In Silico Restriction Mapping of BRCA1, BRCA2, TP53, and ERBB2 Variants for Identification of Potential PCR-RFLP Diagnostic Markers in Breast Cancer

Breast cancer-associated genes ( BRCA1 , BRCA2 , TP53 , and ERBB2 ) harbor pathogenic variants that contribute to tumor development and may alter restriction enzyme recognition sites. This study performed a comparative in silico restriction mapping of wild-type and mutant sequences to identify mutation-associated restriction fragment length polymorphisms (RFLPs) with potential diagnostic relevance. Coding sequences were retrieved from NCBI GenBank, while pathogenic variants were obtained from ClinVar and mapped using Ensembl annotations. Mutant sequences were generated in silico and analyzed using NEBcutter V2.0 with five restriction enzymes (BamHI, EcoRI, HindIII, NotI, and PstI). Descriptive statistical analyses were conducted to assess gene- and enzyme-level variation in restriction site distribution. Results showed marked heterogeneity in restriction site distribution among genes, with BRCA2 exhibiting the highest digestibility and TP53 the lowest. PstI demonstrated the highest cleavage frequency, whereas NotI showed no activity. Comparative analysis revealed that most pathogenic variants did not alter restriction profiles; however, TP53 c.743G>A and ERBB2 c.929C>T produced detectable gain- and loss-of-site polymorphisms. These findings demonstrate that mutation-induced restriction site changes are highly sequence-dependent and can be systematically identified through computational screening. In silico restriction mapping provides a rapid and cost-effective approach for prioritizing candidate PCR-RFLP diagnostic markers in breast cancer genetics.