An efficient method for developing SNP markers based on EST data combined with high resolution melting (HRM) analysis

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Identifying single nucleotide polymorphisms (SNPs) in large genomes presents significant challenges.
• Expressed Sequence Tag (EST) databases offer a valuable resource for gene-focused SNP discovery.

Purpose of the Study:

• To develop an efficient method for identifying single nucleotide polymorphisms (SNPs) in species with large genomes.
• To evaluate the utility of combining EST databases with High Resolution Melting (HRM) analysis for SNP marker development.

Main Methods:

• Generated 574 sequence tagged sites (STSs) from Cryptomeria japonica.
• Designed primers targeting putative SNP sites within ESTs and randomly from cDNA reads.
• Employed High Resolution Melting (HRM) analysis to screen for polymorphisms in STS markers.

Main Results:

• High Resolution Melting (HRM) analysis identified 325 polymorphic markers among eight individuals.
• Sequence tagged sites (STSs) derived from putative SNP sites showed higher polymorphism levels.
• The combined approach yielded efficient development of SNP markers for expressed genes.

Conclusions:

• The integration of EST database screening with HRM analysis provides a highly efficient strategy for SNP marker development in expressed genes.
• This method is beneficial for genetic mapping and SNP identification in non-model organisms.
• Facilitates genetic studies in species lacking extensive genomic resources.