TMC-SNPdb: an Indian germline variant database derived from whole exome sequences

Area of Science:

• Genomics
• Bioinformatics
• Population Genetics

Background:

• Cancer is primarily a somatic disease, meaning mutations occur in non-reproductive cells.
• Accurate identification of somatic mutations requires distinguishing them from germline variants present in public databases.
• Existing databases like dbSNP have limited representation of non-European populations, impacting cancer genomic studies in these groups.

Purpose of the Study:

• To develop a comprehensive SNP database (TMC-SNPdb) tailored for Indian populations.
• To create a subtraction tool to filter population-specific germline variants.
• To enhance the accuracy of somatic mutation detection in cancer genomic analyses.

Main Methods:

• Generated TMC-SNPdb from whole exome data of 62 normal Indian samples, containing 114,309 unique germline variants.
• Developed a subtraction tool with command-line and GUI options to remove SNPs from dbSNP and 1000 Genomes.
• Applied TMC-SNPdb and the tool to whole exome data from 132 Indian samples.

Main Results:

• TMC-SNPdb effectively depleted false positive somatic events in Indian cancer samples.
• Reductions in false positives were 42% for tongue, 33% for gallbladder, and 28% for cervical cancer.
• The database and tool are freely available and compatible with dbSNP build 149 and ANNOVAR.

Conclusions:

• TMC-SNPdb significantly improves the accuracy of somatic mutation identification in Indian populations.
• The developed tool aids in distinguishing true somatic mutations from germline variants.
• TMC-SNPdb has potential applications beyond cancer genomics, including Mendelian germline disease research.