High-throughput primer design by scoring in piecewise logistic model for multiple polymerase chain reaction variants

Abstract

Abstract Polymerase chain reaction (PCR) variants requiring specific primer types are widely used in various PCR experiments, including generic PCR, inverse PCR, anchored PCR, and ARMS PCR. Few tools can be adapted for multiple PCR variants, and many tools select primers by filtration based on the given parameters, which result in frequent design failures. Here we introduce PrimerScore2, a robust high-throughput primer design tool that can design primers in one click for multiple PCR variants. It scores primers using a piecewise logistic model and the highest-scored primers are selected avoiding the issue of design failure and the necessity to loosen parameters to redesign, and it creatively evaluates specificity by predicting the efficiencies of all target/non-target products. To assess the prediction accuracy of the scores and efficiencies, two next generation sequencing (NGS) libraries were constructed—a 12-plex and a 57-plex—and the results showed that 17 out of 19 (89.5%) low-scoring pairs had a poor depth, 18 out of 19 (94.7%) high-scoring pairs had a high depth, and the depth ratios of the products were linearly correlated with the predicted efficiencies with a slope of 1.025 and a coefficient of determination (R2) 0.935. 116-plex and 114-plex anchored PCR panels designed by PrimerScore2 were applied to 26 maternal plasma samples with male fetuses, the results showed that the predicted fetal DNA fractions were concordant with fractions measured in gold standard method (Y fractions). PrimerScore2 was also used to design 77 monoplex Sanger sequencing primers, the sequencing results indicated that all the primers were effective.