Gene expression on an oscilloscope
Geneticists have created an algorithm to identify oscillating genes
A group of geneticists and specialists in biological statistics and computer science from the University of Wisconsin-Madison has developed a statistical approach to identify populations of oscillating genes and build a picture of their long-term dynamics. The scientists implemented their approach in the form of the "Oscope" algorithm in the R programming language (available for free download here). According to the researchers, this will make it possible to "map" most of the existing oscillating genes as accurately as possible at the moment, as well as to find out their role in the early stages of the development of organisms. The work was published in the journal Nature Methods (Leng et al., Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiment).
Scientists have applied a completely original approach based on sequencing the RNA of individual cells – in this method, the primary structure of the RNA molecule from previously isolated single cells is determined. By itself, RNA sequencing has long been used to identify specific groups of oscillating genes, but it did not allow us to see all interacting and probably interconnected systems of oscillating genes at once, and taken in long-term dynamics. Geneticists have called their approach in some way analogous to a "timelapse" for genes.
To overcome the limitations and build a more complete and complex picture, the researchers took a sample from a large number of individual identical cells, but in different states. In other words, instead of a time series of consecutive observations of one cell, scientists simultaneously observed many cells reflecting the entire space of possible states.
The developed algorithm made it possible to identify individual genes, as if they were in the opposite phase – the maximum activity of one gene accounted for (or was close to) the minimum activity of another. Then, by means of cluster analysis, genes with close activity cycles were grouped together. Next, the algorithm calculated a generalized expression cycle for the selected groups. And finally, at the final stage of the analysis, the exact order of activity of each gene within each of the groups was determined.
The general scheme of the method and the algorithm for detecting oscillating genes.
Image: Ning Leng et al. / Nature Method
Oscillating genes got their name due to the fact that they have a fairly accurate and rigid time pattern of their expression. For the first time such a gene was discovered in the visual cells of a fruit fly back in 1971 and was named per (from period), since its expression was directly determined by the time of day and had a strict cyclicity. In most cases, oscillating genes are involved in the regulation of cell division, circadian rhythms, and embryo development (especially in the formation of limbs). However, even now quite little is known about them.
Portal "Eternal youth" http://vechnayamolodost.ru
28.08.2015