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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

Abstract

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.

Keywords

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.

Notes

Acknowledgments

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)

References

  1. Badr A, Muller K, Schafer-Pregl R, El Rabey H, Effgen S et al (2000) On the origin and domestication history of Barley (Hordeum vulgare). Mol Biol Evol 17:499–510PubMedGoogle Scholar
  2. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 57:289–300Google Scholar
  3. Bowcock AM, Ruiz-Linares A, Tomfohrde J, Minch E, Kidd JR et al (1994) High resolution of human evolutionary trees with polymorphic microsatellites. Nature 368:455–457PubMedCrossRefGoogle Scholar
  4. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177PubMedCrossRefGoogle Scholar
  5. Buckler ES, Gaut BS, McMullen MD (2006) Molecular and functional diversity of maize. Curr Opin Plant Biol 9:172–176PubMedCrossRefGoogle Scholar
  6. Caldwell KS, Russell J, Langridge P, Powell W (2006) Extreme population-dependent linkage disequilibrium detected in an inbreeding plant species, Hordeum vulgare. Genetics 172:557–567PubMedCrossRefGoogle Scholar
  7. Casas AM, Yahiaoui S, Ciudad F, Igartua E (2005) Distribution of MWG699 polymorphism in Spanish European barleys. Genome 48:41–45PubMedCrossRefGoogle Scholar
  8. Chelkowski J, Tyrka M, Sobkiewicz A (2003) Resistance genes in barley (Hordeum vulgare L.) and their identification with molecular markers. J Appl Genet 44:291–309PubMedGoogle Scholar
  9. Comadran J, Russell J, Eeuwijk FA, Ceccarelli S, Grando S et al (2008) Mapping adaptation of barley to droughted environments. Euphytica 161:35–45CrossRefGoogle Scholar
  10. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedGoogle Scholar
  11. Felsenstein J (1997) An alternating least squares approach to inferring phylogenies from pairwise distances. Syst Biol 46:101–111PubMedCrossRefGoogle Scholar
  12. Fischbeck G (2002) Contribution of barley to agriculture: a brief overview. In: Slafer GA, Molina-Cano JS, Savin R, Araus JL, Romagosa I (eds) Barley science: recent advances from molecular biology to agronomy of yield and quality. Food Products Press, New York, pp 1–29Google Scholar
  13. Flint-Garcia SA, Thornsberry JM, Buckler ES (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374PubMedCrossRefGoogle Scholar
  14. Grando S, von Bothmer R, Ceccarelli S (2001) Genetic diversity of barley: use of locally adapted germplasm to enhance yield and yield stability of barley in dry areas. In: Cooper HD, Spillane C, Hodgkin T (eds) Broadening the genetic base of crop production, pp 351–372Google Scholar
  15. Gupta PK, Rustgi S, Kulwal PL (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485PubMedCrossRefGoogle Scholar
  16. Heun M (1992) Mapping quantitative powdery mildew resistance of barley using a restriction fragment length polymorphism map. Genome 35:1019–1025Google Scholar
  17. Kilian B, Ozkan H, Kohl J, von Haeseler A, Barale F et al (2006) Haplotype structure at seven barley genes: relevance to gene pool bottlenecks, phylogeny of ear type and site of barley domestication. Mol Genet Genom 276:230–241CrossRefGoogle Scholar
  18. Kim HS, Ward RW (2000) Patterns of RFLP-based genetic diversity in germplasm pools of common wheat with different geographical or breeding program origins. Euphytica 115:108–197CrossRefGoogle Scholar
  19. Kraakman AT, Niks RE, Van PM, den Berg P, Stam FA, Eeuwijk Van (2004) Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics 168:435–446PubMedCrossRefGoogle Scholar
  20. Kunzel G, Korzun L, Meister A (2000) Cytologically integrated physical restriction fragment length polymorphism maps for the barley genome based on translocation breakpoints. Genetics 154:397–412PubMedGoogle Scholar
  21. Lin JZ, Morrell PL, Clegg MT (2002) The influence of linkage and inbreeding on patterns of nucleotide sequence diversity at duplicate alcohol dehydrogenase loci in wild barley (Hordeum vulgare ssp. spontaneum). Genetics 162:2007–2015PubMedGoogle Scholar
  22. Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12:57–63PubMedCrossRefGoogle Scholar
  23. Malysheva-Otto LV, Ganal MW, Roder MS (2006) Analysis of molecular diversity, population structure and linkage disequilibrium in a worldwide survey of cultivated barley germplasm (Hordeum vulgare L.). BMC Genet 24:6–7CrossRefGoogle Scholar
  24. Morrell PL, Lundy KE, Clegg MT (2003) Distinct geographic patterns of genetic diversity are maintained in wild barley (Hordeum vulgare ssp. spontaneum) despite migration. Proc Natl Acad Sci USA 100:10812–10817PubMedCrossRefGoogle Scholar
