The rate of meiotic gene conversion varies by sex and age

Subjects

An Author Correction to this article was published on 20 September 2018

This article has been updated

Abstract

Meiotic recombination involves a combination of gene conversion and crossover events that, along with mutations, produce germline genetic diversity. Here we report the discovery of 3,176 SNP and 61 indel gene conversions. Our estimate of the non-crossover (NCO) gene conversion rate (G) is 7.0 for SNPs and 5.8 for indels per megabase per generation, and the GC bias is 67.6%. For indels, we demonstrate a 65.6% preference for the shorter allele. NCO gene conversions from mothers are longer than those from fathers, and G is 2.17 times greater in mothers. Notably, G increases with the age of mothers, but not the age of fathers. A disproportionate number of NCO gene conversions in older mothers occur outside double-strand break (DSB) regions and in regions with relatively low GC content. This points to age-related changes in the mechanisms of meiotic gene conversion in oocytes.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The study design and method used for detecting gene conversions.
Figure 2: The NCO gene conversion rate, G.
Figure 3: NCO gene conversion rate G as a function of the GC content of the neighboring 100 bp.
Figure 4: Maternal age increase in complex crossovers.

Change history

  • 20 September 2018

    In the version of this article published, statements about the impact of insertions and deletions on gene conversions were incorrect. We reported a bias toward deletions, whereas in fact the bias was toward insertions. We are deeply indebted to Laurent Duret and Brice Letcher for noticing this mistake in our manuscript. Full details can be found in the correction notice.

References

  1. 1

    Sun, H., Treco, D., Schultes, N.P. & Szostak, J.W. Double-strand breaks at an initiation site for meiotic gene conversion. Nature 338, 87–90 (1989).

    CAS  PubMed  Article  Google Scholar 

  2. 2

    Lam, I. & Keeney, S. Mechanism and regulation of meiotic recombination initiation. Cold Spring Harb. Perspect. Biol. 7, a016634 (2014).

    PubMed  Article  CAS  Google Scholar 

  3. 3

    Baudat, F. et al. PRDM9 is a major determinant of meiotic recombination hotspots in humans and mice. Science 327, 836–840 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. 4

    Haber, J. Genome Stability (Garland Science, 2013).

  5. 5

    McMahill, M.S., Sham, C.W. & Bishop, D.K. Synthesis-dependent strand annealing in meiosis. PLoS Biol. 5, e299 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  6. 6

    Jeffreys, A.J. & May, C.A. Intense and highly localized gene conversion activity in human meiotic crossover hot spots. Nat. Genet. 36, 151–156 (2004).

    CAS  PubMed  Article  Google Scholar 

  7. 7

    Odenthal-Hesse, L., Berg, I.L., Veselis, A., Jeffreys, A.J. & May, C.A. Transmission distortion affecting human noncrossover but not crossover recombination: a hidden source of meiotic drive. PLoS Genet. 10, e1004106 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  8. 8

    Cole, F. et al. Mouse tetrad analysis provides insights into recombination mechanisms and hotspot evolutionary dynamics. Nat. Genet. 46, 1072–1080 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. 9

    Allers, T. & Lichten, M. Differential timing and control of noncrossover and crossover recombination during meiosis. Cell 106, 47–57 (2001).

    CAS  Article  Google Scholar 

  10. 10

    Szostak, J.W., Orr-Weaver, T.L., Rothstein, R.J. & Stahl, F.W. The double-strand-break repair model for recombination. Cell 33, 25–35 (1983).

    CAS  PubMed  Article  Google Scholar 

  11. 11

    Galtier, N., Piganeau, G., Mouchiroud, D. & Duret, L. GC-content evolution in mammalian genomes: the biased gene conversion hypothesis. Genetics 159, 907–911 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Glémin, S. et al. Quantification of GC-biased gene conversion in the human genome. Genome Res. 25, 1215–1228 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  13. 13

    Duret, L. & Galtier, N. Biased gene conversion and the evolution of mammalian genomic landscapes. Annu. Rev. Genomics Hum. Genet. 10, 285–311 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  14. 14

    Narasimhan, V.M. et al. A direct multi-generational estimate of the human mutation rate from autozygous segments seen in thousands of parentally related individuals. Preprint at bioRxiv http://dx.doi.org/10.1101/059436 (2016).

  15. 15

    Palamara, P.F. et al. Leveraging distant relatedness to quantify human mutation and gene-conversion rates. Am. J. Hum. Genet. 97, 775–789 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16

    Lachance, J. & Tishkoff, S.A. Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles. Am. J. Hum. Genet. 95, 408–420 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  17. 17

    Kong, A. et al. Fine-scale recombination rate differences between sexes, populations and individuals. Nature 467, 1099–1103 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. 18

    Kong, A. et al. A high-resolution recombination map of the human genome. Nat. Genet. 31, 241–247 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  19. 19

    Kong, A. et al. Recombination rate and reproductive success in humans. Nat. Genet. 36, 1203–1206 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20

    Williams, A.L. et al. Non-crossover gene conversions show strong GC bias and unexpected clustering in humans. eLife 4, e04637 (2015).

