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Imputation of Ancient Whole Genome Sus scrofa DNA Introduces Biases Toward Main Population Components in the Reference Panel

  • J.A.M. Erven
  • , C. Çakirlar
  • , D.G. Bradley
  • , D.C.M. Raemaekers
  • , O. Madsen

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Sequencing ancient DNA to high coverage is often limited by sample quality and cost. Imputing missing genotypes can potentially increase information content and quality of ancient data, but requires different computational approaches than modern DNA imputation. Ancient imputation beyond humans has not been investigated. In this study we report results of a systematic evaluation of imputation of three whole genome ancient Sus scrofa samples from the Early and Late Neolithic (∼7,100–4,500 BP), to test the utility of imputation. We show how issues like genetic architecture and, reference panel divergence, composition and size affect imputation accuracy. We evaluate a variety of imputation methods, including Beagle5, GLIMPSE, and Impute5 with varying filters, pipelines, and variant calling methods. We achieved genotype concordance in most cases reaching above 90%; with the highest being 98% with ∼2,000,000 variants recovered using GLIMPSE. Despite this high concordance the sources of diversity present in the genotypes called in the original high coverage genomes were not equally imputed leading to biases in downstream analyses; a trend toward genotypes most common in the reference panel is observed. This demonstrates that the current reference panel does not possess the full diversity needed for accurate imputation of ancient Sus, due to missing variations from Near Eastern and Mesolithic wild boar. Imputation of ancient Sus scrofa holds potential but should be approached with caution due to these biases, and suggests that there is no universal approach for imputation of non-human ancient species.
Original languageEnglish
Article number872486
JournalFrontiers in Genetics
Volume13
DOIs
Publication statusPublished - 12 Jul 2022
Externally publishedYes

Funding

This study is supported by the Dutch Research Council Open Competition (Grant No. 406.18.HW.026) and the European Research Council award to DB under the European Union’s Horizon 2020 research and innovation programme (885729-AncestralWeave).

FundersFunder number
European Research Council
Horizon 2020 Framework Programme885729
Dutch Research Council Open Competition406.18, HW.026

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