Genes that scientist believe are turned off are actually functioning at a low level that has previously been undetected, a discovery that could help answer questions about chronic disease and aging. The new research from Colorado State University will be released this week.
Of the about 25,000 human genes science has identified, half are believed to be silent at any particular time and activated only when needed. But Andre Ptitsyn, biomedical and computer expert in the Center for Bioinfomatics at Colorado State University, has discovered that current tools cannot measure extraordinarily low levels of gene expression signals.
"Genes that we have believed to be silent are actually whispering," said Ptitsyn, who a applied a common physics principle to find oscillating patterns of gene expression in genes previously thought to be shut off.
In most studies, genes that are believed to be silent are excluded from analysis in early stages of research. However, with Ptitsyn’s research, genes expressed below the current measurements show the pattern of expression coordinated with other genes.
Ptitsyn used the physics principle of stochastic resonance in a computer algorithm. Stochastic resonance seems to be counterintuitive, but it is used to detect weak signals by searching for consistent patterns in stronger (but unrelated) signals. For example, the sound of a marching band in the distance may be undetectable to somebody standing in a room. But if the room has a fan running, it creates a constant and measurable noise. Measured over a period of time, the rhythm of the distant band as it plays – and the absence of the rhythm when the band stops – may be noticed. While the band is playing, the noise in the room is cumulatively louder with the bang of the drum, even though the notes of the band may not be detected and a single bang of a drum is lost in the noise. Over time, the contribution of the band to the overall noise could be detected.
Ptitsyn applied the same principle in gene measurement. When looking at genes, their expressions form a pattern over time of peaks and valleys according to certain rhythms, such as daily circadian rhythm. The silent genes have a rhythm that is detectable as it follows the rhythm of expression of active genes.
Microarrays measure gene expression, but steps are taken to filter out data that seems to be background noise or extra, unexplained low levels of data that scientist previously thought didn’t indicate gene expression. Ptitsyn looked at the background data and found that the unexplained data was the expression of "off" genes, or what he has called whispering genes. He isolated the genes that were believed to be off and studied the patterns of the background "junk signals" overlapping with the genes that are active and expressing at a known level.
The rhythms dominating expression of active genes, called circadian or daily rhythm, are still clearly detectable among the silent genes. When measured, the timing for increasing and decreasing junk signals coordinates with other interacting genes, both active and silent, that perform the same function.
Ptitsyn hopes the discovery will help science build better microarrays, which are currently used to measure gene activity genes, and will help find expressions previously hidden.
Ptitsyn is an assistant professor in the College of Veterinary Medicine and Biomedical Sciences in the Department of Microbiology, Immunology and Pathology.
"These findings provide scientists with a technological advancement to detect and measure gene activity previously ignored," Ptitsyn said. "The ability to study and measure these genes changes our entire perspective on biology. The fact that as many as half of the genes in the human body that have been previously ignored do, indeed, have a role in our bodies changes everything. They are not off, they are on a dimmer switch turned down low. Their role in aging and disease is yet to be discovered, but we could expect that they have an effect."
The article was published this week at http://www.plosone.org/ in PLoS ONE, a scientific journal.