ӳ����ý

At the 5th annual RNAi (RNA interference) and miRNA (microRNA) World Congress held recently in Boston, David Root, Director of the RNAi Platform at the ӳ����ý, gave the keynote presentation. I recently caught up with David and asked him to help explain the fundamentals behind RNA interference technology and why it is such a valuable tool for learning about what specific genes do.

Q1. What is the value of studying RNA interference?

DR: By 2001, the virtually complete human genome sequence was available thanks to the Human Genome Project, providing a complete catalog of possible genes.

A vast amount of insight can be read or inferred from the genome, this "parts list" of human cells, especially when one can compare to genomes of other species or among individuals with different characteristics, for example people who have suffered heart attacks versus those who haven’t. But a lot of what genes do—when and how they’re turned on and off, what their products do, how they interact, and the specific roles they might play in diseases as well as normal functions—can’t all be directly deduced from this parts list. Cells are just far too complicated to predict all this from gene sequences.

That’s where RNAi comes in. RNAi provides a way to turn down the activity of each individual gene. Then by looking for how cells change behavior when a given gene is turned down, you deduce what that gene was doing, in the same way you figure out what that mystery cord coming out the back of your TV does by yanking it out. For example, if you turn down a particular gene in an immune cell and see that the cell now reacts differently to getting infected with a virus – then you say: "Aha, that particular gene must be involved in the immune response to viruses."

The RNAi Platform at the ӳ����ý was established to help researchers systematically determine the function of genes using RNAi (and some similar strategies). We develop better technology, tools, and methods for functional genomics and then we help collaborators adapt them to their biological problems.

With RNAi, sometimes we cast a wide net across the genome to find any genes that might be involved in an important process. Other times, there is already a smaller focused list of genes that are of special interest, for example genes associated with a disease. Whatever the starting point, we’re trying to connect the relevant genes with some process in cells, and we’re trying to make these experiments as easy and reliable as we can for our collaborators in every area of biology.

Q2. How does RNA interference work for studying genes?

DR: RNAi provides a way to specifically suppress the products of individual genes. In a complicated system like a cell with an enormous number of components interacting in complex ways, it’s not simple to figure out what each individual component does. One of the go-to tricks for figuring for that is to perturb each component, each gene to increase or reduce its activity and see what happens to the cells.

An analogy commonly used for this strategy compares it to trying to figure out which of those pesky unlabeled fuses in your fuse box go to which outlets in your house. You pull out the fuse and see what changes – you see what appliance or electronic does not work any longer. Genes are like the fuses and RNAi is a way to pull them out one by one. You then watch to see how the cells change their behavior – just like watching your houselights go on or off – and infer how the cells are “wired.”

Q3. What is the mechanism by which RNA interferes with gene function?

DR: DNA and RNA are two flavors of nucleic acids--long molecules made up of strings of connected smaller molecules known as “bases.” DNA is the master version of the genes, the instructions for what proteins a cell should make. Copying DNA into a messenger RNA (mRNA) is the first step in carrying out those instructions. RNA interference (RNAi) is an innate process in which cells destroy the mRNA copy of a particular gene, blocking that gene’s effects. Normally, cells use this process to silence harmful mRNAs, such as those from viruses, but once researchers learned that cells could perform RNAi, they sought to re-steer it to block whatever genes the researchers chose, and thus co-opt it as a research tool.

RNAi interference is triggered by short double stranded RNA molecules (siRNAs) that match the sequence of a gene.

Several groups, including The RNAi Consortium labs at the ӳ����ý, have made large library of RNAi reagents predesigned to target every mouse and human gene for silencing. So we’re ready to test any gene – or all of them. Our library is now widely used.

Q4. What were the key discoveries making RNAi a useful tool?

DR: The scientific community first needed to discover that this RNAi process existed and that it could be co-opted to knock down one’s gene of choice in mammalian cells. This was figured out about 10 years ago. Then we needed to know the sequence of every gene in the genome so that you could pick RNA sequences specific to the gene you wanted to knock down. And that was largely complete about 10 years ago for the human genome, so the timing of the RNAi discovery and the feat of sequencing the genome was a beautiful coincidence that really helped functional genomics in mammals take off.

Q5. What unique contributions has the ӳ����ý made to the field of RNAi?

DR: This is an example where the ӳ����ý largely helped bridge the gap from realizing the technology was there to really making it work well and scaling it up. We wanted to make sure we had great resources in place for genome-scale RNAi. Today we routinely use RNAi to interrogate genes linked with cancer, immunology, and infectious disease, and every other area of biology.

Editor’s note: By its very name, the focus of RNAi is on studying what happens when genes are turned off. Root’s team is also working with collaborators at the ӳ����ý and the Dana-Farber Cancer Institute to make and screen libraries that test what happens when genes are super-charged to the "on" position using artificial copies of genes called Open Reading Frames (ORFs). Read about this work