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Preprint: New computational method recovers nuclear DNA from the heavily contaminated Teshik-Tash 1 Neandertal

Researchers present admixslug, a method for analysing low-quality archaic human genomes under high modern-human contamination, and apply it to the Teshik-Tash 1 child — the south-easternmost known Neandertal.

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A bioRxiv preprint introduces admixslug, a new computational framework designed to extract population-genetic signal from archaic human genome data that is heavily contaminated with present-day human DNA — a common obstacle when working with ancient specimens from regions where good DNA preservation is rare.

The method is applied to nuclear DNA extracted from Teshik-Tash 1, the remains of a Neandertal child recovered from a cave in Uzbekistan. The site represents the south-easternmost known extent of the Neandertal range, placing it at a geographic crossroads between the better-studied Neandertals of Europe and the Caucasus and those associated with Altai Mountain specimens. Previous attempts to characterise the nuclear genetics of Teshik-Tash 1 have been limited by poor DNA preservation and high contamination levels.

Admixslug jointly models contamination and population relationships, enabling the authors to place Teshik-Tash 1 within the broader Neandertal phylogenetic picture despite the challenging data quality. The preprint will be of interest to researchers in palaeogenomics, computational population genetics, and archaeogenomics, and to educators teaching ancient DNA methodology. The paper also connects to ongoing interest in the geographic and population structure of Neandertals across Eurasia. This is a preprint and has not yet undergone peer review.

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  1. Primary sourcePreprint bioRxiv (Cold Spring Harbor Laboratory) · 2026-08-14
    A Method to Analyze Low-Quality Archaic Human Genomes and its Application to the Teshik-Tash 1 Neandertal

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ancient-dna neandertal teshik-tash palaeogenomics contamination-modelling computational-genomics central-asia preprint
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Genetic Current is the news section of Evagene, an academic, research, and educational pedigree-modelling platform. Stories are AI-drafted summaries of items from trusted public sources, written for researchers, clinicians, educators, students, genealogists, and patients with an interest in genetics. Summaries are for educational and research purposes only and are not medical advice.

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