Skip to main content

Advertisement

SpringerLink
Log in

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye

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

Abstract

Key message

Genetic diversity in elite rye germplasm as well as F 2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids.

Abstract

Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.

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

Similar content being viewed by others

References

  • Auinger HJ, Schönleben M, Lehermeier C, Schmidt M, Korzun V, Geiger HH, Piepho HP, Gordillo A, Wilde P, Bauer E, Schön CC (2016) Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.). Theor Appl Genet 129:2043–2053. doi:10.1007/s00122-016-2756-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Austin DF, Lee M (1996) Comparative mapping in F2:3 and F6:7 generations of quantitative trait loci for grain yield and yield components in maize. Theor Appl Genet 92:817–826. doi:10.1007/BF00221893

    Article  CAS  PubMed  Google Scholar 

  • Bartos J, Paux E, Kofler R, Havránková M, Kopecký D, Suchánková P, Safár J, Simková H, Town CD, Lelley T, Feuillet C, Dolezel J (2008) A first survey of the rye (Secale cereale) genome composition through BAC end sequencing of the short arm of chromosome 1R. BMC Plant Biol 8:95. doi:10.1186/1471-2229-8-95

    Article  PubMed  PubMed Central  Google Scholar 

  • Bauer E, Schmutzer T, Barilar I, Mascher M, Gundlach H, Martis MM, Twardziok SO, Hackauf B, Gordillo A, Wilde P, Schmidt M, Korzun V, Mayer KF, Schmid K, Schön C-C, Scholz U (2017) Towards a whole-genome sequence for rye (Secale cereale L.). Plant J. 89:853–869. doi:10.1111/tpj.13436

    Article  CAS  PubMed  Google Scholar 

  • Beavis WD (1998) QTL analyses: power, precision and accuracy. In: Paterson AH (ed) Molecular dissection of complex traits. CRC Press, Boca Raton, pp 145–162

    Google Scholar 

  • Bolibok H, Gruszczyńska A, Hromadajudycka A, Rakoczy-Trojanowska M (2007) The identification of QTL associated with the in vitro response of rye (Secale cereale L.). Cell Mol Biol Lett 12:523–535. doi:10.2478/s11658-007-0023-0

    Article  CAS  PubMed  Google Scholar 

  • Bolibok-Bragoszewska H, Heller-Uszyńska K, Wenzl P, Uszyński G, Kilian A, Rakoczy-Trojanowska M (2009) DArT markers for the rye genome—genetic diversity and mapping. BMC Genomics 10:578. doi:10.1186/1471-2164-10-578

    Article  PubMed  PubMed Central  Google Scholar 

  • Börner A, Korzun V, Voylokov AV, Weber WE (1999) Detection of quantitative trait loci on chromosome 5R of rye (Secale cereale L.). Theor Appl Genet 98:1087–1090. doi:10.1007/s11032-011-9627-1

    Article  Google Scholar 

  • Börner A, Korzun V, Voylokov AV, Worland AJ, Weber WE (2000) Genetic mapping of quantitative trait loci in rye (Secale cereale L.). Euphytica 116:203–209. doi:10.1023/A:1004052505692

    Article  Google Scholar 

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    CAS  PubMed  PubMed Central  Google Scholar 

  • Collins NC, Shirley NJ, Saeed M, Pallotta M, Gustafson JP (2008) An ALMT1 gene cluster controlling aluminum tolerance at the Alt4 locus of rye (Secale cereale L.). Genetics 179:669–682. doi:10.1534/genetics.107.083451

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Deutscher W (2011) Review of the year: The weather in Germany in 2011. www.dwd.de

  • Deutscher W (2012) Review of the year: The weather in Germany in 2012. www.dwd.de

  • Devos KM, Atkinson MD, Chinoy CN, Francis HA, Harcourt RL, Koebner RMD, Liu CJ, Masojć P, Xie DX, Gale MD (1993) Chromosomal rearrangements in the rye genome relative to that of wheat. Theor Appl Genet 85:673–680. doi:10.1007/BF00225004

    Article  CAS  PubMed  Google Scholar 

  • Dibari B, Murat F, Chosson A, Gautier V, Poncet C, Lecomte P, Mercier I, Bergès H, Pont C, Blanco A, Salse J (2012) Deciphering the genomic structure, function and evolution of carotenogenesis related phytoene synthases in grasses. BMC Genomics 6(13):221. doi:10.1186/1471-2164-13-221

