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TRAILS: Tree reconstruction of ancestry using incomplete lineage sorting.

Iker Rivas-González1, Mikkel H Schierup1, John Wakeley2

  • 1Bioinformatics Research Center (BiRC), Aarhus University, Aarhus, Denmark.

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|February 8, 2024
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TRAILS, a new hidden Markov model, infers ancestral population genetics parameters and speciation times from multi-species alignments. This method aids in understanding evolutionary history and detecting deviations from neutrality.

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Genomics

Background:

  • Genome-wide genealogies offer insights into species' demographic and selection histories.
  • Incomplete lineage sorting (ILS) fragments contain valuable evolutionary information.
  • Accurate inference of ancestral population parameters is crucial for evolutionary studies.

Purpose of the Study:

  • To introduce TRAILS, a novel hidden Markov model for inferring time-resolved population genetics parameters.
  • To leverage ILS fragments for detailed reconstruction of ancestral demographic histories.
  • To enable genome-wide scans for detecting deviations from evolutionary neutrality.

Main Methods:

  • Developed TRAILS, a hidden Markov model utilizing multi-species alignments (three species + outgroup).
  • Modeled genome-wide genealogies as rooted three-leaved trees with coalescent events in discretized time intervals.
  • Employed posterior decoding of the hidden Markov model to infer ancestral recombination graphs and demographic changes.
  • Performed base-pair level analysis for high-resolution genomic scans.

Main Results:

  • Accurately inferred time-resolved population genetics parameters, including ancestral effective population sizes and speciation times.
  • Successfully modeled genealogies and coalescent events within phylogenetic branches.
  • Recovered speciation parameters and detailed information on topology and coalescent times for human-chimp-gorilla-orangutan alignment.
  • Demonstrated the capability of genome-wide scans for detecting deviations from neutrality.

Conclusions:

  • TRAILS provides a powerful framework for inferring detailed ancestral demographic histories from genomic data.
  • The model effectively utilizes information from incomplete lineage sorting across multiple species.
  • TRAILS facilitates high-resolution analysis of evolutionary processes and neutrality testing at the genomic level.