Keywords: Suicide/Depression Research, Ribosome Profiling, Epigenetics

Ribosome profiling (riboseq) is a next generation sequencing technique that captures and profiles ribosomal footprints (RPFs): the fragments of the mRNA transcriptome that are contained under ribosomes as translation occurs (also known as the translatome). This allows riboseq to identify actively translated mRNA regions: and therefore discrepancies between the translatome and transcriptome (or genome) that are sites of epigenetic regulation. This is of great potential benefit to the study of psychiatric conditions where epigenetic changes are implicated in their phenotype, such as suicide completion, particularly when coupled with early life adversity (ELA). Transcriptomic research has found several genes to be differently methylated in ELA/suicides compared to healthy controls and non-ELA/suicides, particularly in brain areas such as the anterior cingulate cortex (ACC). However, translatomic research verifying altered proteins synthesis levels at these differently methylated sites has thus far been unexplored, and could be used further elucidate the epigenetic mechanisms underlying how ELA contributes to suicide. Furthermore, riboseq of non-tumor human brain tissue appears to be unreported in literature due to difficulty with preserving the process in vivo.

I intend to create a novel riboseq procedure for RFP capture in human brain tissue, where sequencing will be completed on samples from the (ACC) with ELA/suicide, non-ELA/suicide, and healthy control cohorts. This riboseq procedure includes trials optimizing nuclease cocktails for RPF capture, amplification cycles, and RPF fragment purification. Procedure optimization is still ongoing: but early fragment size analysis suggests that certain nuclease cocktails are successful at capturing the characteristic ~30 bp RPF fragments compared to total RNA controls. This result is promising and supports the feasibility of RPF capture from human brain homogenate, to be further verified via coding enrichment analysis. I hypothesize that transcriptomic and translatomic differences will be found between ELA/suicide brains compared to both non-ELA/suicides and healthy controls.