Multi-allelic major effect genes interact with minor effect QTLs to control adaptive color pattern variation in Heliconius erato

Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius sp...

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Published inPloS one Vol. 8; no. 3; p. e57033
Main Authors Papa, Riccardo, Kapan, Durrell D, Counterman, Brian A, Maldonado, Karla, Lindstrom, Daniel P, Reed, Robert D, Nijhout, H Frederik, Hrbek, Tomas, McMillan, W Owen
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 22.03.2013
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Abstract Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius species, it is still unclear exactly how many loci underlie pattern variation across the genus. To address this question for Heliconius erato, we created fifteen independent crosses utilizing the four most distinct color pattern races and analyzed color pattern segregation across a total of 1271 F2 and backcross offspring. Additionally, we used the most variable brood, an F2 cross between H. himera and the east Ecuadorian H. erato notabilis, to perform a quantitative genetic analysis of color pattern variation and produce a detailed map of the loci likely involved in the H. erato color pattern radiation. Using AFLP and gene based markers, we show that fewer major genes than previously envisioned control the color pattern variation in H. erato. We describe for the first time the genetic architecture of H. erato wing color pattern by assessing quantitative variation in addition to traditional linkage mapping. In particular, our data suggest three genomic intervals modulate the bulk of the observed variation in color. Furthermore, we also identify several modifier loci of moderate effect size that contribute to the quantitative wing pattern variation. Our results are consistent with the two-step model for the evolution of mimetic wing patterns in Heliconius and support a growing body of empirical data demonstrating the importance of major effect loci in adaptive change.
AbstractList Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius species, it is still unclear exactly how many loci underlie pattern variation across the genus. To address this question for Heliconius erato, we created fifteen independent crosses utilizing the four most distinct color pattern races and analyzed color pattern segregation across a total of 1271 F2 and backcross offspring. Additionally, we used the most variable brood, an F2 cross between H. himera and the east Ecuadorian H. erato notabilis, to perform a quantitative genetic analysis of color pattern variation and produce a detailed map of the loci likely involved in the H. erato color pattern radiation. Using AFLP and gene based markers, we show that fewer major genes than previously envisioned control the color pattern variation in H. erato. We describe for the first time the genetic architecture of H. erato wing color pattern by assessing quantitative variation in addition to traditional linkage mapping. In particular, our data suggest three genomic intervals modulate the bulk of the observed variation in color. Furthermore, we also identify several modifier loci of moderate effect size that contribute to the quantitative wing pattern variation. Our results are consistent with the two-step model for the evolution of mimetic wing patterns in Heliconius and support a growing body of empirical data demonstrating the importance of major effect loci in adaptive change.
Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius species, it is still unclear exactly how many loci underlie pattern variation across the genus. To address this question for Heliconius erato , we created fifteen independent crosses utilizing the four most distinct color pattern races and analyzed color pattern segregation across a total of 1271 F2 and backcross offspring. Additionally, we used the most variable brood, an F2 cross between H. himera and the east Ecuadorian H. erato notabilis , to perform a quantitative genetic analysis of color pattern variation and produce a detailed map of the loci likely involved in the H. erato color pattern radiation. Using AFLP and gene based markers, we show that fewer major genes than previously envisioned control the color pattern variation in H. erato . We describe for the first time the genetic architecture of H. erato wing color pattern by assessing quantitative variation in addition to traditional linkage mapping. In particular, our data suggest three genomic intervals modulate the bulk of the observed variation in color. Furthermore, we also identify several modifier loci of moderate effect size that contribute to the quantitative wing pattern variation. Our results are consistent with the two-step model for the evolution of mimetic wing patterns in Heliconius and support a growing body of empirical data demonstrating the importance of major effect loci in adaptive change.
Audience Academic
Author McMillan, W Owen
Reed, Robert D
Nijhout, H Frederik
Maldonado, Karla
Lindstrom, Daniel P
Papa, Riccardo
Hrbek, Tomas
Kapan, Durrell D
Counterman, Brian A
AuthorAffiliation 5 Department of Biology, University of Guam, Mangilao, Guam
3 Center for Conservation and Research Training, Pacific Biosciences Research Center, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
Oxford Brookes University, United Kingdom
2 Department of Entomology and Center for Comparative Genomics, California Academy of Sciences, San Francisco, California, United States of America
4 Department of Biological Sciences, Mississippi State University, Mississippi State, Mississippi, United States of America
6 Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, United States of America
1 Department of Biology and Center for Applied Tropical Ecology and Conservation, University of Puerto Rico, Rio Piedras, Puerto Rico
7 Department of Biology, Duke University, Durham, North Carolina, United States of America
8 Biology Department, Institute of Biological Sciences, Federal University of Amazonas, Manaus, AM, Brazil
9 Smithsonian Tropical Researc
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ContentType Journal Article
Copyright COPYRIGHT 2013 Public Library of Science
2013 Papa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2013 Papa et al 2013 Papa et al
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– notice: 2013 Papa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Competing Interests: The authors have declared that no competing interests exist.
Provided fundamental edits to the manuscript: DDK RDR HFN WOM. Conceived and designed the experiments: DDK WOM. Performed the experiments: RP DDK KM WOM. Analyzed the data: RP TH. Contributed reagents/materials/analysis tools: BAC DPL RDR HFN. Wrote the paper: RP.
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Snippet Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work...
Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work...
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StartPage e57033
SubjectTerms Adaptive control
Agriculture
Alleles
Amplified fragment length polymorphism
Analysis
Animals
Biology
Butterflies
Butterflies & moths
Butterflies - genetics
Butterflies - metabolism
Chromosome Mapping
Color
Ecology
Empirical analysis
Evolution
Evolution & development
Gene mapping
Genes
Genetic analysis
Genetic crosses
Genetic research
Genomics
Homology
Insect Proteins - genetics
Insect Proteins - metabolism
Loci
Offspring
Pigmentation - genetics
Pigmentation - physiology
Quantitative genetics
Quantitative Trait Loci
Radiation
Science
Variation
Wings, Animal - metabolism
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Title Multi-allelic major effect genes interact with minor effect QTLs to control adaptive color pattern variation in Heliconius erato
URI https://www.ncbi.nlm.nih.gov/pubmed/23533571
https://www.proquest.com/docview/1330893509/abstract/
https://search.proquest.com/docview/1321336894
https://pubmed.ncbi.nlm.nih.gov/PMC3606360
https://doaj.org/article/998cb9ec1c874bafb00efa87fd94d451
http://dx.doi.org/10.1371/journal.pone.0057033
Volume 8
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