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OSU s Venkat Gopalan on Comparing RNase P and RNAi Knockdown in Plants


At A Glance

Name: Venkat Gopalan

Position: Associate professor, Ohio State University

Background: Assistant professor, Ohio State University — 1998-2003; Postdoc, Yale University — 1992-1997; PhD, biochemistry, University of New Mexico, Albuquerque — 1991; BSc, chemistry, University of Madras — 1986

At Ohio State University, Venkat Gopalan is researching ribonuclease P, an essential ribonucleoprotein involved in 5’ maturation of transfer RNAs. His work extends into the use of RNase P in targeted degradation of endogenous RNAs, through a method that involves the expression of a small RNA called an external guide sequence. When bound to the target RNA, the EGS recruits RNase P to cleave the target RNA and thereby disrupt its expression.

He recently was awarded a National Science Foundation grant — running from Feb. 1, 2005, to Jan. 31, 2007 — to compare RNAi and RNase P as tools for targeted RNA degradation in plants. Recently, he spoke with RNAi News about his work.

Could you give an overview of the work done in your lab?

My lab is interested in studying ribonuclease P, which is abbreviated RNase P. It’s an enzyme that’s involved in 5’ maturation of tRNAs in all living cells. There are three ongoing projects in the lab — two of them are basically targeted towards understanding RNA/protein interactions, and the role of proteins in RNA catalysis. These deal with the bacterial and archaeal forms [of RNase P].

With regard to plant RNase P, what we are really interested in is asking whether we can exploit plant RNase P as a functional genomics tool, meaning can we somehow entice a pre-existing cellular enzyme — plant RNase P — to cleave one mRNA or one target RNA at a time.

Just like RNAi, RNase P is cellular. It’s a multiple-turnover enzyme, and it processes precursor tRNAs in all cells including plant cells. The observation that a non-covalent complex of two RNA molecules which structurally resembles a typical precursor tRNA is a good substrate for RNase P led to the idea that any RNA could be targeted for degradation by RNase P if the binding of the target RNA to an external guide sequence, or EGS, forms a sequence- and structure-specific complex resembling a ptRNA. Basically, we are asking if we can use this strategy to knock down gene expression selectively. So far we’ve obtained some encouraging data; we published one paper last year in the Biochemical Journal showing that the strategy works in maize cells. Unpublished data indicate that the strategy is working in Arabidopsis. We have not compared the efficiency of this method with RNAi, and that really is the basis of a new [National Science Foundation grant we have] been given.

Just to clarify, preliminary data indicates that [RNase P] to selectively …

Well, to be more accurate, the strategy was pioneered by [Yale’s] Sidney Altman, who discovered RNase P — he won the Nobel Prize for finding that RNase P owes its catalytic prowess to a RNA moiety. His lab throughout the 90s developed this strategy of [using] RNase P for selective, targeted degradation of one RNA in the cell. They’ve shown how it works in bacterial cells and human cells and mouse cells. What we’re doing is in plant cells, [and] I’d also like to say that we’re the first ones to do this kind of work in a transgenic setting.

Our preliminary [data] indicate that it works in transgenic plants, and we’re now trying to validate those results by doing more control experiments. We also want to extend those studies by comparing it with RNAi, which is a very popular and efficient tool. So, one needs to ask if a new tool is necessary, what are the advantages, and so on.

Could you give an overview of how you plan to approach this comparison study?

Basically, we want to look at some reporter genes in terms of the efficacy of knockout by RNAi and using RNase P. We also want to examine related gene family members and ask whether we can get specific knockout with RNase P [and] RNAi.

Because of transitive RNAi, one runs into the problem of a global shutoff of all related members of a gene family. So we will choose a couple of related genes and ask if we can shut off one but not the other with the two strategies. Going into the experiment, our working hypothesis is that RNAi may not be able to selectively target one member if two members are highly related at the sequence level [because of] transitive RNAi. [Additionally,] you are producing large amounts of siRNAs throughout the gene [and that] might result in the shutoff of two related family members.

But you don’t expect this to occur with RNase P?

No, we don’t think so.

Do you have a timeline on when you expect to start the work?

We’ll be starting in a month, and we hope to get it done in the next 12 to 24 months.

This will be your first formal work with RNA interference?

That is correct.

Are you collaborating with anybody on that?

