Molecular Breeding

, 35:86 | Cite as

Multi-parent advanced generation inter-cross in barley: high-resolution quantitative trait locus mapping for flowering time as a proof of concept

  • Wiebke SannemannEmail author
  • Bevan Emma Huang
  • Boby Mathew
  • Jens Léon


The choice of mapping population is one of the key factors in understanding the genetic effects of complex traits and determines the power and precision of quantitative trait locus (QTL) mapping. We present the results of the first eight-way multi-parent advanced generation inter-cross (MAGIC) doubled haploid (DH) population in barley (Hordeum vulgare ssp. vulgare) applied to mapping complex traits. The results of the genetic architecture within the barley MAGIC population allowed QTL mapping in 533 DH lines with 4,550 single nucleotide polymorphisms (SNPs) with a newly developed mixed linear model in SAS v9.2, incorporating multi-locus analysis and cross validation for flowering time. Two QTL mapping approaches, the binary approach (BA), which is widely used in QTL and association mapping, and a novel haplotype approach (HA) were compared based on their efficiency, precision for QTL detection and estimation of genetic effects. The analysis detected 17 QTLs, five of which were shared between the two approaches; five and two were specifically found with the BA and HA approaches, respectively. The combination of the two mapping approaches enabled high-precision QTL mapping for flowering time. The QTLs corresponded to the genomic regions of major flowering-time genes Vrn-H1, Vrn-H3, HvGI, Ppd-H1, HvFT2, HvFT4, Co1 and linked genes for plant height (sdw1). These results confirm the proof of concept of QTL mapping in a multi-parent population, highlight the advantages and demonstrate that the barley MAGIC DH lines in combination with an advanced QTL mapping approach are valuable resources for mapping complex traits.


Multi-parent advanced generation inter-cross (MAGIC) Flowering time Haplotype analysis QTL mapping Multi-locus analysis Complex trait 



Thanks go to Karola Müller, who established the MAGIC population, and Merle Noschinski, for keeping up with all the samples. We thank the anonymous reviewers; their comments greatly improved this work. The research of W. S. was supported by the Bundesministerium für Bildung und Forschung (BMBF) and was conducted in the network (Förder-Nr. 0315529). The research of E. B. H. was supported by the Australian Research Council DE120101127.

Conflict of interest

We declare that we have no conflict of interest in regard to the present study.

Ethical standard

We declare that we followed all ethical standards while carrying out the present study.

Supplementary material

11032_2015_284_MOESM1_ESM.xlsx (263 kb)
Supplementary material 1 (XLSX 262 kb)
11032_2015_284_MOESM2_ESM.xlsx (2.8 mb)
Supplementary material 2 (XLSX 2879 kb)
11032_2015_284_MOESM3_ESM.docx (738 kb)
Supplementary material 3 (DOCX 738 kb)
11032_2015_284_MOESM4_ESM.docx (347 kb)
Supplementary material 4 (DOCX 347 kb)
11032_2015_284_MOESM5_ESM.docx (1.4 mb)
Supplementary material 5 (DOCX 1445 kb)
11032_2015_284_MOESM6_ESM.tif (190.7 mb)
Supplementary material 6 Dendrogram of 533 barley MAGIC DH lines and their eight parents (TIFF 195297 kb)
11032_2015_284_MOESM7_ESM.docx (287 kb)
Supplementary material 7 (DOCX 287 kb)


