Skip to main content

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

Abstract

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.

This is a preview of subscription content, access via your institution.

Abbreviations

COD:

coefficient of diversity

COP:

coefficient of parentage

GS:

genetic similarity

GD:

genetic distance

GEI:

genotype by environment interaction

HMW:

high molecular weight

LMW:

low molecular weight

SDS-PAGE:

sodium dodecyl sulfate–polyacrylamide gel electrophoresis

SSRs:

simple sequence repeats

SRAPs:

sequence-related amplified polymorphism

References

  • Almanza-Pinzon, M.I., M.L. Warburton, P.N. Fox & M. Khairallah, 2003. Comparison of molecular markers and coefficients of parentage for the analysis of genetic diversity among spring bread wheat accessions. Euphytica 130: 77–86.

    Article  Google Scholar 

  • Baenziger, P.S., D.R. Shelton, M.J. Shipman & R.A. Graybosch, 2001. Breeding for end-use quality: Reflections on the Nebraska experience. Euphytica 119: 95–100.

    Article  Google Scholar 

  • Barrett, B.A., K.K. Kidwell & P.N. Fox, 1998. Comparison of AFLP and pedigree-based genetic diversity assessment methods using wheat cultivars from the Pacific Northwest. Crop Sci 38: 1271–1278.

    Google Scholar 

  • Beer, S.C., W. Siripoonwiwat, L.S.O. Donoughu, E. Souza, D. Mattews & M.E. Sorrells, 1997. Association between molecular markers and quantitative traits in oats germplasm pool: Can we infer linkage? http://www.cabi-publishing.org/jag/index.html.

  • Bohn, M., H.F. Utz & A.E. Melchinger, 1999. Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs, and SSRs and their use for predicting progeny variance. Crop Sci 39: 228–237.

    Google Scholar 

  • Bryan, G.J., P. Stephenson, A.J. Collins, J. Kirby, J.B. Smith & M.D. Gale, 1997. Low levels of DNA sequence variation among adapted genotypes of hexaploid bread wheat. Theor Appl Gent 99: 192–198.

    Article  Google Scholar 

  • Cox, T.S., J.P. Murphy & D.M. Rodgers, 1985. Coefficient of parentages for 400 winter wheat cultivars. In: Agricultural Experiment Station. Kansas State University, Manhattan, USA.

  • Cox, T.S., J.P. Murphy & D.M. Rodgers, 1986. Changes in genetic diversity in the red winter wheat regions of the United States. Proc Natl Acad Sci USA 83: 5583–5586.

    Google Scholar 

  • Domini, P., J.R. Law, R.M.D. Koebner, J.C. Reeves & R.J. Cooke, 2000. Temporal trends in the diversity of UK wheat. Theor Appl Genet 100: 912–917

    Google Scholar 

  • Engles, J.M.M., V.R. Rao, A.H.D. Brown & M.T. Jackson, 2002. Managing Plant Genetic Diversity, p. 487. CABI Publishing, UK.

  • FAO, 1998. The States of the World's Plant Genetic Resources for Food and Agriculture, p. 510. FAO, Rome, Italy.

  • Fufa, H., P.S. Baenziger, B.S. Beecher, R.A. Graybosch, K.M. Eskridge & L A. Nelson, 2005. Genetic improvement trends in agronomic performances and end-use quality characteristics among hard red winter wheat cultivars in Nebraska. Euphytica (in press).

  • Graybosch, R.A., 1992. High molecular weight glutenin subunit composition of cultivars, germplasm and parents of U. S. red winter wheat. Crop Sci 32: 1151–1155

    Google Scholar 

  • Graybosch, R.A. & R. Morris, 1990. An improved SDS-PAGE method for the analysis of wheat endosperm storage proteins. J Cereal Sci 11: 201–212.

    Google Scholar 

  • Graybosch, R.A., J.-H. Lee, C.J. Peterson, D.R. Porter & O.K. Chung, 1999. Genetic, agronomic and quality comparisons of two 1AL.1RS wheat-rye chromosomal translocations. Plant Breed 118: 125–130.

    Article  Google Scholar 

  • Gupta, R.B. & K.W. Shepherd, 1990. Two-step one-dimensional SDS-PAGE analysis of LMW subunits of glutelin. 1. Variation and genetic control of the subunits in hexaploid wheats. Theor Appl Genet 80: 65–74.

    Google Scholar 

  • Gupta, P.K., R.K. Varshney, P.C. Sharma & B. Ramesh, 1999. Molecular markers and their applications in wheat breeding. Plant Breed 118: 369–390.

    Article  Google Scholar 

  • Huang, X.Q., A. Borner, M.S. Roder & M.W. Ganal, 2002. Assessing genetic diversity of wheat (Triticum aestivum L.) germplasm using microsatellite markers. Theor Appl Genet 105: 699–707.

    Article  PubMed  Google Scholar 

  • Kuleung, C., P.S. Baenziger & I. Dweikat, 2004. Transferability of SSR markers among wheat, rye and triticale. Theor Appl Genet 108: 1147–1150.

    Article  PubMed  Google Scholar 

  • Kempthorne, O., 1969. An Introduction to Genetic Statistics. Iowa State University Press, Ames, IA.

    Google Scholar 

  • Kim, H.S. & R.W. Ward, 1997. Genetic diversity in Eastern U.S. soft winter wheat (Triticum aestivum L. em. Thell.) based on RFLPs and coefficient of parentage. Theor Appl Genet 94: 472– 479.

