Overhang Optimizer for Golden Gate Assembly (OOGGA)

Golden Gate cloning is a popular method for achieving ordered assembly of DNA fragments using complementary four-base pair overhangs. The success of this method relies on the ability of DNA ligases to ligate the different fragments. This ability is affected by the relative efficiency and accuracy with which the ligase recognizes and joins overhanging regions. In this study, we report a dynamic programming approach, called Overhang Optimizer for Golden Gate Assembly (OOGGA), that optimizes these overhangs for their accuracy and efficiency. OOGGA provides the theoretically optimal fragments for Golden Gate assembly, provided a DNA sequence, a length range of the fragments and/or the number of required fragments. As expected, OOGGA outperforms NEBridge SplitSet(R) in both fidelity and efficiency metrics in a set of 3 example DNA sequences. OOGGA also provides support of degenerate nucleotide codes, options to exclude/include motifs for predictions and weights to bias the program for efficiency and fidelity.