Common and low-frequency variants associated with genome-wide recombination rate

Journal name:
Nature Genetics
Volume:
46,
Pages:
11–16
Year published:
DOI:
doi:10.1038/ng.2833
Received
Accepted
Published online

Abstract

Meiotic recombination contributes to genetic diversity by yielding new combinations of alleles. Individuals vary with respect to the genome-wide recombination counts in their gametes. Exploiting data resources in Iceland, we compiled a data set consisting of 35,927 distinct parents and 71,929 parent-offspring pairs. Within this data set, we called over 2.2 million recombination events and imputed variants with sequence-level resolution from 2,261 whole genome–sequenced individuals into the parents to search for variants influencing recombination rate. We identified 13 variants in 8 regions that are associated with genome-wide recombination rate, 8 of which were previously unknown. Three of these variants associate with male recombination rate only, seven variants associate with female recombination rate only and three variants affect both. Two are low-frequency variants with large effects, one of which is estimated to increase the male and female genetic maps by 111 and 416 cM, respectively. This variant, located in an intron, would not be found by exome sequencing.

At a glance

Figures

  1. Telomeric region of chromosome 4 harboring four separate variants influencing genome-wide recombination rate.
    Figure 1: Telomeric region of chromosome 4 harboring four separate variants influencing genome-wide recombination rate.
  2. Chromosome-specific effects.
    Figure 2: Chromosome-specific effects.

    Shown are estimates of standardized effects. The calculation of the corresponding 95% confidence intervals is described in the Online Methods. Depending on whether the standardized effect is above or below 1, the effect on a chromosome is either above or below average, with the genetic length of the chromosome taken into account. A negative effect would mean that the effect on the chromosome has an opposite sign compared to the effect of the predictor or variant on the rest of the genome.

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References

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Author information

Affiliations

  1. deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.

    • Augustine Kong,
    • Gudmar Thorleifsson,
    • Michael L Frigge,
    • Gisli Masson,
    • Daniel F Gudbjartsson,
    • Rasmus Villemoes,
    • Stefania B Olafsdottir,
    • Unnur Thorsteinsdottir &
    • Kari Stefansson
  2. Faculty of Physical Sciences, School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.

    • Augustine Kong &
    • Daniel F Gudbjartsson
  3. Faculty of Medicine, University of Iceland, Reykjavik, Iceland.

    • Erna Magnusdottir,
    • Unnur Thorsteinsdottir &
    • Kari Stefansson

Contributions

A.K. and K.S. planned and directed the research. A.K. and G.T. wrote the first draft of the paper and, with K.S., M.L.F. and U.T., wrote most of the final version. Phasing was performed by D.F.G. and M.L.F., assisted by software from R.V., which called the recombination events. D.F.G. and G.M. processed the whole-genome sequencing data and performed imputation. G.T. performed the initial association analyses and also carried out the literature search for associated genes. A.K. performed most of the final analyses and calculations, including the study of chromosome-specific effects and the decomposition of variance. S.B.O. assisted in the imputation of the PRDM9 zinc-finger polymorphism, and E.M. carried out the investigation involving Encyclopedia of DNA Elements (ENCODE) data.

Competing financial interests

A.K., G.T., M.L.F., G.M., D.F.G., R.V., S.B.O., U.T. and K.S. are employees of deCODE Genetics/Amgen, Inc.

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    Supplementary Note, Supplementary Tables 1–9 and Supplementary Figures 1 and 2

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