Puurand Tarmo, Möls Märt, Kaplinski Lauris, Maal Kadri, Krjutskov Kaarel, Salumets Andres, Kivisild Toomas, Remm Maido
Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.
Genome Biol. 2025 Aug 12;26(1):243. doi: 10.1186/s13059-025-03714-3.
Determining genetic ancestry of an individual is challenging from poorly preserved or mixed samples that permit only ultra-low coverage sequence at depths less than 0.1 × at target loci. Leveraging recent advances in telomere-to-telomere sequencing of whole genomes with long reads, we develop a new k-mer based method, Y-mer, and show how information from hundreds of thousands of k-mers in distance-based models enables accurate inference of chrY haplogroup from whole-genome sequence at depth less than 0.01x. We test the performance of Y-mer on ancient DNA and prenatal screening data, showing its potential for genetic ancestry inference for cell-free, forensic and ancient DNA research.
从保存不佳或混合的样本中确定个体的遗传血统具有挑战性，因为这些样本仅允许在目标位点进行深度小于0.1×的超低覆盖度测序。利用全基因组端粒到端粒长读长测序的最新进展，我们开发了一种基于新的k-mer的方法Y-mer，并展示了基于距离模型中数十万个k-mer的信息如何能够从深度小于0.01x的全基因组序列中准确推断Y染色体单倍群。我们在古代DNA和产前筛查数据上测试了Y-mer的性能，显示了其在游离DNA、法医和古代DNA研究中的遗传血统推断潜力。
