In vivo identification of interactions between active microRNAs and target mRNAs
The micro-RNA pathway is required for all developmental processes that have been investigated so far, including neurogenesis. However, our knowledge about the expression and role of specific neuronal microRNAs in brain development and function is still fragmentary. In particular, the in vivo identification of target mRNAs of expressed microRNAs remains a challenging task.
A new method, called ago-APP, has been recently developed in collaboration between the Cremer group at the IBDM and the group of Gunter Meister in Regensburg, Germany. Ago-APP is based on the transgenic expression of a small peptide (called T6B), capable to trap with high specificity regulatory microRNAs in vivo.
- Use Ago-APP to identify and isolate active microRNAs during neurogenesis in the mouse forebrain.
- Use a targeted form of T6B to apply Ago-APP to identify the synaptic miRnome in neurons in vivo.
- Match the Ago-APP derived miRNA datasets with mRNA expression patterns, generated in parallel, to identify and characterize potential regulatory interactions between microRNAs and mRNAs during neurogenesis and at the synapse.
- Validate potential interactions by functional experiments.
T6B is a peptide derived from a component of the RISC complex, TNRC6B. Ectopic expression of T6B competes with endogenous proteins and is able to trap specifically active microRNAs (Hauptmann et al. doi:10.1073/pnas.1506116112). We will first in vivo electroporate a tagged T6B in the ventricular neural stem cells of neonate mice. At successive time points after electroporation, active microRNAs will be immune-precipitated and sequenced. In parallel, total microRNA and mRNA sequencing will be performed on FACS sorted intact cells at the same stages. In parallel, we will use a new transgenic mouse line where T6B is conditionally expressed and eventually targeted to the post-synapse.
The above experimental approach will generate a large amount of datasets representing mircoRNAs and mRNAs in different neuron population, at different differentiation stages and in different subcellular compartments (cytosol/synapse). The computational tools to be used will include a set of prediction algorithms (such as TargetScan, miRDeep2, Mirnovo or miRTarBase) and applications for integrative analysis of trancriptome and miRnome data (such as the and the miARma-Seq pipeline).
PhD student’s expected profile
This PhD project will combine experimental and computational biology. The candidate should have knowledge and/or experience in both domains. The experimental approach includes molecular biology and biochemistry experiments. The computational approach involves the application of prediction algorithms on "big data".