  25. Morrell PL, Toleno DM, Lundy KE, Clegg MT (2005) Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp. spontaneum) despite high rates of self-fertilization. Proc Natl Acad Sci USA 102:2442–2447PubMedCrossRefGoogle Scholar
  26. Park SDE (2001) Trypano tolerance in West African cattle and the population genetic effects of selection. University of Dublin, DublinGoogle Scholar
  27. Payne RW, Harding SA, Murray DA, Soutar DM, Baird DB et al (2006) GenStat release 9 reference manual. Part 2. Directives. VSN International, Hemel HempsteadGoogle Scholar
  28. Piepho HP, Mohring J, Melchinger AE, Buchse A (2008) BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161:209–228CrossRefGoogle Scholar
  29. Pritchard JK, Donnelly P (2001) Case–control studies of association in structured or admixed populations. Theor Popul Biol 60:227–237PubMedCrossRefGoogle Scholar
  30. Pritchard JK, Stephens M, Donnelly P (2000a) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  31. Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000b) Association mapping in structured populations. Am J Hum Genet 67:170–181PubMedCrossRefGoogle Scholar
  32. Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR et al (2001) Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci USA 98:11479–11484PubMedCrossRefGoogle Scholar
  33. Rostoks N, Mudie S, Cardle L, Russell J, Ramsay L et al (2005) Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress. Mol Genet Genom 274:515–527CrossRefGoogle Scholar
  34. Rostoks N, Ramsay L, MacKenzie K, Cardle L, Bhat PR et al (2006) Recent history of artificial outcrossing facilitates whole-genome association mapping in elite inbred crop varieties. Proc Natl Acad Sci USA 103:18656–18661PubMedCrossRefGoogle Scholar
  35. Russell J, Fuller J, Young G, Thomas B, Taramino G et al (1997) Discriminating between barley genotypes using microsatellite markers. Genome 40:442–450PubMedCrossRefGoogle Scholar
  36. Russell J, Ellis RP, Thomas B, Waugh R, Provan J et al (2000) A retrospective analysis of spring barley germplasm development from ‘foundation genotypes’ to currently successful cultivars. Mol Breed 6:553–568CrossRefGoogle Scholar
  37. Shtaya MJY, Marcel TC, Sillero JC, Niks RE, Rubiales D (2006) Identification of QTLs for powdery mildew and scald resistance in barley. Euphytica 151:421–429CrossRefGoogle Scholar
  38. Smith JSC, Kresovich S, Hopkins MS, Mitchell SE, Dean RE et al (2000) Genetic diversity among elite sorghum inbred lines assessed with simple sequence repeats. Crop Sci 40:226–232CrossRefGoogle Scholar
  39. Steffenson BJ, Olivera P, Roy JK, Jin Y, Smith KP et al (2007) A walk on the wild side: mining wild wheat and barley collections for rust resistance genes. Aust J Agr Res 58:532–544CrossRefGoogle Scholar
  40. Stracke S, Presterl T, Stein N, Perovic D, Ordon F et al (2006) Effects of introgression and recombination on haplotype structure and linkage disequilibrium surrounding a locus encoding Bymovirus resistance in barley. Genetics 175:805–817PubMedCrossRefGoogle Scholar
  41. Thomas WTB, Powell W, Waugh R, Chalmers KJ, Barua UM et al (1995) Detection of quantitative trait loci for agronomic, yield, grain and disease characters in spring barley (Hordeum vulgare L.). Theor Appl Genet 91:1037–1047CrossRefGoogle Scholar
  42. Waugh R, Jannink JL, Muller K, Ramsay L (2009) The emergence of whole genome association scans in barley. Curr Opin Plant Biol 12:1–5CrossRefGoogle Scholar
  43. Weir BS (1979) Inferences about linkage disequilibrium. Biometrics 35:235–254PubMedCrossRefGoogle Scholar
  44. Wenzl P, Carling J, Kudrna D, Jaccoud D, Huttner E et al (2004) Diversity Arrays Technology (DArT) for whole-genome profiling of barley. Proc Natl Acad Sci USA 101:9915–9920PubMedCrossRefGoogle Scholar
  45. Wenzl P, Li H, Carling J, Zhou M, Raman H et al (2006) A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits. BMC Genom 7:206CrossRefGoogle Scholar
  46. Yahiaoui S, Igartua E, Moralejo M, Ramsay L, Molina-Cano JL et al (2008) Patterns of genetic and eco-geographical diversity in Spanish barleys. Theor Appl Genet 116:271–282PubMedCrossRefGoogle Scholar
  47. Yu J, Pressoir G, Briggs WH, Vroh B, Yamasaki IM et al (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208PubMedCrossRefGoogle Scholar
  48. Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C et al (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genet 3:e4PubMedCrossRefGoogle Scholar

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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