# FAIR characterization data of genetic resources: making it real?

Anne-Françoise Adam-Blondon

► To cite this version:

Anne-Françoise Adam-Blondon. FAIR characterization data of genetic resources: making it real?. INTEGRAPE 2021 - Achievements, industry needs and next steps, Anne-Françoise Adam-Blondon; Mario Pezzotti, Jun 2021, Virtuel, France. hal-03316847

HAL Id: hal-03316847

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Submitted on 6 Aug 2021

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Distributed under a Creative Commons Attribution 4.0 International License
Data integration to maximise
the power of omics
for grapevine
improvement

# FAIR characterization data of genetic resources: making it real?

A-F Adam-Blondon (INRAE, FR)

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# Genetic Resources are key for changing our model of agriculture and meet current challenges

* Adapt to climate change

* No use of chemicals

* Increase biodiversity

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Develop agro-ecological practices
# Enhancing access to data on genetic resources to better monitor their conservation and enhance their use

Development of a common « European Genetic Resources Strategy » with strong recommendations on:

* Enhancing the characterization of genetic resources as a lever for their better use

* Developing FAIR compliant data management practices as a lever for enhancing access to data and knowledge on genetic resources

An instrument developed by ECPGR: the facilitation of public-private European Evaluation (EVA) Networks of genetic resources
[https://www.ecpgr.cgiar.org/european-evaluation-network-eva](https://www.ecpgr.cgiar.org/european-evaluation-network-eva)

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In collaborative projects involving public and private sector partners and through participatory plant breeding actions EVA is generating standardized evaluation data (phenotypic and genotypic) data for numerous crop accessions and landraces available in European gene banks. EVA is implemented through crop-specific networks, covering both cereal and vegetable crops.

Right now there are networks for as different crops. Follow the links to find out more about each crop network!

For more information or if you are interested in joining the EVA network, please contact EVA coordinator

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# Building « federation » of interoperable information systems about RG

* Networking with many stakeholders at the international level : facilitators such as international infrastructures (GBIF, ELIXIR), consortia (DivSeek), governed networks (ECPGR, ERFP, EUFGIS)

* Networking with many stakeholders at the national level: facilitators National Focal Points/Inventories, national infrastructures/institutes

DATA archiving
Ensuring
interoperability

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DATA quality,
standardization
# Needs for sustaining the building of such federation

* Skills: data stewards

* Guidelines, recommendations for FAIR compliant data management: general and domain related specifications; associated to catalogs

* Operational implementations of these guidelines by:

* Partners from the ELIXIR plant Science community

* Genbank managers

* Wheat and barley european public-private evaluation network

* Academic researchers

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CONVERGE
https://elixir-europe.org/

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AGENT

Activated Genbank Network
https://agent-project.eu/
# SKILLS: bringing the different dimensions of data stewardship in the GR documentation activities

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The EC high level expert group EOSC estimated 3 FTE per 100 researchers are necessary

* Build awareness and capacity across the whole network

* Leverage existing resources from international initiatives: training, tools, ressources

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https://tess.elixir-europe.org/

From Scholtens et al. (2019)

https://doi.org/10.5281/zenodo.3471707

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# Guidelines: capitalizing across Europe

ELIXIR-CONVERGE project: development of a comprehensive repository of guidelines for FAIR data management in the Life Sciences with a participatory approach.

https://rdmkit.elixir-europe.org/ first version launched in April 2021

## RDMkit – what are the components?

Written by field workers in the language of the community

### RDM Lifecycle

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### Guidelines
both generic & specific

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### Tools and resources

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### Role

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### Registries

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### Example tool assemblies

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# Guidelines: capitalizing across Europe

ELIXIR-CONVERGE project: A gateway to resources supporting FAIR data management for research in the Life Sciences.

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# Guidelines: domain specificities

ELIXIR-CONVERGE project: Domain pages -> Plant Sciences pages of the ELIXIR Plant Science community.

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RDMkit

About

Contribute

GitHub

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Give feedback

Data life cycle +

Your role +

Your domain -

Plant sciences

## Relevant tools and resources

<table><thead><tr><th>Tool or resource</th><th>Description</th><th>Tags</th><th>Registry</th></tr></thead><tbody><tr><td>BioSamples</td><td>BioSamples stores and supplies descriptions and metadata about biological samples used in research and development by academia and industry.</td><td>metadata plants</td><td></td></tr><tr><td>BioStudies</td><td>A database hosting datasets from biological studies. Useful for storing or accessing data that is not compliant for mainstream repositories.</td><td>micro biotech metadata plants</td><td></td></tr><tr><td>BrAPI</td><td>Specification for a standard API for plant data: plant material, plant phenotyping data</td><td>IT support plants</td><td></td></tr><tr><td>COPO</td><td>Portal for scientists to broker more easily rich metadata alongside data to public repos.</td><td>metadata researcher plants</td><td></td></tr><tr><td>Crop Ontology</td><td>The Crop Ontology compiles concepts to curate phenotyping assays on crop plants, including anatomy, structure and phenotype.</td><td>researcher data manager IT support plants</td><td></td></tr></tbody></table>

## Plant sciences

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Edit me

* Introduction

* Plant phenotyping metadata management

* phenotyping data sharing and deposition

* relating plant phenotypic and molecular

* plant tools and resources

*aging materials on plant data management

## Action

Science domain includes studying the adaptation of plants to their environment.

