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opencc-by-4.0Jan 2021View details →

NEXUS file describing the taxonomic relationships of the 466 species for which genome sequencing was underway at Tree of Life, Wellcome Sanger Institute, at 31 December 2020

This NEXUS file shows the taxonomic relationships of 466 species of eukaryote. The taxonomy derives from the NCBI TaxonomyDB. The species are those for which genome sequencing is underway at the Tree of Life programme, Wellcome Sanger Institute, as of 31st Decemnber 2020. The NEXUS file includes a figtree block generated in FigTree [<a href="https://github.com/rambaut/figtree">https://github.com/rambaut/figtree</a>] that informs display of the data as a circular tree with species coloured by taxonomic Family, and Families with more than one species represented as triangles. The figure is used in publications and presentations describing the activities of the Tree of Life programme and the projects in which Tree of Life is involved, especially the Darwin Tree of Life project [https://darwintreeoflife.org].

opencc-zeroDec 2016View details →

Data from: Enriching the ant tree of life: enhanced UCE bait set for genome-scale phylogenetics of ants and other Hymenoptera

1. Targeted enrichment of conserved genomic regions (e.g., ultraconserved elements or UCEs) has emerged as a promising tool for inferring evolutionary history in many organismal groups. Because the UCE approach is still relatively new, much remains to be learned about how best to identify UCE loci and design baits to enrich them. 2. We test an updated UCE identification and bait design workflow for the insect order Hymenoptera, with a particular focus on ants. The new strategy augments a previous bait design for Hymenoptera by (a) changing the parameters by which conserved genomic regions are identified and retained, and (b) increasing the number of genomes used for locus identification and bait design. We perform in vitro validation of the approach in ants by synthesizing an ant-specific bait set that targets UCE loci and a set of "legacy" phylogenetic markers. Using this bait set, we generate new data for 84 taxa (16/17 ant subfamilies) and extract loci from an additional 17 genome-enabled taxa. We then use these data to examine UCE capture success and phylogenetic performance across ants. We also test the workability of extracting legacy markers from enriched samples and combining the data with published data sets. 3. The updated bait design (hym-v2) contained a total of 2,590-targeted UCE loci for Hymenoptera, significantly increasing the number of loci relative to the original bait set (hym-v1; 1,510 loci). Across 38 genome-enabled Hymenoptera and 84 enriched samples, experiments demonstrated a high and unbiased capture success rate, with the mean locus enrichment rate being 2,214 loci per sample. Phylogenomic analyses of ants produced a robust tree that included strong support for previously uncertain relationships. Complementing the UCE results, we successfully enriched legacy markers, combined the data with published Sanger data sets, and generated a comprehensive ant phylogeny containing 1,060 terminals. 4. Overall, the new UCE bait design strategy resulted in an enhanced bait set for genome-scale phylogenetics in ants and likely all of Hymenoptera. Our in vitro tests demonstrate the utility of the updated design workflow, providing evidence that this approach could be applied to any organismal group with available genomic information.

opencc-by-4.0May 2023View details →

Supplementary Data for: A time-calibrated 'Tree of Life' of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world

This compendium of files includes the dated phylogenetic tree in Newick format (Data S1), the list of statistical routines used for the three empirical case studies (Data S2), and the high-resolution version of the figures in the supplementary materials and main text (Data S3) for the Earth-Science Reviews paper "A time-calibrated ‘Tree of Life’ of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world", which is under consideration. The best-scoring molecular tree (Data S1) can be opened using freely available programs like R (R Development Core Team, 2021), Dendroscope (Huson and Scornavacca, 2012), and FigTree (Rambaut, 2018). Please, feel free to send an email to the maintainer Dr. Jorge García Girón (jogarg@unileon.es OR Jorge.Garcia-Giron@oulu.fi) if you face any trouble downloading, opening, or using these files. <ul> <li>Huson, D. H., & Scornavacca, C. (2012). Dendroscope 3: An interactive tool for rooted phylogenetic trees and networks. Systematic Biology, 61(6), 1061–1067.</li> <li>R Development Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/</li> <li>Rambaut, A. (2018). FigTree. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK. http://tree.bio.ed.ac.uk/software/figtree/</li> </ul>

opencc-by-4.0Feb 2021View details →

Phylogenomic Analyses of 2,786 Genes in 158 Lineages Support a Root of The Eukaryotic Tree of Life Between Opisthokonts and All Other Lineages

