Balancing selection on genomic deletion polymorphisms in humans

  1. Alber Aqil
  2. Leo Speidel
  3. Pavlos Pavlidis
  4. Omer Gokcumen  Is a corresponding author
  1. University at Buffalo, State University of New York, United States
  2. University College London, United Kingdom
  3. Foundation for Research and Technology Hellas, Greece

Abstract

A key question in biology is why genomic variation persists in a population for extended periods. Recent studies have identified examples of genomic deletions that have remained polymorphic in the human lineage for hundreds of millennia, ostensibly owing to balancing selection. Nevertheless, genome-wide investigation of ancient and possibly adaptive deletions remains imperative. Here, we demonstrate an excess of polymorphisms in present-day humans that predate the modern human-Neanderthal split (ancient polymorphisms), which cannot be explained solely by selectively neutral scenarios. We analyze the adaptive mechanisms that underlie this excess in deletion polymorphisms. Using a previously published measure of balancing selection, we show that this excess of ancient deletions is largely owing to balancing selection. Based on the absence of signatures of overdominance, we conclude that it is a rare mode of balancing selection among ancient deletions. Instead, more complex scenarios involving spatially and temporally variable selective pressures are likely more common mechanisms. Our results suggest that balancing selection resulted in ancient deletions harboring disproportionately more exonic variants with GWAS associations. We further found that ancient deletions are significantly enriched for traits related to metabolism and immunity. As a by-product of our analysis, we show that deletions are, on average, more deleterious than single-nucleotide variants. We can now argue that not only is a vast majority of common variants shared among human populations, but a considerable portion of biologically relevant variants has been segregating among our ancestors for hundreds of thousands, if not millions, of years.

Data availability

All data that are used in the study can be found publically. The references and databases are provided in the manuscript. The code and resulting datasets are all provided either through our laboratory's GitHub page, FigShare, or as supplementary tables.

The following data sets were generated
The following previously published data sets were used
    1. Neale et al
    (2018) UK Biobank - Curated
    https://docs.google.com/spreadsheets/d/1kvPoupSzsSFBNSztMzl04xMoSC3Kcx3CrjVf4yBmESU/edit#gid=227859291.
    1. Londsdale et al
    (2013) GTEX
    dbGaP accession number phs000424.vN.pN.

Article and author information

Author details

  1. Alber Aqil

    Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6784-6495
  2. Leo Speidel

    Genetics Institute, University College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Pavlos Pavlidis

    Institute of Computer Science (ICS), Foundation for Research and Technology Hellas, Heraklion, Greece
    Competing interests
    The authors declare that no competing interests exist.
  4. Omer Gokcumen

    Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, United States
    For correspondence
    gokcumen@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4371-679X

Funding

National Science Foundation (2123284)

  • Omer Gokcumen

Sir Henry Wellcome Fellowship (220457/Z/20/Z)

  • Leo Speidel

Wellcome Trust

  • Alber Aqil

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

Ethics

Human subjects: This study investigated variation in previously published anonymized genome data from the 1000 Genomes Project.

Copyright

© 2023, Aqil et al.

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.

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  1. Alber Aqil
  2. Leo Speidel
  3. Pavlos Pavlidis
  4. Omer Gokcumen
(2023)
Balancing selection on genomic deletion polymorphisms in humans
eLife 12:e79111.
https://doi.org/10.7554/eLife.79111

Share this article

https://doi.org/10.7554/eLife.79111

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