Earth BioGenome Project: Sequencing life for the future of life.

Increasing our understanding of Earth's biodiversity and responsibly stewarding its resources are among the most crucial scientific and social challenges of the new millennium. These challenges require fundamental new knowledge of the organization, evolution, functions, and interactions among millions of the planet's organisms. Herein, we present a perspective on the Earth BioGenome Project (EBP), a moonshot for biology that aims to sequence, catalog, and characterize the genomes of all of Earth's eukaryotic biodiversity over a period of 10 years. The outcomes of the EBP will inform a broad range of major issues facing humanity, such as the impact of climate change on biodiversity, the conservation of endangered species and ecosystems, and the preservation and enhancement of ecosystem services. We describe hurdles that the project faces, including data-sharing policies that ensure a permanent, freely available resource for future scientific discovery while respecting access and benefit sharing guidelines of the Nagoya Protocol. We also describe scientific and organizational challenges in executing such an ambitious project, and the structure proposed to achieve the project's goals. The far-reaching potential benefits of creating an open digital repository of genomic information for life on Earth can be realized only by a coordinated international effort.

The Role of Synthetic Biology in Atmospheric Greenhouse Gas Reduction: Prospects and Challenges.

The long atmospheric residence time of CO2 creates an urgent need to add atmospheric carbon drawdown to CO2 regulatory strategies. Synthetic and systems biology (SSB), which enables manipulation of cellular phenotypes, offers a powerful approach to amplifying and adding new possibilities to current land management practices aimed at reducing atmospheric carbon. The participants (in attendance: Christina Agapakis, George Annas, Adam Arkin, George Church, Robert Cook-Deegan, Charles DeLisi, Dan Drell, Sheldon Glashow, Steve Hamburg, Henry Jacoby, Henry Kelly, Mark Kon, Todd Kuiken, Mary Lidstrom, Mike MacCracken, June Medford, Jerry Melillo, Ron Milo, Pilar Ossorio, Ari Patrinos, Keith Paustian, Kristala Jones Prather, Kent Redford, David Resnik, John Reilly, Richard J. Roberts, Daniel Segre, Susan Solomon, Elizabeth Strychalski, Chris Voigt, Dominic Woolf, Stan Wullschleger, and Xiaohan Yang) identified a range of possibilities by which SSB might help reduce greenhouse gas concentrations and which might also contribute to environmental sustainability and adaptation. These include, among other possibilities, engineering plants to convert CO2 produced by respiration into a stable carbonate, designing plants with an increased root-to-shoot ratio, and creating plants with the ability to self-fertilize. A number of serious ecological and societal challenges must, however, be confronted and resolved before any such application can be fully assessed, realized, and deployed.

Using Big Data to Understand the Human Condition: The Kavli HUMAN Project.

Until now, most large-scale studies of humans have either focused on very specific domains of inquiry or have relied on between-subjects approaches. While these previous studies have been invaluable for revealing important biological factors in cardiac health or social factors in retirement choices, no single repository contains anything like a complete record of the health, education, genetics, environmental, and lifestyle profiles of a large group of individuals at the within-subject level. This seems critical today because emerging evidence about the dynamic interplay between biology, behavior, and the environment point to a pressing need for just the kind of large-scale, long-term synoptic dataset that does not yet exist at the within-subject level. At the same time that the need for such a dataset is becoming clear, there is also growing evidence that just such a synoptic dataset may now be obtainable-at least at moderate scale-using contemporary big data approaches. To this end, we introduce the Kavli HUMAN Project (KHP), an effort to aggregate data from 2,500 New York City households in all five boroughs (roughly 10,000 individuals) whose biology and behavior will be measured using an unprecedented array of modalities over 20 years. It will also richly measure environmental conditions and events that KHP members experience using a geographic information system database of unparalleled scale, currently under construction in New York. In this manner, KHP will offer both synoptic and granular views of how human health and behavior coevolve over the life cycle and why they evolve differently for different people. In turn, we argue that this will allow for new discovery-based scientific approaches, rooted in big data analytics, to improving the health and quality of human life, particularly in urban contexts.

Realizing the potential of the genome revolution: the genomes to life program.

The systems biology revolution is proceeding along multiple pathways as different science agencies and the private sector have adopted strategies suited to their particular needs and cultures. To meet this challenge, the U.S. Department of Energy has developed the Genomes to Life (GTL) program. A central focus of GTL is environmental microbial biology as a way to approach global environmental problems, and its key goal is to achieve, over the next 10 to 20 years, a basic understanding of thousands of microbes and microbial systems in their native environments. This focus demands that we address huge gaps in knowledge, technology, computing, data storage and manipulation, and systems-level integration.

Stepping up the pace of discovery: the genomes to life program.

Genome to life (GTL), the U.S Department of Energy Office of Science's systems biology program, focuses on environmental microbiology. Over the next 10 to 20 years, GTL's key goal is to understand the life processes of thousands of microbes and microbial systems in their native environments. This focus demands that we address huge gaps in knowledge, technology, computing, data capture and analysis, and systems-level integration. Distinguishing features include (1) strategies for unprecedented, comprehensive, and high-throughput data collection; (2) advanced computing, mathematics, algorithms, and data-management technologies; (3) a focus on potential microbial capabilities to help solve energy and environmental challenges; and (4) new research and management models that link production-scale systems biology facilities in an accessible environment. This unprecedented opportunity to provide the scientific foundation for solving urgent problems in energy, global climate change, and environmental cleanup demands that we take bold steps to achieve a much faster, more efficient pace of biological discovery.