Comparison of phenotypic and molecular marker-based classifications of hard red winter wheat cultivars

• Published in: Euphytica 2005-09, Vol.145 (1-2), p.133-146
• Main Authors: Fufa, H, Baenziger, P.S, Beecher, B.S, Dweikat, I, Graybosch, R.A, Eskridge, K.M
• Format: Article
• Language: English
• Subjects: agronomic traits; Agronomy. Soil science and plant productions; Biological and medical sciences; Correlation coefficient; Crop improvement; cultivar identification; Cultivars; Estimates; Fundamental and applied biological sciences. Psychology; Generalities. Genetics. Plant material; genetic distance; Genetic diversity; genetic markers; Genetic resources, diversity; genetic variation; Genetics and breeding of economic plants; gliadin; glutenins; hard red winter wheat; microsatellite repeats; milling quality; Plant material; secalins; seeds; sequence related amplified polymorphism; storage proteins; Triticum aestivum; wheat flour; Winter wheat
• ISSN: 0014-2336; 1573-5060
• DOI: 10.1007/s10681-005-0626-3

Genetic diversity is the basis for successful crop improvement and can be estimated by different methods. The objectives of this study were to estimate the genetic diversity of 30 ancestral to modern hard red winter wheat (Triticum aestivum L.) cultivars adapted to the Northern Great Plains using pedigree information, morphological traits (agronomic measurements from six environments), end-use quality traits (micro-quality assays on 50 g grain or milled flour samples for the six environments), and molecular markers (seed storage proteins separated using SDS-PAGE, 51 SSRs, and 23 SRAP DNA markers), and to determine the relationships of genetic distance estimates obtained from these methods. Relationships among diversity estimates were determined using simple (Pearson) and rank (Spearman) correlation coefficients between distance estimates and by clustering cultivars using genetic-distances for different traits. All methods found a wide range in genetic diversity. The genetic distance estimates based on pedigree had the highest values due to possible over-estimation arising from model assumptions. The genetic diversity estimates based on seed storage protein were lowest because they were the major determinants of end-use quality, which is a highly selected trait. In general, the diversity estimates from each of the methods were positively correlated at a low level with the exceptions of SRAP diversity estimates being independent of morphologic traits (simple correlation), SDS-PAGE, and SSR diversity estimates (rank correlation). However, SSR markers, thought to be among the most efficient markers for estimating genetic diversity, were most highly correlated with seed storage proteins. The procedures used to accurately estimate genetic diversity will depend largely upon the tools available to the researcher and their application to the breeding scheme.[PUBLICATION ABSTRACT]