    Article  Google Scholar 

  • Falke KC, Susić Z, Hackauf B, Korzun V, Schondelmaier J, Wilde P, Wehling P, Wortmann H, Mank R, Rouppe van der Voort J, Maurer HP, Miedaner T, Geiger HH (2008) Establishment of introgression libraries in hybrid rye (Secale cereale L.) from an Iranian primitive accession as a new tool for rye breeding and genomics. Theor Appl Genet 117:641–652. doi:10.1007/s00122-008-0808-1

    Article  CAS  PubMed  Google Scholar 

  • Falke KC, Susić Z, Wilde P, Wortmann H, Möhring J, Piepho HP, Geiger HH, Miedaner T (2009) Testcross performance of rye introgression lines developed by marker-assisted backcrossing using an Iranian accession as donor. Theor Appl Genet 118:1225–1238. doi:10.1007/s00122-009-0976-7

    Article  CAS  PubMed  Google Scholar 

  • Farrall M (2004) Quantitative genetic variation: a post-modern view. Hum Mol Genet 13 Spec No 1: R1-7. doi: 10.1093/hmg/ddh084

  • Fehr WR (1987) Heritability. In: Fehr WR (ed) Principles of cultivar development theory and technique. McMillan Pub. Co., New York, pp 95–105

    Google Scholar 

  • Fisch RD, Ragot M, Gay G (1996) A generalization of the mixture model in the mapping of quantitative trait loci for progeny from a biparental cross of inbred lines. Genetics 143:571–577

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fischer RA (1921) On the “probable error” of a coefficient of correlation deduced from a small sample. Metron 1:1–32

    Google Scholar 

  • Fisher RA (1918) The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinb 52:399–433

    Article  Google Scholar 

  • Fleury D, Jefferies S, Kuchel H, Langridge P (2010) Genetic and genomic tools to improve drought tolerance in wheat. J Exp Bot 61:3211–3222. doi:10.1093/jxb/erq152

    Article  CAS  PubMed  Google Scholar 

  • Gawroński P, Pawełkowicz M, Tofil K, Uszyński G, Sharifova S, Ahluwalia S, Tyrka M, Wędzony M, Kilian A, Bolibok-Brągoszewska H (2016) DArT markers effectively target gene space in the rye genome. Front Plant Sci. 7:1600. doi:10.3389/fpls.2016.01600

    PubMed  PubMed Central  Google Scholar 

  • Geiger HH, Miedaner T (2009) Rye breeding. In: Carena MJ (ed), Cereals, pp. 157–181. Handbook of plant breeding, vol. 3. Springer Science + Business Media

  • Geiger HH, Wahle G (1978) Struktur der Heterosis von Komplexmerkmalen bei Winterrroggen-Einfachhybriden. Z. Pflanzenzüchtg. 80:178–210

    Google Scholar 

  • Hackauf B, Wehling P (2005) Approaching the self-incompatibility locus Z in rye (Secale cereale L.) via comparative genetics. Theor Appl Genet 110:832–845. doi:10.1007/s00122-004-1869-4

    Article  CAS  PubMed  Google Scholar 

  • Hackauf B, Rudd S, van der Voort JR, Miedaner T, Wehling P (2009) Comparative mapping of DNA sequences in rye (Secale cereale L.) in relation to the rice genome. Theor Appl Genet 118:371–384. doi:10.1007/s00122-008-0906-0

    Article  CAS  PubMed  Google Scholar 

  • Hackauf B, Korzun V, Wortmann H, Wilde P, Wehling P (2012) Development of conserved ortholog set markers linked to the restorer gene Rfp1 in rye. Mol. Breed. 30:1507–1518. doi:10.1007/s11032-012-9736-5

    Article  Google Scholar 

  • Haffke S, Kusterer B, Fromme FJ, Roux S, Hackauf B, Miedaner T (2014) Analysis of covariation of grain yield and dry matter yield for breeding dual use hybrid rye. Bioenergy Res. 7:424–429. doi:10.1007/s12155-013-9383-7

    Article  Google Scholar 

  • Hallauer AR, Miranda JB (1988) Quantitative genetics in maize breeding. Iowa State University Press, Ames

    Google Scholar 

  • Hallauer AR, Carena MJ, Miranda Filho JB (2010) Quantitative genetics in maize breeding. Handbook of Plant Breeding vol. 6, 3rd edn, 664 p, Springer, New York

  • Hepting L (1978) Analysis of a 7 × 7-variety diallel for determination of suitable base materials for hybrid breeding in rye. Z. Pflanzenzüchtg. 80:188–197

    Google Scholar 

  • Higgins JA, Bailey PC, Laurie DA (2010) Comparative genomics of flowering time pathways using Brachypodium distachyon as a model for the temperate grasses. PLoS ONE 5:e10065. doi:10.1371/journal.pone.0010065

