Selection experiments play an increasingly important role in comparative and evolutionary physiology. However, selection experiments can be limited by relatively low statistical power, in part because replicate line is the experimental unit for analyses of direct or correlated responses (rather than number of individuals measured). One way to increase the ability to detect correlated responses is through a meta-analysis of studies for a given trait across multiple generations. To demonstrate this, we applied meta-analytic techniques to two traits (body mass and heart ventricle mass, with body mass as a covariate) from a long-term artificial selection experiment for high voluntary wheel-running behavior. In this experiment, all four replicate High Runner (HR) lines reached apparent selection limits around generations 17–27, running approximately 2.5- to 3-fold more revolutions per day than the four non-selected Control (C) lines. Although both traits would also be expected to change in HR lines (relative heart size expected to increase, expected direction for body mass is less clear), their statistical significance has varied, despite repeated measurements. We compiled information from 33 unique studies and calculated a measure of effect size (Pearson's R). Our results indicate that, despite a lack of statistical significance in most generations, HR mice have evolved larger hearts and smaller bodies relative to controls. Moreover, plateaus in effect sizes for both traits coincide with the generational range during which the selection limit for wheel-running behavior was reached. Finally, since reaching the selection limit, absolute effect sizes for body mass and heart ventricle mass have become smaller (i.e. closer to 0).

Author contributions

Conceptualization: N.E.S., T.G.; Funding acquisition: T.G.; Resources: T.G.; Data curation: N.E.S.; Formal analysis: N.E.S.; Investigation: N.E.S.; Methodology: N.E.S.; Project administration: N.E.S.; Software: N.E.S., T.G.; Supervision: T.G.; Validation: N.E.S.; Visualization: N.E.S.; Writing – original draft: N.E.S.; Writing – review & editing: N.E.S., T.G.

Funding

This work was supported by National Science Foundation grant IOS-2038528.

Data availability

All relevant data can be found within the article and its supplementary information.

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