Towards a Joint International Database: Alignment of SSR Marker Data for European Collections of Cherry Germplasm
Matthew Ordidge,
Suzanne Litthauer,
Edward Venison,
Marine Blouin-Delmas,
Felicidad Fernandez-Fernandez,
Monika Höfer,
Christina Kägi,
Markus Kellerhals,
Annalisa Marchese,
Stephanie Mariette,
Hilde Nybom,
Daniela Giovannini
Affiliations
Matthew Ordidge
Department of Crop Science, School of Agriculture, Policy and Development, University of Reading, Reading RG6 6EU, UK
Suzanne Litthauer
NIAB EMR, New Road, East Malling, Kent ME19 6BJ, UK
Edward Venison
Department of Crop Science, School of Agriculture, Policy and Development, University of Reading, Reading RG6 6EU, UK
Marine Blouin-Delmas
INRAE-Unité Expérimentale Arboricole, Domaine de la Tour de Rance, 47320 Bourran, France
Felicidad Fernandez-Fernandez
NIAB EMR, New Road, East Malling, Kent ME19 6BJ, UK
Monika Höfer
Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, Julius Kühn Institute, Pillnitzer Platz 3a, 01326 Dresden, Germany
Christina Kägi
Federal Office for Agriculture, Genetic Resources and Technologies, Schwarzenburgstrasse 165, 3003 Bern, Switzerland
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.