A Novel Teaching-Learning-Based Optimization for Improved Mutagenic Primer Design in Mismatch PCR-RFLP SNP Genotyping

Multiobjective optimization-driven primer design mechanism: towards user-specified parameters of PCR primer

Primers are critical for polymerase chain reaction (PCR) and influence PCR experimental outcomes. Designing numerous combinations of forward and reverse primers involves various primer constraints, posing a computational challenge. Most PCR primer design methods limit parameters because the available algorithms use general fitness functions. This study designed new fitness functions based on user-specified parameters and used the functions in a primer design approach based on the multiobjective particle swarm optimization (MOPSO) algorithm to address the challenge of primer design with user-specified parameters. Multicriteria evaluation was conducted simultaneously based on primer constraints. The fitness functions were evaluated using 7425 DNA sequences and compared with a predominant primer design approach based on optimization algorithms. Each DNA sequence was run 100 times to calculate the difference between the user-specified parameters and primer constraint values. The algorithms based on fitness functions with user-specified parameters outperformed the algorithms based on general fitness functions for 11 primer constraints. Moreover, MOPSO exhibited superior implementation in all experiments. Practical gel electrophoresis was conducted to verify the PCR experiments and established that MOPSO effectively designs primers based on user-specified parameters.

Effective Natural PCR-RFLP Primer Design for SNP Genotyping Using Teaching-Learning-Based Optimization With Elite Strategy

SNP (single nucleotide polymorphism) genotyping is the determination of genetic variations of SNPs between members of a species. In many laboratories, PCR-RFLP (polymerase chain reaction-restriction fragment length polymorphism) is a usually used biotechnology for SNP genotyping, especially in small-scale basic research studies of complex genetic diseases. PCR-RFLP requires an available restriction enzyme at least for identify a target SNP and an effective primer pair conforms numerous constraints. However, the lots of restriction enzymes, tedious sequence and complicated constraints make the mining of available restriction enzymes and the design of effective primer pairs become a major challenge. In the study, we propose a novel and available CI (Computation Intelligence)-based method called TLBO (teaching-learning-based optimization) and introduce the elite strategy to design effective primer pairs. Three common melting temperature computations are available in the method. REHUNT (Restriction Enzymes HUNTing) is first combined with the method to mine available restriction enzymes. Robust in silico simulations for the GA (genetic algorithm), the PSO (particle swarm optimization), and the method for natural PCR-RFLP primer design in the SLC6A4 gene with two hundred and eighty-eight SNPs had been performed and compared. These methods had been implemented in JAVA and they are freely available at https://sites.google.com/site/yhcheng1981/tlbonpd-elite for users of academic and non-commercial interests.

AGTR1 rs3772622 gene polymorphism increase the risk of nonalcoholic fatty liver disease patients suffer coronary artery disease in Northern Chinese Han population

Background

Cardiovascular disease (CAD) responsible and nonalcoholic fatty liver disease (NAFLD) are both metabolic diseases, and they are mostly influenced by genetic factors. The aim of our study is to evaluate the relationship between angiotensin II type-1 receptor (AGTR1) gene rs3772622 polymorphisms and the risk of developing coronary artery disease (CAD) in Chinese patients with NAFLD.

Methods

Genotype for AGTR1 rs3772622 in 574 NAFLD patients with CAD or 589 NAFLD patients without CAD, 332 CAD patients exclude NAFLD and 338 health control subjects were determined by sequencing and polymerase chain reaction analysis. Relevant statistical methods were employed to analyze the genotypes, alleles and the clinical date. Inter-group differences and associations were assessed statistically using t-tests and Chi square and logistic analyses. The relative risk of AGTR1 rs3772622 for NAFLD was estimated by logistic regression analysis.

Results

No significant difference in genotype and allele frequency of AGTR1 rs3772622 was found between the NAFLD without CAD population and the controls (P > 0.05). However, makeable difference was found when compared the CAD in patients with NAFLD and CAD free NAFLD patients (P < 0.001 OR = 2.09). Similarly, significant difference was found in AGTR1 rs3772622 genotype distribution between the groups of CAD patients and control (P = 0.046 OR = 1.71).

Conclusions

AGTR1 rs3772622 gene polymorphism was not associated with the risk of NAFLD, but could increase the risk of NAFLD patients suffering from CAD in the Chinese Han population. Deeply mechanisms underlying the association between AGTR1 rs3772622 gene polymorphism and the risk of CAD in NAFLD patients need more research.