  1. Ali MAM, Okiror SO, Rasmusson DC (1978) Performance of semidwarf barley. Crop Sci 18:418–422. doi: 10.2135/cropsci1978.0011183X001800030015x CrossRefGoogle Scholar
  2. Bandillo N et al (2013) Multi-parent advanced generation inter-cross (MAGIC) populations in rice: progress and potential for genetics research and breeding. Rice 6:1–15. doi: 10.1186/1939-8433-6-11 CrossRefGoogle Scholar
  3. Barua UM et al (1993) Molecular mapping of genes determining height, time to heading, and growth habit in barley (Hordeum vulgare). Genome 36:1080–1087. doi: 10.1139/g93-143 CrossRefPubMedGoogle Scholar
  4. Bezant J, Laurie D, Pratchett N, Chojecki J, Kearsey M (1996) Marker regression mapping of QTL controlling flowering time and plant height in a spring barley (Hordeum vulgare L.) cross. Heredity 77:64–73. doi: 10.1038/Hdy.1996.109 CrossRefGoogle Scholar
  5. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177. doi: 10.1534/genetics.105.044586 CrossRefPubMedCentralPubMedGoogle Scholar
  6. Cavanagh C, Morell M, Mackay I, Powell W (2008) From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants. Curr Opin Plant Biol 11:215–221. doi: 10.1016/j.pbi.2008.01.002 CrossRefPubMedGoogle Scholar
  7. Cockram J, Jones H, Leigh FJ, O’Sullivan D, Powell W, Laurie DA, Greenland AJ (2007) Control of flowering time in temperate cereals: genes, domestication, and sustainable productivity. J Exp Bot 58:1231–1244. doi: 10.1093/jxb/erm042 CrossRefPubMedGoogle Scholar
  8. Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142:169–196. doi: 10.1007/s10681-005-1681-5 CrossRefGoogle Scholar
  9. Comadran J et al (2012) Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley. Nat Genet 44(12):1388–1392.
  10. Darvasi A, Soller M (1995) Advanced intercross lines, an experimental population for fine genetic-mapping. Genetics 141:1199–1207PubMedCentralPubMedGoogle Scholar
  11. Deng W, Nickle DC, Learn GH, Maust B, Mullins JI (2007) ViroBLAST: a stand-alone BLAST web server for flexible queries of multiple databases and user’s datasets. Bioinformatics 23:2334–2336. doi: 10.1093/bioinformatics/btm331 CrossRefPubMedGoogle Scholar
  12. Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3:43–52. doi: 10.1038/nrg703 CrossRefPubMedGoogle Scholar
  13. Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285–294PubMedCentralPubMedGoogle Scholar
  14. Faure S, Higgins J, Turner A, Laurie DA (2007) The FLOWERING LOCUS T-like gene family in barley (Hordeum vulgare). Genetics 176:599–609. doi: 10.1534/genetics.106.069500 CrossRefPubMedCentralPubMedGoogle Scholar
  15. Franklin SB, Gibson DJ, Robertson PA, Pohlmann JT, Fralish JS (1995) Parallel analysis—a method for determining significant principal components. J Veg Sci 6:99–106. doi: 10.2307/3236261 CrossRefGoogle Scholar
  16. Griffiths S, Dunford RP, Coupland G, Laurie DA (2003) The evolution of CONSTANS-like gene families in barley, rice, and Arabidopsis. Plant Physiol 131:1855–1867. doi: 10.1104/pp.102.016188 CrossRefPubMedCentralPubMedGoogle Scholar
  17. Hagenblad J et al (2004) Haplotype structure and phenotypic associations in the chromosomal regions surrounding two Arabidopsis thaliana flowering time loci. Genetics 168:1627–1638. doi: 10.1534/genetics.104.029470 CrossRefPubMedCentralPubMedGoogle Scholar
  18. Hamblin MT, Jannink JL (2011) Factors affecting the power of haplotype markers in association studies. Plant Genome 4:145–153. doi: 10.3835/plantgenome2011.03.0008 CrossRefGoogle Scholar
  19. Holland JB (2007) Genetic architecture of complex traits in plants. Curr Opin Plant Biol 10:156–161. doi: 10.1016/j.pbi.2007.01.003 CrossRefPubMedGoogle Scholar
