Oct 17, 2014

Analysis of computational codon usage models and their association with translationally slow codons

BioRxiv : the Preprint Server for Biology
Oleg MoskvinScott Emrich

Abstract

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae , because RFP data is often considered as a "ground truth'' for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating transla...Continue Reading

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