Dynamic transcriptome analysis (DTA)

So far, much attention has been paid to regulation of transcription. However, it has been realized that controlled mRNA decay is an equally important process. To understand the contributions of mRNA synthesis and mRNA degradation to gene regulation, we developed Dynamic Transcriptome Analysis (DTA). DTA allows to monitor these contributions for both processes and for all mRNAs in the cell without perturbation of the cellular system. DTA works by non-perturbing metabolic RNA labeling that supersedes conventional methods for mRNA turnover analysis. It is accomplished with dynamic kinetic modeling to derive the gene-specific synthesis and decay parameters. DTA reveals that most mRNA synthesis rates result in several transcripts per cell and cell cycle, and most mRNA half-lives range around a median of 11 min. DTA can monitor the cellular response to osmotic stress with higher sensitivity and temporal resolution than standard transcriptomics. In contrast to monotonically increasing total mRNA levels, DTA reveals three phases of the stress response. In the initial shock phase, mRNA synthesis and decay rates decrease globally, resulting in mRNA storage. During the subsequent induction phase, both rates increase for a subset of genes, resulting in production and rapid removal of stress-responsive mRNAs. In the following recovery phase, decay rates are largely restored, whereas synthesis rates remain altered, apparently enabling growth at high salt concentration. Stress-induced changes in mRNA synthesis rates are predicted from gene occupancy with RNA polymerase II. Thus, DTA realistically monitors the dynamics in mRNA metabolism that underlie gene regulatory systems. One of the technical obstacles of standard transcriptomics is the unknown normalization factor between samples, i.e. wild-type and mutant cells. Variations in RNA extraction efficiencies, amplification steps and scanner calibration introduce differences in the global intensity levels. The required normalization limits the precision of DTA. We have extended DTA to comparative DTA (cDTA), to eliminate this obstacle. cDTA provides absolute rates of mRNA synthesis and decay in Saccharomyces cerevisiae (Sc) cells with the use of Schizosaccharomyces pombe (Sp) as an internal standard. It therefore allows for direct comparison of RNA synthesis and decay rates between samples. cDTA reveals that Sc and Sp transcripts that encode orthologous proteins have similar synthesis rates, whereas decay rates are five fold lower in Sp, resulting in similar mRNA concentrations despite the larger Sp cell volume. cDTA of Sc mutants reveals that a eukaryote can buffer mRNA levels. Impairing transcription with a point mutation in RNA polymerase (Pol) II causes decreased mRNA synthesis rates as expected, but also decreased decay rates. Impairing mRNA degradation by deleting deadenylase subunits of the Ccr4–Not complex causes decreased decay rates as expected, but also decreased synthesis rates. In this thesis, we provide a novel tool to estimate RNA synthesis and decay rates: a quantitative dynamic model to describe mRNA metabolism in growing cells to complement the biochemical protocol of DTA/cDTA. It can be applied to reveal rate changes for all kinds of perturbations, e.g. in knock-out or point mutation strains, in responses to stress stimuli or in small molecule interfering assays like treatments with miRNA or siRNA inhibitors. In doing so, we show that DTA is a valuable tool for miRNA target validation. The DTA/cDTA approach is in principle applicable to virtually every organism. The bioinformatic workflow of DTA/cDTA is implemented in the open source R/Bioconductor package DTA