Mechanism-based clustering of genome-wide RNA levels: Roles of transcription and transcript-degradation rates
© 2009 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. DNA array techniques invented over a decade ago enable biologists to measure tens of thousands of mRNA levels in cells simultaneously as functions of environmental perturbations. In a few cases the same technique has been employed to measure not only genome-wide transcript levels (TL) but also the associated transcription rates (TR) simultaneously. Since TL is determined by the balance between two opposing processes, i.e., transcription and transcript degradation, simple theoretical considerations indicate that it would be impossible to determine TR based on TL data alone. This conclusion is supported by the finding that TL and TR do not always vary in parallel. In fact, the genome-wide measurements of TL and TR in budding yeast undergoing glucose-galactose shift indicate that TL can decrease even though TR increases and TL can increase despite the fact that TR decreases. These counter-intuitive findings cannot be accounted for unless transcript-degradation rates (TD) are also taken into account. One of the main objectives of this contribution is to derive a mathematical equation relating TL to TR and TD. Based on this equation, it was predicted that there would be 9 different mechanisms by which TL can be altered in cells. The TL and TR data measured in budding yeast demonstrate that all of the 9 predicted mechanisms are found to be activated in budding yeast during glucose-galactose shift, except Mechanisms 5 (i.e., decreasing TL with no change in TR) and 9 (i.e., no change in TL nor in TR). It was also shown that the opposite changes in the mRNA levels of glycolytic and respiratory genes observed between 5 and 360 minutes following the glucose-galactose shift could be quantitatively accounted for in terms of what is referred to as the transcript-degradation/transcription (D/T) ratios calculated here for the first time. Our results suggest that the predicted 9 mechanisms of controlling TL may be employed to cluster the genome-wide measurements of mRNA levels as a means to characterize the functional states of both normal and diseased cells.
Clustering Challenges in Biological Networks
Digital Object Identifier (DOI)
Ji, Sungchul; Chaovalitwongse, W. Art; Fefferman, Nina; Yoo, Wonsuk; and Perez-Ortin, Jose E., "Mechanism-based clustering of genome-wide RNA levels: Roles of transcription and transcript-degradation rates" (2009). Translational Neuroscience. 918.