|Brummer, Charlie -|
Submitted to: International Symposium of Molecular Breeding of Forage Turf
Publication Type: Abstract Only
Publication Acceptance Date: January 15, 2010
Publication Date: March 15, 2010
Citation: Casler, M.D., Brummer, C. 2010. 40 Years of Genetic Diversity Studies: What Have We Learned and Where Do We Go From Here [abstract]? International Symposium of Molecular Breeding of Forage Turf. p16. Technical Abstract: As DNA marker systems have evolved into platforms that are more readily accessible to a wider range of researchers, genetic diversity studies have expanded our knowledge of genetic structure within many forage and turf species. We take for granted now that about 70-90% of the genetic variability within an allogamous species resides within traditional cross-pollinated and random mating populations or synthetic cultivars. It is unlikely that we would have predicted these values simply from observations of among- and within-population phenotypic variability. Of course, these data now help us to explain why we can make selection progress in populations of extremely limited or narrow pedigree, such as a single half-sib or selfed family. On a broad scale, genetic diversity studies have been extremely useful in taxonomic classifications such as clarification of species relationships, taxonomic reclassification of species, species assignments of unknown plants, identification of genetic structure or groups within species, and quantification of gene flow among and within related species. On a narrow scale, genetic diversity studies provide a mechanism to identify plants with similar or divergent genetic backgrounds with much greater confidence and precision than is possible from phenotypic or passport information. The most useful genetic diversity studies are those with a clear purpose or objective and a germplasm base that is specifically chosen to accomplish that objective. With very few exceptions, genetic diversity studies have not yet allowed us to predict heterotic patterns within forage or turf species, predict genetic gains for quantitative traits within segregating populations, or conclusively identify plants from synthetic cultivars. However, just as advances in software and statistical analysis methods have allowed identification of DNA markers associated with quantitative traits through association mapping, future advances in marker platforms, software, and statistics will likely lead to advances to solve these and other problems.