1 / 12

Programming cells by mutliplex genome engineering and accelerated evolution

Programming cells by mutliplex genome engineering and accelerated evolution. Harris H. Wang, Farren J. Isaacs, Peter A. Carr, Zachary Z. Sun, George Xu , Craig R. Forest, George M. Church Raven Reddy March 30, 2011. MAGE Technology. Wanted to modify genomes on large, parallel scale

katima
Download Presentation

Programming cells by mutliplex genome engineering and accelerated evolution

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Programming cells by mutliplex genome engineering and accelerated evolution Harris H. Wang, Farren J. Isaacs, Peter A. Carr, Zachary Z. Sun, George Xu, Craig R. Forest, George M. Church Raven Reddy March 30, 2011

  2. MAGE Technology • Wanted to modify genomes on large, parallel scale • Automated method to modify many locations • Incorporate ssDNAoligos onto lagging strand of replication fork • Create genetic modifications in 30% of cells every 2-2.5 hrs

  3. MAGE Technology

  4. MAGE Technology

  5. Quantifying Efficiency • Mismatch or Insertion efficiency proportional to amount of homologous sequence

  6. Quantifying Efficiency • Deletion efficiency proportional to size of deletion

  7. Quantifying Efficiency • Hybridization free energy between oligo and chromosome predicts replacement efficiency

  8. Generating Sequence Diversity 30 consecutive mutations 6 consecutive mutations 6 interspersed mutations

  9. Lycopene Optimization

  10. Conclusions • Created adjustable diversity with MAGE • Rationally designed oligos can have specific effects • Oligos with degenerate sequences create diversity • Accelerates the rate of accumulation of useful mutations

  11. Generating Sequence Diversity • Complexity of the oligo pool • Number of loci targeted • Number of MAGE cycles performed

  12. Characterization of allelic replacement frequency

More Related