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QST–FST comparisons: evolutionary and ecological insights from genomic heterogeneity

Nature Reviews Genetics volume 14, pages 179–190 (2013)Cite this article

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Key Points

  • Comparison of divergence in quantitative traits (QST) with divergence in neutral molecular markers (FST) allows the identification of trait divergence caused by natural selection, as opposed to genetic drift.

  • Substantial conceptual, theoretical and methodological improvements to the QST–FST approach have been achieved in recent years, and the number of studies using the QST–FST approach has increased exponentially.

  • QST–FST comparisons have uncovered widespread genomic heterogeneity and adaptive differentiation in a wide range of taxa and traits.

  • The QST–FST method is still underused in 'omics' contexts, in which it may be useful for identifying evolutionary significance in large data sets in the absence of evolutionary models.

Abstract

Comparative studies of the divergence of quantitative traits and neutral molecular markers, known as QST–FST comparisons, provide a means for researchers to distinguish between natural selection and genetic drift as causes of population differentiation in complex polygenic traits. The use of QST–FST comparisons has increased rapidly in the last few years, highlighting the utility of this approach for addressing a wide range of questions that are relevant to evolutionary and ecological genetics. These studies have also provided lessons for the design of future QST–FST comparisons. Methods based on the QST–FST approach could also be used to analyse various types of 'omics' data in new and revealing ways.

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Figure 1: QST is a highly flexible index that is useful for addressing diverse biological questions.
Figure 2: Comparison of mean QST and FST estimates across published studies.
Figure 3: Inferring selection on gene expression.

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Acknowledgements

We thank M. Karhunen for helpful comments on the manuscript. Financial support was provided by the Academy of Finland (grants 250435 to J.M., 252597 to T.L. and 259944 to R.J.S.M.), the Finnish Cultural Foundation (grant to R.J.S.M.) and the Landesoffensive zur Entwicklung wissenschaftlich-ökonomischer Exzellenz (LOEWE) of the state Hesse in Germany through the Biodiversity and Climate Research Centre (Bik-F) in Frankfurt am Main (to R.B.O.).

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Authors and Affiliations

  1. Department of Biosciences, Ecological Genetics Research Unit, PO Box 65, FI-00014 University of Helsinki, Finland.

    Tuomas Leinonen, R. J. Scott McCairns & Juha Merilä

  2. Biodiversity and Climate Research Centre, Frankfurt, D-60325, Germany.

    Robert B. O'Hara

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  1. Tuomas Leinonen
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  2. R. J. Scott McCairns
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Correspondence to Juha Merilä.

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Supplementary information

Supplementary information S1 (table)

Details (data and references) of the studies on which figure 2 is based. (PDF 470 kb)

Glossary

Genetic drift

Random change in allele frequencies due to stochastic factors.

Deme

A group of individuals that actively interbreed and share a common gene pool.

Directional selection

Selection that favours the extreme phenotypes at one end of the distribution but disfavours those at the opposite end.

Uniform selection

Selection that favours similar phenotypes in different populations.

Stabilizing selection

Selection that eliminates both extremes and favours the intermediate phenotypes.

Additive genetic variance

(VA). The part of total genetic variance that determines the response to selection in quantitative traits. It can be modelled as allelic effects that have an additive effect on the phenotype in heterozygotes.

Common garden

An experimental setting in which individuals from different populations are reared under identical environmental conditions to standardize environmental influences on phenotypes.

Bayesian methods

Statistical methods in which the probability of a hypothesis is tested using a prior probability, which is updated whenever new data are obtained. Estimated parameters are derived from a posterior distribution.

Parametric bootstrap

A method of estimating confidence intervals from simulated data sets that are constructed from a fitted statistical model. This contrasts non-parametric bootstrapping in which estimates are derived by resampling data with replacement.

Neutral marker loci

Loci (for example, microsatellites or SNPs) that are inherited in a Mendelian manner and not influenced by selection.

Microsatellites

Short repeated sequences of DNA.

Allozyme

One of two or more enzymes that are encoded by different alleles at the same locus.

Sympatric

Species or populations that exist in the same geographical area.

Anadromous

Fish that spend most of their lives in the sea and migrate to fresh water to breed.

Quantitative trait loci

(QTLs). Segments of a chromosome affecting or linked to a quantitative trait.

Isolation by adaptation

A positive correlation between the degree of adaptive phenotypic and molecular genetic divergence among populations that is independent of the geographical distance separating the populations.

RNA-seq

High-throughput sequencing of cDNA.

Proximate–ultimate distinction

Proximate causation refers to biological functions in terms of physiological factors, whereas ultimate causation explains traits in terms of the evolutionary forces they are subjected to.

Phenomics

Large-scale phenotyping of the full set of phenotypes of individuals.

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Leinonen, T., McCairns, R., O'Hara, R. et al. QST–FST comparisons: evolutionary and ecological insights from genomic heterogeneity. Nat Rev Genet 14, 179–190 (2013). https://doi.org/10.1038/nrg3395

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