Ecobiomics: Environmental metagenomic biomonitoring
Notice bibliographique
Résumé
Land use disturbances are having enormous adverse impacts on the biodiversity and integrity of natural and managed ecosystems around the world. Adverse impacts on biodiversity are compromising ecosystem services and processes, reducing ecosystem resilience, and leading to unpredictable ecosystem responses to environmental change. The Metagenomics-Based Ecosystem Biomonitoring Project (EcoBiomics) focuses on the urgent need to better understand the extent and significance of ongoing changes to biodiversity in the soil and aquatic ecosystems that sustain essential ecosystem services upon which Canadians and the Canadian economy depend. This project uniquely recognizes that a breadth of scientific expertise from within the Canadian government is required to undertake this research, which is spread across relevant departments and agencies with Biodiversity portfolios. It involves over 50 participants (researchers, technicians, bioinformaticians, software developers, managers and students, etc.) contributing to many smaller projects in several locations across Canada organized by themes. The objectives of this project include: Develop standard soil and water methods and a federal Bioinformatics Platform to harmonize analyses of metabarcoding, metagenomics and metatranscriptomics data across federal departments/agencies; Establish genomic observatories and comprehensive biodiversity baselines for assessing future changes to water and soil biodiversity at long-term environmental monitoring sites in Canada; Develop new knowledge to improve water quality and soil health by comprehensively characterizing aquatic microbiomes, soil microbiomes, and invertebrate zoobiomes, and testing hypotheses to enhance environmental assessment, monitoring, and remediation activities. Develop standard soil and water methods and a federal Bioinformatics Platform to harmonize analyses of metabarcoding, metagenomics and metatranscriptomics data across federal departments/agencies; Establish genomic observatories and comprehensive biodiversity baselines for assessing future changes to water and soil biodiversity at long-term environmental monitoring sites in Canada; Develop new knowledge to improve water quality and soil health by comprehensively characterizing aquatic microbiomes, soil microbiomes, and invertebrate zoobiomes, and testing hypotheses to enhance environmental assessment, monitoring, and remediation activities. Our poster will focus primarily on the challenges associated with the first objective. Genomic technologies are revolutionizing biodiversity assessment in soil and aquatic ecosystems, and they now offer the only practical way to comprehensively characterize this enormous biodiversity. These technologies and associated tools allow us to obtain comprehensive baseline biodiversity data that are essential to support evidence-based decision-making. However, a strong focus of this project is to enable environmental assessment, monitoring, and remediation activities by a multitude of potential end users and thus standardized protocols and processes must be determined and shared. For the data generated, several procedures were defined. A minimum metadata profile related to the sampling event is required for all projects, which follows existing standards including the DarwinCore (https://dwc.tdwg.org). Sample preparation was also standardized based primarily on protocols developed in earlier projects that were validated for use in Ecobiomics, for example the Earth Microbiome Project (http://www.earthmicrobiome.org). The procedures for DNA extraction through sequencing largely followed the Minimum Information about “X” Sequence (MIxS) standard (gensc.org/mixs). This data is all input into an in-house custom-built software package, Sequence Database (SeqDB) used by all participants across the entire project, which is made available centrally via a federal high-performance computing centre. SeqDB not only stores the metadata and data generated but also maintains provenance based on defined workflows for metabarcoding, shotgun metagenomics, and other “omics” pipelines. It also supports project management through various metrics and visualizations. We will document some of the challenges to standardizing data and workflows in large multi-domain and multi-department project like Ecobiomics and the need for further standard development to truly support data sharing and integration across a highly diverse ecosystem of genomic observatories globally.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,004 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».