New Insights Emerge from Studies of RNA Regulation

In a faculty candidate seminar at Dartmouth Medical School, Chaolin Zhang, a member of the Molecular Neuro-Oncology laboratory at The Rockefeller, discussed his recent findings on the overall RNA regulation in the mammalian brain. His work has played a major role in the development of new biostatistical approaches to determine different regulatory networks of RNA.

One of the key aspects of Zhang’s studies has centered on RNA splicing, which is a modification of RNA after transcription, cutting out introns and joining exons together. The regulation of this splicing is very important to understand RNA regulation in the brain, Zhang mentioned.

As of now, it is not completely clear of how exons recognize splice sites. This can be heavily due to the vast differences between the “DNA world” and the “RNA world” in biology. RNA only possesses 400 regulators, while over 2000 DNA binding transcription factors exist. In addition, the transcription factor binding sites of RNA are extremely short and degenerate, making RNA binding proteins relatively specific and highly conserved in vertebrates.

Zhang indicated a new approach to these current investigative shortcomings: bioinformatics. Using the FOX target network as a model system, he stressed the importance of high-throughput computational techniques to predict conserved FOX binding sites. The data was represented using the Branch Length Score statistical method to show the number of species with conserved binding sites. Though it was initially used to predict transcription factor binding sites, this technique now has translated into an efficient mechanism for predicting the binding sites of other proteins involved in neuronal activity.

Zhang’s work extends greatly into systems biology. His developments include a nucleotide resolution map of protein-RNA interactions to demonstrate cross-linking induced mutation site analysis. In addition, he combined Bayesian networks, a probabilistic graphical model that represents random variables, to predict splicing target networks by the integration of motif sites, evolutionary signatures, and microarray RNA sequencing.

Overall, Zhang stressed the importance of using more statistical power to discover complex yet subtle rules in biology. In that way only will molecular biology and systems biology effectively unite to produce revolutionary discoveries not only in the studies of RNA, but also in biological research in general.