Advertisement

Euphytica

, Volume 178, Issue 3, pp 373–391 | Cite as

Could EST-based markers be used for the marker-assisted selection of drought tolerant barley (Hordeum vulgare) lines?

  • Fruzsina Szira
  • Andreas Börner
  • Kerstin Neumann
  • Khalil Zaynali Nezhad
  • Gábor Galiba
  • András Ferenc BálintEmail author
Article

Abstract

To improve our knowledge on the genetic control of drought tolerance, the Oregon Wolfe Barleys (OWB), considered as a reference population in genetic mapping, were subjected to various types of water deficit. Overall, when investigating numerous environments and replications, 40 QTLs were identified in three developmental stages. Based on these loci five QTL clusters were separated, which affect various drought-related traits in at least two developmental stages. Several candidate genes were identified for each QTL cluster using an expressed sequence tag (EST)-based map with high marker density. The putative role of the candidates in drought tolerance is discussed. The phenotypic effect of three of the five candidate genes was also tested on 39 barley landraces and cultivars and a significant relationship was found between the allelic composition of these genes and yield production under stress conditions. This study presents a relevant example of the use of reliable QTL data in the candidate gene approach, while also demonstrating how the results could be practically utilized in marker-assisted selection (MAS).

Keywords

Candidate genes Developmental stage Drought Marker-assisted selection Osmotic stress QTL 

Notes

Acknowledgments

This work was supported by the National Office for Research and Technology [GVOP-3.1.1-2004-05-0441/3.0] and the German-Hungarian Project ‘Plant Resource’ [OMFB00515/2007]. The purchase of the Qiagen QIAxcel fragment analyser was financed by AGRISAFE FP7-203288. Meteorological data were kindly provided by N. Harnos, ARI, Martonvásár, Hungary. Thanks are due to N. Csabai, A. Horváth and R. Voss for their technical assistance and for the anonymous reviewers for their useful comments and suggestions.

Supplementary material

10681_2010_317_MOESM1_ESM.doc (86 kb)
Supplementary material 1 (DOC 86 kb)
10681_2010_317_MOESM2_ESM.doc (49 kb)
Supplementary material 2 (DOC 49 kb)

