Missing Genomic Resources for the Next Generation of Environmental Risk Assessment.

genomics new approach methodologies next generation risk assessment predictive ecotoxicology systems ecotoxicology

Journal

Environmental science & technology
ISSN: 1520-5851
Titre abrégé: Environ Sci Technol
Pays: United States
ID NLM: 0213155

Informations de publication

Date de publication:
21 Jan 2024
Historique:
medline: 21 1 2024
pubmed: 21 1 2024
entrez: 21 1 2024
Statut: aheadofprint

Résumé

Environmental risk assessment traditionally relies on a wide range of in vivo testing to assess the potential hazards of chemicals in the environment. These tests are often time-consuming and costly and can cause test organisms' suffering. Recent developments of reliable low-cost alternatives, both in vivo- and in silico-based, opened the door to reconsider current toxicity assessment. However, many of these new approach methodologies (NAMs) rely on high-quality annotated genomes for surrogate species of regulatory risk assessment. Currently, a lack of genomic information slows the process of NAM development. Here, we present a phylogenetically resolved overview of missing genomic resources for surrogate species within a regulatory ecotoxicological risk assessment. We call for an organized and systematic effort within the (regulatory) ecotoxicological community to provide these missing genomic resources. Further, we discuss the potential of a standardized genomic surrogate species landscape to enable a robust and nonanimal-reliant ecotoxicological risk assessment in the systems ecotoxicology era.

Identifiants

pubmed: 38245867
doi: 10.1021/acs.est.3c08701
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Marc-Sven Roell (MS)

R&D Bayer AG, Crop Science Division, Monheim am Rhein 40789, Germany.

Mark-Christoph Ott (MC)

R&D Bayer AG, Crop Science Division, Monheim am Rhein 40789, Germany.

Magdalena M Mair (MM)

Bayreuth Center for Ecology and Environmental Research (BayCEER), Bayreuth 95447, Germany.
Statistical Ecotoxicology, University of Bayreuth, Bayreuth 95447, Germany.

Tobias Pamminger (T)

R&D Bayer AG, Crop Science Division, Monheim am Rhein 40789, Germany.

Classifications MeSH