The Dawn of Open Access to Phylogenetic Data

The scientific enterprise depends critically on the preservation of and open access to published data. This basic tenet applies acutely to phylogenies (estimates of evolutionary relationships among species). Increasingly, phylogenies are estimated from increasingly large, genome-scale datasets using increasingly complex statistical methods that require increasing levels of expertise and computational investment. Moreover, the resulting phylogenetic data provide an explicit historical perspective that critically informs research in a vast and growing number of scientific disciplines. One such use is the study of changes in rates of lineage diversification (speciation - extinction) through time. As part of a meta-analysis in this area, we sought to collect phylogenetic data (comprising nucleotide sequence alignment and tree files) from 217 studies published in 46 journals over a 13-year period. We document our attempts to procure those data (from online archives and by direct request to corresponding authors), and report results of analyses (using Bayesian logistic regression) to assess the impact of various factors on the success of our efforts. Overall, complete phylogenetic data for ~60% of these studies are effectively lost to science. Our study indicates that phylogenetic data are more likely to be deposited in online archives and/or shared upon request when: (1) the publishing journal has a strong data-sharing policy; (2) the publishing journal has a higher impact factor, and; (3) the data are requested from faculty rather than students. Although the situation appears dire, our analyses suggest that it is far from hopeless: recent initiatives by the scientific community -- including policy changes by journals and funding agencies -- are improving the state of affairs

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 humanity's 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

The Relationship Between Ambient Atmospheric Fine Particulate Matter (PM2.5) and Glaucoma in a Large Community Cohort.

Purpose: Glaucoma is more common in urban populations than in others. Ninety percent of the world's population are exposed to air pollution above World Health Organization (WHO) recommended limits. Few studies have examined the association between air pollution and glaucoma. Methods: Questionnaire data, ophthalmic measures, and ambient residential area air quality data for 111,370 UK Biobank participants were analyzed. Particulate matter with an aerodynamic diameter < 2.5 μm (PM2.5) was selected as the air quality exposure of interest. Eye measures included self-reported glaucoma, intraocular pressure (IOP), and average thickness of macular ganglion cell-inner plexiform layer (GCIPL) across nine Early Treatment Diabetic Retinopathy Study (ETDRS) retinal subfields as obtained from spectral-domain optical coherence tomography. We examined the associations of PM2.5 concentration with self-reported glaucoma, IOP, and GCIPL. Results: Participants resident in areas with higher PM2.5 concentration were more likely to report a diagnosis of glaucoma (odds ratio = 1.06, 95% confidence interval [CI] = 1.01-1.12, per interquartile range [IQR] increase P = 0.02). Higher PM2.5 concentration was also associated with thinner GCIPL (β = -0.56 μm, 95% CI = -0.63 to -0.49, per IQR increase, P = 1.2 × 10-53). A dose-response relationship was observed between higher levels of PM2.5 and thinner GCIPL (P < 0.001). There was no clinically relevant relationship between PM2.5 concentration and IOP. Conclusions: Greater exposure to PM2.5 is associated with both self-reported glaucoma and adverse structural characteristics of the disease. The absence of an association between PM2.5 and IOP suggests the relationship may occur through a non-pressure-dependent mechanism, possibly neurotoxic and/or vascular effects

Compensatory Evolution in RNA Secondary Structures Increases Substitution Rate Variation among Sites

There is growing evidence that interactions between biological molecules (e.g., RNA–RNA, protein–protein, RNA–protein) place limits on the rate and trajectory of molecular evolution. Here, by extending Kimura's model of compensatory evolution at interacting sites, we show that the ratio of transition to transversion substitutions (κ) at interacting sites should be equal to the square of the ratio at independent sites. Because transition mutations generally occur at a higher rate than transversions, the model predicts that κ should be higher at interacting sites than at independent sites. We tested this prediction in 10 RNA secondary structures by comparing phylogenetically derived estimates of κ in paired sites within stems (κp) and unpaired sites within loops (κu). Eight of the 10 structures showed an excellent match to the quantitative predictions of the model, and 9 of the 10 structures matched the qualitative prediction κp > κu. Only the Rev response element from the human immunovirus (HIV) genome showed the reverse pattern, with κp < κu. Although a variety of evolutionary forces could produce quantitative deviations from the model predictions, the reversal in magnitude of κp and κu could be achieved only by violating the model assumption that the underlying transition (or transversion) mutation rates were identical in paired and unpaired regions of the molecule. We explore the ability of the APOBEC3 enzymes, host defense mechanisms against retroviruses, which induce transition mutations preferentially in single-stranded regions of the HIV genome, to explain this exception to the rule. Taken as a whole, our findings suggest that κ may have utility as a simple diagnostic to evaluate proposed secondary structures

500,000 fish phenotypes: The new informatics landscape for evolutionary and developmental biology of the vertebrate skeleton: Fish phenotypes

The rich phenotypic diversity that characterizes the vertebrate skeleton results from evolutionary changes in regulation of genes that drive development. Although relatively little is known about the genes that underlie the skeletal variation among fish species, significant knowledge of genetics and development is available for zebrafish. Because developmental processes are highly conserved, this knowledge can be leveraged for understanding the evolution of skeletal diversity. We developed the Phenoscape Knowledgebase (KB; http://kb.phenoscape.org) to yield testable hypotheses of candidate genes involved in skeletal evolution. We developed a community anatomy ontology for fishes and ontology-based methods to represent complex free-text character descriptions of species in a computable format. With these tools, we populated the KB with comparative morphological data from the literature on over 2500 teleost fishes (mainly Ostariophysi) resulting in over 500,000 taxon phenotype annotations. The KB integrates these data with similarly structured phenotype data from zebrafish genes (http://zfin.org). Using ontology-based reasoning, candidate genes can be inferred for the phenotypes that vary across taxa, thereby uniting genetic and phenotypic data to formulate evo-devo hypotheses. The morphological data in the KB can be browsed, sorted, and aggregated in ways that provide unprecedented possibilities for data mining and discovery

Annotation of phenotypic diversity: decoupling data curation and ontology curation using Phenex

BackgroundPhenex (http://phenex.phenoscape.org/) is a desktop application for semantically annotating the phenotypic character matrix datasets common in evolutionary biology. Since its initial publication, we have added new features that address several major bottlenecks in the efficiency of the phenotype curation process: allowing curators during the data curation phase to provisionally request terms that are not yet available from a relevant ontology; supporting quality control against annotation guidelines to reduce later manual review and revision; and enabling the sharing of files for collaboration among curators.ResultsWe decoupled data annotation from ontology development by creating an Ontology Request Broker (ORB) within Phenex. Curators can use the ORB to request a provisional term for use in data annotation; the provisional term can be automatically replaced with a permanent identifier once the term is added to an ontology. We added a set of annotation consistency checks to prevent common curation errors, reducing the need for later correction. We facilitated collaborative editing by improving the reliability of Phenex when used with online folder sharing services, via file change monitoring and continual autosave.ConclusionsWith the addition of these new features, and in particular the Ontology Request Broker, Phenex users have been able to focus more effectively on data annotation. Phenoscape curators using Phenex have reported a smoother annotation workflow, with much reduced interruptions from ontology maintenance and file management issues