RiboProP: A Probabilistic Ribosome Positioning Algorithm for Ribosome Profiling.

Motivation: Ribosome profiling has been widely used to study translation in a genome-wide fashion. It requires deep sequencing of ribosome protected mRNA fragments followed by mapping of fragments to the reference genome. For applications such as identification of ribosome pausing sites, it is not enough to map a fragment to a given gene, but the exact position of the ribosome represented by the fragment must be identified for each mRNA fragment. The assignment of the correct ribosome position is complicated by the broad length distribution of the ribosome protected fragments caused by the known sequence bias of micrococcal nuclease (MNase), the most widely used nuclease for digesting mRNAs in bacteria. Available mapping algorithms suffer from either MNase bias or low accuracy in characterizing the ribosome pausing kinetics.

Results: In this paper, we introduce a new computational method for mapping the ribosome protected fragments to ribosome locations. We first develop a mathematical model of the interplay between MNase digestion and ribosome protection of the mRNAs. We then use the model to reconstruct the ribosome occupancy profile on a per gene level. We demonstrate that our method has the capability of mitigating the sequence bias introduced by MNase and accurately locating ribosome pausing sites at codon resolution. We believe that our method can be broadly applied to ribosome profiling studies on bacteria where codon resolution is necessary.

Availability: Source code implementing our approach can be downloaded under GPL3 license at https://bioserv.mps.ohio-state.edu/RiboProP.

Supplementary information: Supplementary data are available at Bioinformatics online.