Development and assessment of Diversity Arrays Technology for high-throughput DNA analyses in Musa.
Diversity Arrays Technology (DArT) is a DNA hybridisation-based molecular marker technique that can detect simultaneously variation at numerous genomic loci without sequence information. This efficiency makes it a potential tool for a quick and powerful assessment of the structure of germplasm collections. This article demonstrates the usefulness of DArT markers for genetic diversity analyses of Musa spp. genotypes. We developed four complexity reduction methods to generate DArT genomic representations and we tested their performance using 48 reference Musa genotypes. For these four complexity reduction methods, DArT markers displayed high polymorphism information content. We selected the two methods which generated the most polymorphic genomic representations (PstI/BstNI 16.8%, PstI/TaqI 16.1%) to analyze a panel of 168 Musa genotypes from two of the most important field collections of Musa in the world: Cirad (Neufchateau, Guadeloupe), and IITA (Ibadan, Nigeria). Since most edible cultivars are derived from two wild species, Musa acuminata (A genome) and Musa balbisiana (B genome), the study is restricted mostly to accessions of these two species and those derived from them. The genomic origin of the markers can help resolving the pedigree of valuable genotypes of unknown origin. A total of 836 markers were identified and used for genotyping. Ten percent of them were specific to the A genome and enabled targeting this genome portion in relatedness analysis among diverse ploidy constitutions. DArT markers revealed genetic relationships among Musa genotype consistent with those provided by the other markers technologies, but at a significantly higher resolution and speed and reduced cost.
Risterucci, A.M.; Hippolyte, I.; Perrier, X.; Xia, L.; Caig, V.; Evers, M.; Huttner, E.; Kilian, A.; Glaszmann, J.C. Development and assessment of Diversity Arrays Technology for high-throughput DNA analyses in Musa. TAG Theoretical and Applied Genetics (2009) 119 (6) 1093-1103. [DOI: 10.1007/s00122-009-1111-5]