Abstract

Biomolecular ocean observing and research is a rapidly evolving field that uses omics approaches to describe biodiversity at its foundational level, giving insight into the structure and function of marine ecosystems over time and space. It is an especially effective approach for investigating the marine microbiome. To mature marine microbiome research and operations within a global ocean biomolecular observing network (OBON) for the UN Decade of Ocean Science for Sustainable Development and beyond, research groups will need a system to effectively share, discover, and compare “omic” practices and protocols. While numerous informatic tools and standards exist, there is currently no global, publicly-supported platform specifically designed for sharing marine omics [or any omics] protocols across the entire value-chain from initiating a study to the publication and use of its results. Toward that goal, we propose the development of the Minimum Information for an Omic Protocol (MIOP), a community-developed guide of curated, standardized metadata tags and categories that will orient protocols in the value-chain for the facilitated, structured, and user-driven discovery of suitable protocol suites on the Ocean Best Practices System. Users can annotate their protocols with these tags, or use them as search criteria to find appropriate protocols. Implementing such a curated repository is an essential step toward establishing best practices. Sharing protocols and encouraging comparisons through this repository will be the first steps toward designing a decision tree to guide users to community endorsed best practices.

Highlights

  • The term “omics” generally means studying anything holistically, and here we take a broad view of biomolecular omics that includes, but is not limited to: quantitative target gene amplification,barcoding,genomics,transcriptomics,proteomics, and metabolomics; and field collection approaches that target organisms or parts thereof, including single-celled organisms, as well as environmental DNA

  • In collaboration with the broader omics community, through the Omic BON initiative (Buttigieg et al, 2019), we propose to develop a best practice system specific to marine omics research, leveraging the framework of the Ocean Best Practices System (OBPS) to curate a global repository for marine omics protocols

  • Recognizing an urgent need for the ocean omics community to get organized as the UN Decade of Ocean Science for Sustainable Development starts, we identified the demand for publishing protocols into a user-friendly decision tree framework

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Summary

INTRODUCTION

The term “omics” generally means studying anything holistically, and here we take a broad view of biomolecular omics that includes, but is not limited to: quantitative target gene amplification (e.g., qPCR, qNASBA etc.), (meta)barcoding, (meta)genomics, (meta)transcriptomics, (meta)proteomics, and metabolomics; and field collection approaches that target organisms or parts thereof, including single-celled organisms (microorganisms), as well as environmental DNA (eDNA). While the omics community has already achieved high standards for sharing sequence data through the International Nucleotide Sequence Database Collaboration, these data often lack sufficient metadata and provenance information on the protocols used (Dickie et al, 2018), undermining efforts to implement the Findable, Accessible, Interoperable and Reusable (FAIR) data principles (Wilkinson et al, 2016) These limitations create challenges for marine microbiome research and operations from individual labs up to global (meta)data analysis efforts such as MGnify (Mitchell et al, 2019), which must identify data collected using comparable methods, in order to integrate and re-use data for meta-analysis (Berry et al, 2020). The interplay between the activities within and across the steps within a workflow—and how they bring value to the community and society—is complex and beyond the scope of this article; we have provided an initial perspective on this using the Porter’s value chain approach (Porter, 1985; Supplementary Figure 1)

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