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Towards a joint international database: Alignment of ssr marker data for european collections of cherry germplasm

Zugehörigkeit
University of Reading, Department of Crop Science, School of Agriculture, Policy and Development, United Kingdom
Ordidge, Matthew;
Zugehörigkeit
NIAB EMR, United Kingdom
Litthauer, Suzanne;
Zugehörigkeit
University of Reading, Department of Crop Science, School of Agriculture, Policy and Development, United Kingdom
Venison, Edward;
Zugehörigkeit
INRAE-Unité Expérimentale Arboricole, Domaine de la Tour de Rance, France
Blouin-Delmas, Marine;
Zugehörigkeit
NIAB EMR, United Kingdom
Fernandez-Fernandez, Felicidad;
GND
1059103419
Zugehörigkeit
Julius Kühn-Institute (JKI), Institute for Breeding Research on Fruit Crops, Germany
Höfer, Monika;
Zugehörigkeit
Federal Office for Agriculture, Genetic Resources and Technologies, Switzerland
Kägi, Christina;
Zugehörigkeit
Agroscope, Strategic Research Division Plant Breeding, Switzerland
Kellerhals, Markus;
Zugehörigkeit
University of Palermo, Department of Agricultural, Food and Forest Sciences, Italy
Marchese, Annalisa;
Zugehörigkeit
University of Bordeaux, BIOGECO, INRAE, France
Mariette, Stephanie;
Zugehörigkeit
Swedish University of Agricultural Sciences, Balsgård-Department of Plant Breeding, Sweden
Nybom, Hilde;
Zugehörigkeit
CREA-Research Centre for Olive, Fruit and Citrus Crops, Italy
Giovannini, Daniela

The objective of our study was the alignment of microsatellite or simple sequence repeat (SSR) marker data across germplasm collections of cherry within Europe. Through the European Cooperative program for Plant Genetic Resources ECPGR, a number of European germplasm collections had previously been analysed using standard sets of SSR loci. However, until now these datasets remained unaligned. We used a combination of standard reference genotypes and ad-hoc selections to compile a central dataset representing as many alleles as possible from national datasets produced in France, Great Britain, Germany, Italy, Sweden and Switzerland. Through the comparison of alleles called in data from replicated samples we were able to create a series of alignment factors, supported across 448 different allele calls, that allowed us to align a dataset of 2241 SSR profiles from six countries. The proportion of allele comparisons that were either in agreement with the alignment factor or confounded by null alleles ranged from 67% to 100% and this was further improved by the inclusion of a series of allele-specific adjustments. The aligned dataset allowed us to identify groups of previously unknown matching accessions and to identify and resolve a number of errors in the prior datasets. The combined and aligned dataset represents a significant step forward in the co-ordinated management of field collections of cherry in Europe.

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