Probabilistic modelling of transcription dynamics in whole embryos and singel cells | Magnus Rattray скачать в хорошем качестве

Probabilistic modelling of transcription dynamics in whole embryos and singel cells | Magnus Rattray

We are using probabilistic time-series models to gain insights into transcription dynamics in the early drosophila embryo. We consider the very earliest stage of development, where maternal transcripts are progressively replaced by zygotic gene expression. We are using a combination of whole embryo RNA-Seq and live cell imagining time-series datasets to gain insights into the mechanisms regulating RNA levels in the cell. Firstly, using a total RNA-Seq time course that captures intronic and exonic reads, we model the production and degradation of RNA by combining a differential equation model of degradation with a Gaussian process model of transcription (1). We infer half-lives for a large set of zygotic genes and show how degradation rate regulates the difference in timing of peak levels of nascent and mature transcripts. Short half-life mRNAs are more likely to be associated with P-bodies and we find evidence of 5' to 3' degradation occurring in P-bodies for a subset of mRNAs. Secondly, we use live cell imaging to model transcriptional bursting in single cells. A previously proposed compound-state hidden Markov model (cpHMM) provides an effective approach to inferring transcription dynamics from ms2 live imaging data. However, the original formulation has time complexity scaling exponentially with gene length and is not practical in our case. We have therefore developed more scalable inference approaches, including mean-field variational Bayes approaches and a truncated state-space approximation (2). By comparing burst kinetics in cells receiving different levels of BMP signaling, we show that BMP signaling controls burst frequency by regulating the promoter activation rate. The rate of promoter activation depends on both the enhancer and promoter sequences and we show that the main determinant of the RNA polymerase II initiation rate is the enhancer. https://www.dkfz.de/en/datascience/se...