Microsatellites for cultivar identification in Pelargonium View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2000-09

AUTHORS

S. A. Becher, K. Steinmetz, K. Weising, S. Boury, D. Peltier, J.-P. Renou, G. Kahl, K. Wolff

ABSTRACT

We have isolated and characterised microsatellite loci from Pelargonium sp. to explore the potential of these markers for cultivar identification. Small-insert libraries from a zonal (Pelargoniumxhortorum cv. Isabell) and an ivy-leaved variety (P. peltatum cv. Guenievre gergue) were enriched for d(AG), d(AC), d(CAA), d(GAA) and d(GATA) repeats. Of 141 positive clones sequenced, 133 contained a microsatellite. Primers for PCR amplification were designed to the flanking regions of 57 microsatellites, resulting in interpretable amplification products of the expected size for 29 loci. Seventeen primer pairs amplifying 18 loci were used to fingerprint 44 di- and tetra-ploid Pelargonium accessions representative of commercially available varieties. Multilocus genotypes obtained at 3 loci distinguished among all accessions, except for three known flower colour sports and a fourth, phenotypically very similar, variety. Allelic composition was also identical within two other sport ’families’ typed at the same 18 loci. UPGMA and principal co-ordinate analysis of pairwise distance matrices derived from PCR amplification patterns revealed four distinct assemblages. The first group consisted of tetraploid P.x hortorum varieties; a second group contained diploid P. x hortorum, a third, tetraploid P. peltatum accessions, while a fourth, very distinct, group consisted solely of diploid P. peltatum varieties. Polymorphism in P. peltatum was equal or greater than in P. x hortorum at 17 of the 18 loci, indicating that the analysed P. peltatum varieties form a genetically more variable array. More... »

PAGES

643-651

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s001220051526

DOI

http://dx.doi.org/10.1007/s001220051526

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025959540


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