Abstract 5100: Optimization of amplicon design for polymerase chain reaction

Amplicon design is critical important in DNA sequencing technology. Previously the amplicon designer uses exhaustive trial and error method, relying on the individual experience to compare the cost of different amplicon combinations. However, optimization of amplicon design has remained challenging due to the lack of a systematic method. As the magnitude of target DNA region and amplicon combination increases, the complexity of manual calculation and judgment will grow exponentially. In this study, our aim was to design a mathematical model to minimize the cost of amplicon combination. For given amplicon design problem, a linear integer programming model is constructed according to the optimization target and the restrictions. Let’s denote our target regions by R_1⋯ R_M, and amplicon by A_1,⋯, A_N, and conflict value c_ij for the amplicon pair A_i and A_j. The model’s restriction is to find a set of amplicons that could cover the target regions as much as possible, and for each R_i we have at most two A_j which will cover it simultaneously. The model’s optimization target is to minimize the total conflict value. The model is implemented by Python programming and uses Gurobi optimization software. In a project to design amplicon for DNA sequencing, the target regions consist of about 90,000 bits, and there are about 35,000 amplicon available. The above optimization method running on the personal computer with 8GB and 2.2GHz Intel i5-5200 CPU, take about 24 hours and produce total conflict value of 1374. The best trial and error practice took more than one week and produced total conflict value of 4527. Optimization of amplicon design for polymerase chain reaction proves to be more precise and efficient than the exhaustive trial and error method. Using optimization method will help standardize the product design for DNA sequencing.Citation Format: Bolong He, Hao Qin, Fugen Li, Hanyan Yang. Optimization of amplicon design for polymerase chain reaction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5100.