References

  1. Aghnoum R, Marcel TC et al (2010) Basal host resistance of barley to powdery mildew: connecting quantitative trait loci and candidate genes. Mol Plant Microbe Interact 23:91–102. doi: 10.1094/mpmi-23-1-0091 PubMedCrossRefGoogle Scholar
  2. Barrett AJ, Rawlings ND (1992) Oligopeptidases, and the emergence of the prolyl oligopeptidase family. Walter De Gruyter & Co, Berlin, pp 353–360Google Scholar
  3. Baum M, Grando S et al (2003) QTLs for agronomic traits in the Mediterranean environment identified in recombinant inbred lines of the cross ‘Arta’ x H-spontaneum 41-1. Theor Appl Genet 107:1215–1225. doi: 10.1007/s00122-003-1357-2 PubMedCrossRefGoogle Scholar
  4. Bezant J, Laurie D et al (1997) Mapping QTL controlling yield and yield components in a spring barley (Hordeum vulgare L.) cross using marker regression. Mol Breed 3:29–38CrossRefGoogle Scholar
  5. Blum A (1989) Osmotic adjustment and growth of barley genotypes under drought stress. Crop Sci 29(1):230–233CrossRefGoogle Scholar
  6. Cattivelli L, Rizza F, Badeck F-W et al (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. Field Crop Res 105:1–14CrossRefGoogle Scholar
  7. Ceccarelli S (1987) Yield potential and drought tolerance of segregating populations of barley in contrasting environments. Euphytica 36:265–273CrossRefGoogle Scholar
  8. Chen A, Baumann U et al (2009) Flt-2L, a locus in barley controlling flowering time, spike density, and plant height. Funct Integr Genomics 9:243–254. doi: 10.1007/s10142-009-0114-2 PubMedCrossRefGoogle Scholar
  9. Cherian S, Reddy MP et al (2006) Transgenic plants with improved dehydration-stress tolerance: progress and future prospects. Biol Plant 50:481–495CrossRefGoogle Scholar
  10. Costa JM, Corey A et al (2001) Molecular mapping of the Oregon Wolfe Barleys: a phenotypically polymorphic doubled-haploid population. Theor Appl Genet 103:415–424CrossRefGoogle Scholar
  11. Diab AA, Teulat-Merah B et al (2004) Identification of drought-inducible genes and differentially expressed sequence tags in barley. Theor Appl Genet 109:1417–1425. doi: 10.1007/s00122-004-1755-0 PubMedCrossRefGoogle Scholar
  12. Dubouzet JG, Sakuma Y et al (2003) OsDREB genes in rice, Oryza sativa L., encode transcription activators that function in drought-, high-salt- and cold-responsive gene expression. Plant J 33:751–763PubMedCrossRefGoogle Scholar
  13. Fleury D, Jefferies S, Kuchel H, Langridge P (2010) Genetic and genomic tools to improve drought tolerance in wheat. J Exp Bot. doi: 10.10936jxb6erg152
  14. Gaudet DA, Laroche A et al (2003) Cold induced expression of plant defensin and lipid transfer protein transcripts in winter wheat. Physiol Plant 117:195–205CrossRefGoogle Scholar
  15. Guo PG, Baum M et al (2009) Differentially expressed genes between drought-tolerant and drought-sensitive barley genotypes in response to drought stress during the reproductive stage. J Exp Bot 60:3531–3544. doi: 10.1093/jxb/erp194 PubMedCrossRefGoogle Scholar
  16. Hai L, Guo HJ et al (2008) Genomic regions for yield and yield parameters in Chinese winter wheat (Triticum aestivum L.) genotypes tested under varying environments correspond to QTL in widely different wheat materials. Plant Sci 175:226–232. doi: 10.1016/j.plantsci.2008.03.006 Google Scholar
  17. Koizumi M, Yamaguchishinozaki K et al (1993) Structure and expression of 2 genes that encode distinct drought-inducible cysteine proteinases in Arabidopsis-thaliana. Gene 129:175–182PubMedCrossRefGoogle Scholar
  18. Leung H (2008) Stressed genomics—bringing relief to rice fields. Curr Opin Plant Biol 11:201–208. doi: 10.1016/j.pbi.2007.12.005 PubMedGoogle Scholar
  19. Li ZK, Luo LJ et al (2001) Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice. I. Biomass and grain yield. Genetics 158:1737–1753PubMedGoogle Scholar
  20. Ludlow MM, Muchow RC (1990) A critical-evaluation of traits for improving crop yields in water-limited environments. Adv Agron 43:107–153CrossRefGoogle Scholar
  21. Lundoquist U, Lundoquist A (1998) Intermedium mutants in barley (Hordeum vulgare L.)—diversity, interactions and plant breeding value. J Appl Genet 39:85–96Google Scholar
  22. Maccaferri M, Sanguineti MC et al (2008) Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 178:489–511. doi: 10.1534/genetics.107.077297 Google Scholar
  23. Molnar I, Gaspar L et al (2004) Physiological and morphological responses to water stress in Aegilops biuncialis and Triticum aestivum genotypes with differing tolerance to drought. Funct Plant Biol 31:1149–1159. doi: 10.1071/fp03143 CrossRefGoogle Scholar
  24. Ozturk ZN, Talame V et al (2002) Monitoring large-scale changes in transcript abundance in drought- and salt-stressed barley. Plant Mol Biol 48:551–573CrossRefGoogle Scholar