Abstract Advances in phylogenetic methods and high-throughput sequencing have allowed the reconstruction of deep phylogenetic relationships in the evolutionary history of eukaryotes. Yet, the root of the eukaryotic tree of life remains elusive. The most ‘popular’ (i.e. in textbooks and reviews) hypothesis for the root is between Unikonta (Opisthokonta + Amoebozoa) and Bikonta (all other eukaryotes), which emerged from analyses of a single gene fusion and a limited sampling of eukaryotic lineages. Subsequent highly-cited studies based on concatenation of genes supported this hypothesis with some variations or proposed a root within the Excavata. However, concatenation of genes neither considers phylogenetically-informative events (i.e. gene duplications and losses), nor provides an estimate of the root. A more recent study using gene tree-species tree reconciliation methods suggested the root lies between Opisthokonta and all other eukaryotes, but only including 59 taxa and 20 genes. Here we apply a gene tree – species tree reconciliation approach to a gene-rich and taxon-rich dataset (i.e. 2,786 gene families from two sets of ~158 diverse eukaryotic lineages) to assess the root, and we iterate each analysis 100 times to quantify tree space uncertainty. Our results estimate a root between Fungi and all other eukaryotes, or between Opisthokonta and all other eukaryotes, and reject alternative popular roots from the literature. Based on further analysis of genome size we propose Opisthokonta + others as the most likely root. Finding the root of the eukaryotic tree of life is critical for the field of comparative biology as it allows us to understand the timing and mode of evolution of characters across the evolutionary history of eukaryotes. Methods Here we provide the alignments, gene trees, inputs, and outputs from our project entitled "Phylogenomic Analyses of 2,786 Genes in 158 Lineages Support a Root of The Eukaryotic Tree of Life Between Opisthokonts and All Other Lineages". Sequences and alignments were produced using the phylogenomic pipeline PhyloToL, which contains a taxon- and gene-rich database (including eukaryotes, archaea, and bacteria). These data were then used for 1) assessing the root of the eukaryotes and 2) for comparison with other previously published hypotheses. In both cases, we used the species tree - gene tree reconciliation tool iGTP. We also did a comparison of hypotheses using the likelihood-based tool SpeciesRax iGTP Input data These data are divided into four datasets based on taxa selection. For dataset SEL+, taxa were selected based on their taxonomy; for RAN+, taxa were selected randomly among the major eukaryotic clades Opisthokonta, Amoebozoa, Archaeplastida, Excavata, SAR, and some orphan lineages. Datasets SEL- and RAN- are the same as SEL+ and RAN+, but exclude microsporidians in order to account for and avoid long branch attraction due to microsporidians fast-evolutionary rates. We chose the gene families that contain at least 25 taxa representing at least four of the five major eukaryotic clades. Additionally, at least 2 of the major clades had to contain at least 2 minor clades (e.g. Glaucophytes and Rhodophyta are minor clades in the major clade Archaeplastida). In a pilot analysis, we produced an alignment and a phylogenetic tree for each gene family using the default settings of a previous version of PhyloToL (GUIDANCE V1.3.1 sequence cutoff = 0.3 and column cutoff = 0.4; RAxML quick tree with model PROTGAMMALG and no bootstraps). Then, we kept the gene families that are exclusive of eukaryotes or the ones in which eukaryotes were monophyletic. From a total of 3,002 gene families that met our criteria, 2786 passed the initial steps of PhyloToL when including only the data from the dataset SEL+. These 2,786 gene families were used for further analyses with all datasets. MSAs were produced with PhyloToL (GUIDANCE V2.02 sequence cutoff = 0.3, column cutoff = 0.4, number of iterations = 5; Sela, et al. 2015). The default parameters of PhyloToL include up to five iterations of GUIDANCE V2.02 with 10 bootstraps and MAFFT V7 with algorithm E-INS-i for less than 200 sequences or “auto” option if more than 200 sequences, and maxiterate = 1000. Instead, here we run up to five iterations of GUIDANCE with 20 bootstraps and the simple MAFFT algorithm FFT-NS-2. Then, we perform an additional GUIDANCE run with 100 bootstraps and the default MAFFT parameters for PhyloToL. Gene trees were inferred with RAxML v.8.2.4 with 10 ML searches for best-ML tree (option "-# 10"), using the rapid hill-climbing algorithm (option "-f d") and no bootstrap replicates. The protein evolution model used was evaluated during the gene tree inference (option "-m PROTCATAUTO") by testing all models available in RAxML (e.g. JTT, LG, WAG, etc) with optimization of substitution rates and of site-specific evolutionary rates which were categorized into four distinct rate categories for greater computational efficiency. We ran 100 repetitions of iGTP analyses per dataset. But, given the complexity of the datasets and the heuristic nature of some key steps of the iGTP algorithm (e.g. gene tree rooting and initial starting species tree generation), in a preliminary analysis, we faced two systematic challenges with iGTP as the inferred species tree was affected by: 1) the order of the leaves in the input unrooted gene tree Newick strings (i.e. the input trees were treated as rooted even though we specified that they were not); and 2) the input gene order in the 100 replicates. Therefore, we randomly shuffled the order of the leaves in the unrooted gene trees (keeping the same topology), and randomly shuffled the order of the input gene trees in each of the 100 replicates per dataset. Here we provide the 100 input files generated for those iGTP analyses.  Output data Here we also share the data generated after two analyses: 1) root assessment and 2) hypothesis testing. For the former, we allowed iGTP to calculate the more parsimonious root given our input files. For the latter, we allowed iGTP to calculate the reconciliation cost of the gene trees given the input files and constraints in the species trees to reflect previously published root hypotheses. The constraints are explained in the README file. SpeciesRax Since we removed LGT and contamination from our dataset using a series of filters, we applied the model UndatedDL instead of UndatedDTL, which implies that we only took into consideration duplications and losses and ignored the transferences. Then, the command used for SpeciesRax was... ./generax --families forGeneRax/famFile --species-tree forGeneRax/spsTreeAn.newick --strategy SKIP --rec-model UndatedDL --per-family-rates --prefix An_DS1 --si-strategy EVAL  input  Here, we are sharing all the necessary files to run SpeciesRax, including the mapping file (famFile), the species trees (spsTrees; the best iGTP constrained species trees per hypothesis), and their underlying gene trees (trees_r) output Output folder from SpeciesRax, which includes log files, events (duplications, losses) counts, and statistics (i.e., reconciliation likelihood values) Note:  * As in the iGTP analyses, for the SpeciesRax files, the words Op, Fu, Di, Un, An, refer to the five root hypotheses compared: Opisthokonta-others, Fungi-others, Discoba-others, Unikonta-Bikonta, and (Ancyromonadida + Metamonada)-others, respectively.  * For the SpeciesRax analyses, the Un word refers to Ut (Cavalier-Smith 2003)

