Attacks on genetic privacy via uploads to genealogical databases

  1. Michael D Edge  Is a corresponding author
  2. Graham Coop  Is a corresponding author
  1. University of California, Davis, United States

Abstract

Direct-to-consumer (DTC) genetics services are increasingly popular, with tens of millions of customers. Several DTC genealogy services allow users to upload genetic data to search for relatives, identified as people with genomes that share identical by state (IBS) regions. Here, we describe methods by which an adversary can learn database genotypes by uploading multiple datasets. For example, an adversary who uploads approximately 900 genomes could recover at least one allele at SNP sites across up to 82% of the genome of a median person of European ancestries. In databases that detect IBS segments using unphased genotypes, approximately 100 falsified uploads can reveal enough genetic information to allow genome-wide genetic imputation. We provide a proof-of-concept demonstration in the GEDmatch database, and we suggest countermeasures that will prevent the exploits we describe.

Data availability

The dataset used here was assembled from publicly available datasets. The combined dataset has been deposited in Dryad at https://doi.org/10.25338/B8X619, and scripts for assembling and analyzing the data are available at https://github.com/mdedge/IBS_privacy.

The following previously published data sets were used

Article and author information

Author details

  1. Michael D Edge

    Center for Population Biology, University of California, Davis, Davis, United States
    For correspondence
    mdedge@ucdavis.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8773-2906
  2. Graham Coop

    Center for Population Biology, University of California, Davis, Davis, United States
    For correspondence
    gmcoop@ucdavis.edu
    Competing interests
    Graham Coop, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8431-0302

Funding

National Institutes of Health (GM108779)

  • Graham Coop

National Institutes of Health (GM130050)

  • Michael D Edge

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Edge & Coop

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 5,728
    views
  • 608
    downloads
  • 28
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Michael D Edge
  2. Graham Coop
(2020)
Attacks on genetic privacy via uploads to genealogical databases
eLife 9:e51810.
https://doi.org/10.7554/eLife.51810

Share this article

https://doi.org/10.7554/eLife.51810

Further reading

  1. If you've uploaded your DNA on genealogy databases, it may be at risk.

    1. Epidemiology and Global Health
    2. Evolutionary Biology
    Renan Maestri, Benoît Perez-Lamarque ... Hélène Morlon
    Research Article

    Several coronaviruses infect humans, with three, including the SARS-CoV2, causing diseases. While coronaviruses are especially prone to induce pandemics, we know little about their evolutionary history, host-to-host transmissions, and biogeography. One of the difficulties lies in dating the origination of the family, a particularly challenging task for RNA viruses in general. Previous cophylogenetic tests of virus-host associations, including in the Coronaviridae family, have suggested a virus-host codiversification history stretching many millions of years. Here, we establish a framework for robustly testing scenarios of ancient origination and codiversification versus recent origination and diversification by host switches. Applied to coronaviruses and their mammalian hosts, our results support a scenario of recent origination of coronaviruses in bats and diversification by host switches, with preferential host switches within mammalian orders. Hotspots of coronavirus diversity, concentrated in East Asia and Europe, are consistent with this scenario of relatively recent origination and localized host switches. Spillovers from bats to other species are rare, but have the highest probability to be towards humans than to any other mammal species, implicating humans as the evolutionary intermediate host. The high host-switching rates within orders, as well as between humans, domesticated mammals, and non-flying wild mammals, indicates the potential for rapid additional spreading of coronaviruses across the world. Our results suggest that the evolutionary history of extant mammalian coronaviruses is recent, and that cases of long-term virus–host codiversification have been largely over-estimated.