Advertisement

Molecular Breeding

, Volume 34, Issue 3, pp 1373–1387 | Cite as

Detection and validation of novel QTL for shoot and root traits in barley (Hordeum vulgare L.)

  • Md. Arifuzzaman
  • Mohammed A. Sayed
  • Shumaila Muzammil
  • Klaus Pillen
  • Henrik Schumann
  • Ali Ahmad Naz
  • Jens Léon
Article

Abstract

Shoot and root attributes are essential for plant performance in agriculture. Here, we report detection and validation of quantitative trait loci (QTL) for shoot and root traits in 301 BC2DH lines achieved by crossing cultivar Scarlett and wild barley accession ISR42-8. Phenotypic evaluations were made for six traits across 3 years under control and drought conditions. QTL analysis was performed using 371 DNA markers genotyped by different protocols, such as sequence repeats, diversity array technology as well as gene-specific markers. Marker by trait analysis revealed 33 QTL of which 15 and 18 QTL showed trait-improving effects of the exotic and elite alleles, respectively. Two major QTL for plant height (PH) were found on chromosome 2H (QPh.S42.2H) and 3H (QPh.S42.3H.b). The strongest QTL QSdw.S42.5H for increasing shoot dry weight was associated with an exotic allele on chromosome 5H. QTL QTkw.S42.1H underlie a novel exotic allele that improved thousand kernel weight. Seven QTL were associated with root dry weight of which at four loci introgression of exotic alleles enhanced traits values. The strongest QTL QRdw.S42.7H was linked to a gene-specific marker VrnH3 on chromosome 7H. At QRl.S42.5H, the exotic allele accounted for a 9 % increase in root length. In addition, 18 epistatic interactions were linked to PH, shoot and root dry weights. QTL validation was performed with 53 introgression lines (ILs) carrying ISR42-8 introgressions in the Scarlett background. Nine novel QTL alleles of exotic origin were validated in the isogenic background. These QTL-bearing ILs provide valuable genetic resources for plant breeding and positional cloning of the underlying genes.

Keywords

QTL analysis QTL validation Shoot traits Root traits Wild barley 

Notes

Acknowledgments

We offer special thanks to Mrs. Anne Reinders, Mrs. Karola Müller, Mrs. Iris Hermeling and Mrs. Martina Ruland for their support during phenotyping and to Mrs. Karin Woitol and Mr. Stephan Reinert for reading the manuscript. Part of this work was funded by the German Plant Genome Research Initiative (GABI) of the Federal Ministry of Education and Research (BMBF, Project 0312278A).