opencc-zeroJul 2022View details →

DateLife: leveraging databases and analytical tools to reveal the dated Tree of Life

Achieving a high-quality reconstruction of a phylogenetic tree with branch lengths proportional to absolute time (chronogram) is a difficult and time-consuming task. But the increased availability of fossil and molecular data, and time-efficient analytical techniques has resulted in many recent publications of large chronograms for a large number and wide diversity of organisms. Knowledge of the evolutionary time frame of organisms is key for research in the natural sciences. It also represent valuable information for education, science communication, and policy decisions. When chronograms are shared in public, open databases, this wealth of expertly-curated and peer-reviewed data on evolutionary timeframe is exposed in a programatic and reusable way, as intensive and localized efforts have improved data sharing practices, as well as incentivizited open science in biology. Here we present DateLife, a service implemented as an R package and an R Shiny website application available at www.datelife.org, that provides functionalities for efficient and easy finding, summary, reuse, and reanalysis of expert, peer-reviewed, public data on time frame of evolution. The main DateLife workflow constructs a chronogram for any given combination of taxon names by searching a local chronogram database constructed and curated from the Open Tree of Life Phylesystem phylogenetic database, which incorporates phylogenetic data from the TreeBASE database as well. We implement and test methods for summarizing time data from multiple source chronograms using supertree and congruification algorithms, and using age data extracted from source chronograms as secondary calibration points to add branch lengths proportional to absolute time to a tree topology. DateLife will be useful to increase awareness of the existing variation in alternative hypothesis of evolutionary time for the same organisms, and can foster exploration of the effect of alternative evolutionary timing hypotheses on the results of downstream analyses, providing a framework for a more informed interpretation of evolutionary results.

opencc-by-4.0May 2024View details →

Supporting Information for: Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life

