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Related Experiment Videos

AD-LIBS: inferring ancestry across hybrid genomes using low-coverage sequence data.

Nathan K Schaefer1,2, Beth Shapiro3,4, Richard E Green5,4

  • 1Department of Biomolecular Engineering, University of California, Santa Cruz, USA. nkschaefer@soe.ucsc.edu.

BMC Bioinformatics
|April 6, 2017
PubMed
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AD-LIBS is a new software tool that infers ancestry in hybrid genomes without needing high-quality data or phasing. This method works for non-model and ancient organisms, expanding genetic ancestry studies.

Area of Science:

  • Genomics
  • Population Genetics
  • Bioinformatics

Background:

  • Accurate inference of regional ancestry in admixed genomes is crucial for genetic studies.
  • Existing methods necessitate high-coverage genotype data and phased reference panels, limiting their applicability.
  • Novel approaches are needed for non-model organisms and low-coverage datasets, such as ancient DNA.

Purpose of the Study:

  • To introduce AD-LIBS, a software application for inferring ancestry across hybrid genomes.
  • To demonstrate AD-LIBS's utility without requiring variant calling or phasing.
  • To enable ancestry inference in challenging datasets, including low-coverage and non-model organisms.

Main Methods:

  • Utilized a hidden Markov model (HMM) for ancestry inference.
Keywords:
AdmixtureAncestryBearsHybridizationSpeciation

Related Experiment Videos

  • Applied AD-LIBS to synthetic datasets for validation.
  • Tested AD-LIBS on published datasets of human-Neanderthal and bear-polar bear admixture.

    • Main Results:

    • AD-LIBS achieved 87-91% accuracy in ancestry inference on simulated data.
    • Results from human and bear datasets showed agreement with published findings.
    • AD-LIBS identified higher polar bear ancestry in brown bears than previously reported.
    • Demonstrated superior performance of AD-LIBS over HAPMIX when reference data are unavailable or coverage is low.

    Conclusions:

    • AD-LIBS is an effective ancestry inference tool, particularly for low-coverage genomes and limited reference data.
    • The software is valuable for studies involving non-model or ancient organisms.
    • AD-LIBS expands the scope of admixture mapping studies, making them accessible for a wider range of biological research.