Both consensus shuffling and coincidence filtering protocols were effective in reducing errors in synthetic GFPuv populations ( Figure 3 ). In both cases, two iterations of either consensus shuffling or coincidence filtering increased fluorescent colonies from average values of $60 to >90%. Sequencing data from two independent experiments showed a 4.3-and 3.5-fold reduction in the error rate for the consensus shuffled populations compared with the input populations giving final error rates of 0.3 and 0.28 errors/kb, respectively. These results demonstrate the usefulness of the MBP-MutS-H6 error filter in both consensus shuffling and coincidence filtering protocols. Taq MutS has previously been shown to bind to deletion mutations with high affinity (27) , a mutation common in synthetic DNA. However, it is important to note that Taq MutS has lower affinity for specific point mutations and binds weakly to homoduplex DNA (27) . These factors may limit the stepwise efficiency of the error filter. Moreover, specific point mutations may be refractory to removal even after multiple rounds of consensus shuffling. Two rounds of consensus shuffling using the MBP-MutS-H6 error filter proved most effective in reducing deletions and G/C to A/T transitions, consistent with previous reports for the selectivity of Taq MutS (27) . However, it must be emphasized that each synthetic oligonucleotide point mutation would generate two heteroduplex DNA molecules containing unique mismatches after PCR amplification and re-hybridization ( Figure 1A and Table 1 ). For example, a G to A transition mutation in a synthetic oligonucleotide would generate heteroduplexes with G-T or A-C mismatches after PCR amplification and re-hybridization. For consensus shuffling, either of these mismatch containing heteroduplexes could evade precipitation by the MBP-MutS-H6 error filter and participate in the reassembly of full-length GFPuv. Therefore, Table 1 lists the pair of mismatches that could give rise to the observed transition or transversion mutation. These results show that the MBP-MutS-H6 error filter was most effective at removing insertion/deletion loops and G-T/A-C mismatches from the population.