Climate-driven population divergence in sex-determining systems

Journal name:
Nature
Volume:
468,
Pages:
436–438
Date published:
DOI:
doi:10.1038/nature09512
Received
Accepted
Published online

Sex determination is a fundamental biological process, yet its mechanisms are remarkably diverse1, 2. In vertebrates, sex can be determined by inherited genetic factors or by the temperature experienced during embryonic development2, 3. However, the evolutionary causes of this diversity remain unknown. Here we show that live-bearing lizards at different climatic extremes of the species’ distribution differ in their sex-determining mechanisms, with temperature-dependent sex determination in lowlands and genotypic sex determination in highlands. A theoretical model parameterized with field data accurately predicts this divergence in sex-determining systems and the consequence thereof for variation in cohort sex ratios among years. Furthermore, we show that divergent natural selection on sex determination across altitudes is caused by climatic effects on lizard life history and variation in the magnitude of between-year temperature fluctuations. Our results establish an adaptive explanation for intra-specific divergence in sex-determining systems driven by phenotypic plasticity and ecological selection, thereby providing a unifying framework for integrating the developmental, ecological and evolutionary basis for variation in vertebrate sex determination.

At a glance

Figures

  1. Experimental effects of thermal conditions on sex ratio and birth date.
    Figure 1: Experimental effects of thermal conditions on sex ratio and birth date.

    Sex ratio = male/(male+female). Poor thermal condition during gestation (filled squares) results in delayed birth compared to good thermal condition (open squares), with a corresponding significant effect on offspring sex in lowland (a) but not highland (b) females. Error bars are s.e.m. Logistic regression with the proportion of males as a dependent variable and treatment and birth date (measured in days from birth) as predictors: birth date for lowland population χ2 = 20.66, P = 0.0001, Nfemales = 13, 18 and for highland population, χ2 = 0.15, P = 0.70, Nfemales = 31, 24.

  2. Life-history and temperature differences between lowland and highland populations of N.[thinsp]ocellatus.
    Figure 2: Life-history and temperature differences between lowland and highland populations of N.ocellatus.

    a, Probability of maturation (±s.e.m.) at a given age for female offspring in relation to their timing of birth (E, early; M, intermediate; L, late) for lowland (red) and highland (blue) populations. Estimates based on field data from 2000–2007 (details provided in the Supplementary Information). b, Annual variation in mean maximum temperature experienced during the first half of gestation for lowland (red) and highland (blue) populations.

  3. Evolutionary simulation results with genetic sex determination as ancestral state.
    Figure 3: Evolutionary simulation results with genetic sex determination as ancestral state.

    Upper panels, lowland parameter settings; lower panels, highland parameter settings. a and d, Population distributions of allelic values at threshold locus changing over time. We note branching in d for highland parameter settings, resulting in a novel sex-determining locus: males are ‘homozygous’ for alleles causing low thresholds and females ‘heterozygous’ for low and high threshold alleles. b and e, Evolved average reaction norm for offspring sex ratio as a function of developmental temperature. The vertical dotted line is the average temperature experienced by natural populations. c and f, Predicted (from evolved reaction norm; line) and observed (natural populations; squares) cohort sex ratios for annual mean maximum temperature in the wild.

References

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Author information

Affiliations

  1. Theoretical Biology Group, University of Groningen, PO Box 14, 9750 AA Haren, the Netherlands

    • Ido Pen,
    • Barbara Feldmeyer &
    • Anna Harts
  2. Edward Grey Institute, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK

    • Tobias Uller
  3. School of Zoology, Private Bag 5, University of Tasmania, Hobart 7001, Tasmania, Australia

    • Geoffrey M. While &
    • Erik Wapstra
  4. Present address: Biodiversity and Climate Research Centre (BiK-F), Siesmayerstrasse 70A, D-60325 Frankfurt and Main, Germany.

    • Barbara Feldmeyer

Contributions

T.U., I.P. and E.W. initiated, planned and coordinated the project; E.W. collected field and experimental data, assisted by G.M.W.; T.U., G.M.W. and I.P. analysed data and generated parameter estimates for the model; I.P., B.F., A.H. and T.U. constructed the model and analysed its outcome; T.U. and I.P. wrote the paper with input from all other authors.

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The authors declare no competing financial interests.

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Supplementary information

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  1. Supplementary Information (1.6M)

    This file contains Supplementary Text, additional references, Supplementary Tables 1-3 and Supplementary Figures 1-6 with legends.

Additional data