A call for an international network of genomic observatories (GOs)

Neil Davies,Kathy Willis,Linda Amaral-Zettler,Chris Meyer,John Deck,Susanna Assunta-Sansone,Mesude Bicak,Philippe Rocca-Serra,Dawn Field,Jack A Gilbert

doi:10.1186/2047-217x-1-5

Abstract

We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into ‘Genomic Observatories’ (GOs). Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series ’omics studies. The foundational layer of biodiversity–genetic variation–would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.

Highlights

We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research
What we learn from pioneering place-based genomic research efforts will reduce global costs by developing best practice and testing new techno-logies. It will help evaluate the benefits of describing the various dimensions of biodiversity, guiding approaches, and helping prioritize outside the focal research sites. What will it take to achieve these goals and what will this vast new body of data tell us about our planetary life support systems? Here we address this question and argue for a coordinated effort to develop genomic observatories at intensively studied ‘research hotspots’ around the world
In order to maximize scientific return on investment, we propose the establishment of Genomic Observatories (GOs) as a network of places that will serve as innovation incubators for ecogenomics

Summary

Introduction

We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Technological advances in DNA sequencing initially focused on the characterization of single genes, both from model organisms and environmental samples [13].

Results

Conclusion