Publication of first draft of the tree of life

We are excited to publish the first draft of the Open Tree of Life in PNAS:

Scientists have used gene sequences and morphological data to construct tens of thousands of evolutionary trees that describe the evolutionary history of animals, plants, and microbes. This study is the first, to our knowledge, to apply an efficient and automated process for assembling published trees into a complete tree of life. This tree and the underlying data are available to browse and download from the Internet, facilitating subsequent analyses that require evolutionary trees. The tree can be easily updated with newly published data. Our analysis of coverage not only reveals gaps in sampling and naming biodiversity but also further demonstrates that most published phylogenies are not available in digital formats that can be summarized into a tree of life.

This is only a first draft, and there are plenty of places where the tree does not represent what we know about phylogenetic relationships. We can improve this tree through incorporation of new taxonomic and phylogenetic data. Our data store of trees (which contains many more trees than are included in the draft tree of life) is also a resource for other analyses. If you want to contribute a published tree for synthesis (or for analyses of coverage, conflict, etc), you can upload it through our curation interface.

Other pages and links:

Many thanks to all of the people that provided data, discussion, review, curation, and code and of course to NSF Biology for funding this work!

Proposal for OpenTree node stability

Currently, OpenTree has two different types of node IDs. Taxonomy (OTT) IDs are assigned to named nodes when we construct a taxonomy release, and phylogenetic node IDs are assigned by the treemachine neo4j graph database for nodes that do not align to an OTT ID (i.e. nodes added due to phylogenetic resolution). The OTT IDs are fairly stable over time, but the neo4j node IDs are definitely not stable, and the same neo4j ID may point to a completely unrelated node in future versions of the graph.

This system is problematic because we expose both types of IDs in the APIs (and also in URLs for the tree browser). The lack of neo4j node stability therefore affects API calls that use nodeIDs, browser bookmarks to nodes in the synthetic tree, and feedback left by users about specific nodes in the tree (see feedback issue #63 and treemachine issue #183). The OTT IDs are problematic as well: it is not straightforward to document when we reuse an existing OTT ID, mint a new ID, or delete an existing ID, when going from one version of the taxonomy version to the next.

At our recent face-to-face meeting, we discussed a proposal for a node identifier registry and are looking for feedback. We don’t intend this system to be a universally-used set of node definitions (i.e. we aren’t trying making a PhyloCode registry). We want a lightweight system that prevents exposure of unstable nodeIDs through the APIs to clients (including our own web application) and provides some measure of predictability. Feeedback on this proposal would be greatly appreciated.


  • be able to use the same node ID definitions across OTT and the synthetic tree
  • transparency about when we re-use a nodeID from a previous version of tree or taxonomy (or not)
  • users get an error when using a node ID from a previous version where there is no current node that fits that definition
  • fixing errors (such as moving a snail found in a worm taxon to its proper location) should not involve massive numbers of ID changes
  • generation of node definitions based on a given taxonomy must be automated and efficient
  • application of node definitions to an existing tree / taxonomy must be automated and efficient


Develop a lightweight registry of node definitions based on the structure of the OpenTree taxonomy. For each new version of the taxonomy and synthetic tree, use the registry to decide when to re-use existing node IDs and when to register a new definition + ID.

Leaf nodes will be assigned IDs during creation of OTT based on name (together with enough taxonomic context to separate homonyms).

The definition of the ID for a non-leaf node will include a list of IDs for nodes that are descendents of the intended clade, a list that are excluded from being descendents, and (optionally) a taxonomic name.

Definitions would never be deleted from the registry, although not all definitions will be used in any given tree / taxonomy.

Implementation questions

  • How many descendant and excluded nodes to include in the definitions: The definition needs some specificity but also can’t assume a complete list due to future addition of new species. Perhaps, for example, four descendants and three exclusions would be a decent compromise between one and thousands?
  • How to choose the specific nodes in the lists of descendants and exclusions: Should be ‘popular’  (should occur in as many sources as possible) and informative (if T has children T1 and T2 then at least one definition descendant should be taken from T1, and at least one from T2). Excluded nodes should be ‘near misses’ rather than arbitrarily chosen.
  • What to do when >1 node meets the definition: Add an option of adding constraints to the registered definition in order to remove the ambiguity while preserving the ID.
  • What to do when >1 definition matches a node: Ambiguous assignments can be resolved either by the addition of constraints, or by the creation of new ids.
  • Modification / versioning of definitions: If we add constraints to a definition (for example, to resolve ambiguity), does this mint a new ID or version the existing definition?


