Karen Cranston

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanitys projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

Synthesis of phylogeny and taxonomy into a comprehensive tree of life

Significance 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. Reconstructing the phylogenetic relationships that unite all lineages (the tree of life) is a grand challenge. The paucity of homologous character data across disparately related lineages currently renders direct phylogenetic inference untenable. To reconstruct a comprehensive tree of life, we therefore synthesized published phylogenies, together with taxonomic classifications for taxa never incorporated into a phylogeny. We present a draft tree containing 2.3 million tips—the Open Tree of Life. Realization of this tree required the assembly of two additional community resources: (i) a comprehensive global reference taxonomy and (ii) a database of published phylogenetic trees mapped to this taxonomy. Our open source framework facilitates community comment and contribution, enabling the tree to be continuously updated when new phylogenetic and taxonomic data become digitally available. Although data coverage and phylogenetic conflict across the Open Tree of Life illuminate gaps in both the underlying data available for phylogenetic reconstruction and the publication of trees as digital objects, the tree provides a compelling starting point for community contribution. This comprehensive tree will fuel fundamental research on the nature of biological diversity, ultimately providing up-to-date phylogenies for downstream applications in comparative biology, ecology, conservation biology, climate change, agriculture, and genomics.

Species trees from highly incongruent gene trees in rice

Several methods have recently been developed to infer multilocus phylogenies by incorporating information from topological incongruence of the individual genes. In this study, we investigate 2 such methods, Bayesian concordance analysis and Bayesian estimation of species trees. Our test data are a collection of genes from cultivated rice (genus Oryza) and the most closely related wild species, generated using a high-throughput sequencing protocol and bioinformatics pipeline. Trees inferred from independent genes display levels of topological incongruence that far exceed that seen in previous data sets analyzed with these species tree methods. We identify differences in phylogenetic results between inference methods that incorporate gene tree incongruence. Finally, we discuss the challenges of scaling these analyses for data sets with thousands of gene trees and extensive levels of missing data.

Summarizing a Posterior Distribution of Trees Using Agreement Subtrees

Bayesian inference of phylogeny is unique among phylogenetic reconstruction methods in that it produces a posterior distribution of trees rather than a point estimate of the best tree. The most common way to summarize this distribution is to report the majority-rule consensus tree annotated with the marginal posterior probabilities of each partition. Reporting a single tree discards information contained in the full underlying distribution and reduces the Bayesian analysis to simply another method for finding a point estimate of the tree. Even when a point estimate of the phylogeny is desired, the majority-rule consensus tree is only one possible method, and there may be others that are more appropriate for the given data set and application. We present a method for summarizing the distribution of trees that is based on identifying agreement subtrees that are frequently present in the posterior distribution. This method provides fully resolved binary trees for subsets of taxa with high marginal posterior probability on the entire tree and includes additional information about the spread of the distribution.

Science incubators: synthesis centers and their role in the research ecosystem.

How should funding agencies enable researchers to explore high-risk but potentially high-reward science? One model that appears to work is the NSF-funded synthesis center, an incubator for community-led, innovative science.

The Fossil Calibration Database-A New Resource for Divergence Dating

Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important-often least appreciated-step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for nonspecialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as a key pipeline for peer-reviewed calibrations to enter the database.

Phylotastic! Making tree-of-life knowledge accessible, reusable and convenient

BackgroundScientists rarely reuse expert knowledge of phylogeny, in spite of years ofeffort to assemble a great “Tree of Life” (ToL). A notableexception involves the use of Phylomatic, which provides tools togenerate custom phylogenies from a large, pre-computed, expert phylogeny ofplant taxa. This suggests great potential for a more generalized systemthat, starting with a query consisting of a list of any known species, wouldrectify non-standard names, identify expert phylogenies containing theimplicated taxa, prune away unneeded parts, and supply branch lengths andannotations, resulting in a custom phylogeny suited to the user’sneeds. Such a system could become a sustainable community resource ifimplemented as a distributed system of loosely coupled parts that interactthrough clearly defined interfaces.ResultsWith the aim of building such a “phylotastic” system,the NESCent Hackathons, Interoperability, Phylogenies (HIP) workinggroup recruited 2 dozen scientist-programmers to a weeklong programminghackathon in June 2012. During the hackathon (and a three-month follow-upperiod), 5 teams produced designs, implementations, documentation,presentations, and tests including: (1) a generalized scheme for integratingcomponents; (2) proof-of-concept pruners and controllers; (3) a meta-API fortaxonomic name resolution services; (4) a system for storing, finding, andretrieving phylogenies using semantic web technologies for data exchange,storage, and querying; (5) an innovative new service, DateLife.org,which synthesizes pre-computed, time-calibrated phylogenies to assign agesto nodes; and (6) demonstration projects. These outcomes are accessible viaa public code repository (GitHub.com), a website(http://www.phylotastic.org), and a server image.ConclusionsApproximately 9 person-months of effort (centered on a software developmenthackathon) resulted in the design and implementation of proof-of-conceptsoftware for 4 core phylotastic components, 3 controllers, and 3 end-userdemonstration tools. While these products have substantial limitations, theysuggest considerable potential for a distributed system that makesphylogenetic knowledge readily accessible in computable form. Widespread useof phylotastic systems will create an electronic marketplace for sharingphylogenetic knowledge that will spur innovation in other areas of the ToLenterprise, such as annotation of sources and methods and third-partymethods of quality assessment.

