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Abstract

Successful primer design for polymerase chain reaction (PCR) hinges on the ability to identify primers
that efciently amplify template sequences. Here, we generated a novel Taq PCR data set that reports
the amplifcation status for pairs of primers and templates from a reference set of 47 immunoglobulin
heavy chain variable sequences and 20 primers. Using logistic regression, we developed TMM, a model
for predicting whether a primer amplifes a template given their nucleotide sequences. The model
suggests that the free energy of annealing, ΔG, is the key driver of amplifcation (p=7.35e-12) and that
3′ mismatches should be considered in dependence on ΔG and the mismatch closest to the 3′ terminus
(p=1.67e-05). We validated TMM by comparing its estimates with those from the thermodynamic
model of DECIPHER (DE) and a model based solely on the free energy of annealing (FE). TMM
outperformed the other approaches in terms of the area under the receiver operating characteristic
curve (TMM: 0.953, FE: 0.941, DE: 0.896). TMM can improve primer design and is freely available via
openPrimeR (http://openPrimeR.mpi-inf.mpg.de).