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temperature at which 50 % of the target is bound by the oligonucleotide and 50 % is unbound. 392 However, the Tm does not indicate the amount of hybridization at the desired annealing 393 temperature for primers or at the extension temperature for TaqMan probes. A common 394 misconception is that the best way to design primers is to match their Tm’s (14). This procedure 395 is suboptimal, however, for two reasons: 1) even if the Tm’s are matched, the binding curves 396 have different slopes (due to different  H  values) and thus different amounts bound at the 397 annealing temperature; and 2) the 2-state Tm does not capture the competing unimolecular 398 secondary structures. Primer and target unimolecular secondary structure can be predicted using 399 dynamic programming algorithms such as MFOLD (16), RNAStructure (17) or OMP (14). 400 Rather than focusing on Tm-based metrics, it is recommended to use software that focuses on 401 solving the competing equilibrium for the actual amount bound at the desired temperature. The 402 algorithms should try a wide variety of primer/probe lengths so that G-C rich targets will use 403 shorter primers/probes to achieve a particular amount bound, while A-T rich targets will 404 naturally select longer primers/probes to achieve a similar amount bound. Computation of the 405 amount bound is best accomplished using a multi-state coupled equilibrium model (14, 18). In 406 addition to computing bimolecular hybridization and competing unimolecular folding, it is useful 407 to check sets of primers to ensure that they do not form primer-dimer species involving the 3’- 408 ends of the primers. This can be predicted with programs such as AutoDimer (19) and 409 ThermoBLAST (14). There are also a variety of experimental approaches for eliminating primer- 410 dimers (20, 21).

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