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

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Abstract Determining genetic ancestry of an individual is challenging from poorly preserved or mixed samples that permit only ultra-low coverage sequence (ulcWGS) depth < 0.1x to be gained at target loci. Leveraging the recent advances in telomere-to-telomere sequencing of the 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 WGS sequence at depth less than 0.01x without additional PCR or capture. 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 from short read WGS data.
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Y-mer: A k-mer based method for determining human Y chromosome haplogroups from ultra-low sequencing depth data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article Y-mer: A k-mer based method for determining human Y chromosome haplogroups from ultra-low sequencing depth data Tarmo Puurand, Märt Möls, Lauris Kaplinski, Kadri Maal, Kaarel Krjutskov, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5042960/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Aug, 2025 Read the published version in Genome Biology → Version 2 posted 10 You are reading this latest preprint version Show more versions Abstract Determining genetic ancestry of an individual is challenging from poorly preserved or mixed samples that permit only ultra-low coverage sequence (ulcWGS) depth < 0.1x to be gained at target loci. Leveraging the recent advances in telomere-to-telomere sequencing of the 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 WGS sequence at depth less than 0.01x without additional PCR or capture. 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 from short read WGS data. aDNA ulcWGS NIPS NIPT k-mer human chrY haplogroups prediction Full Text Additional Declarations No competing interests reported. Supplementary Files Ymer240823Model.pdf Ymerrevisedsuppltables070525.xlsx YmerSIrevised070525.docx Cite Share Download PDF Status: Published Journal Publication published 12 Aug, 2025 Read the published version in Genome Biology → Version 2 posted Editorial decision: Revision requested 20 Jun, 2025 Reviews received at journal 11 Jun, 2025 Reviews received at journal 10 Jun, 2025 Reviews received at journal 02 Jun, 2025 Reviewers agreed at journal 18 May, 2025 Reviewers agreed at journal 16 May, 2025 Reviewers agreed at journal 13 May, 2025 Reviewers invited by journal 13 May, 2025 Submission checks completed at journal 13 May, 2025 First submitted to journal 12 May, 2025 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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