Workshop: Barriers to assembling phylogeny and data layers across the tree of life

The challenges to completing the Tree of Life and integrating data layers (NSF GoLife goals) are huge and vary across clades. Some groups have a nearly-complete tree but lack publicly available data layers, whereas other groups lack phylogenetic resolution or the resources to support tree / data integration. Partnering with Open Tree of Life and Arbor Workflows, FuturePhy will support a series of clade-based workshops to identify and solve specific challenges in tree of life synthesis and data layer integration.

RFP: 2 page proposals to fund small workshops and/or hackathons on completing the tree of life and integrating data layers for specific clades.
Proposal deadline: Nov. 1, 2015
Meeting dates: Feb 20-23 26-28, 2016 *note changed dates!*
Location: Gainesville, University of Florida
Participants per workshop: 10 maximum funded (virtual attendees possible)
Contacts: (FuturePhy), (OpenTree), (Arbor)

The full call for participation and a link to a proposal template is available at the FuturePhy website.

Have questions about this or future workshops? Attend our webinar Thursday, September 17 at 1 pm EDT. See details on how to connect.

The Open Tree of Life’s education and outreach site

Screen Shot 2015-06-26 at 1.50.43 PM

A little known side element to the Open Tree of Life project is the “Edu Tree of Life,” an interactive educational experience to engage the public. Nearing completion, our goal with this website has been to educate young students as well as the general public on topics surrounding evolution and phylogenetic trees. Our approach is to visually inform and engage users with colorful and entertaining animation, interactive features, and contextualization of facts and figures.

Our educational site is composed of three unique, interactive views of the ToL:

1) A “Big Picture” tree provides a zoomed-out timeline perspective of life’s history on earth and explains key elements of the tree of life using a stylized, graphic visualization. This ‘macro’ view presents the evolutionary history of Earth, starting from the creation of our planet and spanning all the way to present day. As the user moves up the timeline, the tree ‘grows’ in front of them revealing historical information; each new screen also offers a detailed explanation of one of several core concepts surrounding evolution. Video explanations containing animations live narrators explain each of these core concepts. Along with the videos, ‘pop-up’ information boxes also offer information.

Key elements:

  • A macro View
  • Key Concepts
  • Timeline of Life
  • Chaptered Format/Parallax Scrolling
  • Videos and Animation

The core concepts we explore are:

  • The Origin of Life
  • The Three Domains of Life
  • Common Ancestors
  • Extinction
  • Biodiversity
  • Lateral/Horizontal Gene Transfer & Genes

2) The page titled ““Categorizing Life on Earth” is a mid-sized view of life, a data-driven interactive tree with a focus on the groupings of species (clades). This Tree uses a sampling of data to illustrate hierarchy with a familiar ‘tree’ structure that employs branching lines of evolution. It pulls images from Phylopic and data from EOL for descriptions. A user can expand and contract nodes to view clades they find interesting. Still to come: we are exploring ways to illustrate LGT and are working on connecting nodes back via their common ancestry, so that clicking any two nodes will show you a visualization of how those species are connected through the whole tree of life.

Key elements:

  • Mid-sized view of major clades
  • Data-driven interactive
  • Shows Common Ancestry, Phylogeny and Clades
  • Species groupings ending in Clades

3) The “Explore Species” page is our ‘micro view’ of species on Earth. This interactive spinning wheel allows a user to select any of about 180 species to learn about. The 180 species were chosen as exemplary based on many factors: some were chosen for their relative familiarity with the general public, but many were chosen due to specific scientific breakthroughs associated with them. Many were the first species within their field of study to be gene-sequenced, some are keystone species with important evolutionary relatives, and others have strange or unique characteristics worthy of mention.