    PubMed Central  Article  PubMed  Google Scholar 

  21. 21

    Guillon, H., Baudat, F., Grey, C., Liskay, R.M. & de Massy, B. Crossover and noncrossover pathways in mouse meiosis. Mol. Cell 20, 563–573 (2005).

    CAS  PubMed  Article  Google Scholar 

  22. 22

    Webb, A.J., Berg, I.L. & Jeffreys, A. Sperm cross-over activity in regions of the human genome showing extreme breakdown of marker association. Proc. Natl. Acad. Sci. USA 105, 10471–10476 (2008).

    CAS  PubMed  Article  Google Scholar 

  23. 23

    Gudbjartsson, D.F. et al. Sequence variants from whole genome sequencing a large group of Icelanders. Sci. Data 2, 150011 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  24. 24

    Pratto, F. et al. Recombination initiation maps of individual human genomes. Science 346, 1256442 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  25. 25

    Kong, A. et al. Common and low-frequency variants associated with genome-wide recombination rate. Nat. Genet. 46, 11–16 (2014).

    CAS  PubMed  Article  Google Scholar 

  26. 26

    Padhukasahasram, B. & Rannala, B. Meiotic gene-conversion rate and tract length variation in the human genome. Eur. J. Hum. Genet. http://dx.doi.org/10.1038/ejhg.2013.30 (2013).

  27. 27

    Barrett, J.C. & Cardon, L.R. Evaluating coverage of genome-wide association studies. Nat. Genet. 38, 659–662 (2006).

    CAS  PubMed  Article  Google Scholar 

  28. 28

    Pardo-Manuel de Villena, F. & Sapienza, C. Recombination is proportional to the number of chromosome arms in mammals. Mamm. Genome 12, 318–322 (2001).

    CAS  PubMed  Article  Google Scholar 

  29. 29

    Duret, L. & Arndt, P.F. The impact of recombination on nucleotide substitutions in the human genome. PLoS Genet. 4, e1000071 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  30. 30

    Martin, H.C. et al. Multicohort analysis of the maternal age effect on recombination. Nat. Commun. 6, 7846 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31

    Myers, S., Freeman, C., Auton, A., Donnelly, P. & McVean, G. A common sequence motif associated with recombination hot spots and genome instability in humans. Nat. Genet. 40, 1124–1129 (2008).

    CAS  PubMed  Article  Google Scholar 

  32. 32

    Frazer, K.A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).

    CAS  PubMed  Article  Google Scholar 

  33. 33

    Assis, R. & Kondrashov, A.S. A strong deletion bias in nonallelic gene conversion. PLoS Genet. 8, e1002508 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34

    Leushkin, E.V. & Bazykin, G.A. Short indels are subject to insertion-biased gene conversion. Evolution 67, 2604–2613 (2013).

    PubMed  Article  Google Scholar 

  35. 35

    Gudbjartsson, D.F. et al. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet. 47, 435–444 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36

    1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  37. 37

    Handel, M.A. & Schimenti, J.C. Genetics of mammalian meiosis: regulation, dynamics and impact on fertility. Nat. Rev. Genet. 11, 124–136 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  38. 38

    Subramanian, V.V. & Bickel, S.E. Aging predisposes oocytes to meiotic nondisjunction when the cohesin subunit SMC1 is reduced. PLoS Genet. 4, e1000263 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  39. 39

    Weng, K.A., Jeffreys, C.A. & Bickel, S.E. Rejuvenation of meiotic cohesion in oocytes during prophase I is required for chiasma maintenance and accurate chromosome segregation. PLoS Genet. 10, e1004607 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  40. 40

    Leland, S. et al. Heterozygosity for a Bub1 mutation causes female-specific germ cell aneuploidy in mice. Proc. Natl. Acad. Sci. USA 106, 12776–12781 (2009).

    CAS  PubMed  Article  Google Scholar 

  41. 41

    Hodges, C.A., Revenkova, E., Jessberger, R., Hassold, T.J. & Hunt, P.A. SMC1β-deficient female mice provide evidence that cohesins are a missing link in age-related nondisjunction. Nat. Genet. 37, 1351–1355 (2005).

