Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Journal Article · 08 March 2023 · Ecology and Evolution

DOI: https://doi.org/10.1002/ece3.9872 · OSTI ID:1960454

Martinez, Neo D.  ^[1]

---

1. Center for Complex Networks and Systems, School of Informatics, Computing, and Engineering Indiana University, Bloomington Indiana Bloomington USA, Pacific Ecoinformatics and Computational Ecology Lab CA Berkeley USA

Abstract Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

• Research Organization: Univ. of California, Oakland, CA (United States)
• Sponsoring Organization: National Science Foundation (NSF); USDOE; USDOE Office of Science (SC)
• Grant/Contract Number: SC0016247
• OSTI ID: 1960454
• Journal Information: Ecology and Evolution, Journal Name: Ecology and Evolution Journal Issue: 3 Vol. 13; ISSN 2045-7758
• Publisher: Wiley Blackwell (John Wiley & Sons)Copyright Statement
• Country of Publication: United Kingdom
• Language: English