The information offered for each species includes an image (when available), scientific and common names, the major domain within which the species resides, and then a brief description of the species. This was achieved using the Encyclopedia of Life’s online API, which allowed us to pull information and other resources off of their site to show on ours. As a way of opening an educational portal between the two, any species you click on in the Wheel of Life can also be visited on its parent page at the Encyclopedia of Life, where much more information about all species can be found. We hope that this partnership will prove very fruitful for bringing in casual interest and turning it into a burning passion for evolutionary science and history. Even if we only end up with a few more zoologists, we’ll be happy.

Key elements:

  • Micro View
  • Exemplary/representative species
  • Connects to EoL API, a gateway for further learning
  • Catalogue of interesting species.­­
  • Some info on Major Domains.
  • Fun, introductory look into species and their connections.

We welcome your comments. —John Allison and Karl Gude


This is the first in a series of posts about several  phylogeny initiatives newly-funded by NSF focused on both technical and community aspects of phylogeny.  Plenty of potential for mutually beneficial work with OpenTree, and we are excited to help.

First up… FuturePhy!

FuturePhy is an NSF-sponsored, three-year program of conferences, workshops and hackathons on the Tree of Life. The project aims to promote novel, integrative data analyses and visualization, interdisciplinary syntheses of phylogenetic sciences, and cross-cutting uses of phylogenetics to develop and address new research questions and applications.

The first phase of this mission is critical: to bring together a broad community of people from diverse backgrounds who are active in phylogenetics research, who use the tree of life in research or education, who will benefit in applied or practical ways from a comprehensive tree of life, or who come from a background that offers new perspectives on defining, addressing or transcending key challenges in phylogenetics.

Help accelerate progress in all aspects of phylogenetics research by joining FuturePhy today. Diverse opportunities will be available to attend FuturePhy sessions in person or virtually, and to link FuturePhy to existing projects and initiatives.

  1. We invite you to participate in the project in several ways:
    Register on Scientists from all aspects of the phylogenetic sciences, educators, members of the tree-using community, and others interested in phylogenetics are welcome.
  2. Take the community survey and let FuturePhy what workshop and hackathon topics they should fund.
  3. Contribute to the discussion forum on This is the best way to log your interest and contribute ideas.
  4. Send email at with ideas or comments
  5. Tweet to the FuturePhy community: @FuturePhy
  6. Comment in the FuturePhy phylobabble thread

Crandall Lab Update: What can we do with synthetic trees?

Currently, the Crandall Lab is examining ways to use the underlying OpenTree taxonomy to gather metadata, associate it with nodes and tips in our synthetic trees, and apply it to evolutionary studies. Below we discuss them in the context of ongoing projects in the lab.


Curated taxonomy

One of the major outcomes of the OpenTree project is the underlying taxonomy. A curated taxonomy allows us to search and align names across independent databases to pull out additional information to associate with node and tip names. The Crandall Lab taxonomy curation started with the freshwater crayfish, which are in the Infraorder Astacidea and includes 711 species spread among 7 families.   This was a great group to start with because of the limited number of species and there are only a few active systematists revising the alpha-taxonomy, which makes the literature less dense and easier to work with. Initially, our investigations deemed the taxonomy very accurate, but the main issue we had to contend with was spelling errors attributed to depositing sequences into GenBank. In all, we identified and removed 10 misspelled taxa. Although that seems small, it was a great warm-up for two larger groups we are now working on, the Decapoda (crabs, shrimps, lobsters) which includes ~15,000 species and the Hemiptera (true bugs) which includes ~ 50,000-80,000 species.


Using a curated taxonomy to obtain additional data

As mentioned above, once the names have been curated we can use them to search across databases. This has been extremely useful in obtaining additional metadata to associate with our synthetic trees. For example, the Crandall Lab recently published a synthetic tree of the crayfish (Fig. 1), which included IUCN Red List values plotted for those taxa with assigned values (Owen et al. 2015, Richman et al. 2015). This is only feasible because we are able to search across IUCN Red Listed crayfish species using the OpenTree curated taxonomy names.

Other applications of using a curated taxonomy to obtain metadata include searching across GenBank to identify whether a particular taxon or rank has molecular data associated with it. This is useful for determining sampling strategies for new and continuing studies. For example, using the OpenTree taxonomy to search GenBank for Hemiptera families and genera, we found a wealth of sequence data has been generated for most of the higher taxa. The most diverse suborder within Hemiptera is Heteroptera and our query of names against NCBI GenBank suggests 70 of the 83 described families within Heteroptera have sequence data for one or more of the traditional eight molecular loci used in Hemiptera systematics (Fig. 2A). As for the Hemiptera genera identified in GenBank, we are currently validating the numbers in Fig. 2B because Hemiptera alpha-taxonomy is very active because many species are vectors for human pathogens and agricultural pests (e.g., kissing bug, aphids, psyllids, etc.).