  20. Huang BE, George AW (2011) R/mpMap: a computational platform for the genetic analysis of multiparent recombinant inbred lines. Bioinformatics 27:727–729. doi: 10.1093/bioinformatics/btq719 CrossRefPubMedGoogle Scholar
  21. Huang X, Paulo M-J, Boer M, Effgen S, Keizer P, Koornneef M, van Eeuwijk FA (2011) Analysis of natural allelic variation in Arabidopsis using a multiparent recombinant inbred line population. Proc Natl Acad Sci USA 108:4488–4493. doi: 10.1073/pnas.1100465108 CrossRefPubMedCentralPubMedGoogle Scholar
  22. Huang BE, George AW, Forrest KL, Kilian A, Hayden MJ, Morell MK, Cavanagh CR (2012) A multiparent advanced generation inter-cross population for genetic analysis in wheat. Plant Biotechnol J 10:826–839. doi: 10.1111/j.1467-7652.2012.00702.x CrossRefPubMedGoogle Scholar
  23. Jung C, Muller AE (2009) Flowering time control and applications in plant breeding. Trends Plant Sci 14:563–573. doi: 10.1016/j.tplants.2009.07.005 CrossRefPubMedGoogle Scholar
  24. King EG et al (2012) Genetic dissection of a model complex trait using the Drosophila synthetic population resource. Genome Res 22:1558–1566. doi: 10.1101/gr.134031.111 CrossRefPubMedCentralPubMedGoogle Scholar
  25. Koornneef M, Alonso-Blanco C, Peeters AJ, Soppe W (1998) Genetic control of flowering time in arabidopsis. Annu Rev Plant Physiol Plant Mol Biol 49:345–370. doi: 10.1146/annurev.arplant.49.1.345 CrossRefPubMedGoogle Scholar
  26. Kover PX et al (2009) A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet 5:e1000551. doi: 10.1371/journal.pgen.1000551 CrossRefPubMedCentralPubMedGoogle Scholar
  27. Kuczynska A, Surma M, Adamski T, Mikoajczak K, Krystkowiak K, Ogrodowicz P (2013) Effects of the semi-dwarfing sdw1/denso gene in barley. J Appl Genet 54:381–390. doi: 10.1007/s13353-013-0165-x CrossRefPubMedCentralPubMedGoogle Scholar
  28. Laurie DA, Pratchett N, Romero C, Simpson E, Snape JW (1993) Assignment of the denso dwarfing gene to the long arm of chromosome 3(3H) of barley by use of RFLP markers. Plant Breed 111:198–203. doi: 10.1111/j.1439-0523.1993.tb00630.x CrossRefGoogle Scholar
  29. Laurie DA, Pratchett N, Snape JW, Bezant JH (1995) RFLP mapping of five major genes and eight quantitative trait loci controlling flowering time in a winter × spring barley (Hordeum vulgare L.) cross. Genome 38:575–585CrossRefPubMedGoogle Scholar
  30. Lorenz AJ, Hamblin MT, Jannink JL (2010) Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS ONE. doi: 10.1371/journal.pone.0014079 Google Scholar
  31. Lu X, Niu T, Liu JS (2003) Haplotype information and linkage disequilibrium mapping for single nucleotide polymorphisms. Genome Res 13:2112–2117. doi: 10.1101/gr.586803 CrossRefPubMedCentralPubMedGoogle Scholar
  32. Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12:57–63. doi: 10.1016/j.tplants.2006.12.001 CrossRefPubMedGoogle Scholar
  33. Mackay IJ et al (2014) An eight-parent multiparent advanced generation inter-cross population for winter-sown wheat: creation, properties, and validation. Genes Genom Genet 4:1603–1610. doi: 10.1534/g3.114.012963 Google Scholar
  34. Manichaikul A, Dupuis J, Sen S, Broman KW (2006) Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus. Genetics 174:481–489. doi: 10.1534/genetics.106.061549 CrossRefPubMedCentralPubMedGoogle Scholar
  35. Milne I et al (2010) Flapjack-graphical genotype visualization. Bioinformatics 26:3133–3134. doi: 10.1093/bioinformatics/btq580 CrossRefPubMedCentralPubMedGoogle Scholar
