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First, the questions

The rhinoceros, zebra, elephant, and peacock all illustrate the phenotypic diversity that can come from similar genomes.
Click here for a high resolution photograph.

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 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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