In addition to searching GenBank, we are currently associating geographic, morphological, and ecological metadata to our curated names through GBIF and EOL TraitBank. We believe the curated OpenTree taxonomies of these groups and the accumulation of metadata for taxa will surely add a new dimension to our evolutionary studies and allow us to expand the scope the questions we can answer.

Figure 1 Synthetic tree of crayfish with 20 source trees.  Family names noted on the edge of the synthetic tree.  Paraphyly of Cambaridae is not novel and needs to be addressed in a morphological revision.  Color blocks note the IUCN Redlist value.

Figure 1 Synthetic tree of crayfish with 20 source trees. Family names noted on the edge of the synthetic tree. Paraphyly of Cambaridae is not novel and needs to be addressed in a morphological revision. Color blocks note the IUCN Redlist value.

Figure 2 Histograms depicting number of sequences found on GenBank given OTT names. 2A) Hemiptera families within suborders with nucleotide sequence data on NCBI GenBank. 2B) Hemiptera genera within suborders with nucleotide sequence data on NCBI GenBank.

Figure 2 Histograms depicting number of sequences found on GenBank given OTT names. 2A) Hemiptera families within suborders with nucleotide sequence data on NCBI GenBank. 2B) Hemiptera genera within suborders with nucleotide sequence data on NCBI GenBank.

Keith Crandall is a professor and director of the Computational Biology Institute at George Washington University. 

Chris Owen is a post-doctoral researcher for the AVAToL grant.


Owen, C. L., Bracken-Grissom, H., Stern, D., & Crandall, K. A. (2015). A synthetic phylogeny of freshwater crayfish: insights for conservation.Philosophical Transactions of the Royal Society of London B: Biological Sciences370(1662), 20140009.

Richman, N. I., Böhm, M., Adams, S. B., Alvarez, F., Bergey, E. A., Bunn, J. J., … & Collen, B. (2015). Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea). Philosophical Transactions of the Royal Society B: Biological Sciences370(1662), 20140060.

Update on synthesis methods

The current Open Tree of Life synthesis methods are based on the Tree Alignment Graphs described by Smith et al 2013. The examples presented in that paper used much simpler datasets than the dataset that is used for draft tree synthesis by the Open Tree of Life (which contains hundreds of original source trees and the entire OTT taxonomy with over 2.3 million terminal taxa). To accommodate the goals of synthesis, some modifications were made to the methods presented in Smith et al 2013. The current version of the draft tree (v2, which is presented at as of February 2015 and described in a preprint on bioRxiv), was built using these modified methods. The changes to synthesis that were introduced since Smith et al 2013 are not well-described elsewhere, so we present them below in this document.

We are continually testing and improving the methods we use to develop synthesis trees, and through this process we have recently discovered some methodological properties of the modified TAG procedures that are undesirable for our synthesis goals. We are making progress toward fixing them for the next version of the draft tree, and there are details at the end of this post.

General background on the Open Tree of Life project and the draft tree

The overall goal of OpenTree is to summarize what is known about phylogenetic relationships in a transparent manner with a clear connection to analyses and the published studies that support different clades. Comprehensive coverage of published phylogenetic statements is a very long term goal which would require work from a large community of biologists. The short-term goal for the supertree presented on the tree browser is to summarize a small set of well-curated inputs in a clear manner.

Background on Tree Alignment Graph methods

The current synthesis method uses a Tree Alignment Graph (TAG), described in Smith et al 2013. We have been using TAGs because:

  • These graphs can provide a view on conflict and congruence among input trees.
  • TAG-based are computationally tractable on the scale which the open tree of life project operates (2.3 million tips on the tree, and hundreds of input trees).
  • TAG-based approaches provide a straightforward way to handle inputs in which tips of a tree are assigned to higher taxa (any taxon above the species level). It is fairly common for published phylogenies to have tips mapped at the genus level (or higher).
  • When coupled with expert knowledge in the form of ranking of input trees, TAG methods can produce a sensible summary of our (rather limited) input trees. At this point in the project, our data store does not contain a large number of trees sufficiently curated* to be included in the supertree operations.

