Molecular Breeding

, Volume 27, Issue 3, pp 301–314 | Cite as

Mapping of quantitative trait loci associated with protein expression variation in barley grains

  • Katja Witzel
  • Christof Pietsch
  • Marc Strickert
  • Andrea Matros
  • Marion S. Röder
  • Winfriede Weschke
  • Ulrich Wobus
  • Hans-Peter MockEmail author


Barley (Hordeum vulgare) is an important cereal crop grown for both the feed and malting industries. Hence, there is great interest to gain deeper insight into the determinants of grain nutritional quality in order to improve the assessment of new traits. Two-dimensional gel electrophoresis was employed for the characterization of the grain proteome of doubled-haploid introgression lines (IL) representing a wild barley genome (Hordeum spontaneum Hs213) within a modern cultivar background (H. vulgare cv. Brenda). Proteome maps were subjected to differential cluster analysis and revealed ILs with similar or different protein expression patterns compared to the Brenda parent. A total of 51 quantitative trait loci for protein expression (pQTL) were detected, and proteins underlying these pQTL were further examined by mass spectrometry. Identification was successful for 49 of the segregating spots and functional annotation of proteins revealed that most proteins are involved in metabolism and disease/defence-related processes. Among those, multigene families of glyceraldehyde-3-phosphate dehydrogenases, heat shock proteins, peroxidases, and serpins were identified. Overall, eight pQTL signals were discovered in two independently grown sets of plants. The mapped spots included protein disulfide isomerase, α-amylase inhibitor BDAI, NADP malic enzyme, adenosine kinase and peroxidase BP1. Specific marker information of proteins involved in developmental events and protein storage as well as in disease- and defence-related processes now allows for targeted breeding approaches to improve the grain quality in barley.


2-D gel electrophoresis QTL analysis Proteome analysis Mass spectrometry Barley grain 



2-Dimensional gel electrophoresis


Advanced backcross


α-Amylase inhibitor


Barley peroxidase 1


Glyceraldehyde-3-phosphate dehydrogenase


Glucose and ribitol dehydrogenase


Introgression line


Immobilized pH gradient


Mass spectrometry


Quantitative trait loci



We thank Annegret Wolf for excellent technical assistance. This work was supported by the German Federal Ministry of Education and Research (GABISEED II; FKZ 0313115). We greatly appreciate the valuable comments of two anonymous reviewers.