    Article  PubMed  PubMed Central  Google Scholar 

  • Hou J, Jiang Q, Hao C, Wang Y, Zhang H, Zhang X (2014) Global selection on sucrose synthase haplotypes during a century of wheat breeding. Plant Physiol 164:1918–1929. doi:10.1104/pp.113.232454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hung HY, Browne C, Guill K, Coles N, Eller M, Garcia A, Lepak N, Melia-Hancock S, Oropeza-Rosas M, Salvo S, Upadyayula N, Buckler ES, Flint-Garcia S, McMullen MD, Rocheford TR, Holland JB (2012) The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population. Heredity 108:490–499. doi:10.1038/hdy.2011.103

    Article  CAS  PubMed  Google Scholar 

  • Jiang Y, Jiang Q, Hao C, Hou J, Wang L, Zhang H, Zhang S, Chen X, Zhang X (2015) A yield-associated gene TaCWI, in wheat: its function, selection and evolution in global breeding revealed by haplotype analysis. Theor Appl Genet 128:131–143. doi:10.1007/s00122-014-2417-5

    Article  CAS  PubMed  Google Scholar 

  • Kawahara Y, de la Bastide M, Hamilton JP, Kanamori H, McCombie WR, Ouyang S, Schwartz DC, Tanaka T, Wu J, Zhou S, Childs KL, Davidson RM, Lin H, Quesada-Ocampo L, Vaillancourt B, Sakai H, Lee SS, Kim J, Numa H, Itoh T, Buell CR, Matsumoto T (2013) Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice 6:4. doi:10.1186/1939-8433-6-4

    Article  PubMed  PubMed Central  Google Scholar 

  • Khlestkina EK, Than MH, Pestsova EG, Röder MS, Malyshev SV, Korzun V, Börner A (2004) Mapping of 99 new microsatellite-derived loci in rye (Secale cereale L.) including 39 expressed sequence tags. Theor Appl Genet 109:725–732. doi:10.1007/s00122-004-1659-z

    Article  CAS  PubMed  Google Scholar 

  • Kimura M (1983) The neutral theory of molecular evolution. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Knapp SJ, Holloway JL, Bridges WC, Liu B-H (1995) Mapping dominant markers using F2 matings. Theor Appl Genet 91:74–81. doi:10.1007/BF00220861

    Article  CAS  PubMed  Google Scholar 

  • Korzun V, Malyshev S, Voylokov AV, Börner A (2001) A genetic map of rye (Secale cereale L.) combining RFLP, isozyme, protein, microsatellite and gene loci. Theor Appl Genet 102:709–717. doi:10.1007/s001220051701

    Article  CAS  Google Scholar 

  • Kovach MJ, McCouch SR (2008) Leveraging natural diversity: back through the bottleneck. Curr Opin Plant Biol 11:193–200. doi:10.1016/j.pbi.2007.12.006

    Article  CAS  PubMed  Google Scholar 

  • Kumar GR, Sakthivel K, Sundaramm RM, Neeraja CN, Balachandran SM, Rani NS, Viraktamath BC, Madhav MS (2010) Allele mining in crops: prospects and potentials. Biotechnol Adv 28:451–461. doi:10.1016/j.biotechadv.2010.02.007

    Article  CAS  PubMed  Google Scholar 

  • Laidig F, Piepho HP, Rentel D, Drobek T, Meyer U, Huesken A (2017) Breeding progress, variation, and correlation of grain and quality traits in winter rye hybrid and population varieties and national on-farm progress in Germany over 26 years. Theor Appl Genet. doi:10.1007/s00122-017-2865-9

    PubMed Central  Google Scholar 

  • Langer SM, Longin CF, Würschum T (2014) Flowering time control in European winter wheat. Front Plant Sci 5:537. doi:10.3389/fpls.2014.00537

    Article  PubMed  PubMed Central  Google Scholar 

  • Li H, Zhang L, Wang J (2012a) Estimation of statistical power and false discovery rate of QTL mapping methods through computer simulation. Chin Sci Bull 57:2701–2710. doi:10.1007/s11434-012-5239-3

    Article  Google Scholar 

  • Li J, Chu H, Zhang Y, Mou T, Wu C, Zhang Q, Xu J (2012b) The rice HGW gene encodes a ubiquitin-associated (UBA) domain protein that regulates heading date and grain weight. PLoS ONE 7:e34231. doi:10.1371/journal.pone.0034231

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lo SF, Yang SY, Chen KT, Hsing YI, Zeevaart JA, Chen LJ, Yu SM (2008) A novel class of gibberellin 2-oxidases control semidwarfism, tillering, and root development in rice. Plant Cell 20:2018–2603. doi:10.1105/tpc.108.060913

