A new digital approach to SNP encoding for DNA identification

• Published in: Forensic science international 2020-12, Vol.317, p.110520-110520, Article 110520
• Main Authors: Garafutdinov, Ravil R., Sakhabutdinova, Assol R., Slominsky, Petr A., Aminev, Farit G., Chemeris, Alexey V.
• Format: Article
• Language: English
• Subjects: 72-Plex SNP panel; Binary format; Biological materials; Computational Biology; Data processing; Deoxyribonucleic acid; Digitization; DNA; DNA Fingerprinting; Forensic Genetics - methods; Forensic sciences; Format; Gene Frequency; Genetic Identification number (GIN); Genotype & phenotype; Graphical representations; Graphics; Humans; Identification; Nucleotides; Polymorphism; Polymorphism, Single Nucleotide; Programming Languages; Single nucleotide polymorphism (SNP); Single-nucleotide polymorphism; Software; Uniqueness
• ISSN: 0379-0738; 1872-6283
• DOI: 10.1016/j.forsciint.2020.110520

•SNP data are digitized as whole 4-bit boxes in the most convenient binary format.•Digitization of SNP data enables creating unique genetic identification numbers (GINs).•All SNPs used for GINs creation should be analyzed as tetra-allelic.•72 SNPs are sufficient for GINs assignment to people all over the world. Identification of individuals has become an urgent problem for mankind. In the last three decades, STR-based DNA identification has actively evolved along with traditional biometric methods. Nonetheless, single-nucleotide polymorphisms (SNPs) are now of great interest and a number of relevant SNP panels have been proposed for DNA identification. Here, a simple approach to SNP data digitization that can provide assigning a unique genetic identification number (GIN) to each person is proposed. The key points of this approach are as follows: 1) SNP data are digitized as whole 4-bit boxes in the most convenient binary format, where character “1” (YES) is assigned to revealed nucleotides, and character “0” (NO) to missing nucleotides after SNP-typing; 2) all SNPs should be considered tetra-allelic. Calculations showed that a 72-plex SNP panel is enough to provide the population with unique GINs, which can be represented in digital (binary or hexadecimal) or graphic (linear or two-dimensional) formats. Simple software for SNP data processing and GINs creation in any format was written. It is likely that the national and global GIN databases will facilitate the solution of problems related to identification of individuals or human biological materials. The proposed approach may be extended to other living organisms as well.