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Anonymous (2012) Food and agriculture organization, food outlook. http://www.fao.org/docrep/016/al993e/al993e00.pdf. (Accessed Jan 2013)
  2. Bauer AM, Hoti F, von Korff M, Pillen K, Léon J, Sillanpää MJ (2009) Advanced backcross QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials. Theor Appl Genet 119:105–123PubMedCrossRefPubMedCentralGoogle Scholar
  3. Benjamini Y, Yekutieli D (2005) Quantitative trait loci analysis using the false discovery rate. Genetics 171:783–790PubMedCrossRefPubMedCentralGoogle Scholar
  4. Bot AJ, Nachtergaele FO, Young A (2000) Land resource potential and constraints at regional and country levels. World soil resources reports 90. FAO, Rome, p 49Google Scholar
  5. Broman KW, Speed TP (2002) A model selection approach for identification of quantitative trait loci in experimental crosses. J R Stat Soc B 64:641–656CrossRefGoogle Scholar
  6. Chen Y, Carver BF, Wang S, Cao S, Yan L (2010) Genetic regulation of developmental phases in winter wheat. Mol Breed 26:573–582CrossRefGoogle Scholar
  7. Courtois B, McLaren G, Sinha PK, Prasad K, Yadav R, Shen L (2000) Mapping QTLs associated with drought avoidance in upland rice. Mol Breed 6:55–66CrossRefGoogle Scholar
  8. Davies WJ, Wilkinson S, Loveys B (2002) Stomatal control by chemical signalling and the exploitation of this mechanism to increase water use efficiency in agriculture. N Phytol 153:449–460CrossRefGoogle Scholar
  9. Hackett CA, Ellis RP, Forster BP, McNicol JW, Macaulay M (1992) Statistical analysis of a linkage experiment in barley involving quantitative trait loci for height and ear emergence time and two genetic markers on chromosome 4. Theor Appl Genet 85:120–126PubMedCrossRefGoogle Scholar
  10. Hoffmann A, Maurer A, Pillen K (2012) Detection of nitrogen deficiency QTL in juvenile wild barley introgression lines growing in a hydroponic system. BMC Genet 13:88PubMedCrossRefPubMedCentralGoogle Scholar
  11. Jenks MA, Hasegawa PM (2005) Plant abiotic stress. Blackwell, UKCrossRefGoogle Scholar
  12. Kavar T, Maras M, Kidric M, Sustar-Vozlic J, Meglic V (2007) Identification of genes involved in the response of leaves of Phaseolus vulgaris to drought stress. Mol Breed 21:159–172CrossRefGoogle Scholar
  13. Kleinhofs A, Graner A (2001) An integrated map of the barley genome. In: Phillips RL, Vasil IK (eds) DNA-based markers in plants. Kluwer, Dordrecht, pp 187–199CrossRefGoogle Scholar
  14. Lancashire PD, Bleiholder H, Van Den Boom T, Langelüddecke P, Stauss R, Weber E, Witzenberger A (1991) An uniform decimal code for growth stages of crops and weeds. Ann Appl Biol 119:561–601CrossRefGoogle Scholar
  15. Li Z, Mu P, Li C, Zhang H, Li Z, Gao Y, Wang X (2005) QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments. Theor Appl Genet 110:1244–1252PubMedCrossRefGoogle Scholar
  16. Liu X, Li R, Chang X, Jing R (2012) Mapping QTLs for seedling root traits in a doubled haploid wheat population under different water regimes. Euphytica 189:51–66CrossRefGoogle Scholar
  17. Morgan JA, LeCain DR, McCaig TN, Quick JS (1993) Gas exchange, carbon isotope discrimination, and productivity in winter wheat. Crop Sci 33:178–186CrossRefGoogle Scholar
  18. Naz AA, Ehl A, Pillen K, Léon J (2012) Validation of root-related quantitative trait locus effects of wild origin in the cultivated background of barley (Hordeum vulgare L.). Plant Breed 131:392–398CrossRefGoogle Scholar
  19. Pillen K, Zacharias A, Léon J (2004) Comparative AB-QTL analysis in barley using a single exotic donor of Hordeum vulgare ssp spontaneum. Theor Appl Genet 108:1591–1601PubMedCrossRefGoogle Scholar
  20. Price AH, Tomos AD, Virk DS (1997) Genetic dissection of root growth in rice (Oryza sativa L.). I: a hydrophonic screen. Theor Appl Genet 95:132–142CrossRefGoogle Scholar
  21. SAS Institute (2008) The SAS enterprise guide for windows, release 9.2. SAS Institute, CaryGoogle Scholar
