Data from: Origins and diversification of Myasis across blowflies
Data files
Feb 18, 2025 version files 482.57 MB
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Complete_tree.tre
34.36 KB
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control_temp.txt
9.26 KB
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control_tissue.txt
9.32 KB
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control_trophic.txt
8.79 KB
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LOG_temp_gamma.Log.txt
154.55 MB
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LOG_temp_gamma.Schedule.txt
8 MB
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LOG_tissue_gamma.Log.txt
154.60 MB
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LOG_tissue_gamma.Schedule.txt
8 MB
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LOG_trophic_gamma.Log.txt
149.30 MB
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LOG_trophic_gamma.Schedule.txt
8 MB
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ml_temp.Log.txt
1.50 KB
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ml_tissue.Log.txt
1.50 KB
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ml_trophic.Log.txt
1.50 KB
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Origin_divers_myiasis_blowflies.Rmd
35.90 KB
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README.md
6.64 KB
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temp.txt
1.24 KB
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temperature_tree.tre
4.30 KB
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tissue_tree.tre
4.29 KB
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tissue.txt
1.24 KB
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trophic_tree.tre
4.15 KB
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trophic.txt
1.16 KB
Abstract
Parasitism represents a prevalent and successful ecological strategy that has evolved independently numerous times across metazoa. Understanding the origin and diversification of parasitism is a central question in evolutionary biology. This study investigated the evolutionary path leading to a specific form of parasitism in blowflies known as myiasis, where larvae develop on or within a vertebrate. We modeled myiasis-associated traits, including trophic specialization (obligatory parasitism, facultative parasitism and saprophagy), larval food substrate (necrotic, fresh or both) and developmental temperature (constant, variable or both), across the blowfly phylogeny. Our results suggested that the ancestral state of blowflies likely encompassed saprophagy or facultative parasitism, with larvae developing in corpses or necrotic tissues from wounds in either homeothermic or heterothermic hosts. Furthermore, our analysis highlights the role of facultative parasitism as an intermediate step for obligate parasitism in blowflies, indicating that pre-adaptations for a facultative parasitic lifestyle may serve as stepping stones for emerging obligate parasitism. These findings shed light on the complex evolutionary history of blowfly vertebrate parasitism, emphasizing the importance of facultative parasitism as a critical transitional stage in this evolutionary process.
https://doi.org/10.5061/dryad.nzs7h4522
Description of the data and file structure
This dataset contains the raw data, phylogenetic tree, and scripts required to replicate analyses in Cardoso and Cunha et al accepted in Ecology and Evolution. We investigated the tempo and mode of vertebrate parasitism (myiasis) evolution across blowflies (Diptera: Calliphoridae) by modeling the rate and direction of change individually for three categorical traits: (i) trophic specialization, (ii) larval food substrate, and (iii) larval developmental temperature. We used BayesTraits v4.0.1 to conduct a discrete multistate trait evolution analysis to estimate ancestral states and transition rates.
Files and variables
Below is a summary of the included files:
- Phylogenetic Tree File
Complete_tree.tre: phylogenitic tree generated with comprising 61 calliphorid species and three Sarcophagidae species (Oxysarcodexia thornax, Sarcophaga bullata and Peckia ingens) as outgroups.trophic_tree.tre: phylogenetic tree used in the trophic specialization analysis.tissue_tree.tre: phylogenetic tree used in the larval food substrate analysis.temperature_tree.tre: phylogenetic tree used in the developmental temperature analysis.
- Raw Data
trophic.txt: Raw data for trophic specialization analysis.tissue.txt: Raw data for larval food substrate analysis.temp.txt: Raw data for developmental temperature analysis.
- Results
ml_trophic.Log.txt: Results of the estimated transitions rates using Maximum Likelihood analysis on BayesTraits for trophic specialization.ml_tissue.Log.txt: Results of the estimated transitions rates using Maximum Likelihood analysis on BayesTraits for larval food substrate.ml_temp.Log.txt: Results of the estimated transitions rates using Maximum Likelihood analysis on BayesTraits for developmental temperature.LOG_trophic_gamma.Log.txtOutput 1 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for trophic specialization using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.LOG_tissue_gamma.Log.txtOutput 1 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for larval food substrate using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.LOG_temp_gamma.Log.txtOutput 1 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for developmental temperature using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.LOG_trophic_gamma.Schedule.txtOutput 2 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for trophic specialization using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.LOG_tissue_gamma.Schedule.txtOutput 2 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for larval food substrate using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.LOG_temp_gamma.Schedule.txtOutput 2 from the discrete multistate trait evolution analysis on BayesTraits to estimate ancestral states and transition rates for developmental temperature using reversible-jump Markov Chain Monte Carlo (rjMCMC) approach and a uniform hyperprior to determine the range and shape of the gamma prior distribution.
Code/software
- Programs needed
- R version 4.3.3
- R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2024. Disponível em: https://www.R-project.org/
- BayesTraits v4.0.1
- Pagel M, Meade A. Bayesian Analysis of Correlated Evolution of Discrete Characters by Reversible‐Jump Markov Chain Monte Carlo. Am Nat. 2006 Jun;167(6):808–25.
- R version 4.3.3
- Analysis Scripts
Origin_divers_myiasis_blowflies.Rmd: R script in Markdown used for statistical analyses and visualizations.control_trophic.txt: Script for BayesTraits analysis on larval food substrate.control_tissue.txt: Script for BayesTraits analysis on larval food substrate.control_temp.txt: Script for BayesTraits analysis on developmental temperature.
- Loaded packages for R scripts
- phytools
- Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution. 2012;3(2):217–23.
- ape
- Paradis E, Claude J, Strimmer K. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics. 2004;20(2):289–90.
- Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35(3):526–8.
- tidyr
- Wickham H, Vaughan D, Girlich M. tidyr: Tidy Messy Data [Internet]. 2024. Available at: https://tidyr.tidyverse.org
- dplyr
- Wickham H, François R, Henry L, Müller K, Vaughan D. dplyr: A Grammar of Data Manipulation [Internet]. 2023. Available at: https://dplyr.tidyverse.org
- readr
- Wickham H, Hester J, Bryan J. readr: Read Rectangular Text Data [Internet]. 2024. Available at: https://readr.tidyverse.org
- ggtree
- Yu G, Lam TTY, Zhu H, Guan Y. Two Methods for Mapping and Visualizing Associated Data on Phylogeny Using Ggtree. Molecular Biology and Evolution. 1o de dezembro de 2018;35(12):3041–3.
- Yu G, Smith DK, Zhu H, Guan Y, Lam TTY. ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution. 2017;8(1):28–36.
- tibble
- Müller K, Wickham H. tibble: Simple Data Frames [Internet]. 2024. Available at: https://tibble.tidyverse.org/
- phytools