Codon Context Optimization in Synthetic Gene Design

TL;DR

This paper investigates the impact of codon context on mRNA translation efficiency, analyzes its statistical properties, and develops algorithms and tools for optimizing gene sequences based on codon context.

Contribution

It introduces a formal analysis of codon context measures, computational complexity results, and efficient algorithms for gene recoding with codon context optimization.

Findings

Codon context significantly influences translational efficiency.

Efficient algorithms for gene recoding based on codon context are developed.

A web tool for evaluating codon context bias is presented.

Abstract

Advances in de novo synthesis of DNA and computational gene design methods make possible the customization of genes by direct manipulation of features such as codon bias and mRNA secondary structure. Codon context is another feature significantly affecting mRNA translational efficiency, but existing methods and tools for evaluating and designing novel optimized protein coding sequences utilize untested heuristics and do not provide quantifiable guarantees on design quality. In this study we examine statistical properties of codon context measures in an effort to better understand the phenomenon. We analyze the computational complexity of codon context optimization and design exact and efficient heuristic gene recoding algorithms under reasonable constraint models. We also present a web-based tool for evaluating codon context bias in the appropriate context.