DOI: 10.5061/dryad.7h44j104b
title: Phylogeny, systematics and evolution of mimicry patterns in Neotropical limenitidine butterflies

description: The Neotropical butterfly genus Adelpha Hübner exhibits remarkable species
 diversity and striking convergence in wing colour patterns, potentially
 explained by mimicry, making it an exceptional model for exploring trait
 evolution and its relationship with speciation. To date, unresolved
 phylogenetic relationships hinder a comprehensive understanding of the
 evolutionary biology of the genus. Using a novel multi-marker dataset
 combining one mitochondrial and 15 nuclear gene fragments, we generate the
 most comprehensive phylogeny of the genus Adelpha to revisit its
 systematics and investigate the evolution of mimicry colour patterns. Our
 data set encompasses 83 of the 87 known extant species and six Limenitis
 species that were recently excluded from Adelpha (134 of c. 160 subspecies
 in total), collectively displaying 14 distinct mimicry patterns. We
 provide conclusive evidence that corroborates previous work on the
 polyphyly of Adelpha as historically conceived, and describe the genus
 Adelphina Páez & Willmott n. gen. to stabilize the nomenclature,
 both genera representing Neotropical limenitidines. The comprehensive
 phylogeny provided in this study lays a solid foundation for future
 research into the processes driving diversification within these species
 interacting through mimicry. Ancestral character state reconstruction
 reveals the gradual evolution of the mimicry pattern. The more common
 mimicry pattern IPHICLUS (forewing with orange subapical spot and white
 band) is inferred as ancestral, but repeated convergent evolution is also
 recovered. Evolutionary convergence is also observed for the second most
 abundant mimicry pattern, COCALA (orange-white banded) mimicry patterns.
 Increased rates of mimicry pattern evolution are also found toward the
 equator. These results underscore the complexity of mimicry evolution in
 the Neotropical limenitidines, i.e., Adelpha and Adelphina, emphasizing
 the need to explore its interplay with other biotic and abiotic
 factors. 
description: # **Data from: Phylogeny, systematics and evolution of mimicry patterns in
 Neotropical limenitidine butterflies** Dataset DOI:
 [10.5061/dryad.7h44j104b](10.5061/dryad.7h44j104b) ## Description of the
 data and file structure This README file was generated on 14-03-2025 by
 Erika Paez Vargas This dataset, integral to our research paper, contains
 crucial data for understanding our key findings. It includes phylogenetic
 analysis data and results, raw data used to assess mimicry pattern
 evolution along with their R scripts, as well as supplementary materials
 and appendix data. ### Files and variables Below is a summary of the
 included files: ##### **1. Phylogenetic and dating analyses** Folder:
 Paez_et_al_SYEN_PhylogeneticAnalyses_R1.zip This folder contains the
 dataset and results of the topological tests, molecular phylogenetic and
 dating analyses. * AU_test folder: the files and results to perform
 topological tests and ML analyses under IQ-TREE (v3.0.1). - BEAST folder:
 the files to perform molecular dating analyses (using Bayesian relaxed
 clocks) using BEAST software package (v1.10.4), and results.  - IQTREE -
 gene tree analyses folder: files to perform molecular phylogenetic
 analyses per gene under IQTREE ( IQ-TREE v3.0.1), and tree file results
 for 1 mitochondrial gene and 15 nuclear genes. - IQTREE2 - unconstrained
 folder: files to perform ML analyses under IQTREE (v2.2.2.7) with all
 subspecies included. ##### 2. **Reconstruction of the evolution of mimicry
 wing colour patterns** Folder:
 Paez_et_al_SYEN_mimpatt_evol_datasets_R1.zip This folder contains the raw
 datasets and the tree file to perform all the analyses for the mimicry
 pattern evolution. * Adelpha.pattern_list.txt: raw data for the ancestral
 state reconstruction analysis. - Adelpha_Adelphina_Limenitis.txt: raw data
 for the ancestral state reconstruction analysis (Limenitidinae). -
