Skip to main content
SpringerLink
Log in

Genetic diversity and population structure of pea (Pisum sativum L.) varieties derived from combined retrotransposon, microsatellite and morphological marker analysis

  • Original Paper
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

One hundred and sixty-four accessions representing Czech and Slovak pea (Pisum sativum L.) varieties bred over the last 50 years were evaluated for genetic diversity using morphological, simple sequence repeat (SSR) and retrotransposon-based insertion polymorphism (RBIP) markers. Polymorphic information content (PIC) values of 10 SSR loci and 31 RBIP markers were on average high at 0.89 and 0.73, respectively. The silhouette method after the Ward clustering produced the most probable cluster estimate, identifying nine clusters from molecular data and five to seven clusters from morphological characters. Principal component analysis of nine qualitative and eight quantitative morphological parameters explain over 90 and 93% of total variability, respectively, in the first three axes. Multidimensional scaling of molecular data revealed a continuous structure for the set. To enable integration and evaluation of all data types, a Bayesian method for clustering was applied. Three clusters identified using morphology data, with clear separation of fodder, dry seed and afila types, were resolved by DNA data into 17, 12 and five sub-clusters, respectively. A core collection of 34 samples was derived from the complete collection by BAPS Bayesian analysis. Values for average gene diversity and allelic richness for molecular marker loci and diversity indexes of phenotypic data were found to be similar between the two collections, showing that this is a useful approach for representative core selection.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Baranger A, Aubrey G, Aran G, Laine AL, Deniot G, Potier J, Burstin J (2004) Genetic diversity within Pisum sativum using protein and PCR-based markers. Theor Appl Genet 108:1309–1321

    Article  PubMed  CAS  Google Scholar 

  • Beaumont MA, Rannala B (2004) The Bayesian revolution in genetics. Nature Rev 5:251–261

    CAS  Google Scholar 

  • Beckmann JS, Soller M (1990) Toward a unified approach to genetic mapping of eukaryotes based on sequence tagged microsatellite sites. Biotechnology 10:930–932

    Google Scholar 

  • Bredemeijer GMM, Cooke RJ, Ganal MW, Peeter R, Isakk P, Noordijk Y, Rendell S, Jackson J, Roder MS, Wendehake K, Dijcks M, Amelaine M, Wickaert V, Bertrand L, Vosman B (2002) Construction and testing of a microsatellite database containing more than 500 tomato varieties. Theor Appl Genet 105:1019–1026

    Article  PubMed  Google Scholar 

  • Brown AHD, Spillane C (1999) Implementing core collections––principles, procedures, progress, problems and promise. In: Johnson RC, Hodgkin T (eds) Core collections for today and tommorow. IPGRI, Rome

    Google Scholar 

  • Brown AHD, Weir BS (1983) Measuring genetic variability in plant populations. In: Tanksley SD, Orton TJ (eds) Isozymes in plant genetics and breeding, part A. Elsevier, Amsterdam

    Google Scholar 

  • Burstin J, Deniot G, Potier J, Weinachter C, Aubert G, Baranger A (2001) Microsatellite polymorphism in Pisum sativum. Plant Breed 120:311–217

    Article  CAS  Google Scholar 

  • Corander J, Martiinen P (2006) Bayesian identification of admixture events using multilocus molecular markers. Mol Ecology 15:2833–2843

    Article  Google Scholar 

  • Corander J, Waldmann P, Marttinen P, Sillanpää MJ (2004) BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinformatics 20:2363–2369

    Article  PubMed  CAS  Google Scholar 

  • Corander J, Gyllenberg M, Koski T (2007) Random partition models and exchangeability for Bayesian identification of population structure. Bull Math Biol 69:797–815

    Article  PubMed  Google Scholar 

  • Donini P, Law JR, Koebner RMD, Reeves JC, Cooke RJ (2000) Temporal trends in the diversity of UK wheat. Theor Appl Genet 100:912–917

    Article  Google Scholar 

  • Ellis THN, Poyser SJ, Knox MR, Vershinin AV, Ambrose MJ (1998) Polymorphism of insertion sites of Ty1-copia class retrotransposons and its use for linkage and diversity analysis in pea. Mol Gen Genet 260:9–19

