of research,” Prensner says, “scientists can potentially publish imprecise analyses due to a lack of best practices, which we actually already see happening in some instances.”
To tackle this challenge head-on, Presner harnessed an international team of RNA researchers, and presented the results front and center in his paper, What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?,” published recently in “Molecular & Cellular Proteomics.” Working with experts in protein biology, RNA biology, and gene annotation, Prensner and the larger team codified a set of working principles that can be used to standardize how Ribo-Seq is used to find noncanonical ORFs.
Prensner and his team hope to create a road map for RNA researchers around the world to follow, that would lead them to perform more precise ribosome profiling, and subsequently catapult this valuable tool to the top of the genomic arsenal.
Read more in the recent Health Lab article, “Improvements in human genome databases offer a promising future for cancer research.”