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DBI s Pam Green and Blake Meyers on Methods For Analyzing Small Non-Coding RNAs

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At A Glance

Name: Pamela Green

Position: Crawford H Greenewalt professor, plant and soil sciences/ marine studies — Delaware Biotechnology Institute, University of Delaware

Background: PhD, biochemistry/molecular biology, State University of New York at Stony Brook — 1985

BS, biology, Purdue University — 1979


Name: Blake Meyers

Position: Assistant professor, plant and soil sciences — Delaware Biotechnology Institute, University of Delaware

Background: PhD, genetics, University of California, Davis — 1998

MS, genetics, University of California, Davis — 1995

BA, biology, University of Chicago — 1992


At the Delaware Biotechnology Institute, Pamela Green and Blake Meyers are collaborating on a project to use Lynx Therapeutics' (now Solexa's) massively parallel signature sequencing technology to isolate, clone, and sequence small RNAs, such as siRNAs and miRNAs, on a large scale in Arabidopsis and rice.

With an 18-month National Science Foundation grant, awarded last August, Green and Meyers are working to refine the technology, and develop methods for the characterization and analysis of resulting small RNA data.

Recently, they spoke with RNAi News about their research.

Could you give an overview of what's going on in your respective labs?

Green: My lab focuses primarily on RNA biology. We study the control of messenger RNA degradation, the function and regulation of ribonucleases, and the functional genomics of non-coding RNAs. I also have a couple of marine biology graduate students who work on horseshoe crabs.

Meyers: My lab works in two areas, one of which is disease resistance with a particular emphasis on Toll-like receptors and the evolution and role of Toll-like protein domains. The other area of interest, which is more technology based, is the use of MPSS for analyzing gene expression.

Did small non-coding RNAs come into your work independently, or did you come in it together?

Meyers: We really got into it together. Pam came to me one day and said that she was interested in these non-coding RNAs. At first we were thinking along the lines of where she had started, which was at the 100 to 600 nucleotide range, I think — and she thought it would be quite interesting to use MPSS to look at those non-coding RNAs.

We started to work on the methodology and, at the same time, we were thinking about small RNAs — the microRNAs [and] the siRNAs that many other labs were working on. We thought that as long as we were developing an application that could be used for 100 to 600 nucleotide [long] non-coding RNAs, we should also test it and make sure [the application] would work with small, 21-to-24-nucleotide-long RNAs. So, as it developed, [the small RNA work] became a much more interesting direction for us to go in because of the incredible diversity of these molecules.

Green: It shortly became apparent to us that our contribution could be much greater if we focused on the small RNAs rather than the size class we were originally thinking about developing the technology for.

Jumping back for a moment, Blake, was this the first time you had worked with non-coding RNA molecules?

Meyers: Yes. It was the first time I'd worked with small RNAs, although we had identified many potential non-coding RNAs through our work with mRNA-based MPSS.

But Pam, you had been looking into this sort of thing for awhile?

Green: We'd been working on it for some time, and we'd actually cloned some way, way back, not realizing that they were non-codings at the time, and [these] have turned out to be very interesting.

In [my lab's] project on ribonucleases, we recently published in Molecular Cell [by Souret et al. in 2004] describing a ribonuclease from Arabidopsis called AtXRN4. We were interested in what the substrates of that ribonuclease were — it's a 5' to 3' exoribonuclease, so it degrades uncapped RNA molecules from the 5' to the 3' end, and it turns out that that enzyme degrades the 3' fragment after microRNA cleavage of about half the microRNA targets that we looked at.

Can you talk a bit about the NSF project and how it came about?

Green: Well, Blake and I have adjacent laboratories, and our postdocs and students share and office, so it was a natural sort of collaboration that developed from our constant interaction and thinking together. Our expertises are very complementary with Blake being an expert in MPSS, having pioneered the whole technology in plants. He also is a really talented computational biologist. My expertise in RNA analysis fits together with his — he's had a lot of experience doing mRNA profiling with MPSS, so it was a great, natural fit.

As soon as we were able to get the technology to work — and it did take us about a year and a half to adapt the MPSS to these small molecules — we started to get the first data, [and] it was really apparent that this was going to be a major improvement over existing technologies. [It was also clear] that we could contribute a lot more by making additional libraries and demonstrating that the impact could be great not only in plants but also other systems.

Meyers: Early on in the development, we were uncertain what we would find because we thought that maybe when we sequenced these libraries, we would just get a few hundred sequences. I remember being a little apprehensive about the cost and whether it would actually be worth doing the experiments, so we're pretty excited to see how it's panning out. It turns out these are very complex data sets, they're very rich in sequences, very diverse sequences.

In retrospect, it makes perfect sense that they would be that way, but for me it's always interesting to look back to that time, before we got first dataset and [were wondering,] 'What are we doing here? Are these going to be worthwhile experiments?'

Can you give a breakdown of the project and what you hope to accomplish?

Meyers: One aspect was just the development of the technology itself. We had been working with Lynx in order to do that, and … they really helped us in terms of working on the vectors and methodology. But we were doing this without any sort of funding, so the [NSF grant] at the very basic level was the funding that would allow us to get the very first resources and data sets.

Green: [The grant] lets us, essentially, make a few libraries of small RNAs from both the model plant Arabidopsis … and a model cereal, rice. Then [it allowed us] to continue the development of the bioinformatics methods we used for characterization.

Meyers: Part of the reason we chose those two plants is because the genomes were either fully available or nearly complete.

Green: One thing that the MPSS offers us above a lot of the other methods that have traditionally been used to just sequence small RNAs is that it's quantitative, so we compare the abundance of different small RNAs either within a sample or across samples.

Once you've fully gathered together this information, where do you go from there?

Meyers: One of our goals is to make the data available to the public, because there are so many loci where these sequences match that no one lab could possibly sort through all of the data. So what we've done with the mRNA data is construct a custom database that allows users to select their favorite gene or genomic region, or just browse through the genome, to look to see what's there. That's what we're working towards with the small RNA data. Once we've made it available to the community as a whole, then everybody will be able to look at their genes of interest, and many of those genes are going to contain small RNAs. Then researschers will be able to ask very focused questions about the importance of [a] group of small RNAs or [a] particular sequence.

Green: Blake and I also have an interest in how biotic and abiotic stress will influence … specific small RNAs, and how that impacts plants and, ultimately, other organisms. Also, I think that one can address global questions about small RNA biology and chemistry based on the distribution of these molecules across the genome.

The technology certainly isn't limited to plants because it's applicable to any organism that has endogenous small RNAs as a regulatory mechanism.

Is the idea to make these [data] accessible through a website?

Green: That's right.

Is there an address at this point?

Green: Not yet, but the data will ultimately be available through Blake's existing public MPSS site at http://mpss.udel.edu.

Do you have a sense of when these data might start being available?

Meyers: Pretty soon, hopefully. We're working towards publication.

Are either of you collaborating with anybody outside of [DBI] on this research?

Green: We have had an excellent collaboration with Christian Hauldenschild and Shujun Luo at Lynx, [which is] now Solexa, during the development of this method.

Meyers: For the rice experiments, we have an ongoing collaboration with Guo-liang Wang at the Ohio State [University], and he's an expert in rice biology. Pam and I also have a funded rice project from the [US Department of Agriculture] to generate more of these small RNA libraries. Those will be additional libraries that will complement the very first set that we'll get through the NSF grant.

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