Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE (Open Access)

Genetic diversity in the U.S. hard red winter wheat cultivars as revealed by microsatellite markers

B. Prasad A , M. A. Babar B F , X. Y. Xu C , G. H. Bai D and A. R. Klatt E
+ Author Affiliations
- Author Affiliations

A Rice Research and Extension Center, University of Arkansas, Stuttgart, AR 72160, USA.

B Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA.

C Department of Crop and Soil Sciences, University of Georgia, Athens, GA 30602, USA.

D USDA-ARS, Kansas State University, Manhattan, KS 66506, USA.

E Department of Plant and Soil Sciences, Oklahoma State University, Stillwater, OK 74078, USA.

F Corresponding author. Email: mababar@ksu.edu, mdalibabar@yahoo.com

Crop and Pasture Science 60(1) 16-24 https://doi.org/10.1071/CP08052
Submitted: 13 February 2008  Accepted: 17 October 2008   Published: 5 January 2009

Abstract

Knowledge of the genetic diversity existing in previously released hard red winter wheat (HRWW, Triticum aestivum L.) cultivars in the Great Plains region, United States, is essential for effective utilisation of these genetic resources in the various HRWW breeding programs. To ascertain a measure of the genetic diversity of the existing US HRWW, 60 cultivars were analysed with 62 microsatellite markers distributed throughout the wheat genome. Marker data were subjected to distance-based analysis and analysis of molecular variances. In total, 341 polymorphic alleles were scored with a range of 2–12 alleles per locus. Genetic diversity gradually increased in cultivars released after the 1970s. Cultivars released in the 1990s had the highest allelic richness (4.79), gene diversity (0.60), and polymorphic information content (0.56). Levels of genetic diversity were similar between the major HRWW breeding programs. Cluster analysis resulted in eight clusters. Cluster grouping gave close matches with pedigrees and with regional distribution of the cultivars. Using decadal information, cultivars released from 1900–1969 were grouped into one cluster, cultivars from 1990–2005 were grouped into a separate cluster, whereas cultivars from the 1980s did not group with any other decades. Analysis of molecular variance revealed a significant variation among the clusters, signifying that a true genetic variation existed among the clusters. The higher proportion of genetic variation explained by cultivars within clusters compared with among clusters indicates greater genetic diversity among cultivars within clusters. Our results indicate that genetic diversity of Great Plains HRWW cultivars has increased in the past century, and the trend is continuing.

Additional keywords: molecular markers, cluster analysis.


Acknowledgments

We thank NPGS (USDA-ARS) and the wheat breeders of Oklahoma, Kansas, Texas, Colorado, and Nebraska for providing the germplasm. Our sincere thanks go to Dr Allan Fritz for his comments and information regarding the pedigree of some genotypes.


References


Barrett BA, Kidwell KK, Fox PN (1998) Comparison of AFLP and pedigree-based genetic diversity assessment methods using wheat cultivars from the Pacific Northwest. Crop Science 38, 1271–1278.
CAS |
open url image1

Bohn M, Utz HF, Melchinger AE (1999) Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs, and SSRs and their use for predicting progeny variance. Crop Science 39, 228–237.
CAS |
open url image1

Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32, 314–331.
CAS | PubMed |
open url image1

Chao S, Zhang W, Dubcovsky J, Sorrells M (2007) Evaluation of genetic diversity and genome-wide linkage disequilibrium among U.S. wheat (Triticum aestivum L.) germplasm representing different market classes. Crop Science 47, 1018–1030.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Christiansen MJ, Andersen SB, Oritiz R (2002) Diversity changes in an intensively bred wheat germplasm during the 20th century. Molecular Breeding 9, 1–11.
Crossref | GoogleScholarGoogle Scholar | open url image1

Clunies-Ross T (1995) Mangolds, manure and mixtures: The importance of crop diversity on British farms. The Ecologist 25, 181–187. open url image1

Cox TS, Murphy JP, Rodgers DM (1986) Changes in genetic diversity in the red winter wheat regions of the United States. Proceedings of the National Academy of Sciences of the United States of America 83, 5583–5586.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Devos KM, Bryan GJ, Collins AJ, Stephenson P, Gale MD (1995) Application of two microsatellite sequences in wheat storage proteins as molecular markers. Theoretical and Applied Genetics 90, 247–252.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Donini P, Law JR, Koebner RMD, Reeves JC, Cooke RJ (2000) Temporal trend in the diversity of UK wheat. Theoretical and Applied Genetics 100, 912–917.
Crossref | GoogleScholarGoogle Scholar | open url image1

Dreisigacker S, Zhang P, Warburton ML, van Ginkel M, Hoisington D, Melchinger AE (2004) SSR and pedigree analyses of genetic diversity among CIMMYT wheat lines targeted to different mega-environments. Crop Science 44, 381–388.
CAS |
open url image1

Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1, 47–50.
CAS |
open url image1