  25. Paterson AH, Damon S et al (1991) Mendelian factors underlying quantitative traits in tomato—comparison across species, generations, and environments. Genetics 127:181–197PubMedGoogle Scholar
  26. Peighambari SA, Samadi BY et al (2005) QTL analysis for agronomic traits in a barley doubled haploids population grown in Iran. Plant Sci 169:1008–1013. doi: 10.1016/j.plantsci.2005.05.018 CrossRefGoogle Scholar
  27. Pernas M, Garcia-Casado G et al (2007) A protein phosphatase 2A catalytic subunit is a negative regulator of abscisic acid signalling. Plant J 51:763–778. doi: 10.1111/j.1365-313X.2007.03179.x PubMedCrossRefGoogle Scholar
  28. Plaschke J, Ganal MW et al (1995) Detection of genetic diversity in closely-related bread wheat using microsatellite markers. Theor Appl Genet 91:1001–1007CrossRefGoogle Scholar
  29. Price AH (2006) Believe it or not, QTLs are accurate! Trends Plant Sci 11:213–216. doi: 10.1016/j.tplants.2006.03.006 PubMedCrossRefGoogle Scholar
  30. Reynolds M, Calderini D et al (2007) Association of source/sink traits with yield, biomass and radiation use efficiency among random sister lines from three wheat crosses in a high-yield environment. J Agric Sci 147:3–16CrossRefGoogle Scholar
  31. Roder MS, Korzun V et al (1998) A microsatellite map of wheat. Genetics 149:2007–2023PubMedGoogle Scholar
  32. Rostoks N, Mudie S et al (2005) Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress. Mol Genet Genomics 274:515–527. doi: 10.1007/s00438-005-0046-z PubMedCrossRefGoogle Scholar
  33. Samarah NH, Alqudah AM, Amayreh JA, McAndrews GM (2009) The effect of late-terminal drought stress on yield components of four barley cultivars. J Agron Crop Sci 195:427–441. doi: 10.1111/j.1439-037X.2009.00387.x CrossRefGoogle Scholar
  34. Stein N, Prasad M et al (2007) A 1,000-loci transcript map of the barley genome: new anchoring points for integrative grass genomics. Theor Appl Genet 114:823–839. doi: 10.1007/s00122-006-0480-2 PubMedCrossRefGoogle Scholar
  35. Stiller I, Dulai S et al (2008) Effects of drought on water content and photosynthetic parameters in potato plants expressing the trehalose-6-phosphate synthase gene of Saccharomyces cerevisiae. Planta 227:299–308. doi: 10.1007/s00425-007-0617-9 PubMedCrossRefGoogle Scholar
  36. Szira F, Balint AF et al (2008) Evaluation of drought-related traits and screening methods at different developmental stages in spring barley. J Agron Crop Sci 194:334–342. doi: 10.1111/j.1439-037X.2008.00330.x CrossRefGoogle Scholar
  37. Szűcs P, Blake VC et al (2009) An integrated resource for barley linkage map and malting quality QTL alignment. Plant Genome 2:134–140CrossRefGoogle Scholar
  38. Talame V, Ozturk NZ et al (2007) Barley transcript profiles under dehydration shock and drought stress treatments: a comparative analysis. J Exp Bot 58:229–240. doi: 10.1093/jxb/erl163 PubMedCrossRefGoogle Scholar
  39. Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Science 327:818–822PubMedCrossRefGoogle Scholar
  40. Teulat B, Borries C et al (2001) New QTLs identified for plant water status, water-soluble carbohydrate and osmotic adjustment in a barley population grown in a growth-chamber under two water regimes. Theor Appl Genet 103:161–170CrossRefGoogle Scholar
  41. Teulat B, Merah O et al (2002) QTLs for grain carbon isotope discrimination in field-grown barley. Theor Appl Genet 106:118–126. doi: 10.1007/s00122-002-1028-8 PubMedGoogle Scholar
  42. Teulat B, Zoumarou-Wallis N et al (2003) QTL for relative water content in field-grown barley and their stability across Mediterranean environments. Theor Appl Genet 108:181–188. doi: 10.1007/s00122-003-1417-7 PubMedCrossRefGoogle Scholar
  43. von Korff M, Grando S et al (2008) Quantitative trait loci associated with adaptation to Mediterranean dryland conditions in barley. Theor Appl Genet 117:653–669. doi: 10.1007/s00122-008-0787-2 CrossRefGoogle Scholar
  44. Xiong LM, Ishitani M et al (2001) The Arabidopsis LOS5/ABA3 locus encodes a molybdenum cofactor sulfurase and modulates cold stress- and osmotic stress-responsive gene expression. Plant Cell 13:2063–2083PubMedCrossRefGoogle Scholar
  45. Yang J, Zhu J (2005) Methods for predicting superior genotypes under multiple environments based on QTL effects. Theor Appl Genet 110:1268–1274. doi: 10.1007/s00122-005-1963-2 PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Fruzsina Szira
    • 1
  • Andreas Börner
    • 2
  • Kerstin Neumann
    • 2
  • Khalil Zaynali Nezhad
    • 2
    • 3
  • Gábor Galiba
    • 1
  • András Ferenc Bálint
    • 1
    Email author
  1. 1.Agricultural Research Institute of the Hungarian Academy of SciencesMartonvásárHungary
  2. 2.Leibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
  3. 3.Department of Agronomy and Plant Breeding, College of AgricultureIsfahan University of TechnologyIsfahanIran

Personalised recommendations