    Article  Google Scholar 

  • Lo SF, Ho TD, Liu YL, Jiang MJ, Hsieh KT, Chen KT, Yu LC, Lee MH, Chen CY, Huang TP, Kojima M, Sakakibara H, Chen LJ, Yu SM (2016) Ectopic expression of specific GA2 oxidase mutants promotes yield and stress tolerance in rice. Plant Biotechnol J. doi:10.1111/pbi.12681

    Google Scholar 

  • Ma XF, Wanous MK, Houchins K, Rodriguez MA, Milla Goicoechea PG, Wang Z, Xie M, Gustafson JP (2001) Molecular linkage mapping in rye (Secale cereale L.). Theor Appl Genet 102:517–523. doi:10.1007/s001220051676

    Article  CAS  Google Scholar 

  • Ma L, Li T, Hao C, Wang Y, Chen X, Zhang X (2016) TaGS5-3A, a grain size gene selected during wheat improvement for larger kernel and yield. Plant Biotechnol J 14:1269–1280. doi:10.1111/pbi.12492

    Article  CAS  PubMed  Google Scholar 

  • Mackay TFC, Stone EA, Ayroles JF (2009) The genetics of quantitative traits: challenges and prospects. Nat Rev Genet 10:565–577. doi:10.1038/nrg2612

    Article  CAS  PubMed  Google Scholar 

  • Mago R, Miah H, Lawrence GJ, Wellings CR, Spielmeyer W, Bariana HS, McIntosh RA, Pryor AJ, Ellis JG (2005) High-resolution mapping and mutation analysis separate the rust resistance genes Sr31, Lr26 and Yr9 on the short arm of rye chromosome 1. Theor Appl Genet 112:41–50. doi:10.1007/s00122-005-0098-9

    Article  CAS  PubMed  Google Scholar 

  • Martis MM, Zhou R, Haseneyer G, Schmutzer T, Vrána J, Kubaláková M, König S, Kugler KG, Scholz U, Hackauf B, Korzun V, Schön CC, Dolezel J, Bauer E, Mayer KF, Stein N (2013) Reticulate evolution of the rye genome. Plant Cell. 25:3685–3698. doi:10.1105/tpc.113.114553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Masojć P, Milczarski P (2005) Mapping QTL for alpha-amylase activity in rye grain. J Appl Genet 46:115–123

    PubMed  Google Scholar 

  • Masojć P, Milczarski P (2008) Relationship between QTL for preharvest sprouting and alpha-amylase activity in rye grain. Mol Breed 23:75–84. doi:10.1007/s11032-008-9215-1

    Article  Google Scholar 

  • McIntosh RA, Yamazaki Y, Dubcovsky J, Rogers J, Morris C, Appels R, Xia XC (2013) Catalogue of gene symbols for wheat. In:12th International Wheat Genetics Symposium 8–13 September 2013, Yokohama, Japan

  • Melchinger AE, Gumber RK, Leipert RB, Vuylsteke M, Kuiper M (1998) Prediction of testcross means and variances among F3 progenies of F1 crosses from testcross means and genetic distances of their parents in maize. Theor Appl Genet 96:503–512. doi:10.1007/s001220050767

    Article  CAS  PubMed  Google Scholar 

  • Mester DI, Ronin YI, Hu Y, Peng J, Nevo E, Korol AB (2003) Efficient multipoint mapping: making use of dominant repulsion-phase markers. Theor Appl Genet 107:1102–1112. doi:10.1007/s00122-003-1305-1

    Article  CAS  PubMed  Google Scholar 

  • Meuwissen THE, Hayes B, Goddard M (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    CAS  PubMed  PubMed Central  Google Scholar 

  • Miedaner T, Hübner M, Korzun V, Schmiedchen B, Bauer E, Haseneyer G, Wilde P, Reif JC (2012) Genetic architecture of complex agronomic traits examined in two testcross populations of rye (Secale cereale L.). BMC Genomics 13:706. doi:10.1186/1471-2164-13-706

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Miedaner T, Schwegler DD, Wilde P, Reif J (2014) Association between line per se and testcross performance for eight agronomic and quality traits in winter rye. Theor Appl Gen 127:33–41. doi:10.1007/s00122-013-2198-2

    Article  Google Scholar 

  • Miedaner T, Herter CP, Goßlau H, Wilde P, Hackauf B (2017) Correlated effects of exotic pollen-fertility restorer genes on agronomic and quality traits of hybrid rye. Plant Breed. doi:10.1111/pbr.12456

    Google Scholar 

  • Miftahudin Scoles GJ, Gustafson JP (2004) Development of PCR-based codominant markers flanking the Alt3 gene in rye. Genome 47:231–238. doi:10.1139/g03-093

