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Pleiotropic scaling and QTL data

Author

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  • Joachim Hermisson

    (* Fakultät für Mathematik and Max F. Perutz Laboratories, University of Vienna, Nordbergstr. 15, 1090 Vienna, Austria. joachim.hermisson@univie.ac.at)

  • Alistair P. McGregor

    († Institut für Populationsgenetik, Veterinärmedizinische Universität Wien, Veterinärpl. 1, 1210 Vienna, Austria)

Abstract

Arising from: G. P. Wagner et al. Nature 452, 470–472 (2008)10.1038/nature06756 ; Wagner et al. reply Wagner et al.1 have recently introduced much-needed data to the debate on how complexity of the genotype–phenotype map affects the distribution of mutational effects. They used quantitative trait loci (QTLs) mapping analysis of 70 skeletal characters in mice2 and regressed the total QTL effect on the number of traits affected (level of pleiotropy). From their results they suggest that mutations with higher pleiotropy have a larger effect, on average, on each of the affected traits—a surprising finding that contradicts previous models3,4,5,6,7. We argue that the possibility of some QTL regions containing multiple mutations, which was not considered by the authors, introduces a bias that can explain the discrepancy between one of the previously suggested models and the new data.

Suggested Citation

  • Joachim Hermisson & Alistair P. McGregor, 2008. "Pleiotropic scaling and QTL data," Nature, Nature, vol. 456(7222), pages 3-3, December.
    • Handle: RePEc:nat:nature:v:456:y:2008:i:7222:d:10.1038_nature07452
    DOI: 10.1038/nature07452
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