Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ali MAM, Okiror SO, Rasmusson DC (1978) Performance of semidwarf barley. Crop Sci 18:418–422. doi:10.2135/cropsci1978.0011183X001800030015x
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
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
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
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
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
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
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
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. http://www.nature.com/ng/journal/vaop/ncurrent/abs/ng.2447.html#supplementary-information
Darvasi A, Soller M (1995) Advanced intercross lines, an experimental population for fine genetic-mapping. Genetics 141:1199–1207
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
Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3:43–52. doi:10.1038/nrg703
Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285–294
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 38:575–585
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
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
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
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
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
Milne I et al (2010) Flapjack-graphical genotype visualization. Bioinformatics 26:3133–3134. doi:10.1093/bioinformatics/btq580
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 97:12649–12654
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
Pritchard JK, Przeworski M (2001) Linkage disequilibrium in humans: models and data. Am J Hum Genet 69:1–14. doi:10.1086/321275
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
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
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
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
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
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
Yalcin B, Flint J, Mott R (2005) Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics 171:673–681
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
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
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 2005
Zhao HY, Pfeiffer R, Gail MH (2003) Haplotype analysis in population genetics and association studies. Pharmacogenomics 4:171–178
Acknowledgments
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 CROP.SENSe.net (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.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Sannemann, W., Huang, B.E., Mathew, B. et al. Multi-parent advanced generation inter-cross in barley: high-resolution quantitative trait locus mapping for flowering time as a proof of concept. Mol Breeding 35, 86 (2015). https://doi.org/10.1007/s11032-015-0284-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11032-015-0284-7