    Article  CAS  PubMed  Google Scholar 

  • Mihaljevic R, Schön CC, Utz HF, Melchinger AE (2005) Correlations and QTL correspondence between line per se and testcross performance for agronomic traits in four populations of European maize. Crop Science 45:114–122

    Article  Google Scholar 

  • Milczarski P, Masojć P (2003) Interval mapping of genes controlling growth of rye plants. Plant Breed. Seed Sci. 48:135–142

    Google Scholar 

  • Milczarski P, Bolibok-Brągoszewska H, Myśków B, Stojałowski S, Heller-Uszyńska K, Góralska M, Brągoszewski P, Uszyński G, Kilian A, Rakoczy-Trojanowska M (2011) A high density consensus map of rye (Secale cereale L.) based on DArT markers. PLoS ONE 6:e28495. doi:10.1371/journal.pone.0028495

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Monaco MK, Stein J, Naithani S, Wei S, Dharmawardhana P, Kumari S, Amarasinghe V, Youens-Clark K, Thomason J, Preece J, Pasternak S, Olson A, Jiao Y, Lu Z, Bolser D, Kerhornou A, Staines D, Walts B, Wu G, D’Eustachio P, Haw R, Croft D, Kersey PJ, Stein L, Jaiswal P, Ware D (2014) Gramene 2013: comparative plant genomics resources. Nucleic Acids Res 42:D1193–D1199. doi:10.1093/nar/gkt1110

    Article  CAS  PubMed  Google Scholar 

  • Munkvold JD, Greene RA, Bermudez-Kandianis CE, La Rota CM, Edwards H, Sorrells SF, Dake T, Benscher D, Kantety R, Linkiewicz AM, Dubcovsky J, Akhunov ED, Dvorák J, Miftahudin Gustafson JP, Pathan MS, Nguyen HT, Matthews DE, Chao S, Lazo GR, Hummel DD, Anderson OD, Anderson JA, Gonzalez-Hernandez JL, Peng JH, Lapitan N, Qi LL, Echalier B, Gill BS, Hossain KG, Kalavacharla V, Kianian SF, Sandhu D, Erayman M, Gill KS, McGuire PE, Qualset CO, Sorrells ME (2004) Group 3 chromosome bin maps of wheat and their relationship to rice chromosome 1. Genetics 168:639–650. doi:10.1534/genetics.104.034819

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Myśków B, Stojałowski S, Łań A, Bolibok-Bragoszewska H, Rakoczy-Trojanowska M, Kilian A (2011) Detection of the quantitative trait loci for α-amylase activity on a high-density genetic map of rye and comparison of their localization to loci controlling preharvest sprouting and earliness. Mol Breeding 30:367–376. doi:10.1007/s11032-011-9627-1

    Google Scholar 

  • Myśków B, Hanek M, Banek-Tabor A, Maciorowski R, Stojałowski S (2014) The application of high-density genetic maps of rye for the detection of QTL controlling morphological traits. J Appl Genet 55:15–26. doi:10.1007/s13353-013-0186-5

    Article  PubMed  Google Scholar 

  • Orr HA (1998) The population genetics of adaptation: the distribution of factors fixed during adaptive evolution. Evolution 52:935–949. doi:10.2307/2411226

    Article  PubMed  Google Scholar 

  • Passioura JB (1996) Drought and drought tolerance. Plant Growth Regul 20:79–83. doi:10.1007/978-94-017-1299-6_1

    Article  CAS  Google Scholar 

  • Phillips PC (2005) Testing hypotheses regarding the genetics of adaptation. Genetica 123:15–24. doi:10.1007/s10709-004-2704-1

    Article  PubMed  Google Scholar 

  • Qi W, Sun F, Wang Q, Chen M, Huang Y, Feng YQ, Luo X, Yang J (2011) Rice ethylene-response AP2/ERF factor OsEATB restricts internode elongation by down-regulating a gibberellin biosynthetic gene. Plant Physiol 157:216–228. doi:10.1104/pp.111.179945

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Qin L, Hao C, Hou J, Wang Y, Li T, Wang L, Ma Z, Zhang X (2014) Homologous haplotypes, expression, genetic effects and geographic distribution of the wheat yield gene TaGW2. BMC Plant Biol 14:107. doi:10.1186/1471-2229-14-107

    Article  PubMed  PubMed Central  Google Scholar 

  • Quraishi UM, Abrouk M, Murat F, Pont C, Foucrier S, Desmaizieres G, Confolent C, Rivière N, Charmet G, Paux E, Murigneux A, Guerreiro L, Lafarge S, Le Gouis J, Feuillet C, Salse J (2011a) Cross-genome map based dissection of a nitrogen use efficiency ortho-metaQTL in bread wheat unravels concerted cereal genome evolution. Plant J 65(5):745–756. doi:10.1111/j.1365-313X.2010.04461.x

