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Rapid genotype imputation from sequence with reference panels

Nature Genetics volume 53, pages 1104–1111 (2021)Cite this article

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Abstract

Inexpensive genotyping methods are essential to modern genomics. Here we present QUILT, which performs diploid genotype imputation using low-coverage whole-genome sequence data. QUILT employs Gibbs sampling to partition reads into maternal and paternal sets, facilitating rapid haploid imputation using large reference panels. We show this partitioning to be accurate over many megabases, enabling highly accurate imputation close to theoretical limits and outperforming existing methods. Moreover, QUILT can impute accurately using diverse technologies, including long reads from Oxford Nanopore Technologies, and a new form of low-cost barcoded Illumina sequencing called haplotagging, with the latter showing improved accuracy at low coverages. Relative to DNA genotyping microarrays, QUILT offers improved accuracy at reduced cost, particularly for diverse populations that are traditionally underserved in modern genomic analyses, with accuracy nearly doubling at rare SNPs. Finally, QUILT can accurately impute (four-digit) human leukocyte antigen types, the first such method from low-coverage sequence data.

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Fig. 1: Schematic of the QUILT model.
Fig. 2: Assessment of read label partitioning.
Fig. 3: Imputation accuracy of the NA12878 sample.
Fig. 4: Imputation accuracy of 5-Family, GBR and ONT samples.
Fig. 5: Imputation accuracy of the 1000 Genomes Project samples.
Fig. 6: Imputation accuracy of HLA loci.
Fig. 7: Relative increase in effective sample size and power using lcWGS and QUILT.

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Data availability

The HRC haplotypes are available at the European Genome-phenome Archive under accession no. EGAD00001002729; they are available through the Sanger Institute under controlled access. The high-coverage, whole-genome sequence from the 1000 Genomes NYGC collection is available at https://www.internationalgenome.org/data-portal/data-collection/30x-grch38. Specifically, we used file http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_2504_high_coverage.sequence.index. High-coverage ONT data from Bowden et al.25 are available through the ENA under accession no. PRJEB30620. High-coverage ONT and Illumina (10×) samples from Shafin et al.27 are available through https://s3-us-west-2.amazonaws.com/human-pangenomics/index.html?prefix=. gnomAD SNP frequencies from the version 3.0 release were downloaded as detailed at https://gnomad.broadinstitute.org/downloads from URLs such as https://storage.googleapis.com/gnomad-public/release/3.0/vcf/genomes/gnomad.genomes.r3.0.sites.chr1.vcf.bgz. IPD-IMGT/HLA data were downloaded through their github database (https://github.com/ANHIG/IMGTHLA), specifically v.3.39 through https://github.com/ANHIG/IMGTHLA/blob/032815608e6312b595b4aaf9904d5b4c189dd6dc/Alignments_Rel_3390.zip?raw=true. Previously inferred HLA types for 1000 Genomes Project participants (v.20181129) were downloaded from the 1000 Genomes FTP (http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/HLA_types/20181129_HLA_types_full_1000_Genomes_Project_panel.txt). Recombination rates for the CEU 1000 Genomes Project samples were downloaded from ftp-trace.ncbi.nih.gov/1000genomes/ftp/technical/working/20130507_omni_recombination_rates/CEU_omni_recombination_20130507.tar. All new high- and low-coverage sequencing done for this study are available at the Sequence Read Archive under BioProject accession no. PRJNA669554.

Code availability

QUILT is available from https://github.com/rwdavies/QUILT under a General Public License. The specific versions of QUILT used in this manuscript are available from Figshare40.

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Acknowledgements

We thank C. Lanz, R. Schwab, O. Weichenrieder and I. Bezrukov at the MPI Developmental Biology for assistance with high-throughput sequencing and associated data processing and A. Noll and the MPI Tübingen IT team for computational support. We used high-coverage resequencing of 1000 Genomes Project data performed by the NYGC. These data were generated at the NYGC with funds provided by National Human Genome Research Institute grant no. 3UM1HG008901-03S1. The research was supported by the Wellcome Trust Core Award Grant no. 203141/Z/16/Z with additional support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre and by Wellcome Trust grant nos. 200186/Z/15/Z and 212284/Z/18/Z (to S.M.). The views expressed are those of the author(s) and not necessarily those of the NHS, NIHR or the Department of Health. We acknowledge the contribution and support from affected persons and their families who contributed to the Bloom Syndrome Repository. We thank the New York Community Trust and Weill Cornell Medicine’s Clinical and Translational Science Center for providing funding. M.K., D.S. and Y.F.C. are supported by the Max Planck Society and a European Research Council Starting Grant (no. 639096 HybridMiX).

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Author notes

  1. These authors contributed equally: Yingguang Frank Chan, Simon Myers.

Authors and Affiliations

  1. Department of Statistics, University of Oxford, Oxford, UK

    Robert W. Davies, Sinan Shi & Simon Myers

  2. Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany

    Marek Kucka, Dingwen Su & Yingguang Frank Chan

  3. Department of Pediatrics, Weill Cornell Medical College, New York, NY, USA

    Maeve Flanagan & Christopher M. Cunniff

  4. The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

    Simon Myers

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Contributions

R.W.D. developed and implemented QUILT. M.K., D.S. and Y.F.C. developed haplotagging. R.W.D., M.K. and S.S. performed the analyses. M.F. and C.M.C. developed the 5-Family dataset. S.M. developed and implemented the QUILT-HLA typer. R.W.D., Y.F.C. and S.M. wrote the paper. All authors reviewed and approved the final manuscript.

Corresponding author

Correspondence to Robert W. Davies.

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Competing interests

M.K. and Y.F.C. declare competing interests in the form of patent and employment by the Max Planck Society. The remaining authors declare no competing interests.

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Davies, R.W., Kucka, M., Su, D. et al. Rapid genotype imputation from sequence with reference panels. Nat Genet 53, 1104–1111 (2021). https://doi.org/10.1038/s41588-021-00877-0

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