This data repository contains supporting information, data, and code for figures and analysis pipelines the PLOS Biology article: "Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life." <ul> <li>4d_full.treefile: Data underlying Figure 1 (note: tree was plotted as a cladogram and key groups collapsed on iToL; the treefile was not modified) and Figure S1.</li> <li>S2_data.csv: Data underlying Figure 2.</li> <li>S3_data.csv: Data underlying Figure 3.</li> <li>Data underlying Figure 4 is found in Table S4 of supplementary_tables.xlsx in the main manuscript</li> <li>S5_data.csv Data underlying Figure 5</li> <li>S6_data.csv Data underlying Figure S2 </li> <li>illumina_only_assms.tar.gz: Archive of Illumina-only assemblies (FASTA) based on publicy available data that we did not generate. Assemblies generated from our own short-read data have been submitted to NCBI GenBank.</li> <li>illumina_vcfs.tar.gz: Illumina-based variant calls and BED tracks of masked bases.</li> <li>genomes.tar.gz: Genome files, for archival purposes.</li> <li>repeatModeler-lib.tar.gz: RepeatModeler2 libraries.</li> <li>diploid_genomes.tar.gz: diploid genomes and BED tracks of phased regions.</li> <li>trees.tar.gz: phylogenies</li> </ul>

opencc-zeroJun 2024View details →

Data from: Meta-analytical evidence for frequency-dependent selection across the tree of life

Explaining the maintenance of genetic variation in fitness related traits within populations is a fundamental challenge in ecology and evolutionary biology. Frequency-dependent selection (FDS) is one mechanism that can maintain such variation, especially when selection favours rare variants (negative FDS). However, our general knowledge about the occurrence of FDS, its strength and direction remain fragmented, limiting general inferences about this important evolutionary process. We systematically reviewed the published literature on FDS and assembled a database of 747 effect sizes from 101 studies to analyse the occurrence, strength, and direction of FDS, and the factors that could explain heterogeneity in FDS. Using a meta-analysis, we found that overall, FDS is more commonly negative, although not significantly when accounting for phylogeny. An analysis of absolute values of effect sizes, however, revealed the widespread occurrence of modest FDS. However, negative FDS was only significant in laboratory experiments and non-significant in mesocosms and field-based studies. Moreover, negative FDS was stronger in studies measuring fecundity and involving resource competition over studies using other fitness components or focused on other ecological interactions. Our study unveils key general patterns of FDS and points in future promising research directions that can help us understand a long-standing fundamental problem in evolutionary biology and its consequences for demography and ecological dynamics.

opencc-zeroJun 2024View details →

Eye morphology contributes to the ecology and evolution of the avian tree of life

The avian eye is the single most important external anatomical trait for interpreting light environments by birds and varies widely in size and shape across the avian tree of life. The attached dataset provides measurements on eye size taken from preserved museum specimens for roughly one third of the avian tree of life (N = 3,475 species). The original dataset was collected by Stanley Ritland and Alice Hutchinson and archived as appendices in Stanley Ritland's Dissertation from the University of Chicago (1982): "The Allometry of the Vertebrate Eye".

Fig. 40 in The Amphibian Tree Of Life

Fig. 40. Maximumlikelihood tree of ranoids of Delorme et al. (2004), based on sequences 12S and 16S rRNA for a total of 1198 bp. Alignment was made using the program SeAl (1995; cost functions not provided) and by comparison with models of secondary structure. treated as missing data. The maximumlikelihood nucleotide substitution model accepted was

Fig. 66. A in The Amphibian Tree Of Life

Fig. 66. A simplied tree of our results (fig. 50) tree showing families. Numbers on branches branch lengths, Bremer, and jackknife values, as well as molecular synapomorphies to be appendices 4 and 5. See table 5 for taxon names associated with internal numbered branches

Fig. 20 in The Amphibian Tree Of Life

Fig. 20. Consensus of 12 equally parsimonious trees of selected members of Megophryidae Delorme and Dubois (2001), rooted on Scaphiopus and Pelodytes. Underlying data were 54

Fig. 10 in The Amphibian Tree Of Life

Fig. 10. Parsimony tree of Plethodontidae by Macey (2005), a reanalysis of entire mt DNA sequence data provided by Mueller et al. (2004). On right are the traditional taxonomy and

Fig. 9 in The Amphibian Tree Of Life

Fig. 9. Tree of Plethodontidae by Mueller et al. (2004), with the traditional taxonomic (Desmognathinae 1 tribes of Plethodontinae; Wake, 1966) placed on the right, with taxonomic

Fig. 7 in The Amphibian Tree Of Life

Fig. 7. Relationships of salamanders suggested by Wiens et al. (2005). Families are noted Results reflect a parsimony analysis of 326 character transformations of morphology (221 informative), and DNA sequences from nu rRNA (212 bp from Larson, 1991; 147

Fig. 47. A in The Amphibian Tree Of Life

Fig. 47. A, Rhacophorid and mantellid Liem (1970) based on 36 direct to dendritic phological transformation series, rooted pothetical generalized ranid ancestor.