Fufa H, Baenziger PS, Beecher I, Dweikat V, Graybosch RA, Eskridge KM (2005) Comparison of phenotypic and molecular marker-based classifications of hard red winter wheat cultivars. Euphytica 145, 133–146.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Gupta K, Balyan S, Edwards J, Isaac P, Korzun V, Röder M, Gautier MF, Joudrier P, Schlatter R, Dubcovsky J, De La Pena C, Khairallah M, Penner G, Hayden J, Sharp P, Keller B, Wang C, Hardouin P, Jack P, Leroy P (2002) Genetic mapping of 66 new microsatellite (SSR) loci in bread wheat. Theoretical and Applied Genetics 105, 413–422.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Hai L, Wagner C, Friedt W (2007) Quantitative structure analysis of genetic diversity among spring bread wheats (Triticum aestivum L.) from different geographical regions. Genetica 130, 213–225.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Huang XQ, Börner A, Röder MS, Ganal MW (2002) Assessing genetic diversity of wheat (Triticum aestivum L.) germplasm using microsatellite markers. Theoretical and Applied Genetics 105, 699–707.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Joshi CP, Nguyen HT (1993) RAPD (random amplified polymorphic DNA) analysis based intervarietal genetic relationships among hexaploid wheat. Plant Science 93, 95–103.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Landjeva M, Korzum V, Borner A (2007) Molecular markers: actual and potential contributions to wheat genome characterization and breeding. Euphytica 156, 271–296.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21, 2128–2129.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Maccaferri M, Sanguineti MC, Noli E, Tuberosa R (2005) Population structure and long-range linkage disequilibrium in a durum wheat elite collection. Molecular Breeding 15, 271–289.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Manifesto MM, Schlatter AR, Hopp HP, Suarez EY, Dubcovsky J (2001) Quantitative evaluation of genetic diversity in wheat germplasm using molecular markers. Crop Science 41, 682–690.
CAS |
open url image1

Nei M (1972) Genetic distance between populations. American Naturalist 106, 283–292.
Crossref | GoogleScholarGoogle Scholar | open url image1

Oetting WS, Lee HK, Flanders DJ, Wiesner GL, Seller TA, King RA (1995) Linkage analysis with multiplexed short tandem repeat polymorphisms using infrared fluorescence and M13 tailed primers. Genomics 30, 450–458.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Ortiz R (2001) Germplasm enhancement to sustain genetic gains in crop improvement. In ‘Managing plant genetic diversity’. (Eds JMM Engels, VR Ramanatha, AHD Brown, M Jackson) pp. 275–290. (IPGRI: Italy, & CAB International: Wallingford, UK)

Röder MS, Korzun V, Gill BS, Ganal MW (1998b) The physical mapping of microsatellite marker in wheat. Genome 41, 278–283.
Crossref | GoogleScholarGoogle Scholar | open url image1

Röder MS, Korsun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal MW (1998a) A microsatellite map of wheat. Genetics 149, 2007–2023.
PubMed |
open url image1

Roussel V, Koenig J, Beckert M, Balfourier F (2004) Molecular diversity in French bread wheat accessions related to temporal trends and breeding programs. Theoretical and Applied Genetics 108, 920–930.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Roussel V, Leisova L, Exbrayat F, Stehno Z (2005) SSR allelic diversity changes in 480 European bread wheat varieties released from 1840 to 2000. Theoretical and Applied Genetics 111, 162–170.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Schut JW, Qi X, Stam P (1997) Association between relationship measures based on AFLP markers, pedigree data and morphological traits in Barley. Theoretical and Applied Genetics 95, 1161–1168.
Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Song QJ, Shi JR, Singh S, Fickus EW, Costa JM, Lewis J, Gill BS, Ward R, Cregan PB (2005) Development and mapping of microsatellite (SSR) markers in wheat. Theoretical and Applied Genetics 110, 550–560.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software ver. 4.0. Molecular Biology and Evolution 24, 1596–1599.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Tanksley SD, McCouch SR (1997) Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277, 1063–1066.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Tripp R (1996) Biodiversity and modern crop varieties: sharpening the debate. Agriculture and Human Values 13, 48–63.
Crossref | GoogleScholarGoogle Scholar | open url image1

Velle R (1993) The decline of diversity of European agriculture. The Ecologist 23, 64–69. open url image1

Watkins WS, Rogers AR, Ostler CT, Wooding S, Bamshad MJ, Brassington A-M E, Carroll ML, Nguyen SV, Walker JA, Prasad BVR, Reddy PG, Das PK, Batzer MA, Jordel LB (2003) Genetic variation among world populations: inferences from 100 Alu insertion polymorphisms. Genome Research 13, 1607–1618.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1

Weir BS (1996) ‘Genetic data analysis II.’ (Sinauer Associated Inc.: Sunderland, MA)

Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370.
Crossref | GoogleScholarGoogle Scholar | open url image1

Zhang XY, Li CW, Wang LF, Wang HM, You GX, Dong YS (2002) An estimation of the minimum number of SSR alleles needed to reveal genetic relationships in wheat varieties. I. Information from large-scale planted varieties and cornerstone breeding parents in Chinese wheat improvement and production. Theoretical and Applied Genetics 106, 112–117.
Crossref | GoogleScholarGoogle Scholar | CAS | PubMed | open url image1