  36. Mott R, Talbot CJ, Turri MG, Collins AC, Flint J (2000) A method for fine mapping quantitative trait loci in outbred animal stocks. Proc Natl Acad Sci USA 97:12649–12654CrossRefPubMedCentralPubMedGoogle Scholar
  37. Pasam RK, Sharma R, Malosetti M, van Eeuwijk FA, Haseneyer G, Kilian B, Graner A (2012) Genome-wide association studies for agronomical traits in a world wide spring barley collection. BMC Plant Biol 12:16. doi: 10.1186/1471-2229-12-16 CrossRefPubMedCentralPubMedGoogle Scholar
  38. Pritchard JK, Przeworski M (2001) Linkage disequilibrium in humans: models and data. Am J Hum Genet 69:1–14. doi: 10.1086/321275 CrossRefPubMedCentralPubMedGoogle Scholar
  39. Putterill J, Laurie R, Macknight R (2004) It’s time to flower: the genetic control of flowering time. BioEssays: News Rev Mol cell Develop Biol 26:363–373. doi: 10.1002/bies.20021
  40. Schmalenbach I, Leon J, Pillen K (2009) Identification and verification of QTLs for agronomic traits using wild barley introgression lines. Theor Appl Genet 118:483–497. doi: 10.1007/s00122-008-0915-z CrossRefPubMedGoogle Scholar
  41. Szucs P et al (2007) Validation of the VRN-H2/VRN-H1 epistatic model in barley reveals that intron length variation in VRN-H1 may account for a continuum of vernalization sensitivity. Mol Genet Genom 277:249–261. doi: 10.1007/s00438-006-0195-8 CrossRefGoogle Scholar
  42. Trevaskis B, Hemming MN, Dennis ES, Peacock WJ (2007) The molecular basis of vernalization-induced flowering in cereals. Trends Plant Sci 12:352–357. doi: 10.1016/j.tplants.2007.06.010 CrossRefPubMedGoogle Scholar
  43. von Korff M, Wang H, Leon J, Pillen K (2006) AB-QTL analysis in spring barley: II. Detection of favourable exotic alleles for agronomic traits introgressed from wild barley (H. vulgare ssp. spontaneum). Theor Appl Genet 112:1221–1231. doi: 10.1007/s00122-006-0223-4 CrossRefGoogle Scholar
  44. Wang GW, Schmalenbach I, von Korff M, Leon J, Kilian B, Rode J, Pillen K (2010) Association of barley photoperiod and vernalization genes with QTLs for flowering time and agronomic traits in a BC2DH population and a set of wild barley introgression lines. Theor Appl Genet 120:1559–1574. doi: 10.1007/s00122-010-1276-y CrossRefPubMedCentralPubMedGoogle Scholar
  45. Yalcin B, Flint J, Mott R (2005) Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics 171:673–681CrossRefPubMedCentralPubMedGoogle Scholar
  46. Yan L et al (2004) The wheat VRN2 gene is a flowering repressor down-regulated by vernalization. Science 303:1640–1644. doi: 10.1126/science.1094305 CrossRefPubMedGoogle Scholar
  47. Yan L et al (2006) The wheat and barley vernalization gene VRN3 is an orthologue of FT. Proc Natl Acad Sci USA 103:19581–19586. doi: 10.1073/pnas.0607142103 CrossRefPubMedCentralPubMedGoogle Scholar
  48. Zhang J YX, Moolhuijzen P, Li C, Bellgard M, Lance R, Appels R (2005) Towards isolation of the barley green revolution gene. Paper presented at the proceedings of the 12th Australian barley technical symposium, 11–14 Sept 2005Google Scholar
  49. Zhao HY, Pfeiffer R, Gail MH (2003) Haplotype analysis in population genetics and association studies. Pharmacogenomics 4:171–178CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Wiebke Sannemann
    • 1
    Email author
  • Bevan Emma Huang
    • 2
  • Boby Mathew
    • 1
  • Jens Léon
    • 1
  1. 1.Institute for Crop Science and Resource Conservation, Chair of Plant BreedingUniversity BonnBonnGermany
  2. 2.CSIRO Computational Informatics and Food Futures National Research FlagshipDutton ParkAustralia

Personalised recommendations