Theoretical and Applied Genetics

, Volume 119, Issue 1, pp 175–187 | Cite as

Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin

  • Jordi Comadran
  • W. T. B. Thomas
  • F. Á. van Eeuwijk
  • S. Ceccarelli
  • S. Grando
  • A. M. Stanca
  • N. Pecchioni
  • T. Akar
  • A. Al-Yassin
  • A. Benbelkacem
  • H. Ouabbou
  • J. Bort
  • I. Romagosa
  • C. A. Hackett
  • J. R. Russell
Original Paper


Population structure and genome-wide linkage disequilibrium (LD) were investigated in 192 Hordeum vulgare accessions providing a comprehensive coverage of past and present barley breeding in the Mediterranean basin, using 50 nuclear microsatellite and 1,130 DArT® markers. Both clustering and principal coordinate analyses clearly sub-divided the sample into five distinct groups centred on key ancestors and regions of origin of the germplasm. For given genetic distances, large variation in LD values was observed, ranging from closely linked markers completely at equilibrium to marker pairs at 50 cM separation still showing significant LD. Mean LD values across the whole population sample decayed below r 2 of 0.15 after 3.2 cM. By assaying 1,130 genome-wide DArT® markers, we demonstrated that, after accounting for population substructure, current genome coverage of 1 marker per 1.5 cM except for chromosome 4H with 1 marker per 3.62 cM is sufficient for whole genome association scans. We show, by identifying associations with powdery mildew that map in genomic regions known to have resistance loci, that associations can be detected in strongly stratified samples provided population structure is effectively controlled in the analysis. The population we describe is, therefore, shown to be a valuable resource, which can be used in basic and applied research in barley.


Linkage Disequilibrium Powdery Mildew Simple Sequence Repeat Marker Association Mapping Polymorphism Information Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The above work was funded by the European Union-INCO-MED program (ICA3-CT2002-10026). SCRI received grant in aid from the Scottish Government Rural and Environment Research and Analysis Department.

Supplementary material

122_2009_1027_MOESM1_ESM.doc (2.1 mb)
Supplementary material 1 (DOC 2,133 kb)


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Jordi Comadran
    • 1
  • W. T. B. Thomas
    • 1
  • F. Á. van Eeuwijk
    • 2
  • S. Ceccarelli
    • 3
  • S. Grando
    • 3
  • A. M. Stanca
    • 4
  • N. Pecchioni
    • 5
  • T. Akar
    • 6
  • A. Al-Yassin
    • 7
  • A. Benbelkacem
    • 8
  • H. Ouabbou
    • 9
  • J. Bort
    • 10
  • I. Romagosa
    • 11
  • C. A. Hackett
    • 12
  • J. R. Russell
    • 1
  1. 1.Genetics ProgrammeScottish Crop Research Institute (SCRI)DundeeScotland, UK
  2. 2.Biometrics Applied StatisticsWageningen UniversityWageningenThe Netherlands
  3. 3.International Center for Agricultural Research in the Dry Areas (ICARDA)AleppoSyria
  4. 4.CRA, Genomic Research CentreFiorenzuola d’Arda (PC)Italy
  5. 5.Dipartimento di Scienze AgrarieUniversità di Modena e Reggio EmiliaReggio EmiliaItaly
  6. 6.Central Research for Field CropsAnkaraTurkey
  7. 7.NCARTTAmmanJordan
  8. 8.ITGCConstantineAlgeria
  9. 9.INRA Morocco, CRRASettatMorocco
  10. 10.Department de Biologia VegetalUniversitat de BarcelonaBarcelonaSpain
  11. 11.Centre UdL-IRTAUniversitat de LleidaLleidaSpain
  12. 12.BioSSSCRIDundeeScotland, UK

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