    Article  CAS  PubMed  Google Scholar 

  • Quraishi UM, Murat F, Abrouk M, Pont C, Confolent C, Oury FX, Ward J, Boros D, Gebruers K, Delcour JA, Courtin CM, Bedo Z, Saulnier L, Guillon F, Balzergue S, Shewry PR, Feuillet C, Charmet G, Salse J (2011b) Combined meta-genomics analyses unravel candidate genes for the grain dietary fiber content in bread wheat (Triticum aestivum L.). Funct Integr Genomics 11(1):71–83. doi:10.1007/s10142-010-0183-2

    Article  CAS  PubMed  Google Scholar 

  • Röder MS, Korzun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal MW (1998) A microsatellite map of wheat. Genetics 14:2007–2023

    Google Scholar 

  • Rustgi S, Shafqat MN, Kumar N, Baenziger PS, Ali ML, Dweikat I, Campbell BT, Gill KS (2013) Genetic dissection of yield and its component traits using high-density composite map of wheat chromosome 3A: bridging gaps between QTL and underlying genes. PLoS ONE 8:e70526. doi:10.1371/journal.pone.0070526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schön CC, Utz HF, Groh S, Truberg B, Openshaw S, Melchinger AE (2004) Quantitative trait locus mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits. Genetics 167:485–498. doi:10.1534/genetics.167.1.485

    Article  PubMed  PubMed Central  Google Scholar 

  • She KC, Kusano H, Koizumi K, Yamakawa H, Hakata M, Imamura T, Fukuda M, Naito N, Tsurumaki Y, Yaeshima M, Tsuge T, Matsumoto K, Kudoh M, Itoh E, Kikuchi S, Kishimoto N, Yazaki J, Ando T, Yano M, Aoyama T, Sasaki T, Satoh H, Shimada H (2010) A novel factor FLOURY ENDOSPERM2 is involved in regulation of rice grain size and starch quality. Plant Cell. 22:3280–32394. doi:10.1105/tpc.109.070821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Slafer GA, Whitechurch EM (2001) Manipulating wheat development to improve adaptation and to search for alternative opportunities to increase yield potential. In: Reynolds MP, Ortiz-Monasterio JI, McNab A (eds) Application of physiology in wheat breeding. CIMMYT, Mexico, pp 160–170

    Google Scholar 

  • Stange M, Utz HF, Schrag TA, Melchinger AE, Würschum T (2013) High-density genotyping: an overkill for QTL mapping? Lessons learned from a case study in maize and simulations. Theor Appl Genet 126:2563–2574. doi:10.1007/s00122-013-2155-0

    Article  CAS  PubMed  Google Scholar 

  • Su Z, Hao C, Wang L, Dong Y, Zhang X (2011) Identification and development of a functional marker of TaGW2 associated with grain weight in bread wheat (Triticum aestivum L.). Theor Appl Genet 122:211–223. doi:10.1007/s00122-010-1437-z

    Article  CAS  PubMed  Google Scholar 

  • Swamy BP, Vikram P, Dixit S, Ahmed HU, Kumar A (2011) Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus. BMC Genomics 12:319. doi:10.1186/1471-2164-12-319

    Article  PubMed  PubMed Central  Google Scholar 

  • Utz HF (2010) PLABSTAT. Computerprogramm für statistische Analyse für Pflanzenzüchtungsversuche. Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik, Universität Hohenheim, Stuttgart

  • Utz HF (2012) PlabMQTL—Software for meta-QTL analysis with composite interval mapping. Version 0.5 s. Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim. PlabMQTL Manual

  • Valluru R, Reynolds MP, Salse J (2014) Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat. Theor Appl Genet 127:1463–1489. doi:10.1007/s00122-014-2332-9

    Article  CAS  PubMed  Google Scholar 

  • Van Ooijen JW (2006) JoinMap ® 4, Software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, Wageningen, Netherlands

  • Viana JMS, e Silva FF, Mundim GB, Azevedo CF, Jan HU (2017) Efficiency of low heritability QTL mapping under high SNP density. Euphytica 213:13. doi:10.1007/s10681-016-1800-5

    Article  Google Scholar 

  • Vikram P, Swamy BP, Dixit S, Ahmed HU, Teresa Sta Cruz M, Singh AK, Kumar A (2011) qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genet 12:89. doi:10.1186/1471-2156-12-89

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Voorrips RE (2002) MapChart: Software for the graphical presentation of linkage maps and QTL. J Hered 93:77–78

