bioRxivEvolutionary BiologyPreprint
Recovering signatures of archaic introgression using ancestral recombination graphs
Yulin ZhangiD, Arjun BiddandaiD, Sarah JohnsoniD, Colm T. O’DushlaineiD, Priya MoorjaniiD
Abstract
Neanderthal and Denisovan genomes have reshaped our understanding of archaic introgression. Yet, the limited number of archaic genomes sequenced and the reliance on unadmixed outgroups have left much of this history unresolved. We introduce TRACE, a method to identify archaic ancestry using features of ancestral recombination graphs inferred from contemporary genomes alone. Simulations show that TRACE reliably detects archaic introgression without requiring archaic genomes or unadmixed outgroups. Applied to 1000 Genomes data, TRACE recovers known Neanderthal and Denisovan introgression and reveals signals of ghost admixture from previously uncharacterized hominins in both Africans and non-Africans. Strikingly, ghost ancestry persists in Neanderthal and Denisovan ancestry deserts, challenging their interpretation as Homo sapiens-specific regions. In Oceanians, TRACE finds deep lineages enriched in Denisovan--and not Neanderthal--regions, supporting a model of super-archaic gene flow. TRACE provides a scalable framework for mapping the legacy of archaic introgression in the absence of archaic genome sequences.
- organism: human
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- research focus: host-pathogen & immune response
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
- Citations
- 2
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