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The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

A Single Amino Acid Mutation Contributes to Adaptive Beach Mouse Color Pattern

Open access
Hoekstra, Hopi E., Hirschmann, Rachel J., Bundey, Richard A., Insel, Paul A., Crossland, Janet P.·2006·Science

Abstract

Natural populations of beach mice exhibit a characteristic color pattern, relative to their mainland conspecifics, driven by natural selection for crypsis. We identified a derived, charge-changing amino acid mutation in the melanocortin-1 receptor ( Mc1r ) in beach mice, which decreases receptor function. In genetic crosses, allelic variation at Mc1r explains 9.8% to 36.4% of the variation in seven pigmentation traits determining color pattern. The derived Mc1r allele is present in Florida's Gulf Coast beach mice but not in Atlantic coast mice with similar light coloration, suggesting that different molecular mechanisms are responsible for convergent phenotypic evolution. Here, we link a single mutation in the coding region of a pigmentation gene to adaptive quantitative variation in the wild.

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Crossref · 10.1126/science.1126121

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Metadata

Authors
Hoekstra, H. E., Hirschmann, R. J., Bundey, R. A., Insel, P. A., & Crossland, J. P.
Venue
Science
Published
2006-07-07
Volume
313
Issue
5783
Pages
101-104
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2062935524
Cited by
716
References
2
FWCI
15.85
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A Single Amino Acid Mutation Contributes to Adaptive Beach Mouse Color Pattern. https://app.cochat.ai/papers/10.1126/science.1126121
The paper
Hoekstra, H. E., Hirschmann, R. J., Bundey, R. A., Insel, P. A., & Crossland, J. P. (2006). A Single Amino Acid Mutation Contributes to Adaptive Beach Mouse Color Pattern. Science. https://doi.org/10.1126/science.1126121

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.