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Updated: May 22, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
Published on: July 11, 2025
Algorithms for optimizing cross-overs in DNA shuffling
Lu He1, Alan M Friedman, Chris Bailey-Kellogg
1Dept of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755, USA.
This study introduces CODNS, a novel DNA shuffling method that enables recombination of more diverse gene parents. This approach generates predictable and optimized chimeric libraries for protein engineering.
Area of Science:
- Protein Engineering
- Molecular Biology
- Bioinformatics
Background:
- DNA shuffling creates gene libraries by recombining parent genes for selection.
- Current DNA shuffling is limited to homologous sequences and lacks control over recombination.
- This limits its application to closely related gene families.
Purpose of the Study:
- To develop efficient methods for DNA shuffling with diverse parents.
- To generate more predictable and optimized chimeric gene libraries.
- To extend the scope and control of DNA shuffling.
Main Methods:
- Developed CODNS (cross-over optimization for DNA shuffling) using dynamic programming algorithms.
- Optimized local sequence identity and free energy approximation for annealing.
- Implemented algorithms to control recombination frequency and localization by creating nucleotide runs.
Main Results:
- CODNS efficiently selects codons and allocates substitutions for targeted recombination.
- Demonstrated effectiveness with diverse parents including GAR transformylases, DNA polymerases (Pol X and β), and beta-lactamases.
- Successfully promoted recombination between distantly related genes (down to 15% sequence identity).
Conclusions:
- The new DNA shuffling approach supports significantly more diverse parents.
- The method is more deterministic, leading to predictable chimeric library generation.
- Protein engineers gain enhanced control for creating diverse and optimized gene libraries.
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