Ancient mitogenomes reveal the evolutionary history and biogeography of sloths
- 1. Institut des Sciences de l'Evolution de Montpellier (ISEM), CNRS, IRD, EPHE, Université de Montpellier, Montpellier, France
- 2. McMaster Ancient DNA Centre, Department of Anthropology, McMaster University, Hamilton, Ontario, Canada
- 3. Wildlife and Ecology Group, School of Agriculture and Environment, Massey University, Palmerston North, New Zealand
- 4. Department of Anthropology, Trent University, Peterborough, Ontario, Canada
- 5. Instituto Superior de Estudios Sociales, CONICET/Instituto de Arqueología y Museo, Universidad Nacional de Tucumán, San Miguel de Tucumán, Argentina
- 6. East Tennessee State University Natural History Museum, Johnson City, Tennessee, United States of America
- 7. Bureau of Land Management, Utah State Office, Salt Lake City, Utah, United States of America
- 8. Division of Vertebrate Zoology/Mammalogy, American Museum of Natural History, New York, United States of America
- 9. Centre de Recherche en Paléontologie - Paris (CR2P), UMR CNRS 7207, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
Description
Supplementary Material for:
Delsuc F., Kuch M., Gibb G.C., Karpinski E., Hackenberger D., Szpak P., Martínez J.G., Mead J.I., McDonald H.G., MacPhee R.D.E., Billet G., Hautier L., and Poinar H.N. (2019). Ancient mitogenomes reveal the evolutionary history and biogeography of sloths. Current Biology. doi:10.1016/j.cub.2019.05.043.
Delsuc-CurrBiol-2019_capture_baits.fasta: Sequence baits designed from living xenarthran mitogenomes and reconstructed ancestral sequences used to capture ancient sloth mitogenomes.
Delsuc-CurrBiol-2019_dataset.fasta: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in fasta format.
Delsuc-CurrBiol-2019_dataset.phylip: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in phylip format.
Delsuc-CurrBiol-2019_dataset_partitions.nex: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in nexus format with partitions.
Delsuc-CurrBiol-2019_FigS2_RAxML_MLtree_100BP_nexus_for_FigTree.tree: Maximum likelihood mitogenomic tree inferred under the best-fitting partitioned model using RAxML. Related to Figure 1. Maximum-likelihood bootstrap percentages are indicating at nodes (100 replicates). Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree.
Delsuc-CurrBiol-2019_FigS3_IQ-TREE_MLtree_100BP_nexus_for_FigTree.tree: Maximum likelihood mitogenomic tree inferred under the best-fitting partitioned model using IQ-TREE. Related to Figure 1. Maximum-likelihood bootstrap percentages are indicating at nodes (100 replicates). Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree.
Delsuc-CurrBiol-2019_FigS4_MrBayes_consensus_nexus_for_FigTree.tree: Bayesian consensus mitogenomic tree inferred under the best-fitting partitioned model using MrBayes. Related to Figure 1. Clade posterior probabilities (PP) are indicated at nodes. Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree.
Delsuc-CurrBiol-2019_FigS5_PhyloBayes_consensus_nexus_for_FigTree.tree: Bayesian consensus mitogenomic tree inferred under the CAT-GTR+G4 mixture model using PhyloBayes. Related to Figure 1. Clade posterior probabilities (PP) are indicated at nodes. Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree.
Delsuc-CurrBiol-2019_FigS6_PhyloBayes_chronogram_nexus_for_FigTree.tree: Bayesian mitogenomic chronogram. Related to Figure 2. This chronogram was inferred under the CAT-GTR+G4 mixture model and an autocorrelated lognormal model of clock relaxation using PhyloBayes. Tree in nexus format viewable with FigTree.
Delsuc-CurrBiol-2019_Megatherium_bone_extraction_protocol.pdf: Detailed protocol for Megatherium americanum MAPB4R 3965 bone sample preparation.
Delsuc-CurrBiol-2019_ML_ancestral_reconstruction_MOL_constraint.pdf: Maximum likelihood ancestral character state reconstruction. Related to Figure 3. Maximum likelihood estimation of ancestral states for six dental characters from Varela et al. (2019) under the Mk model on the maximum likelihood topology obtained using the molecular topology as a backbone constraint.
Delsuc-CurrBiol-2019_ML_ancestral_reconstruction_MORPH_constraint.pdf: Maximum likelihood ancestral character state reconstruction. Related to Figure 3. Maximum likelihood estimation of ancestral states for six dental characters from Varela et al. (2019) under the Mk model on the maximum likelihood topology obtained using the same topological constraint that these authors used in their Bayesian phylogenetic reconstructions.
Delsuc-CurrBiol-2019_MP_ancestral_reconstruction_MOL_constraint.pdf: Maximum parsimony ancestral character state reconstruction. Related to Figure 3. Maximum parsimony estimation of ancestral states for six dental characters from Varela et al. obtained using the molecular topology as a backbone constraint.
Delsuc-CurrBiol-2019_MP_ancestral_reconstruction_MORPHO_constraint.pdf: Maximum parsimony ancestral character state reconstruction. Related to Figure 3. Maximum parsimony estimation of ancestral states for six dental characters from Varela et al. (2019) on the maximum parsimony topology obtained using the same topological constraint that these authors used in their Bayesian phylogenetic reconstructions.
Delsuc-CurrBiol-2019_TableS1_PartitionFinder_RAxML_best_partition_scheme.txt: Detailed results of the PartitionFinder analysis for RAxML.
Delsuc-CurrBiol-2019_TableS2_ModelFinder_IQ-TREE_best_partition_scheme.txt: Detailed results of the ModelFinder analysis for IQ-TREE.
Delsuc-CurrBiol-2019_TableS3_PartitionFinder_MrBayes_best_partition_scheme.txt: Detailed results of the PartitionFinder analysis for MrBayes.
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Delsuc-CurrBiol-2019_Megatherium_bone_extraction_protocol.pdf
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Additional details
Related works
- Is supplement to
- 10.1016/j.cub.2019.05.043 (DOI)