    Article  Google Scholar 

  • Li, G. & C.F. Quiros, 2001. Sequence-related amplified polymorphism (SRAP), a new marker system based on a sample PCR reaction: Its application to mapping and gene tagging in Brassica. Theor Appl Genet 103: 455–461.

    Article  Google Scholar 

  • Manifesto, M.M., A.R. Schlatter, H.E. Hopp, E.Y. Suarez & J. Dubcovsky, 2001. Quantitative evaluation of genetic diversity in wheat germplasm using molecular markers. Crop Sci 41: 682– 690.

    Google Scholar 

  • May, O.L., D.T. Bowman & D.S. Calhoun, 1995. Genetic diversity of U.S upland cotton cultivars released between 1980 and 1990. Crop Sci 35: 1570–1574.

    Google Scholar 

  • Murphy, J.P., T.S. Cox & D.M. Rodgers, 1986. Cluster analysis of red winter wheat cultivars based upon coefficients of parentage. Crop Sci 26: 672–676.

    Google Scholar 

  • Nei, M. & W.H. Li, 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Natl Acad Sci USA 76: 5269–5273.

    PubMed  Google Scholar 

  • Payne, P.I., 1987. Genetics of wheat storage proteins and the effect of allelic variation on bread-making quality. Ann Rev Plant Physiol 38: 141–153.

    Article  Google Scholar 

  • Payne, P.I. & G.J. Lawrence, 1983. Catalogue of alleles for the complex loci, Glu-A1, Glu-B1, and Glu-D1, which code for high-molecular-weight subunits of glutenin in hexaploid wheat. Cereal Res Commun 11: 29–35.

    Google Scholar 

  • Plaschke, J., M.W. Ganal & M.S. Roder, 1995. Detection of genetic diversity in closely related bread wheat using microsatellite markers. Theor Appl Genet 91: 1001–1007.

    Article  Google Scholar 

  • Powell, W., M. Morgante, C. Andree, M. Hanafey, J. Vogel, S. Tingery & A. Rafalski, 1996. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol Breed 2: 225–238.

    Article  Google Scholar 

  • Prasad, M., R.K. Varshney, J K. Roy & H.S. Balyan, 2000. The use of microsatellites for detecting DNA polymorphism, genotype identification and genetic diversity in wheat. Theor Appl Genet 100: 584–592.

    Google Scholar 

  • Roder, M.S., V. Korzun, K. Wendehake, J. Plaschke, M. Tixier, P. Lorey & M.W. Ganal, 1998. A microsatellite map of wheat. Genetics 149: 2007–2023.

    PubMed  Google Scholar 

  • Roldan-Ruiz, I., F.A. Van Eeuwijk, T.J. Gilliland, P. Dubreuil, C. Dillmann, J. Lallemand, M. DeLoose & C.P. Baril, 2001. A comparative study of molecular and morphological methods of describing relationships between perennial ryegrass (Lolium perenne L.) varieties. Theor Appl Genet 103: 1138–1150.

    Article  Google Scholar 

  • Rohlf, F.J., 2000. NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, v. 2.202k. Exeter Software, Setauket, New York.

  • Saghai-Maroof, M.A., K.M. Soliman, R.A. Jorgensen & R.W. Allard, 1984. Ribosomal DNA spacer-length polymorphism in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci USA 81: 8014–8018.

    PubMed  Google Scholar 

  • SAS Institute Inc, 1996. SAS/STAT User's Guide, Version 6, 4th edn., Vols. 1 and 2. SAS Institute, Inc., Cary, NC.

  • Sneath, P.H.A. & R.R. Sokal, 1973. Numerical Taxonomy. The Principles and Practices of Classification. W.H. Freeman and Co., San Francisco.

    Google Scholar 

  • Souza, E. & M.E. Sorrells, 1989. Pedigree analysis of North American oat cultivars released from 1951 to 1985. Crop Sci 29: 595–601.

    Google Scholar 

  • Sun, Q., Z. Ni, Z. Liu, J. Gao & T. Haung, 1998. Genetic relationships and diversity among Tibetan wheat, common wheat and European spelt wheat revealed by RAPD markers. Euphytica 99: 205–211.

    Article  Google Scholar 

  • Tatham, A.S. & P.R. Shewry, 1995. The S-poor prolamins of wheat, barley and rye. J Cereal Sci 22: 1–16.

    Article  Google Scholar 

  • Tinker, N.A. & D.E. Mather, 1993. Software for computing kinship coefficients. Heredity 84: 238.

    Google Scholar 

  • U.S. Wheat and Barley Scab Initiative, 2003. Preliminary BARC SSR maps and primer pair. http://www.scabusa.org/pdfs/BARC-SSR.html.

  • van Beuningen, L.T. & R.H. Busch. 1997a. Genetic diversity among North American spring wheat cultivars: I. Analysis of the coefficients of parentage matrix. Crop Sci 37: 570–579.

    Google Scholar 

  • van Beuningen, L.T. & R.H. Busch, 1997b. Genetic diversity among North American spring wheat cultivars: III. Cluster analysis based on quantitative morphological traits. Crop Sci 37: 981– 988.

    Google Scholar 

  • Weir, B.S., 1996. Genetic Analysis. II. Sinauer Publishers, Sunderland, MA, USA.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Fufa.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Fufa, H., Baenziger, P.S., Beecher, B. et al. Comparison of phenotypic and molecular marker-based classifications of hard red winter wheat cultivars. Euphytica 145, 133–146 (2005). https://doi.org/10.1007/s10681-005-0626-3

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10681-005-0626-3

Keywords