    PubMed  CAS  Google Scholar 

  • Erskine W, Muehlbauer FJ (1991) Allozyme and morpfological variability, outcrossing rate and core collection formation in lentil germplasm. Theor Appl Genet 83:119–125

    Article  CAS  Google Scholar 

  • Esquinas-Alacazar J (2005) Protecting crop genetic diversity for food security: political, ethical and technical challenges. Nature Rev Genet 6:946–953

    Article  Google Scholar 

  • Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587

    PubMed  CAS  Google Scholar 

  • Flavell AJ, Knox MR, Pearce SR, Ellis THN (1998) Retrotransposon-based insertion polymorphisms (RBIP) for high throughput marker analysis. Plant J 16:643–650

    Article  PubMed  CAS  Google Scholar 

  • Ford R, LeRoux K, Itman C, Brouwer JB, Tayler PWJ (2002) Diversity analysis and genotyping in Pisum with sequence tagged microsatellite (STSM) primers. Euphytica 124:397–405

    Article  CAS  Google Scholar 

  • Flavell AJ, Bolshakov VN, Booth A, Jing R, Russell J, Ellis THN, Isaac P (2003) A microarray-based high throughput molecular marker genotyping method: the tagged microarray marker (TAM) approach. Nucleic Acids Res e31:e115

    Article  CAS  Google Scholar 

  • Frankel OH, Brown AHD (1984) Current plant genetic resources––a critical appraisal. In: Genetics: new Frontiers, vol IV. Oxford and IBH Publ. Co., New Delhi

    Google Scholar 

  • Goudet J (1995) FSTAT (ver. 1.2): a computer program to calculate F-statistics. J Heredity 86:485–486

    Google Scholar 

  • Hu J, Zhu J, Xu HM (2000) Methods of constructing core collections by stepwise clustering with three sampling strategies based on the genotypic values of crops. Theor Appl Genet 101:264–268

    Article  CAS  Google Scholar 

  • Jing RC, Knox MR, Lee JM, Vershinin AV, Ambrose M, Ellis THN, Flavell AJ (2005) Insertional polymorphism and antiquity of PDR1 retrotransposon insertions in Pisum species. Genetics 171:741–752

    Article  PubMed  CAS  Google Scholar 

  • Jing R, Bolshakov VI, Flavell AJ (2007) The Tagged Microarray Marker (TAM) method for high throughput detection of single nucleotide and indel polymorphisms. Nature Protocols 2:168–177

    Article  PubMed  CAS  Google Scholar 

  • Kalendar R, Grob T, Regina M, Suoniemi A, Schulman A (1999) IRAP and REMAP: two new retrotransposon-based DNA fingerprinting techniques. Theor Appl Genet 98:704–711

    Article  CAS  Google Scholar 

  • Kimura M, Crow JF (1964) The number of alleles that can be maintained in a finite population. Genetics 49:725–738

    PubMed  CAS  Google Scholar 

  • Kruskal JB (1964) Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29:1–27

    Article  Google Scholar 

  • Le Clerc V, Bazante F, Baril C, Guiard J, Zhang D (2005) Assessing temporal changes in genetic diversity of maize varieties using microsatellite markers. Theor Appl Genet 110:294–302

    Article  PubMed  CAS  Google Scholar 

  • Le Clerc V, Cadot V, Canadas M, Lallemand J, Guerin D, Boulineau F (2006) Indicators to assess temporal genetic diversity in the French Catalogue: no losses for maize and peas. Theor Appl Genet 113:1197–1209

    Article  PubMed  CAS  Google Scholar 

  • Lewontin RC (1972) The apportionment of human diversity. Evol Biol 6:381–398

    Google Scholar 

  • Loridon K, McPhee K, Morin J, Dubreuil P, Pilet-Nayel ML, Aubert G, Rameau C, Baranger A, Coyne C, Lejeune-Henaut I, Burstin J (2005) Microsatellite marker polymorphism and mapping in pea (Pisum sativum L.). Theor Appl Genet 111:1022–1031

    Article  PubMed  CAS  Google Scholar 

  • Maccaferri M, Sanguineti MC, Noli E, Tuberosa R (2005) Population structure and long-range linkage disequilibrium in a durum wheat elite collection. Mol Breed 15:271–289