Extreme environments select for reproductive assurance: evidence from evening primroses (Oenothera)

Competing evolutionary forces shape plant breeding systems (e.g. inbreeding depression, reproductive assurance). Which of these forces prevails in a given population or species is predicted to depend upon such factors as life history, ecological conditions, and geographical context. Here, we examined two such predictions: that self-compatibility should be associated with the annual life history or extreme climatic conditions. We analyzed data from a clade of plants remarkable for variation in breeding system, life history and climatic conditions (Oenothera, sections Anogra and Kleinia, Onagraceae). We used a phylogenetic comparative approach and Bayesian or hybrid Bayesian tests to account for phylogenetic uncertainty. Geographic information system (GIS)-based climate data and ecological niche modeling allowed us to quantify climatic conditions. Breeding system and reproductive life span are not correlated in Anogra and Kleinia. Instead, self-compatibility is associated with the extremes of temperature in the coldest part of the year and precipitation in the driest part of the year. In the 60 yr since this pattern was anticipated, this is the first demonstration of a relationship between the evolution of self-compatibility and climatic extremes. We discuss possible explanations for this pattern and possible implications with respect to anthropogenic climate change.

Best Practices for Data Sharing in Phylogenetic Research

As phylogenetic data becomes increasingly available, along with associated data on species’ genomes, traits, and geographic distributions, the need to ensure data availability and reuse become more and more acute. In this paper, we provide ten “simple rules” that we view as best practices for data sharing in phylogenetic research. These rules will help lead towards a future phylogenetics where data can easily be archived, shared, reused, and repurposed across a wide variety of projects.

Phylesystem: a git-based data store for community-curated phylogenetic estimates

Motivation: Phylogenetic estimates from published studies can be archived using general platforms like Dryad (Vision, 2010) or TreeBASE (Sanderson et al., 1994). Such services fulfill a crucial role in ensuring transparency and reproducibility in phylogenetic research. However, digital tree data files often require some editing (e.g. rerooting) to improve the accuracy and reusability of the phylogenetic statements. Furthermore, establishing the mapping between tip labels used in a tree and taxa in a single common taxonomy dramatically improves the ability of other researchers to reuse phylogenetic estimates. As the process of curating a published phylogenetic estimate is not error-free, retaining a full record of the provenance of edits to a tree is crucial for openness, allowing editors to receive credit for their work and making errors introduced during curation easier to correct. Results: Here, we report the development of software infrastructure to support the open curation of phylogenetic data by the community of biologists. The backend of the system provides an interface for the standard database operations of creating, reading, updating and deleting records by making commits to a git repository. The record of the history of edits to a tree is preserved by git’s version control features. Hosting this data store on GitHub (http://github.com/) provides open access to the data store using tools familiar to many developers. We have deployed a server running the ‘phylesystem-api’, which wraps the interactions with git and GitHub. The Open Tree of Life project has also developed and deployed a JavaScript application that uses the phylesystem-api and other web services to enable input and curation of published phylogenetic statements. Availability and implementation: Source code for the web service layer is available at https://github.com/OpenTreeOfLife/phylesystem-api. The data store can be cloned from: https://github.com/OpenTreeOfLife/phylesystem. A web application that uses the phylesystem web services is deployed at http://tree.opentreeoflife.org/curator. Code for that tool is available from https://github.com/OpenTreeOfLife/opentree. Contact: mtholder@gmail.com