 Adelpha_node_states.txt: raw data for the ancestral state reconstruction
 analysis (Adelpha + Adelphina) - lowland_Adelpha_node_states.txt: raw data
 for the ancestral state reconstruction analysis (only Adelpha) -
 Adelpha_phylo.nwk: phylogenetic tree used in the ancestral state
 reconstruction analysis. - Adelpha_tip_data.txt: raw data for
 the ancestral state reconstruction analysis. -
 Adelpha_macroecol_traits.txt: raw data for the macroecological traits
 analyses using Phylogenetic Generalized Linear Models (PGLS). -
 Adelpha_tip_data_Dstat.txt: raw data for the phylogenetic signal analysis
 (D-statistic). - Adelpha_traits_plgs_2024: It summarizes ecological and
 evolutionary traits of various species in a dataset, with each row
 representing a different species (e.g., A.abia, A.abyla, etc.). This can
 be used to explore patterns in mimicry, niche breadth, geographic
 distribution, and evolutionary rates across species. ##### 3. **Electronic
 supplementary materials** Folder: Paez_et_al_SYEN_ESM_0309 * Figure
 S1: Estimation of ancestral character states for mimicry colour patterns
 in *Adelpha + Adelphina + Limenitis* showed that IPHICLUS colour pattern
 was most likely to be the state of the common ancestor of the Neotropical
 limenitidines *Adelpha* and *Adelphina* species. * Figure S2: Estimation
 of ancestral character states for mimicry colour patterns only in
 *Adelpha* (lowland) species showed that IPHICLUS colour pattern was most
 likely to be the state of the common ancestor. * Figure S3: A comparison
 of tree topologies from recent molecular phylogenetic studies, simplified
 to clades relevant to generic classification. - Table S1: List of
 sequences including Voucher and GenBank accession numbers for the sixteen
 gene fragments. * Table S2: Partition scheme inferred by the Modelfinder
 analysis of the specimen-level dataset. * Table S3: Results of the
 AU-tests carried out with IQ-TREE. * Table S4: Results for mimicry rate
 evolution analyses. * Table S5: Summary of relevant limenitidine taxa
 included within recent molecular phylogenetic studies, a suggested
 generic-level classification, type species of genera, and inferred ages of
 genera from the present study. ##### **4. Appendix files** Folder:
 Paez_et_al_SYEN__Appendix_R1.zip This folder contains appendix files: *
 Appendix S1: Details on generation of the transcriptomic data * Appendix
 S2: Explanation for the calculation of the distribution maps for *Adelpha*
 species and macroecological traits. * Appendix S3: Macroecological traits
 raw dataset.; ## Code/software All mimicry pattern evolution analyses were
 performed using R software. 1. **Programs needed:** * BayesTraits v4.0
 Pagel, M., Meade, A., & Barker, D. (2004). Bayesian estimation of
 ancestral character states on phylogenies. Systematic Biology, 53(5),
 673–684. [https://doi.org/10.1080/10635150490522232](https://doi.org/10.1080/10635150490522232) * BEAST v1.10.4 Suchard, M. A., Lemey, P., Baele, G., Ayres, D. L., Drummond, A. J., & Rambaut, A. (2018). Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evolution, 4(1), vey016. * Codoncode Aligner (v3.7.1.1, CodonCode Corporation, [http://www.codoncode.com/](http://www.codoncode.com/)) * IQ-TREE v2.2.2.7 Minh, B. Q., Schmidt, H. A., Chernomor, O., Schrempf, D., Woodhams, M. D., von Haeseler, A., & Lanfear, R. (2020). IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era. Molecular Biology and Evolution, 37(5), 1530–1534. [https://doi.org/10.1093/molbev/msaa015](https://doi.org/10.1093/molbev/msaa015) * ModelFinder Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A., & Jermiin, L. S. (2017). ModelFinder: fast model selection for accurate phylogenetic estimates. Nature Methods, 14(6), 587–589. [https://doi.org/10.1038/nmeth.4285](https://doi.org/10.1038/nmeth.4285) * Sequence Capture Processor (SECAPR) pipeline ([http://htmlpreview.github.io/?https://github.com/AntonelliLab/seqcap_processor/blob/master/docs/documentation/main_doc.html](http://htmlpreview.github.io/?https://github.com/AntonelliLab/seqcap_processor/blob/master/docs/documentation/main_doc.html)) * Tracer v1.7.2 Rambaut, A., Drummond, A. J., Xie, D., Baele, G., & Suchard, M. A. (2018). Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Systematic Biology, 67(5), 901–904. [https://doi.org/10.1093/sysbio/syy032](https://doi.org/10.1093/sysbio/syy032) 2. **Analysis Scripts:** Folder: Paez_et_al_SYEN_scripts_pattern_evolution_R1.zip All anaylses were performed using R software.  * R-ASRPLOT_2025: Script for Ancestral State Reconstruction analyses of wing colour patterns * R-D_stat_2025: Script for D statistics analyses * R-PGLS_2025: Script for PGLS. wing colour pattern rates of evolution correlated to macroecological traits.  * R-TipRatesEvol_2025: Script for wing colour pattern evolution analyses  3. **Loaded packages for R scripts:** * ade4 Thioulouse J, Dray S, Dufour A, Siberchicot A, Jombart T, Pavoine S (2018). Multivariate Analysis of Ecological Data with ade4. Springer. doi:10.1007/978-1-4939-8850-1 * ape Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35(3):526–8. * caper Orme, D., Freckleton, R.P., Thomas, G.H., Petzoldt, T., Fritz, S. & Isaac, N. (2013) Caper: Comparative analyses of phylogenetics and evolution in R. R package version 0.5.2 * dplyr Wickham H, François R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data Manipulation. R package version 1.1.4, [https://CRAN.R-project.org/package=dplyr](https://CRAN.R-project.org/package=dplyr). * geiger Pennell, M. W., J. M. Eastman, G. J. Slater, J. W. Brown, J. C. Uyeda, R. G. FitzJohn, M. E. Alfaro, and L. J. Harmon {2014} geiger v2.0: an expanded suite of methods for fitting macroevolutionary models to phylogenetic trees. Bioinformatics, 30, 2216-2218 * ggimage Yu G (2023). \_ggimage: Use Image in 'ggplot2'_. R package version 0.3. * ggplot2 H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. * ggtree Guangchuang Yu. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics, 2020, 69:e96. doi: 10.1002/cpbi.96 * ggtreeExtra S Xu, Z Dai, P Guo, X Fu, S Liu, L Zhou, W Tang, T Feng, M Chen, L Zhan, T Wu, E Hu, Y Jiang, X Bo, G Yu. ggtreeExtra: Compact visualization of richly annotated phylogenetic data. Molecular Biology and Evolution 2021, 38(9):4039-4042. doi: 10.1093/molbev/msab166 * MASS Venables, W. N. & Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth Edition. Springer, New York. ISBN 0-387-95457-0 * mvtnorm Genz A, Bretz F (2009). Computation of Multivariate Normal and t Probabilities, series. Lecture Notes in Statistics. Springer-Verlag, Heidelberg. ISBN 978-3-642-01688-2. * phangorn Schliep K.P. 2011. phangorn: phylogenetic analysis in R. Bioinformatics, 27(4) 592-593 * phytools Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505. * picante S.W. Kembel, P.D. Cowan, M.R. Helmus, W.K. Cornwell, H. Morlon, D.D. Ackerly, S.P. Blomberg, and C.O. Webb. 2010. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463-1464 * RColorBrewer Neuwirth E (2022).  RColorBrewer: ColorBrewer*palettes. R package version 1.1-3*[https://CRAN.R-project.org/package=RColorBrewer](https://CRAN.R-project.org/package=RColorBrewer) * reshape2 Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20. URL [http://www.jstatsoft.org/v21/i12/](http://www.jstatsoft.org/v21/i12/) * scales Wickham H, Pedersen T, Seidel D (2025). scal*es: Scale Functions for Visualization. R*package version 1.4.0, [https://CRAN.R-project.org/package=scales](https://CRAN.R-project.org/package=scales). * tidyr Wickham H, Vaughan D, Girlich M (2024). tidyr: Tidy Messy Data. *package version 1.3.1*[https://CRAN.R-project.org/package=tidyr](https://CRAN.R-project.org/package=tidyr). * TreePar Stadler T (2015). TreePar: Estimating Birth and Death Rates Based on Phylogenies. R package version 3.3 * TreeSim Stadler T (2019).  TreeSim: Simulating Phylogenetic Trees. R package version 2.4. [https://CRAN.R-project.org/package=TreeSim](https://CRAN.R-project.org/package=TreeSim) ## Access information Other publicly accessible locations of the data: * Genbank Data was derived from the following sources: * NA