Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology
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 genot...
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| Format: | Article |
| Language: | English |
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Wiley
2023-03-01
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| Series: | Ecology and Evolution |
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| Online Access: | https://doi.org/10.1002/ece3.9872 |
| _version_ | 1797857497859489792 |
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| author | Neo D. Martinez |
| author_facet | Neo D. Martinez |
| author_sort | Neo D. Martinez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T20:57:34Z |
| format | Article |
| id | doaj.art-974d212365964d46b20e7c6fcc8a8b5b |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-04-09T20:57:34Z |
| publishDate | 2023-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-974d212365964d46b20e7c6fcc8a8b5b2023-03-29T14:14:47ZengWileyEcology and Evolution2045-77582023-03-01133n/an/a10.1002/ece3.9872Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biologyNeo D. Martinez0Center for Complex Networks and Systems, School of Informatics, Computing, and Engineering Indiana University, Bloomington Indiana Bloomington USAAbstract 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.https://doi.org/10.1002/ece3.9872computationdata scienceecologyecosystemenvironmental nucleic acidsevolution |
| spellingShingle | Neo D. Martinez Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology Ecology and Evolution computation data science ecology ecosystem environmental nucleic acids evolution |
| title | Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology |
| title_full | Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology |
| title_fullStr | Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology |
| title_full_unstemmed | Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology |
| title_short | Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology |
| title_sort | predicting ecosystem metaphenome from community metagenome a grand challenge for environmental biology |
| topic | computation data science ecology ecosystem environmental nucleic acids evolution |
| url | https://doi.org/10.1002/ece3.9872 |
| work_keys_str_mv | AT neodmartinez predictingecosystemmetaphenomefromcommunitymetagenomeagrandchallengeforenvironmentalbiology |