Kmer2SNP: Reference-Free Heterozygous SNP Calling Using k-mer Frequency Distributions

Area of Science:

• Genomics and Bioinformatics
• Population Genetics
• Molecular Biology

Background:

• DNA sequencing generates genetic profiles rapidly.
• Single-nucleotide polymorphism (SNP) identification is vital for genetic studies, including disease association, ancestry, and relationship inference.
• Current SNP calling methods typically rely on species-specific reference genomes, which are not always available.

Purpose of the Study:

• To develop a reference-free algorithm for identifying heterozygous SNPs from raw sequencing reads.
• To facilitate genetic studies in species where high-quality reference genomes are unavailable.
• To provide a robust method for SNP discovery without relying on a reference genome.

Main Methods:

• Developed Kmer2SNP, a reference-free algorithm.
• Calculates k-mer frequency distribution from raw sequencing reads to identify k-mers containing heterozygous SNPs.
• Matches exact heterozygous k-mers to identify haplotype pairs and uses overlapping k-mers to assign SNP confidence weights.

Main Results:

• Successfully identified heterozygous SNPs without a reference genome.
• Kmer2SNP efficiently processes k-mer frequency distributions and matches k-mers for accurate SNP calling.
• The algorithm assigns weights to SNP assignments based on overlapping k-mers, enhancing discovery confidence.

Conclusions:

• Kmer2SNP offers a valuable tool for SNP identification in species lacking reference genomes.
• The reference-free approach broadens the scope of genetic research in understudied organisms.
• This method supports diverse genetic applications, including population genetics and evolutionary studies.