* Sufficiently curated = 1. tips mapped to taxa in the Open Tree Taxonomy; 2. rooted as described in the publication; 3. ingroup noted. Incorrect rootings and assignments of tips to taxa can introduce a lot of noise in the estimate, so we have opted for careful vetting of input trees rather scraping together every estimate available. We are hopeful that community involvement in the curation will get us to a point of having enough input trees to allow more traditional supertree approaches to work well, so that we can present multiple estimates of the tree of life.

Methods used to produce the v2 draft tree

The open tree of life project has been alternating between phases where we (1) add more trees to our set of curated input trees, and then (2) generate new versions of the “synthetic” draft tree of life. Thus far two versions of the tree have been publicly posted to The process of generating a new public draft tree involves the creation and critical review of many unpublished draft trees in order to detect errors or problems with the process (which could be due to misspecified taxa in input trees, software bugs, etc.).

This process has led to a few modifications of the TAG procedure as it was described in the PLoS Comp. Bio. paper. These modifications have been made to our treemachine software, and they include:

  • In the original paper, conflict was assessed by whether there was conflicting overlap among the descendant taxa of the nodes, not the edes. The software that produced the v2 tree assessed conflict between edges of the graph by looking for conflict based on the taxon sets contributed by each tree. This change is referred to as the “relationship taxa” rule in this issue on GitHub).
  • The supertree operation moves from root to tips, and occasionally a species attaches to a node via a series of low ranking relationships. When all of these are rejected (due to conflict with higher ranking trees), the species would be absent in the full tree if we followed the original TAG description faithfully. Instead, the treemachine version for v2 tree reattached these taxa based on their taxonomy after sweeping over the full tree.
  • The “Partially overlapping taxon sets” section of the paper described a procedure for eliminating order-dependence of the input trees. We have recently discovered a case in which the structure of a TAG built according to those procedures would differ depending on the input order of the trees. We have implemented a new procedure that pre-processes all the input trees, which removes this order-dependence (code for the new procedure can be accessed in the find-mrcas-when-creating-nodes branch of the treemachine repo on github).
  • To increase the overlap between different input trees, an additional step was implemented in treemachine that mapped the tips of an input tree to deeper nodes in the taxonomy that they may have represented. This was done by determining the most inclusive taxon that a tip could belong to without including any other tips in the tree, and then mapping the tip to that taxon instead of the taxon actually specified for the tip in the input tree itself. For example if the only primate in a tree was Homo sapiens, but the tree contained other mammals from the taxon sister to Primates (in the taxonomy), then the Homo sapiens tip would be assigned to the taxon Primates.

Undesirable properties of the procedures used to produce v2

  • It was possible for edges to exist in the draft tree that were not supported by any of the input trees. There were a very small number (111) of such groups in the v2 tree; this GitHub issue discusses the issue more thoroughly. This is not an unusual property for a supertree method to have – in fact most supertree methods can produce such groups. And under some definitions of support (e.g. induced triples) these groupings would probably have had support in our input trees. However, not being able to link every branch in the supertree to an branch in at least one supporting branch in an input tree made the draft tree more difficult to understand. We are working on modifications to the procedure that do not produce these groupings.
  • There were 22 taxonomic groupings mislabeled in the supertree (see issue 154 for details) and the definition of support used to indicate when an input tree “supported” a particular edge in the synthesis could be counterintuitive in some cases. The current view of the tree reports an input tree in the “supported by” panel if the branch in the draft tree passes along an edge that is parallel to an edge contributed by that input tree. Because some of the included taxa may have been culled from the group and reattached in a position closer to the root, the input tree can be in conflict with a grouping but still be listed as supporting it (see issues 155 and 157).

The draft tree contains over 2 million tips and many hundreds of thousands of internal edges. Thus, the undesirable properties mentioned above affected less than 0.0001% of the draft tree v2. Nonetheless, we are in the process of developing fixes for these problems, which should further improve the interpretability as well as the biological accuracy of future versions.


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