Long-term analysis of the Arabidopsis thaliana leaf microbiome in Germany
Creators
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Mahmoudi, Maryam
(Contact person)1
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Jalali, Hamed
(Data manager)1
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Runge, Paul
(Data collector)1
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Almario, Juliana
(Data collector)2
- Ruhe, Jonas (Data collector)1
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Gómez Pérez, Daniel
(Data collector)3
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Mari, Alfredo
(Data collector)4
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Kroll, Samuel
(Data collector)5
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Seabra, Ana Rita
(Data collector)6
- Krohn, Maria (Data collector)1
- Placzek, Aleksandra (Data collector)1
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Agler, Matthew
(Data collector)7
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Kemen, Ariane
(Data collector)1
- Klenk, Elke (Data collector)1
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Chaudhry, Vasvi
(Data collector)1
- Lutap, Katrina (Data collector)1
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Kemen, Eric
(Supervisor)1
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1.
University of Tübingen
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2.
Université Claude Bernard Lyon 1
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3.
Earlham Institute
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4.
University of Basel
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5.
University of Cologne
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6.
University of Lisbon
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7.
Friedrich Schiller University Jena
Description
This project investigates the phyllosphere of Arabidopsis thaliana, beginning with a field study that collected samples from natural ecosystems in Tübingen, Germany, over a span of six years. DNA was extracted from the leaves and analyzed using two distinct assays. The first assay, amplicon sequencing, was used to characterize the leaf microbiome, including bacteria and eukaryotes. The second assay, whole-genome sequencing, analyzed the host's genetic material.
To explore this project and its related datasets, please refer to this public repository:
https://gitlab.nfdi4plants.de/maryam_mahmoudi/LongTermLeafMicrobiomeOfArabidopsisGermany
Files
LongTermLeafMicrobiomeOfArabidopsinGermany-FDAT_release_000.zip
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Additional details
Identifiers
Related works
- Is original form of
- Text: 10.1093/ismeco/ycae103 (DOI)
- Text: 10.1371/journal.pbio.1002352 (DOI)
- Is source of
- Text: 10.1101/2024.10.25.620230 (DOI)
- Text: 10.1093/ismeco/ycae117 (DOI)
- Text: 10.1111/nph.18995 (DOI)
Data quality
- Accuracy
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This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Completeness
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Conformity
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Consistency
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Credibility
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Processability
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Relevance
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Timeliness
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.
- Understandability
-
This dataset has been created based on the Annotated Research Context (ARC). ARC is a framework for organizing and documenting research data. It also serves as a container that continuously supports collaboration, data exchange, and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) among various researchers. The ARC framework can be assessed for completeness and quality at any time and is built on widely accepted research data standards, such as ISA (Investigation, Study, Assay). This project encompasses experimental data, annotation and metadata, computational processes, protocols, and other necessary information related to the entire research project life cycle.