Combining ex situ and in situ data in the Musa Germplasm Information System (MGIS)
Genetic Resources are made available to researchers, breeders, farmers and other stakeholders in the agricultural sector who need to identify and select germplasm based on a combination of passport, genotypic and phenotypic data. Therefore, documenting this germplasm is critical in order to facilitate its effective use. Integrated information systems powered by large databases are thus required to achieve this objective. The Musa Germplasm Information System (MGIS) (www.cropdiversity. org/mgis) has been developed to address those needs in a user-friendly way. Since 1997, the efforts of documenting banana (Musa spp.) gene banks worldwide have been supported in the MusaNet (www.musanet.org) by a dedicated database called Musa Germplasm Information System (MGIS) to provide standardized passport and characterization data. During recent years, tremendous progress in genotyping and phenotyping allowed scientists to generate a huge amount of data for material maintained in gene banks. Therefore, we started to map of individual accession with data from literature in order to link germplasm with those datasets. As an example, MGIS manages diversity trees with dedicated viewers, and enable retrieval of individual of underlying SNP markers using modern bioinformatic tools. User-friendly interfaces are being developed in parallel for phenotyping datasets annotated with the banana ontology. Finally, we have been testing solutions to facilitate the capture and display of in situ information. For instance, MGIS harvests worldwide observations of banana plants from anyone registered in the Banana natural biodiversity mapping project in iNaturalist (www.inaturalist.org/projects/banana-natural-biodiversity-mapping). Combining this dataset with collecting mission locations will allow us to identify possible gaps in Musa collections. The challenges remain to improve the navigation among these heterogeneous datasets in order to display meaningful information adapted to the audience and to link it with relevant environmental and socio-economic data.
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
IRD
|
| Online Access: | http://agritrop.cirad.fr/595535/ http://agritrop.cirad.fr/595535/1/ID595535.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Genetic Resources are made available to researchers, breeders, farmers and other stakeholders in the agricultural sector who need to identify and select germplasm based on a combination of passport, genotypic and phenotypic data. Therefore, documenting this germplasm is critical in order to facilitate its effective use. Integrated information systems powered by large databases are thus required to achieve this objective. The Musa Germplasm Information System (MGIS) (www.cropdiversity. org/mgis) has been developed to address those needs in a user-friendly way. Since 1997, the efforts of documenting banana (Musa spp.) gene banks worldwide have been supported in the MusaNet (www.musanet.org) by a dedicated database called Musa Germplasm Information System (MGIS) to provide standardized passport and characterization data. During recent years, tremendous progress in genotyping and phenotyping allowed scientists to generate a huge amount of data for material maintained in gene banks. Therefore, we started to map of individual accession with data from literature in order to link germplasm with those datasets. As an example, MGIS manages diversity trees with dedicated viewers, and enable retrieval of individual of underlying SNP markers using modern bioinformatic tools. User-friendly interfaces are being developed in parallel for phenotyping datasets annotated with the banana ontology. Finally, we have been testing solutions to facilitate the capture and display of in situ information. For instance, MGIS harvests worldwide observations of banana plants from anyone registered in the Banana natural biodiversity mapping project in iNaturalist (www.inaturalist.org/projects/banana-natural-biodiversity-mapping). Combining this dataset with collecting mission locations will allow us to identify possible gaps in Musa collections. The challenges remain to improve the navigation among these heterogeneous datasets in order to display meaningful information adapted to the audience and to link it with relevant environmental and socio-economic data. |
|---|