Towards a joint international database: alignment of SSR marker data for european collections of cherry germplasm
2021
Ordidge, Matthew | Litthauer, Suzanne | Venison, Edward | Blouin-Delmas, Marine | Fernandez-Fernandez, Felicidad | Höfer, Monika | Kägi, Christina | Kellerhals, Markus | Marchese, Annalisa | Mariette, Stéphanie | Nybom, Hilde | Giovannini, Daniela | University of Reading (UOR) | National Institute of Agricultural Botany (NIAB) | Unité Expérimentale Arboricole (UE ARBO) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Julius Kühn-Institut (JKI) | Office Fédéral de l'Agriculture - Federal Office for Agriculture - Bundesamtes für Landwirtschaft [Berne] (OFAG) | Agroscope | Università degli studi di Palermo - University of Palermo (UNIPA) | Biodiversité, Gènes & Communautés (BioGeCo) ; Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet (SLU) | Research Centre on Food and Nutrition (CREA) ; Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA) | This research was funded by the European Cooperative Program for Plant Genetic Resources: Activity Grant Scheme (Project: Prunus Alignment) and Defra, UK (Project: GC0147 The Long Term Housing, Maintenance and Scientific Curation of the [UK] National Fruit Collections).
International audience
Show more [+] Less [-]English. 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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