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This article is part of the supplement: ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2011

Open Access Proceedings

Algorithms for optimizing cross-overs in DNA shuffling

Lu He1, Alan M Friedman2* and Chris Bailey-Kellogg1*

Author Affiliations

1 Dept of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755, USA

2 Dept of Biological Sciences, Markey Center for Structural Biology, Purdue Cancer Center, and Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA

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BMC Bioinformatics 2012, 13(Suppl 3):S3  doi:10.1186/1471-2105-13-S3-S3

Published: 21 March 2012

Abstract

Background

DNA shuffling generates combinatorial libraries of chimeric genes by stochastically recombining parent genes. The resulting libraries are subjected to large-scale genetic selection or screening to identify those chimeras with favorable properties (e.g., enhanced stability or enzymatic activity). While DNA shuffling has been applied quite successfully, it is limited by its homology-dependent, stochastic nature. Consequently, it is used only with parents of sufficient overall sequence identity, and provides no control over the resulting chimeric library.

Results

This paper presents efficient methods to extend the scope of DNA shuffling to handle significantly more diverse parents and to generate more predictable, optimized libraries. Our CODNS (cross-over optimization for DNA shuffling) approach employs polynomial-time dynamic programming algorithms to select codons for the parental amino acids, allowing for zero or a fixed number of conservative substitutions. We first present efficient algorithms to optimize the local sequence identity or the nearest-neighbor approximation of the change in free energy upon annealing, objectives that were previously optimized by computationally-expensive integer programming methods. We then present efficient algorithms for more powerful objectives that seek to localize and enhance the frequency of recombination by producing "runs" of common nucleotides either overall or according to the sequence diversity of the resulting chimeras. We demonstrate the effectiveness of CODNS in choosing codons and allocating substitutions to promote recombination between parents targeted in earlier studies: two GAR transformylases (41% amino acid sequence identity), two very distantly related DNA polymerases, Pol X and β (15%), and beta-lactamases of varying identity (26-47%).

Conclusions

Our methods provide the protein engineer with a new approach to DNA shuffling that supports substantially more diverse parents, is more deterministic, and generates more predictable and more diverse chimeric libraries.