    Article  CAS  Google Scholar 

  • Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27:209–220

    PubMed  CAS  Google Scholar 

  • Nei M (1973) Analysis of gene diversity in subdivaded populations. Proc Natl Acad Sci USA 70:3321–3323

    Article  PubMed  CAS  Google Scholar 

  • Nei M (1978) Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583–590

    PubMed  CAS  Google Scholar 

  • Nersting LG, Andersen SB, von Bothmer R, Gullord M, Jorgensen RB (2006) Morphological and molecular diversity of Nordic oat through one hundred years of breeding. Euphytica 150:327–337

    Article  Google Scholar 

  • Pavelková A, Moravec J, Hájek D, Bareš I, Sehnalová J (1986) Descriptor list genus Pisum L. RICP Prague. Genové zdroje 32:46

    Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    PubMed  CAS  Google Scholar 

  • Reif JC, Melchinger AE, Frish M (2005) Genetical and mathematical properties of similarity and dissimilarity coefficients applied in plant breeding and seed bank management. Crop Sci 45:1–7

    Google Scholar 

  • Reynolds J, Weir BS, Cockerham C (1983) Estimation of the coancestry coefficient: basis for a short-term genetic distance. Genetics 105:767–776

    PubMed  CAS  Google Scholar 

  • Rohlf F (2006) NTSYSpc: Numerical Taxonomy System (ver. 2.2). Exeter Publishing, Ltd., Setauket

    Google Scholar 

  • Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53–65

    Article  Google Scholar 

  • Roussel V, Leisova L, Exbrayat F, Stehno Z, Balfourier F (2005) SSR allelic diversity changes in 480 European bread wheat varieties released from 1840 to 2000. Theor Appl Genet 111:162–170

    Article  PubMed  CAS  Google Scholar 

  • Roussel V, Koenig J, Beckert M, Balfourier F (2006) Molecular diversity in French bread wheat accessions related to temporal trends and breeding programmes. Theor Appl Genet 108:920–930

    Article  CAS  Google Scholar 

  • Shannon CE, Weaver W (1962) The mathematical theory of communication. Univer. of Illinois Press, Urbana

    Google Scholar 

  • Simioniuc D, Uptmoor R, Friedt W, Ordon F (2002) Genetic diversity and relationships among pea cultivars revealed by RAPDs and AFLPs. Plant Breed 121:429–435

    Article  CAS  Google Scholar 

  • Smýkal P (2006) Development of an efficient retrotransposon-based fingerprinting method for rapid pea variety identification. J Appl Genet 47:221–230

    PubMed  Google Scholar 

  • Smýkal P, Valledor L, Rodríguez R, Griga M (2007) Assessment of genetic and epigenetic stability in long-term in vitro shoot culture of pea (Pisum sativum L.). Plant Cell Rep 26:1985–1998

    Article  PubMed  CAS  Google Scholar 

  • SPSS for Windows, Rel. 12.0.1 (2003) SPSS Inc., Chicago

  • StatSoft Inc (2006) STATISTICA (data analysis software system), version 7.1. http://www.statsoft.com

  • Tanksley SD, McCouch SR (1997) Seed bank and molecular maps: unlocking genetic potential from the wild. Science 277:1063–1066

    Article  PubMed  CAS  Google Scholar 

  • Tar’an B, Zhang C, Wankertin T, Tullu A, Vandenberg A (2005) Genetic diversity among varietis and wild species accessions of pea (Pisum sativum L.) based on molecular markers, and morphological and physiological characters. Genome 48:257–272

    PubMed  CAS  Google Scholar 

  • Tohme J, Jones P, Beebe S, Iwanaga M (1995) The combined use of agroecological and characterization data to establish the CIAT Phaseolus vulgaris core collection. In: Hodgkin T, Brown AHD, van Hintum TJL, Morales EAV (eds) Core collections of plant genetic resources. Wiley, Chichester, pp 95–107

    Google Scholar 

  • Van Hintum TJL (1999) The general methodology for creating a core collection. In: Johnson RC, Hodgkin T (eds) Core collections for today and tomorrow. International Plant Genetic Resources Institute, Rome, pp 10–17

    Google Scholar 

  • Vavilov NI (1926) Studies on the origin of cultivated plants, Bulletin of Applied Botany, vol 26. Leningrad, USSR

