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.