Epitranscriptomics and RNA Dynamics

A current major challenge in biology is to understand how gene expression is regulated with surgical precision in a tissue-dependent, spatial and temporal dimension. Historically, genome-wide studies of gene expression have typically measured mRNA abundance rather than protein synthesis, in large part because such data are much easier to obtain. However, the correlation between mRNA levels and protein abundance is as low as r=0.35-0.40, suggesting that transcriptional regulation alone is not sufficient to unveil the complex orchestration of gene expression. In the last few decades, the scientific community has started to acknowledge the pivotal role that post-transcriptional regulatory mechanisms play in gene expression, however, we are still far from understanding how gene expression is finely tuned and regulated across tissues and conditions, suggesting that we are missing variables in the equation.

In our lab, we are employing a combination of experimental (RNASeq, polysome profiling, mouse/cell knockouts, Oxford Nanopore direct RNA sequencing) and computational techniques (NGS data analysis, algorithm development, machine learning), to unveil the secrets of three post-transcriptional regulatory layers: the epitranscriptome, RNA structure and ribosome specialization.

• Develop novel methods to obtain single molecule RNA structure maps
• Develop novel methods to detect RNA modifications, including the use of using third generation sequencing (Nanopore Technologies) and Phage Display Technologies
• Decipher the role of RNA modifications in embryogenesis and maternal-to-zygotic transition
• Decipher the role of RNA modifications in intergenerational inheritance
• Understand the role of ribosomal protein paralogs in mammalian protein translation

Beaudoin JD*, Novoa EM*, Vejnar CE, Kellis M, Giraldez A.
“Analyses of mRNA structure dynamics identify the embryonic RNA regulome.”
Nat Struct Mol Biol, 25:677-686, 2018. (*equal contribution)