    Article  CAS  PubMed  Google Scholar 

  • Wang Y, Mette MF, Miedaner T, Gottwald M, Wilde P, Reif JC, Zhao Y (2014) The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years. BMC Genom 15:556. doi:10.1186/1471-2156-12-89

    Article  Google Scholar 

  • Wricke G (2002) Two major genes for kernel weight in rye. Plant Breed 121:26–28. doi:10.1046/j.1439-0523.2002.00666.x

    Article  CAS  Google Scholar 

  • Wright SI, Vroh Bi I, Schroeder SG, Yamasaki M, Doebley JF, McMullen MD, Gaut BS (2005) The effects of artificial selection on the maize genome. Science 308:1310–1314. doi:10.1126/science.1107891

    Article  CAS  PubMed  Google Scholar 

  • Xing Y, Zhang Q (2010) Genetic and molecular bases of rice yield. Annu Rev Plant Biol 61:421–442. doi:10.1146/annurev-arplant-042809-112209

    Article  CAS  PubMed  Google Scholar 

  • Xu S (2003) Theoretical basis of the Beavis effect. Genetics 165:2259–2268

    PubMed  PubMed Central  Google Scholar 

  • Yamamoto E, Yonemaru JI, Yamamoto T, Yano M (2012) OGRO: the overview of functionally characterized genes in rice online database. Rice 5:26. doi:10.1186/1939-8433-5-26

    Article  PubMed  PubMed Central  Google Scholar 

  • Yamasaki M, Tenaillon MI, Bi IV, Schroeder SG, Sanchez-Villeda H, Doebley JF, Gaut BS, McMullen MD (2005) A large-scale screen for artificial selection in maize identifies candidate agronomic loci for domestication and crop improvement. Plant Cell 17:2859–2872. doi:10.1105/tpc.105.037242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yonemaru JI, Yamamoto T, Fukuoka S, Uga Y, Hori K, Yano M (2010) Q-TARO: QTL annotation rice online database. Rice 3:194–203. doi:10.1007/s12284-010-9041-z

    Article  Google Scholar 

  • Yue A, Li A, Mao X, Chang X, Li R, Jing R (2015) Identification and development of a functional marker from 6-SFT-A2 associated with grain weight in wheat. Mol Breed 35:63. doi:10.1007/s11032-015-0266-9

    Article  PubMed  PubMed Central  Google Scholar 

  • Zanke C, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Beier S, Ganal W, Röder MS (2014) Genetic architecture of main effect QTL for heading date in European winter wheat. Front Plant Sci 5:217. doi:10.3389/fpls.2014.00217

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhang L, Zhao YL, Gao LF, Zhao GY, Zhou RH, Zhang BS, Jia JZ (2012) TaCKX6-D1, the ortholog of rice OsCKX2, is associated with grain weight in hexaploid wheat. New Phytol 195:184–574. doi:10.1111/j.1469-8137.2012.04194.x

    Google Scholar 

  • Zhang B, Liu X, Xu W, Chang J, Li A, Mao X, Zhang X, Jing R (2015) Novel function of a putative MOC1 ortholog associated with spikelet number per spike in common wheat. Sci Rep. 5:12211. doi:10.1038/srep12211

    Article  PubMed  PubMed Central  Google Scholar 

  • Zuo J, Li J (2014) Molecular dissection of complex agronomic traits of rice: a team effort by Chinese scientists in recent years. Natl Sci Rev. 1:253–276. doi:10.1093/nsr/nwt004

    Article  Google Scholar 

Download references

Acknowledgements

We highly appreciate the teams at the respective stations of HYBRO Saatzucht GmbH & Co. KG, University of Hohenheim, and Julius Kühn-Institut Groß Lüsewitz for their excellent technical assistance in performing the field trials and data collection. We gratefully acknowledge the excellent technical assistance of Gunda Kölzow in genotyping of the population. This study was financially supported by the Federal Ministry of Education and Research (Grant no. 0315445A, 0315445C, and 0315445D) and the company HYBRO Saatzucht GmbH & Co. KG, Germany. The responsibility of the content of this publication rests with the authors.

