Prediction of ribosome footprint profile shapes from transcript sequences

Joyce Tzu-Yu Liu, Yun S. Song

Abstract:

Motivation: Ribosome profiling is a useful technique for studying translational dynamics and quantifying
protein synthesis. Applications of this technique have shown that ribosomes are not uniformly
distributed along mRNA transcripts. Understanding how each transcript-specific distribution
arises is important for unraveling the translation mechanism.
Results: Here, we apply kernel smoothing to construct predictive features and build a sparse model
to predict the shape of ribosome footprint profiles from transcript sequences alone. Our results on
Saccharomyces cerevisiae data show that the marginal ribosome densities can be predicted with
high accuracy. The proposed novel method has a wide range of applications, including inferring
isoform-specific ribosome footprints, designing transcripts with fast translation speeds and discovering
unknown modulation during translation.