Download New Computational Tools Help Solve Puzzle of RNA Structure

Health and Wellbeing
New Computational Tools Help
Solve Puzzle of RNA Structure
RNA, once considered a backbencher in the biological process, is
now causing quite a buzz in scientific circles. With support from
Microsoft External Research, scientists at the University of Texas are
developing new computational tools that could help researchers
decipher a fast-growing volume of RNA data, which in turn could
lead to breakthroughs in medicine and expand our general understanding of biological processes.
A
quarter-century ago, when Robin Gutell was finishing up his Ph.D. work in molecular biology, scientists searching for the secret of life were pretty much convinced
that ribonucleic acid (RNA) was just a bit player in the workings of the cell.
“At the time, it was felt that DNA and proteins were the really important macro­
molecules and RNA was just this labile, passive molecule,” says Gutell, now a professor of
biology at the University of Texas at Austin.
For decades, conventional wisdom held that three different RNAs (transfer, ribosomal
and messenger) were involved in the production of proteins such as enzymes and hormones—considered biology’s real movers and shakers. Now, however, molecular biology
is in the midst of a paradigm shift that is dramatically changing scientists’ understanding
of how cells function. And RNA is at the center of that revolution.
“They are finding on a massive, massive level that huge amounts of RNA are made
in cells—much more than we ever anticipated,” Gutell says. “And now there is a raging
debate. Some people say that all this RNA is just junk, that it is made and then is immediately broken down.” Others, including Gutell, believe that the majority of this RNA is
used in the cell’s metabolism and regulation.
A portion of a diagram developed by the Gutell Lab, illustrating secondary
and tertiary structure of an RNA molecule.
Fast Facts
Project Principals:
Robin Gutell, Ph.D., professor of biology,
University of Texas at Austin
David Gardner, doctoral student in
computational biology, University of
Texas at Austin
Web Sites:
http://www.microsoft.com/mscorp/tc/
determining-fundamental-principles.mspx
http://www.rna.ccbb.utexas.edu/
http://www.biosci.utexas.edu/IB/faculty/
gutell.htm
Profile:
New research is showing that RNA likely
plays a far more significant role in the
function of cells than was previously believed, but scientists face a challenge in
managing the vast amounts of biological
data associated with this emerging field
of study. Researchers at the University of
Texas are collaborating with Microsoft
Research to develop data management
and analysis tools that will help scientists
better understand RNA and its function.
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As he has throughout his career, Gutell is using computers to help resolve the RNA debate. His lab is collaborating
with Microsoft External Research to develop new computational tools and methods that could help scientists better
understand the structure—and ultimately the function—of
various RNA molecules.
As a student, Gutell worked under both Harry Noller
and Carl Woese, prominent researchers who were among
the first to propose that RNA likely plays a pivotal role in
cell function. Now an abundance of recent research supports that view, and some researchers are looking to RNA to
develop new drugs for combating diseases such as cancer, to
solve biological mysteries such as sex determination and to
better understand the evolutionary process.
“It seems like every week researchers find another
new RNA that is associated with a function inside the cell,”
Gutell says.
“My mentors taught me 30 years
ago, long before it was fashionable,
that RNA has unique properties that
were not appreciated at the time.”
Robin Gutell, Ph.D., professor of biology,
University of Texas at Austin
Gutell has spent his entire career studying RNA. (He even
has personalized license plates that read “rRNA,” the abbreviation for ribosomal RNA.) Gutell says he was drawn to RNA
research for several reasons.
“My mentors taught me 30 years ago, long before it
was fashionable, that RNA has unique properties that were
not appreciated at the time,” Gutell says. He says he is also
driven by an awareness that “great discoveries result from
fresh and novel changes in our modeling of complex systems such as molecular biology.”
Aside from helping to explain how cells function, a better understanding of RNA might also help scientists better
explain the complexity of different organisms. Since the
completion of the Human Genome Project, scientists have
puzzled over the fact that humans have roughly the same
number of protein- and RNA-coding genes as less complex
organisms such as worms or fruit flies. New research, however, is showing that the complexity of an organism scales
with the number of RNA.
The surge of interest in RNA, combined with rapid
advances in research methods, is generating huge amounts
of new data. Each year, hundreds of thousands of new
RNA sequences are added to GenBank, a central genetic
sequence repository maintained by the National Center for
Biotechnology Information. This wave of new information
will enable scientists to vastly increase their understanding of
the structure, function and evolution of cellular components,
Gutell says. But he says it also has created a research “bottleneck” that poses significant computational challenges.
Those challenges are what drew David Gardner, a doctoral student in Gutell’s lab, into RNA research. Gardner, who
has a master’s degree in computational and applied mathematics, is developing an algorithm that, if successful, will
make it possible to take a single RNA sequence and predict
how it folds into its secondary structure.
“With any protein or RNA, in order for people to really
understand how it works, they have to know its structure
and where the interactions are happening,” says Gardner,
who plans to have his initial RNA folding program completed in 2009.
Gutell says Gardner’s preliminary results have been
promising. The goal is to eventually develop a software
modeling program that can predict tertiary—three-dimensional—RNA structure.
Gardner’s project is extremely data intensive. “We have
so much data, so many sequences and so many statistics of
structural motifs that the biggest challenge is figuring out
which is relevant and most useful,” Gardner says.
To help sort through the data, Gardner’s project is relying heavily on an ongoing collaboration between the Gutell
Lab and Microsoft. With financial, technical and software
support from Microsoft, the Gutell Lab has developed a
novel database system called the RNA Comparative Analysis
Database (rCAD). (Comparative analysis is a technique that
has been used to successfully determine the structure of
RNA molecules.)
Gutell says the database will eventually store as many
as 1.5 million RNA sequences. The database was built on
Microsoft® SQL Server®, with assistance from Stuart Ozer, a
data management expert at Microsoft.
rCAD is capable of organizing enormous amounts of
biological information for efficient retrieval and multidimensional analysis. By uniting multiple dimensions of
information—including sequence, structure and evolutionary data—rCAD enables new, innovative analyses of the
fundamentals of RNA, according to Gutell.
The lab is also developing a software package that Gutell
believes will be the most sophisticated comparative RNA
sequence and structure visualization and analysis tool available. As was the case with rCAD, Microsoft will be providing
direct technical assistance.
“Given this revolution in molecular biology, we hope
many labs will benefit from these new and novel computational tools as a growing number of scientists pursue the
larger significance of RNA in the mechanics of molecular and
cellular biology,” Gutell says.
Software developed under this project is available for free
download from CodePlex at http://www.codeplex.com/rcat.
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