Guidelines meant to better connect plant genetic resources with their characterization data
# COST Integrape is declining for grapevine the plant domain guidelines

http://www.integrape.eu/index.php/resources/data-management

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You are here: Home › Resources › Data management

## Data management

### Guidelines for Data Management

The scope of these guidelines is to give recommendations to provide meaningful information on experiments, starting with the plant material used. Additionally, we set up an ontology for the organs, some of them being not present in general plant ontologies, as well as some recommendations to describe the phenological stages. This will allow a more accurate and standard description of grapevine biological samples. This will support the grapevine research community in opening its data according to the FAIR principles.

- How to describe an experiment

- How to submit sequence data to ENA

- How to submit metabolomic data to MetaboLights

- How to standardize JBrowse's tracks

- Apollo Manual Curation Guide for the PN40024.v4 assembly (under construction)

Use them and give feedback!
# From guidelines to implementation : planning the data and metadata capture

## Set of Genebank Accessions

* Unique identifiers

Derived material

## Lots, Cuttings, Samples

* Unique identifiers

* Developmental stages

* Sampling method

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Sample preparation

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Image acquisition

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## Phenotypic/genomic raw data

* Experimental protocole

* Trait identifiers/standards vocabularies

Environmental conditions

Factor

Environment

Data recording

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Light quantity,
Light quality,
Nutrients,
Air humidity,
Water,
Temperature,

⋮

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Molecular work

DNA sequencing,
RNA sequencing,
Expression profiling,
Genetic profiling
Biochemical regulation,
Protein identification,
Protein quantification,
Hormones and Other molecular study.

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Data= Phenotypic data
+ Molecular data
+ Environmental data

Phenotype image data

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## Phenotypic/genomic processed data (e.g. quality control)

* Data analysis process

* Reference data sets

## Final published dataset

* Project description

* Authors

* Data integration & analysis process

* DATASET WITH ALL METADATA

Phenotypic data

Height, area(ton/side).

cc
sa

## Phenotypic/genomic curated data

* Data analysis process

* Reference data sets

ization 2020 Framework Programme
nion

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# From guidelines to implementation : planning the data and metadata capture

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* Example: current AGENT workflow phenotyping data management

* Problems to be solved:

* getting international ID

* namings for phenotyping variables

* MIAPPE/EURISCO templates
# Platforms facilitating the capture of metadata

Seek/FAIRDOM: https://fairdomhub.org/

* Develop projects containers within FAIRDOMhub

* Develop a private instance of Seek/FAIRDOM

* CESGO (https://www.cesgo.org/fr/): a service for data management proposed by the GenOuest facility of ELIXIR-FR

* pISA-Tree: Standard Directory Tree as a support for Reproducible Research (https://github.com/ablejec/pISA-tree) used for data management in the H2020 adapt project (Developing heat- and drought-stress tolerant potatoes)

* FAIRDOM instance for the data management of the H2020 AGENT project

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# FAIRDOM supports the ISA data model

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# Trainings/datathons, coordination and governance

* Are necessary to understand and agree on details (this is where the devil lies usually)

* To agree on who is responsible of what when decision and actions are necessary (the devil is here also)

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## Examples:

Who is responsible for issuing DOI to accessions (Laboratories, Genbanks, national focal points or EURISCO)?

Who is responsible for issuing unique Sample identifiers and do we use also project internal ID in addition of BioSample IDs?
Still a long way to go but we can help each others

* Sharing experience on guidelines implementations

* Contributing to raise awareness

* In the scientific community about guidelines and best practices

* To our institutes and funders: on the importance of skills and means for data stewardship.

* See for instance OECD (2020), "Building digital workforce capacity and skills for data-intensive science", *OECD Science, Technology and Industry Policy Papers*, n° 90, Éditions OCDE, Paris, https://doi.org/10.1787/e08aa3bb-en.

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COST Action
CA 17111
INTEGRAPE
# Aknowledgements

## GenRes Bridge partners (WP4)

* M. Bozzano (EFI, coord), M. Westergren (Gozdis)

* S. Weise (IPK), T. Van Hintum (WUR)

* E. Charvolin-Lemaire (INRAE), D. Laloe (INRAE), M. Boichard (INRAE)

* S. Sharrock (BGCI)

* E. Sturaro (Unipd)

* S.Goritschnig (Cgiar/ECPGR)

## ELIXIR CONVERGE partners (too many...)

* Hub: N. Blomberg, J. Arenas (coord. and management)

* C. Goble (UK) and F. Coppens (BE; WP3 and RDMkit)

* S. Cappella and L. Portell (SP; WP5 and use cases)

* D. Faria: Plant use case (PT)

## AGENT partners (too many...)

* N. Stein (IPK, coord)

* P. Kersey (RBGK), M. Alaux (INRAE), S. Weise (IPK), C. Pommier (INRAE), M. Lange (IPK), R. Finkers (WUR), J. Destin (INRAE)

* V. Holubec (CRI; link with phenotyping WP)

* The GenRes Bridge project has received fundings from the European Union's Horizon 2020 research and innovation programme under grant agreement No 817580

* The ELIXIR-CONVERGE project has received fundings from the European Union's Horizon 2020 research and innovation programme under grant agreement No 817580

* The AGENT project has received fundings from the European Union's Horizon 2020 research and innovation programme under grant agreement No 862613

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Thank you!

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