Evidence map›Paper›PMID 41748326›Full record

ArticleGenome biology and evolution2026

Assessing the Potential of Ancient Protein Sequences in the Study of Hominid Evolution.

Ioannis Patramanis, Laurits Skov, Enrico Cappellini, Fernando Racimo

Abstract read
In one paragraph

Article in Genome biology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Protein Structural Phylogenetics.Genome biology and evolution · 2025
    Review
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ioannis PatramanisGlobe Institute, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-1852-2451
Laurits SkovGlobe Institute, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-9582-0391
Enrico CappelliniGlobe Institute, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-7885-7811
Fernando RacimoGlobe Institute, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-5025-2607

Funding

European Research Council 101021361European Research Council 101077592European Research Council 951385European Union's EU Framework Programme for Research and Innovation Horizon 861389
6 · The paper itself

Abstract

Palaeoproteomic data can provide invaluable insights into hominid evolution over long timescales. Yet, the potential and limitations of ancient protein sequences to resolve evolutionary relations between species remains largely unexplored. In this study, we aim to quantify how much information about these relations can be obtained from limited ancient protein data, at the scale that is currently available or will be available in the near future. We harness sequence alignments of 12 enamel and collagen proteins that have been previously reported in fossil material that is at least 1 million years old. We utilize in silico translations of hominid DNA sequences of these proteins and highlight their differential sequence conservation, indicating some of them contain much larger amounts of information than others. We also evaluate the extent to which inferred topologies from protein data differ from inferred topologies from the more informationally dense DNA data. We show that the former may sometimes lead to inferences of the wrong tree topology due to the informational loss that comes when working with peptide data. Additionally, we determine the number of concatenated proteins necessary to confidently reconstruct the population/species tree summarizing the relations between humans, chimpanzees, and gorillas, as well as those between modern humans, Neanderthals, and Denisovans. As expected, increasing the number of proteins in a concatenation enhances resolution, but we note that trees inferred from the full set of collagen and enamel proteins do not necessarily correspond to population trees inferred from genome-wide data. We show this is especially the case in the closely related groups of our recent ancestors. We further demonstrate that while a number of proteins fall within archaic introgressed haplotypes of present day humans, ancient admixture is not the main source of the observed tree incongruence. Our study underscores the potential and limitations of utilizing palaeoproteomic data in deep time phylogenetic reconstructions, indicating that these will be aided not only by increased recovery of proteins in the future, but also by more careful modeling of evolutionary relations across the genome, beyond simply building single phylogenetic trees.

Indexed as

CollagenDental Enamel ProteinsEvolution, MolecularHominidaeAmino Acid SequenceAnimalsFossilsHumansPhylogenySequence AlignmentCollagenDental Enamel Proteinshuman evolutionincomplete lineage sortingpalaeoprotoemicsphylogeneticspopulation genetics

Identifiers

PMID41748326
PMCPMC12962811

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.