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Embryonic development
What roles do RNA molecules play in embryogenesis, development and fertility?
Living cells has the remarkable ability to change their identity in responses to both external and internal signals.
One of the most striking examples of such "cell state transitions" happens during embryonic development. A single-celled egg transforms into a complex animal, with many different cell types, tissues and organs. Thus, embryonic cells undergo complex cell-state transitions.
The RNA content of cells defines their molecular machinery and thus their properties. Different cells express different genes that give them different properties.
Understanding this process has many important implications in fertility and embryogenesis, including efforts to reprogram cells for regenerative medicine.
Gene Regulation
How do cells control their RNA molecules after their production?
When cells change their identity, they both produce new RNAs and remove pre-existing RNAs that encoded a previous identity.
To do that, molecular circuits inside cells control each RNA molecule throughout its life-cycle: from its 'birth' by transcription, through its processing (e.g., splicing, polyadenylation), localization, translation, and to its ultimate 'death' by degradation.
Together these encompass the dynamic mRNA life-cycle, allowing cells to compute accurate levels of each type of RNA at each time and place.
RNA biology
How do RNA molecules encode regulatory information?
RNA molecules play a dual function both as carriers of genetic information, and as functional components of cellular machinery.
We aim to systematically decipher layers of the RNA regulatory code, and to understand their physiological implications on cellular transitions. We use this understanding in order to develop models that predict RNA regulation within cells.
Such models are highly useful to uncover the impact of genetic variations, and to improve bioengineering of RNA molecules for example in the context of mRNA-based therapeutics.
Our approach
We combine computational and experimental work:
Computational big-data analysis, machine learning and statistical models to dissect large-scale genomic data, and predict system behavior and outcomes.
Experimental high-throughput technologies and analysis tools to systematically measure RNA regulation, with a global-view on regulation.
The zebrafish embryo model is a powerful experimental system to systematically investigate these questions.
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