Confronting two-pair primer design for enzyme-free SNP genotyping based on a genetic algorithm

Abstract

Background: Polymerase chain reaction with confronting two-pair primers (PCR-CTPP) method produces allele-specific DNA bands of different lengths by adding four designed primers and it achieves the single nucleotide polymorphism (SNP) genotyping by electrophoresis without further steps. It is a time- and cost-effective SNP genotyping method that has the advantage of simplicity. However, computation of feasible CTPP primers is still challenging.

Results: In this study, we propose a GA (genetic algorithm)-based method to design a feasible CTPP primer set to perform a reliable PCR experiment. The SLC6A4 gene was tested with 288 SNPs for dry dock experiments which indicated that the proposed algorithm provides CTPP primers satisfied most primer constraints. One SNP rs12449783 in the SLC6A4 gene was taken as an example for the genotyping experiments using electrophoresis which validated the GA-based design method as providing reliable CTPP primer sets for SNP genotyping.

Conclusions: The GA-based CTPP primer design method provides all forms of estimation for the common primer constraints of PCR-CTPP. The GA-CTPP program is implemented in JAVA and a user-friendly input interface is freely available at http://bio.kuas.edu.tw/ga-ctpp/.

Figure 1

Parameters of the template DNA and the CTPP primer set. Symbols indicate: F: Forward primer; R: Reverse primer; s: Start nucleotide position; e: End nucleotide position; P: Length of PCR product using a primer set (F/R); l: Length of primer or product;ι: Length of DNA template; δ₁: Length from the R_s1 end to downstream of template DNA; δ₂: Length from F_s2 to the downstream end of template DNA.

Figure 2

Flowchart of the GA-based CTPP primer design. At first, a random initial population is generated and then all fitness values of all chromosomes in the population are calculated by the fitness function. A judgment on termination conditions is carried out, and if the termination conditions are reached then the algorithm will be finished, or else the algorithm proceeds with the following processes. Selection, crossover and mutation operations are performed and finally the worst chromosomes are replaced by the better chromosomes. The procedure is repeated in the next iteration until the termination conditions are reached.

Figure 3

Crossover flowchart for CTPP primer design. Two P_v from the population are randomly selected for crossover. At first, a six bit binary mask is generated and indicates which variables need to be exchanged. All exchanged variables are checked for violation of a constraint. If a constriction is violated, the exchanged variables will be restored, or else the process goes on to the next step.

Figure 4

An example of a crossover operation for CTPP primer design. First, randomly select two P_v from the population, for example P_v1 = (25, 118, 23, 24, 256, 25) and P_v2 = (23, 212, 26, 25, 119, 22). Then randomly generate a mask of 6 binary bits i.e., 011001, and based on this mask, exchange the value of P_l1, R_l1 and R_l2. Finally, the new offsprings P'_v1 = (25, 212, 26, 24, 256, 22) and P'_v2 = (23, 118, 23, 25, 119, 25) are generated.

Figure 5

Mutation flowchart for CTPP primer design. When a mutation operation is performed, a mutation point in P_v will be randomly selected and a corresponding value generated. Then the variable will be checked for violation of a constriction. If a constriction is violated, a random point is reselected and the variable is regenerated; otherwise the original value is replaced by the variable and the process continues in the next step.

Figure 6

An example of a mutation operation for CTPP primer design. At the beginning, a P_v = (25, 118, 23, 24, 256, 25) is randomly selected from the offsprings. Then one mutation point of the position F_l1, P_l1, R_l1, F_l2, P_l2 or R_l2 is randomly generated. In our example the position the mutation point is F_l2. Then a random value between 16 and 28 of F_l2 is generated. This value replaces the corresponding variable value in P_v. Finally, the new offspring P'_v = (25, 118, 23, 25, 256, 25) is generated.

Figure 7

The SNP genotyping results of rs12449783 by (A) PCR-CTPP running in gel electrophoresis and (B) by TaqMan probe. (A) M and B indicate the 100 bp markers and blank, respectively. CC, AA, and AC indicate the control DNAs with known genotypes for CC, AA, and AC, respectively. The P_f2/P_r2 (lanes 1, 5, and 9) and P_f1/P_r1 (lanes 2, 6, and 10) primer pairs are designed to specifically amplify the A- and C-containing alleles for genotypes AA and AC vs. genotypes CC and AC, respectively. The P_f1/P_r2 (lanes 3, 7, and 11) primer pair is designed to amplify the A- or C-containing alleles (CC, AA, and AC). For PCR-CTPP using four primers in one tube, it is marked with "P_f1, P_f2, P_r1, P_r2" for lanes 4, 8, and 12. The relative positions for P_f1, P_f2, P_r1, and P_r2 are shown in Figure 1.