No. We’ll be making transgenic plants that express double-stranded RNA inside the cell. All the work will be in transgenic plans, so we won’t be doing tissue-culture work. We want to ask, in the transgenic setting, how does it work.

Based off what you know now, do you have any predictions on how you expect the comparison to turn out?

In terms of the effectiveness of RNAi, I think there is no doubt that RNAi is a very attractive strategy. I think that it will fare as well or better than the RNase P-based method.

What I’m not very sure about is how the methods will compare if we use a low-abundance versus a high-abundance transcript. It’s clear that low-abundance transcripts are less susceptible to RNAi compared to medium- and high-abundance transcripts. In terms of RNase P cleavage, we think that low-abundance transcript may be more susceptible to RNase P. So it could be that RNAi and [external guide sequence]/RNase P-based methods are complementary to one another in the sense that [when] the RNAi-based method doesn’t work with the low-copy transcripts, maybe RNase P/EGS could be used.

[In terms of] effectiveness, my guess is that [RNAi and RNase P] will be comparable, and RNAi might even be better. But in terms of the literature, my guess is that RNAi will be less effective with low-abundance transcripts, and this may be an area where RNase P might be more successful.

Finally, I think that tissue-specific control of gene expression is made difficult by the transport of siRNAs in the phloem. We think that such transport mechanisms will not be applicable to the external guide sequences and therefore the RNase P-based method might have an advantage.

The literature is not very clear on this, but if you express a dsRNA in the root, there are reports that the RNAi signal moves to the shoot. Even though you use a root-specific promoter to make the dsRNA, because the siRNA moves along the phloem, you get shutoff in the shoot as well.

How then do you get tissue-specific shutoff? It’s been [proposed] that the external guide sequences, which are needed for the RNase P-based knockout, will not be subjected to the same transport mechanisms as RNAi. That’s the early premise that we want to test in the plants as well.

So there are three things we want to test. One is effectiveness — meaning if you introduce a dsRNA or an external guide sequence against a reporter construct, how many plants show [gene] shutoff and what is the extent of shutoff?

[The] next [question is:] If you took two related family members and tried to knock them out with specific dsRNAs or specific external guide sequences, what do you see? Do you see specificity with one method and not the other? This is a serious concern that many people have raised with any gene-knockout tool, not just RNAi. Any gene-knockout tool is robust only if you can have a very specific shutoff and there’s no off-target specificity.

The last aim we want to examine is if one method has better tissue-specific control than the other. This may simply be the way nature has designed things. Nature has designed siRNAs to be transportable in the phloem, perhaps with the idea of shutting off gene expression of an invading species. Unfortunately, that makes it less useful as a tool when you want tissue-specific knockout. It’s conceivable that RNase P, with the external guide sequences, might circumvent the problem, if the external guide sequences are not subject to the same siRNA-based transport mechanisms.

If things pretty much turn out the way you expect with a sort-of complementary relationship between RNase P and RNAi, what would be the next step for you? Would you continue to refine the use of RNase P?

Absolutely, and we’ll of course make the methodology, the tools, the vectors, everything available to whomever wants to try it.

I think the first thing is to find out which methodologies are applicable for what kinds of transcripts. While it’s easy for one to say, “Let’s go and try to knock out every gene in the genome,” they’re all not the same — for instance one might be transcribed into a low-abundance transcript, another into a high-abundance transcript, and perhaps you need two different methodologies to knock down these genes.

The more we know about which tools are better for what situation, I see hope for different kinds of gene-knockdown tools to play a valuable role in forming the comprehensive picture that we all seek. So my guess is that the comparative study will shed some light, and from there on we’ll see which one should be adopted for which part of a high-throughput approach.

I’m not saying that one method is better or worse than another. In fact, my goal is to ask what are the pros and cons of different gene-knockout methods to see if a certain method may be applicable in a certain setting. I think that, sometimes, as history has taught us, one can get carried away with one kind of approach and not spend too much time examining alternatives.

Then you wish you had examined alternatives because alternatives always have value in different situations. RNAi … may prove to be one of the most effective tools we have for gene knockout, but efficiency is different from the other issues such as sequence specificity. In fact, efficiency may be a double-edged sword — if you’re too good, because of that you may have a price to pay.

Depending on the results [of your study], you’ll probably get some industry interest as well.

Already some people have expressed some interest, and we’re looking at that now.

Anybody you can name?

I don’t want to right now.


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