Efficient codon optimization with motif engineering

Authors:
Anne Condon;Chris Thachuk
Affiliations:
Department of Computer Science, University of British Columbia, Vancouver, BC, Canada;Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
Venue:
IWOCA'11 Proceedings of the 22nd international conference on Combinatorial Algorithms
Year:
2011

Citing 3
Cited 1

Algorithms for finding patterns in strings

Handbook of theoretical computer science (vol. A)
Algorithms on strings, trees, and sequences: computer science and computational biology

Algorithms on strings, trees, and sequences: computer science and computational biology
A Pattern Matching Algorithm for Codon Optimization and CpG Motif-Engineering in DNA Expression Vectors

CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics

Efficient codon optimization with motif engineering

Journal of Discrete Algorithms

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Abstract

It is now common to add protein coding genes into cloning vectors for expression within non-native host organisms. Codon optimization supports translational efficiency of the desired protein product, by exchanging codons which are rarely found in the host organism with more frequently observed codons. Motif engineering, such as removal of restriction enzyme recognition sites or addition of immuno-stimulatory elements, is also often necessary. We present an algorithm for optimizing codon bias of a gene with respect to a well motivated measure of bias, while simultaneously performing motif engineering. The measure is the previously studied codon adaptation index, which favors the use, in the gene to be optimized, of the most abundant codons found in the host genome. We demonstrate the efficiency and effectiveness of our algorithm on the GENCODE dataset and provide a guarantee that the solution found is always optimal.