Author information

Authors and Affiliations

  1. Julius Kühn-Institut, Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Agricultural Crops, Groß Lüsewitz, 18190, Sanitz, Germany

    Bernd Hackauf, Steffen R. Roux & Dörthe Musmann

  2. HYBRO Saatzucht GmbH and Co. KG, 17291, Schenkenberg, Germany

    Franz Joachim Fromme, Barbara Kusterer & Dörthe Musmann

  3. State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany

    Stefan Haffke & Thomas Miedaner

  4. Bundessortenamt, Osterfelddamm 80, 30627, Hannover, Germany

    Stefan Haffke

  5. Diversity Arrays Technology, Bruce, ACT, 2617, Australia

    Andrzej Kilian

Authors
  1. Bernd Hackauf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan Haffke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Franz Joachim Fromme
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Steffen R. Roux
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Barbara Kusterer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dörthe Musmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Andrzej Kilian
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Thomas Miedaner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bernd Hackauf.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Additional information

Communicated by Aimin Zhang.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (XLSX 28 kb)

Supplementary material 2 (XLSX 188 kb)

Supplementary material 3 (XLSX 1006 kb)

Supplementary material 4 (XLSX 350 kb)

122_2017_2926_MOESM5_ESM.jpg

Supplementary material 5 (JPEG 467 kb) Comparative QTL mapping between rye and rice. Gene-derived markers are given in bold and allow to integrate a 98.2 cM segment of rye chromosome 1R into the physical map of rice chromosomes 5 (R5) and 10 (R10). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of he markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indic te the position of the following quantitative traits: QTgw-1R.1, QTgw-1R.2: thousand grain weight, KW10: kernel weight, w5: 1000-seed weight. A description of the genes indicated in the rice physical maps is given in ESM4

122_2017_2926_MOESM6_ESM.jpg

Supplementary material 6 (JPEG 284 kb) Comparative QTL mapping between rye and rice. Gene-derived markers are given in bold andallow to integrate a 6.8 cM segment of rye chromosome 3R into the physical map of rice chromosome 1 (R1). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of the markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indicate the position of the following quantitative traits: QTgw-3R: thousand grain weight, gw1: 1000-seed weight, QSsm-3R: spikes per square meter, QGyd-3R: grain yield. A description of the genes indicated in the rice physical maps is given in ESM4

122_2017_2926_MOESM7_ESM.jpg

Supplementary material 7 (JPEG 451 kb) Comparative QTL mapping between rye and rice. G 1026 ene-derived markers are given in bold and allow to integrate a 44 cM segment of rye chromosome 4R into the physical map of rice chromosomes 6 (R6) and 11 (R11). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of the markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indicate the position of the following quantitative traits: QHdt-4R.1, QHdt-4R.2: heading date, QPh3-4R.1, QPh3-4R.2: plant height, QTgw-4R.1, QTgw-4R.2, QTgw-4R.3: thousand grain weight, hd6: heading date, tgwt11, gw6: 1000-seed weight, ph11: plant height. A description of the genes indicated in the rice physical maps is given in ESM4

122_2017_2926_MOESM8_ESM.jpg

Supplementary material 8 (JPEG 560 kb) Comparative QTL mapping between rye and rice. Gene-derived markers are given in bold and allow to integrate a 33.3 cM segment of rye chromosome 5R into the physical map of rice chromosome 3 (R3). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of the markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indicate the position of the following quantitative traits: QHdt-5R: heading date, QTgw-5R: thousand grain weight, QGyd-5R: grain yield, QSsm-5R: spikes per square meter, Hd3b, Hd3c, Hd6: days to heading, QKw3a: 1000-seed weight, qgy3.1: grain yield. A description of the genes indicated in the rice physical maps is given in ESM4

122_2017_2926_MOESM9_ESM.jpg

Supplementary material 9 (JPEG 334 kb) Comparative QTL mapping between rye and rice. Gene-derived markers are given in bold and allow to integrate a 35.6 cM segment of rye chromosome 6R into the physical map of rice chromosome 2 (R2). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of the markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indicate the position of the following quantitative traits: QHdt-6R: heading date, QTgw-6R: thousand grain weight, dth2.1: days to heading, QKwa2a: 1000-seed weight. A description of the genes indicated in the rice physical maps is given in ESM4

122_2017_2926_MOESM10_ESM.jpg

Supplementary material 10 (JPEG 268 kb) Comparative QTL mapping between rye and rice. Gene-derived markers are given in bold and allow to integrate a 12.4 cM segment of rye chromosome 7R into the physical map of rice chromosome 3 (R3). The gene-derived markers and their orthologs in rice are connected by dotted lines. The positions of the markers in the rye map are given in cM and in the physical map of rice in Mb. The vertical bars and QTL symbols indicate the position of the following quantitative traits: QTgw-7R: thousand grain weight, QHdt-7R: heading date, Qhd3b: days to heading. A description of the genes indicated in the rice physical maps is given ESM4

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hackauf, B., Haffke, S., Fromme, F.J. et al. QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye. Theor Appl Genet 130, 1801–1817 (2017). https://doi.org/10.1007/s00122-017-2926-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-017-2926-0

Search

Navigation