Abstract

Toxicological evaluation of chemicals using early-life stage zebrafish (Danio rerio) involves the observation and recording of altered phenotypes. Substantial variability has been observed among researchers in phenotypes reported from similar studies, as well as a lack of consistent data annotation, indicating a need for both terminological and data harmonization. When examined from a data science perspective, many of these apparent differences can be parsed into the same or similar endpoints whose measurements differ only in time, methodology, or nomenclature. Ontological knowledge structures can be leveraged to integrate diverse data sets across terminologies, scales, and modalities. Building on this premise, the National Toxicology Program’s Systematic Evaluation of the Application of Zebrafish in Toxicology undertook a collaborative exercise to evaluate how the application of standardized phenotype terminology improved data consistency. To accomplish this, zebrafish researchers were asked to assess images of zebrafish larvae for morphological malformations in two surveys. In the first survey, researchers were asked to annotate observed malformations using their own terminology. In the second survey, researchers were asked to annotate the images from a list of terms and definitions from the Zebrafish Phenotype Ontology. Analysis of the results suggested that the use of ontology terms increased consistency and decreased ambiguity, but a larger study is needed to confirm. We conclude that utilizing a common data standard will not only reduce the heterogeneity of reported terms but increases agreement and repeatability between different laboratories. Thus, we advocate for the development of a zebrafish phenotype atlas to help laboratories create interoperable, computable data.

Highlights

  • Zebrafish are a key animal model for toxicology because they are maintained and bred in the laboratory and they have rapid, observed development

  • The requirement in Survey 2 that raters use ontology terms from Zebrafish Phenotype Ontology (ZP) resulted in greater consistency in some categories of endpoint reporting across laboratories compared to the free-text responses obtained from Survey 1 by reducing the heterogeneity of terms

  • The most notable result of the study was the overall decrease in repeatability and mean concordance in the granular endpoint annotations from Survey 1 to Survey 2

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Summary

INTRODUCTION

Zebrafish are a key animal model for toxicology because they are maintained and bred in the laboratory and they have rapid, observed development. Different laboratories test the same chemical and observe the same endpoint but report their observations differently according to each laboratory’s internal standard Mapping these terms to an ontology reduces this heterogeneity and aids in data integration across laboratories. To improve the current state of data reporting, we tested the hypothesis that providing ontology terms to raters would improve the consistency of endpoint reporting across laboratories in highthroughput zebrafish embryo-larval assays that assess larvae shortly after hatching. This manuscript describes the results of these experiments and discusses the computational advantages of annotating data with ontology terms

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