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First,
the Questions
Tough
scientific questions drive systems biology research at
ORNL. |
Scientists
believe they are on the brink of solving some mysteries underlying
the miracle of life. The confluence of increasingly sophisticated analytical
techniques, more powerful computing capabilities, and multidisciplinary
partnerships linking some of the world's best researchers have set
the stage for a revolution in biology. This revolution, spawned by
systems biology research on the heels of the Human Genome Project,
could produce answers to some very profound questions. In addition,
it could suggest new questions to ask, based on the flood of data resulting
from experimental analysis and computer modeling.
What
Makes Species Different
The quest
begins with some fundamental questions, such as: Biologically, what
makes humans different from mice or flies? Researchers need to use
systems biology to resolve these classical questions in biology: How
is an organism's complexity created from a single-celled embryo? Why
is one human individual more likely than another to develop a certain
disease?

The rhinoceros, zebra, elephant, and peacock all
illustrate the phenotypic diversity that can come from similar
genomes.
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The recent
sequencing of human, mouse, and other genomes has not yet provided
full answers to these questions. What we have learned, however, is
that humans and other large mammals share many genes and proteins found
in multicellular animals such as worms and mice. So, what makes species
different?
"A half a billion
years ago, around the Cambrian era, the evidence suggests a huge explosion
in the number of different body plans for multicellular animals," says
Jay Snoddy, a bioinformatics researcher at the University of Tennessee-ORNL
Graduate School of Genome Science and Technology. "The protein-coding part of the genome for genes involved in laying down the
body plan of different animals, like humans and insects, did not seem to diverge
that much."
Subtle changes,
however, do occur in the genome, including the part that helps determine
when the RNA and protein for a gene are made. These subtle changes
may affect whether a gene in a cell will be silent or active. These
changes outside of the protein-coding part of a gene can determine
when and where that gene makes a protein in a subset of cells during
the development of an organism from an egg. In some sense, the evolution
of body plans is often the evolution of changes in development, and
changes in development are often initiated by subtle changes in the
networks that regulate the expression of genes in cells.
"According
to some researchers, what makes humans different from mice does not
lie in the protein coding part of the genome," Snoddy says. "The difference
often lies in the genome parts targeted by regulatory transcription
factors that decide when and where a protein should be made."
Snoddy compares
genes and proteins to conserved computer hardware and chips, designed
millions of years ago. "What has evolved over the centuries has been
subtle changes in networked wiring and software—subtle changes
in the regulation of genes and in the timing and location of the regulation," he
says. "Small changes in gene regulatory networks, cell-to-cell communication,
and protein interaction networks are among the forces that have contributed
to the huge amount of complexity, diversity, and variability of species
on the earth. Understanding these relationships should be a long-term
goal for systems biology."
Snoddy and
his UT colleagues Bing Zhang, Stefan Kirov, Rob Williams, and Michael
Langston are using computer analysis of gene expression data sets to
study regulatory networks in the brain. These networks "read out" the
genome information and integrate it with other information signals
that a cell receives from the extracellular environment during physiology
and development. These regulatory networks are key to understanding
many fundamental parts of biology. This knowledge is also useful in
practical matters, such as biomedical applications; parts of these
regulatory networks seem to be affected both by disease and drugs used
to treat it.
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