RNA interference: small molecules that carry a big stick

Innovation Matters


It all began in the late 1980’s with Rich Jorgensen’s effort to engineer deep purple petunias by introducing extra copies of chalcone synthase, a key enzyme in anthocyanin biosynthesis, in the form of double stranded RNA: this resulted in engineered petunias that turned out white or patterned. In the late ‘90s, scientists realized that what was responsible for the results of the petunia experiments was a mechanism now known as post-transcriptional gene silencing or “RNA interference” (RNAi for short). The mechanism resulted in the decrease of expression for both the introduced and the endogenous copy of the chalcone synthase gene thus leading to white or patterned petunias.

Since Jorgensen’s serendipitous discovery, scientists have learned a lot about RNAi. Initially, it was thought to be a defense mechanism that organisms devised to protect themselves from the activity of viruses and transposable elements that have invaded their genomes. But nowadays, RNAi is believed to be an indispensable component for running the biological processes that we have come to know from our decades-long studies of cells: important processes like limb formation, heart development, stem cell division etc., which were thought to be managed entirely by the action of proteins, have already been shown to be controlled by microRNAs. And in an entirely analogous manner, some first examples are now available which show that proteins can and do control the action of microRNAs. Among other ramifications, the existence of this feedback loop argues strongly for a need to revisit our protein-centric views of cellular processes which would be incomplete without the inclusion of microRNAs. In turn, this raises two important questions: how many and which microRNAs does one need to take into account when working with a specific organism? and, how many genes does each one of these microRNAs control?

Widely-held beliefs among the practitioners currently state that the number of endogenously encoded microRNAs in an organism like humans and mice is around 400-500; for a model organism like the fruit-fly and the worm the estimate is that they encode ~100 microRNAs. With respect to the number of targeted genes, the current estimate is that roughly 30% of human genes are under the control of microRNAs, with each microRNA targeting and thus regulating a few tens of genes.

Through the work we are doing in the Bioinformatics and Pattern Discovery group, we try to revisit and address precisely these two questions. In particular, we have developed a pattern-discovery based method that can analyze whole genomic sequences and identify endogenously-encoded microRNA precursors and the corresponding mature microRNA sequences that define the targeting sequence. Also, for a given microRNA and set of transcribed sequences, it can determine the microRNA’s binding sites and thus the genes which are regulated by it through the RNAi process.

Our computational analysis to date suggests several hypotheses that paint a picture of cell regulation that is substantially different than what is currently believed: first, we find that there may be as many as 50,000 endogenously encoded microRNAs (and their respective precursors) in the human genome and not only 400-500; second that as many as 90% of the known protein-coding human genes are likely targets of one or more microRNAs; and, third, that each microRNA likely targets tens of genes while some of them target hundreds and possibly thousands of genes. The large number of genes that our computational analysis suggests as being regulated by microRNAs, if proven true, will radically change the current views on cell process regulation. With the help of collaborators in academic and research centers, we are in the process of attempting to experimentally validate novel microRNAs that we have predicted in the fruit-fly genome, and also targets for select microRNAs that are known to be active in mouse tissues.

RNAi process
Figure 1. The RNAi process in a nutshell

It is very important to understand how RNAi works for a number of reasons. First, we will gain additional insight into the various cellular processes of interest, their function and regulation. Second, we will be able to identify novel endogenous causal agents of disease and better understand the transition from healthy to disease states. In fact, studies have shown for several microRNAs that they are involved in processes leading to the onset of cancer or that the microRNAs act as oncogenes themselves. Third, we expect to eventually be able to harness that regulatory power in a therapeutic setting. Studies in one small model organism (fruitfly) have shown that microRNAs regulate stem cell division. In another organism (worm) microRNAs were shown to regulate lifespan. What scientists aim at is to harness the power that these tiny sequences hold in a very specific and focused manner in regenerative medicine and for therapeutic efforts: experiments have demonstrated that specially designed microRNA-like sequences that were 22 nucleotides in length successfully prevented, in vivo, the replication of hepatitis C virus; promising results have also been obtained in the context of cancer, autoimmune diseases, neurodegenerative diseases, etc.

To learn more about RNAi:

Innovator's corner  

Isidore RigoutsosIsidore Rigoutsos Researcher

What is the most exciting potential future use for the work you're doing?
I think that there is great potential in furthering our knowledge of the workings of cellular processes and by extension learning how to develop novel therapeutic protocols that harness the cell’s existing machinery in an intelligent way. This is not going to be an easy process by any means: indeed, RNAi has been presenting us with one surprise after another. But the promise is undoubtedly there and numerous scientists around the world are already investing a lot of their time and effort toward that goal.

What is the most interesting part of your research?
The element of the unknown. Also the ability through our collaborations to actually validate, or at times refute, our computational predictions. That is where the rubber meets the asphalt and it is very exciting.

What inspired you to go into this field?
It was a chance visit with colleagues at the University of Pennsylvania more than 3 years ago. They told me about the problem that they were working on (RNAi) which I found fascinating because of the conceptual simplicity and the power of the underlying mechanism. I worked alone for about a year before I was joined by Kevin and Tien; since then, we have been working on a method for computationally analyzing this problem effectively non-stop.

What is your favorite invention of all time?
Wired and wireless communications.

Research team  

Tien Huynh

Tien Huynh

Kevin Miranda

Kevin Miranda