  22. Sayed MA, Schumann H, Pillen K, Naz AA, Léon J (2012) AB-QTL analysis reveals new alleles associated to proline accumulation and leaf wilting under drought stress conditions in barley (Hordeum vulgare L.). BMC Genet 13:61PubMedCrossRefPubMedCentralGoogle Scholar
  23. Schachtman DP, Goodger JQD (2008) Chemical root to shoot signaling under drought. Trends Plant Sci 13:281–287PubMedCrossRefGoogle Scholar
  24. Schmalenbach I, Pillen K (2009) Detection and verification of malting quality QTLs using wild barley introgression lines. Theor Appl Genet 118(8):1411–1427PubMedCrossRefPubMedCentralGoogle Scholar
  25. Schmalenbach I, Körber N, Pillen K (2008) Selecting a set of wild barley introgression lines and verification of QTL effects for resistance to powdery mildew and leaf rust. Theor Appl Genet 117:1093–1106PubMedCrossRefGoogle Scholar
  26. Schmalenbach I, Léon J, Pillen K (2009) Identification and verification of QTLs for agronomic traits using wild barley introgression lines. Theor Appl Genet 118:483–497PubMedCrossRefGoogle Scholar
  27. Schmalenbach I, March TJ, Bringezu T, Waugh R, Pillen K (2011) High-resolution genotyping of wild barley introgression lines and fine-mapping of the threshability locus thresh-1 using the Illumina GoldenGate assay. G3 1:187–196PubMedCrossRefPubMedCentralGoogle Scholar
  28. Schuppler U, He PH, John PCL, Munns R (1998) Effects of water stress on cell division and cell-division-cycle-2-like cell-cycle kinase activity in wheat leaves. Plant Physiol 117:667–678PubMedCrossRefPubMedCentralGoogle Scholar
  29. Songsri P, Jogloy S, Holbrook CC, Kesmala T, Vorasoot N, Akkasaeng C, Patanothai A (2009) Association of root, specific leaf area and SPAD chlorophyll meter reading to water use efficiency of peanut under different available soil water. Agric Water Manag 96:790–798CrossRefGoogle Scholar
  30. Talamé V, Sanguineti MC, Chiapparino E, Bahri H, Ben Salem M, Forster BP, Ellis RP, Rhouma S, Zoumarou W, Waugh R, Tuberosa R (2004) Identification of Hordeum spontaneum QTL alleles improving field performance of barley grown under rainfed conditions. Ann Appl Biol 144:309–319CrossRefGoogle Scholar
  31. Tanksley SD (1993) Mapping polygenes. Annu Rev Genet 27:205–233PubMedCrossRefGoogle Scholar
  32. Tanksley SD, Nelson JC (1996) Advanced backcross QTL analysis: a method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines. Theor Appl Genet 92:191–203PubMedCrossRefGoogle Scholar
  33. von Korff M, Wang H, Léon J, Pillen K (2006) AB-QTL analysis in spring barley: II. Detection of favorable exotic alleles for agronomic traits introgressed from wild barley (H. vulgare ssp. spontaneum). Theor Appl Genet 112:1221–1231CrossRefGoogle Scholar
  34. von Korff M, Léon J, Pillen K (2010) Detection of epistatic interactions between exotic alleles introgressed from wild barley (H. vulgare ssp spontaneum). Theor Appl Genet 121:1455–1464CrossRefGoogle Scholar
  35. Wang G, Schmalenbach I, von Korff M, Léon 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 120:1559–1574PubMedCrossRefPubMedCentralGoogle Scholar
  36. Yadav R, Courtois B, Huang N, McLaren G (1997) Mapping genes controlling root morphology and root distribution in a doubled haploid population of rice. Theor Appl Genet 94:619–632CrossRefGoogle Scholar
  37. Yamauchi M, Aragones DV (1997) Root system and grain yield of rice with emphasis on F1 hybrids. In: Proceedings of the 4th JSRR symposium (JSRR), The University of Tokyo, Tokyo, Japan, pp 24–25Google Scholar
  38. Yu GT, Horsley RD, Zhang B, Franckowiak JD (2010) A new semi-dwarfing gene identified by molecular mapping of quantitative trait loci in barley. Theor Appl Genet 120:853–861PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Md. Arifuzzaman
    • 1
  • Mohammed A. Sayed
    • 1
  • Shumaila Muzammil
    • 1
  • Klaus Pillen
    • 2
  • Henrik Schumann
    • 1
  • Ali Ahmad Naz
    • 1
  • Jens Léon
    • 1
  1. 1.Crop Genetics and Biotechnology Unit, Institute of Crop Science and Resource ConservationUniversity of BonnBonnGermany
  2. 2.Plant Breeding, Institute of Agricultural and Nutritional SciencesMartin-Luther-University Halle-WittenbergHalleGermany

Personalised recommendations