All righrs reserved. This group of methods is aimed at the identification of single nucleotide-scale differences between the comparing DNA samples. Mutation and polymorphism detection is of increasing importance in the field of molecular genetics because the study of mutations reveals the normal functions of genes, proteins, noncoding RNAs, the causes of many malignancies, and the variability of responses among individuals. A plethora of single nucleotide polymorphisms (SNPs) are not deleterious by themselves, but are linked to phenotypes associated with diseases and drug responses, thus providing a great opportunity for their use in large-scale association and population studies. Millions of SNPs have been identified in recent years. However, this figure seems negligible compared to the real number of SNPs and other mutations presented in the genomes. Many mutation discovery methods quickly and effectively indicate the presence of a mutation in a sample region, but fail to resolve its characterization and localization; another family of methods permits precise mutation mapping, but in a greatly more laborious and expensive way. The group of novel approaches for mutation detection, which combines high performance, cost-efficiency, reliability, and detailed mutation characterization, will be reviewed in this chapter.