Poster abstracts
Poster number 141 submitted by Hao Wang
Translation rate evaluation with ribosome profiling data
Hao Wang (Lane center for computational biology, Carnegie Mellon University), Joel McManus (Department of Biological Science, Carnegie Mellon Univeristy), Carl Kingsford (Lane center for computational biology, Carnegie Mellon University)
Abstract:
Ribosome profiling is a recently developed sequencing technique that provides approximately 30-base sequences that are protected by ribosomes translating a transcript. Because it measures activity at translation, we can use it to more directly measure protein abundance and understand buffering or amplification of differences in transcription. The challenge with this data is mapping short sequences to isoforms to get an isoform-level estimation of ribosome positions. We are developing a method that combines a model of ribosome motion with short-read mapping in an expectation-maximization framework to estimate isoform-specific ribosome positions. Using this approach, we will be able to estimate sequence-specific rates of ribosome motion and to relate transcript abundance with translational efficiency.
References:
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3. Reuveni, S. et al. (2011). PLoS comp. bio., 7(9), e1002127.
Keywords: ribosome profiling, translation rate, translation model