    Google Scholar 

  • Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407–4414

    Article  PubMed  CAS  Google Scholar 

  • Wang JC, Hu J, Xu HM, Zhang S (2007) A strategy on constructing core collections by least distance stepwise sampling. Theor Appl Genet 115:1–8

    Article  PubMed  CAS  Google Scholar 

  • Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236

    Article  Google Scholar 

  • Waugh R, McLean K, Flavell AJ, Pearce SR, Kumar A, Thomas BT, Powell W (1997) Genetic distribution of BARE-1 retrotransposable elements in the barley genome revealed by sequence-specific amplification polymorphisms (S-SAP). Mol Gen Genet 253:687–694

    Article  PubMed  CAS  Google Scholar 

  • Williams JGK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV (1990) DNA polymorphism amplified by arbitrary primers are usefull as genetic markers. Nucleic Acids Res 18:6531–6535

    Article  PubMed  CAS  Google Scholar 

  • Wright S (1965) The interpretation of population structure by F-statistics with special regards to systems of mating. Evolution 19:395–420

    Article  Google Scholar 

  • Yeh FC, Boyle TJB (1997) Population genetic analysis of co-dominant and dominant markers and quantitative traits. Belg J Bot 129:157

    Google Scholar 

  • Zietkiewicz E, Rafalski A, Labuda D (1994) Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction. Genomics 20:176–183

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This work was financially supported by Ministry of Education of Czech Republic research project MSMT 2678424601 and Czech Ministry of Agriculture project no. 33083/03-3000. Technical support of Mrs. L.Vítámvásová, E. Fialová, M. Vachatová and E. Kamlerová are greatly acknowledged.

Author information

Authors and Affiliations

  1. Plant Biotechnology Department, Agritec Plant Research Ltd, Zemědělská 2520/16, 787 01, Šumperk, Czech Republic

    Petr Smýkal, Miroslav Hýbl & Miroslav Griga

  2. Grain Legumes Department, Agritec Plant Research Ltd, Zemědělská 2520/16, 787 01, Šumperk, Czech Republic

    Miroslav Hýbl

  3. Department of Mathematics and Statistics, Åbo Akademi University, P.O. Box 68, Turku, 20500, Finland

    Jukka Corander

  4. Institute of Biostatistics and Analysis, Masaryk University, Kamenice 3, 625 00, Brno, Czech Republic

    Jiří Jarkovský

  5. Plant Research Unit, University of Dundee at SCRI, Invergowrie, Dundee, DD2 5DA, Scotland, UK

    Andrew J. Flavell

Authors
  1. Petr Smýkal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miroslav Hýbl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jukka Corander
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiří Jarkovský
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrew J. Flavell
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Miroslav Griga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Petr Smýkal.

Additional information

Communicated by D. A. Hoisington.

Electronic supplementary material

Below is the link to the electronic supplementary material.

List of

Pisum sativum accessions used in analysis. Accession number, pedigree, date of entry into collection, breeding period, accession type (breeding line, wild accession, land race, variety) and user type (fodder and dry-seed) are indicated. A set of 34 accessions forming the deduced core collection based upon BAPS analysis is indicated (DOC 44 kb)

Ward hierarchical classification performed on the combined SSR and RBIP molecular distance matrix.

The silhouette method calculation of the most probable cluster number (9) is indicated in the upper corner (DOC 127 kb)

Class frequency distributions;

A. 15 qualitative morphological characters B. 18 quantitative morphological characters in the full set of 164 accessions (DOC 47 kb)

A.

Eigenvalue matrices and vectors of principal components for; A. 9 qualitative characters. B. 18 quantitative characters, of field and fodder pea assessed in field trials (DOC 107 kb)

Ward hierarchical ascendant classification of morphological characters calculated by simple matching coefficient.

4 clusters revealed by the silhouette method as the most homogeneous solution are indicated (DOC 23 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Smýkal, P., Hýbl, M., Corander, J. et al. Genetic diversity and population structure of pea (Pisum sativum L.) varieties derived from combined retrotransposon, microsatellite and morphological marker analysis. Theor Appl Genet 117, 413–424 (2008). https://doi.org/10.1007/s00122-008-0785-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-008-0785-4

Keywords

Search

Navigation