Y-mer: a k-mer based method for determining human Y chromosome haplogroups from ultra-low sequencing depth data

Area of Science:

• Genetics
• Bioinformatics
• Population Genetics

Background:

• Genetic ancestry determination is difficult with degraded or mixed DNA samples.
• Ultra-low coverage sequencing (depth < 0.1x) limits traditional methods.
• Advances in long-read sequencing provide new opportunities for low-input DNA analysis.

Purpose of the Study:

• To develop a novel method for accurate genetic ancestry inference from ultra-low coverage whole-genome sequencing data.
• To leverage k-mer information for robust haplogroup determination.
• To demonstrate the method's utility across diverse challenging sample types.

Main Methods:

• Developed Y-mer, a k-mer based computational method.
• Utilized distance-based models incorporating hundreds of thousands of k-mers.
• Applied the method to whole-genome sequence data at depths below 0.01x.

Main Results:

• Y-mer accurately infers Y-chromosome (chrY) haplogroups from ultra-low coverage data.
• The method demonstrates high performance on ancient DNA samples.
• Successful application shown on prenatal screening data, highlighting broad applicability.

Conclusions:

• Y-mer enables reliable genetic ancestry inference even with highly degraded or limited DNA.
• The method has significant potential for applications in ancient DNA, forensics, and cell-free DNA research.
• This work advances the analysis of challenging genomic samples for population and clinical genetics.