    CAS  PubMed  Article  Google Scholar 

  42. 42

    Nagaoka, S.I., Hassold, T.J. & Hunt, P.A. Human aneuploidy: mechanisms and new insights into an age-old problem. Nat. Rev. Genet. 13, 493–504 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43

    Campbell, C.L., Furlotte, N.A., Eriksson, N., Hinds, D. & Auton, A. Escape from crossover interference increases with maternal age. Nat. Commun. 6, 6260 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. 44

    Martini, E. et al. Genome-wide analysis of heteroduplex DNA in mismatch repair–deficient yeast cells reveals novel properties of meiotic recombination pathways. PLoS Genet. 7, e1002305 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45

    Tsaponina, O. & Haber, J.E. Frequent interchromosomal template switches during gene conversion in S. cerevisiae. Mol. Cell 55, 615–625 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  46. 46

    de Boer, E., Jasin, M. & Keeney, S. Local and sex-specific biases in crossover vs. noncrossover outcomes at meiotic recombination hot spots in mice. Genes Dev. 29, 1721–1733 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47

    Wong, W.S.W. et al. New observations on maternal age effect on germline de novo mutations. Nat. Commun. 7, 10486 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48

    Goldmann, J.M. et al. Parent-of-origin-specific signatures of de novo mutations. Nat. Genet. 48, 935–939 (2016).

    CAS  PubMed  Article  Google Scholar 

  49. 49

    Kong, A. et al. Rate of de novo mutations and the importance of father's age to disease risk. Nature 488, 471–475 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. 50

    Efron, B. & Tibshirani, R.J. An Introduction to the Bootstrap (CRC Press, 1994).

  51. 51

    Ihaka, R. & Gentleman, R.R. A language for data analysis and graphics. J. Comput. Graph. Stat. 5, 299–314 (1996).

    Google Scholar 

  52. 52

    van Rossum, G. & Drake, F.L. PYTHON Reference Manual (Centrum voor Wiskunde en Informatica, 1995).

Download references

Acknowledgements

This work was supported in part by the NIH (NIDA) (R01-DA017932).

Author information

Affiliations

Authors

Contributions

B.V.H., D.F.G. and K.S. designed the experiments. B.V.H. wrote the first draft of the manuscript. B.V.H., M.T.H., B.K., U.S., P.S., A.H., A.K., D.F.G. and K.S. reviewed and contributed to subsequent drafts of the manuscript. B.V.H., M.T.H. and A.G. implemented the methodology. B.V.H., M.T.H. and B.K. prepared tables and figures. Aslaug Jonasdottir and Adalbjorg Jonasdottir performed the Sanger sequencing. U.T. oversaw the operations of the genotyping facility. B.V.H., M.T.H., F.Z., G.T., A.G. and G.M. processed the data. B.V.H. and M.T.H. analyzed the data. All authors contributed to the final version of the manuscript.

Corresponding authors

Correspondence to Bjarni V Halldorsson or Kari Stefansson.

Ethics declarations

Competing interests

All authors are employees of deCODE Genetics/Amgen.

Integrated supplementary information

Supplementary Figure 1 Repair mechanisms of DNA double-strand breaks.

Small gray boxes show regions where heteroduplex DNA is formed. DSBs are resolved via either synthesis-dependent strand annealing (SDSA) or double Holliday junctions (dHjs). dHjs result in either dissolution or resolution; resolution results in either crossover (CO) or non-crossover (NCO).

Supplementary Figure 2 Odds ratio of an NCO gene conversion being in a male DSB region and a crossover recombination hotspot as a function of mother’s age in the chip data set.

Error bars, 95% confidence intervals. The dotted lines represent linear models.

Supplementary Figure 3 Crossover recombination rate of NCO gene conversions in the chip data set.

Error bars, 95% confidence intervals. The dotted line represents a linear model.

Supplementary Figure 4 MPPs by local GC content.

(a) Distribution of SNP MPPs by local GC content. (b) Probability that a SNP MPP is in a DSB region by local GC content.

Supplementary Figure 5 Number of verified gene-converted MPPs per event as a function of mother’s age in the chip data set.

Error bars, 95% confidence intervals. The dotted line represents a linear model.

Supplementary Figure 6 Detection of complex crossover gene conversions.

Two equally parsimonious locations exist to place a crossover recombination. The navy blue haplotype represents the background haplotype, and the cyan haplotype represents the other haplotype. The location of gene conversion depends on the assignment of the background haplotype.

Supplementary Figure 7 Schematic overview of the algorithm for detecting gene conversions.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Tables 1–10 and Supplementary Note. (PDF 2505 kb)

Supplementary Data

Gene conversion MPPs. Data set of all gene conversion MPPs found and neighboring MPPs. (XLSX 1263 kb)

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Halldorsson, B., Hardarson, M., Kehr, B. et al. The rate of meiotic gene conversion varies by sex and age. Nat Genet 48, 1377–1384 (2016). https://doi.org/10.1038/ng.3669

Download citation

Further reading

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing