By Branwyn Wagman

Santa Cruz, CA–A new technology for ribonucleic acid (RNA) structure detection developed at the University of California, Santa Cruz, combines test tube RNA biochemistry, high-throughput sequencing, and computational biology to shine new light on the structure and function of these versatile molecules.

The method, called FragSeq, provides a new tool for characterizing RNAs in a complex mixture, such as all the RNAs in particular cell. Prior high-throughput methods could identify and count RNAs, but the FragSeq technique described in the November 7, 2010, issue of Nature Methods takes a step in a new direction by detecting structural information.

The strategy was developed collaboratively in the laboratories of biomolecular engineers David Haussler and Todd Lowe. In the Haussler laboratory, postdoctoral scholar Jason Underwood, a molecular biologist, developed the strategy for structure-specific RNA fragmentation and prepared the samples for high-throughput sequencing with the help of the UCSC Genome Sequencing Center, directed by Nader Pourmand.

The methods and computer program to translate the sequencing data into RNA structure information were developed by Andrew Uzilov, a graduate student in the Lowe laboratory, with help from Haussler lab graduate students Sol Katzman and Courtney Onodera and from David Mathews, an expert in computational RNA structure prediction at University of Rochester.

While RNA, a single-stranded copy of DNA, is commonly known to bridge the gap between the double-stranded DNA that makes up our genetic code and the proteins that carry out thousands of essential cellular functions, it can actually do much more than just encode information. Biologists have been uncovering the full inventory of cellular RNA, called the transcriptome.

Underwood said, “Historically, RNA has continued to surprise the scientific community with its fascinating ability to perform many different functions. In fact, more functions may be yet undiscovered, since some noncoding RNAs can be quite scarce in the cell.”

Some important cellular RNAs fold up into specific structured units–much like enzymes do–to perform a reaction. Like protein enzymes, some folded RNAs can possess catalytic power. Other specialized non-protein-coding RNAs serve as cellular sensors, scaffolds, building blocks, and gears in critical cellular machines that are responsible for splicing or translating the genetic code in proteins.

To arrive at the FragSeq method, researchers in the Haussler laboratory treated RNAs from mouse stem cells with enzymes that are sensitive to the RNA structure and then made RNA sequencing libraries from those various preparations.

They then fed the sequencing information from these enzyme treatments into a computer program that they developed for the purpose. The software can use the data to help predict the correct structure of multiple RNA molecules that are in the mixture at the same time.

The data output from FragSeq is graphical and can be displayed on the UCSC Genome Browser. While the FragSeq method does not replace other RNA detection methods, it adds a new way to use cutting-edge sequencing technology to probe new areas of biology.

Uzilov said, “The molecular biologists and the computational people worked very closely to get these results, and such dynamic projects that successfully bring together experimental and computational sciences are really the future of a lot of fruitful research.”

This work was a cross-disciplinary project between wet lab biochemists, genomics experts, and computational biologists. The project was coordinated and directed by corresponding author Sofie Salama, who directs the Haussler molecular biology laboratory, and by Haussler and Lowe.