Supplementary material

11032_2010_9432_MOESM1_ESM.pdf (530 kb)
PDF 531 kb


  1. Abbo S, Dunford RP, Miller TE, Reader SM, King IP (1993) Primer-mediated in situ detection of the B-hordein gene cluster on barley chromosome 1H. PNAS 90:11821–11824PubMedCrossRefGoogle Scholar
  2. Amme S, Rutten T, Melzer M, Sonsmann G, Vissers JPC, Schlesier B, Mock H-P (2005) A proteome approach defines protective functions of tobacco leaf trichomes. Proteomics 5:2508–2518PubMedCrossRefGoogle Scholar
  3. Amme S, Matros A, Schlesier B, Mock H-P (2006) Proteome analysis of cold stress response in Arabidopsis thaliana using DIGE-technology. J Exp Bot 57:1537–1546PubMedCrossRefGoogle Scholar
  4. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19:185–193PubMedCrossRefGoogle Scholar
  5. Breitling R, Li Y, Tesson BM, Fu J, Wu C, Wiltshire T, Gerrits A, Bystrykh LV, de Haan G, Su AI, Jansen RC (2008) Genetical genomics: spotlight on QTL hotspots. PLoS Genet 4:e1000232PubMedCrossRefGoogle Scholar
  6. Churchill G, Doerge R (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971PubMedGoogle Scholar
  7. Consoli L, Lefevre A, Zivy M, de Vienne D, Damerval C (2002) QTL analysis of proteome and transcriptome variations for dissecting the genetic architecture of complex traits in maize. Plant Mol Biol 48:575–581PubMedCrossRefGoogle Scholar
  8. de Hoon MJL, Imoto S, Nolan J, Miyano S (2004) Open source clustering software. Bioinformatics 20:1453–1454PubMedCrossRefGoogle Scholar
  9. de Koning DJ, Haley CS (2005) Genetical genomics in humans and model organisms. Trends Genet 21:377–381PubMedCrossRefGoogle Scholar
  10. de Vienne D, Leonardi A, Damerval C, Zivy M (1999) Genetics of proteome variation for QTL characterization: application to drought-stress responses in maize. J Exp Bot 50:303–309CrossRefGoogle Scholar
  11. Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. PNAS 95:14863–14868PubMedCrossRefGoogle Scholar
  12. Fernie AR, Tadmor Y, Zamir D (2006) Natural genetic variation for improving crop quality. Curr Opin Plant Biol 9:196–202PubMedCrossRefGoogle Scholar
  13. Finnie C, Bagge M, Steenholdt T, Østergaard O, Bak-Jensen K, Backes G, Jensen A, Giese H, Larsen J, Roepstorff P, Svensson B (2009) Integration of the barley genetic and seed proteome maps for chromosome 1H, 2H, 3H, 5H and 7H. Funct Integr Genomics 9:135–143PubMedCrossRefGoogle Scholar
  14. Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini A, Sawitzki G, Smith C, Smyth G, Tierney L, Yang J, Zhang J (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80PubMedCrossRefGoogle Scholar
  15. Gyenis L, Yun SJ, Smith KP, Steffenson BJ, Bossolini E, Sanguineti MC, Muehlbauer GJ (2007) Genetic architecture of quantitative trait loci associated with morphological and agronomic trait differences in a wild by cultivated barley cross. Genome 50:714–723PubMedCrossRefGoogle Scholar
  16. Hansen BG, Halkier BA, Kliebenstein DJ (2008) Identifying the molecular basis of QTLs: eQTLs add a new dimension. Trends Plant Sci 13:72–77PubMedGoogle Scholar
  17. Hynek R, Svensson B, Jensen ON, Barkholt V, Finnie C (2006) Enrichment and identification of integral membrane proteins from barley aleurone layers by reversed-phase chromatography, SDS–PAGE, and LC-MS/MS. J Proteome Res 5:3105–3113PubMedCrossRefGoogle Scholar
  18. Iimure T, Takoi K, Kaneko T, Kihara M, Hayashi K, Ito K, Sato K, Takeda K (2008) Novel prediction method of beer foam stability using protein Z, barley dimeric alpha-amylase inhibitor-1 (BDAI-1) and yeast thioredoxin. J Agric Food Chem 56:8664–8671PubMedCrossRefGoogle Scholar
  19. Jansen RC, Nap J-P (2001) Genetical genomics: the added value from segregation. Trends Genet 17:388–391PubMedCrossRefGoogle Scholar
  20. Keurentjes JJB, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G, Snoek LB, Peeters AJM, Vreugdenhil D, Koornneef M, Jansen RC (2007) Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci. PNAS 104:1708–1713PubMedCrossRefGoogle Scholar
  21. Lapitan N, Botha-Oberholster A-M, Close TJ, Lawrence C (2005) Transcriptional profiling of gene expression during malting in barley. In 18th North American Barley Researchers Workshop. Red Deer, AlbertaGoogle Scholar
  22. Lazaro A, Sanchez-Monge R, Salcedo G, Paz-Ares J, Carbonero P, Garcia-Olmedo F (1988) A dimeric inhibitor or insect alpha-amylase from barley. Eur J Biochem 172:129–134PubMedCrossRefGoogle Scholar
  23. Li J, Burmeister M (2005) Genetical genomics: combining genetics with gene expression analysis. Hum Mol Genet 14:R163–R169PubMedCrossRefGoogle Scholar
  24. Li CD, Langridge P, Zhang XQ, Eckstein PE, Rossnagel BG, Lance RCM, Lefol EB, Lu MY, Harvey BL, Scoles GJ (2002) Mapping of barley (Hordeum vulgare L.) Beta-amylase alleles in which an amino acid substitution determines beta-amylase isoenzyme type and the level of free beta-amylase. J Cereal Sci 35:39–50CrossRefGoogle Scholar
  25. Li J, Huang XQ, Heinrichs F, Ganal MW, Röder MS (2005) Analysis of QTLs for yield, yield components, and malting quality in a BC3-DH population of spring barley. Theor Appl Genet 110:356–363PubMedCrossRefGoogle Scholar
  26. Li JZ, Huang XQ, Heinrichs F, Ganal MW, Röder MS (2006) Analysis of QTLs for yield components, agronomic traits, and disease resistance in an advanced backcross population of spring barley. Genome 49:454–466PubMedCrossRefGoogle Scholar
  27. Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27:209–220PubMedGoogle Scholar
  28. Marquez-Cedillo LA, Hayes PM, Kleinhofs A, Legge WG, Rossnagel BG, Sato K, Ullrich SE, Wesenberg DM (2001) QTL analysis of agronomic traits in barley based on the doubled haploid progeny of two elite North American varieties representing different germplasm groups. Theor Appl Genet 103:625–637CrossRefGoogle Scholar
  29. Merlino M, Leroy P, Chambon C, Branlard G (2009) Mapping and proteomic analysis of albumin and globulin proteins in hexaploid wheat kernels (Triticum aestivum L.). Theor Appl Genet 118:1321–1337PubMedCrossRefGoogle Scholar
  30. Nduulu L, Mesfin A, Muehlbauer G, Smith K (2007) Analysis of the chromosome 2(2H) region of barley associated with the correlated traits Fusarium head blight resistance and heading date. Theor Appl Genet 115:561–570PubMedCrossRefGoogle Scholar
  31. Okada Y, Limure T, Takoi K, Kaneko T, Kihara M, Hayashi K, Ito K, Sato K, Takeda K (2008) The influence of barley malt protein modification on beer foam stability and their relationship to the barley dimeric alpha-amylase inhibitor-1 (BDAI-1) as a possible foam-promoting protein. J Agric Food Chem 56:1458–1464PubMedCrossRefGoogle Scholar
  32. Østergaard O, Melchior S, Roepstorff P, Svensson B (2002) Initial proteome analysis of mature barley seeds and malt. Proteomics 2:733–739PubMedCrossRefGoogle Scholar
  33. Østergaard O, Finnie C, Laugesen S, Roepstorff P, Svensson B (2004) Proteome analysis of barley seeds: identification of major proteins from two-dimensional gels (pl 4–7). Proteomics 4:2437–2447PubMedCrossRefGoogle Scholar
  34. Payan F (2004) Structural basis for the inhibition of mammalian and insect [alpha]-amylases by plant protein inhibitors. Biochim Biophys Acta Prot Proteomics 1696:171–180CrossRefGoogle Scholar
  35. Pietsch C, Sreenivasulu N, Wobus U, Röder MS (2009) Linkage mapping of putative regulator genes of barley grain development characterized by expression profiling. BMC Plant Biol 9:4PubMedCrossRefGoogle Scholar
  36. Pillen K, Zacharias A, Leon J (2003) Advanced backcross QTL analysis in barley (Hordeum vulgare L.). Theor Appl Genet 107:340–352PubMedCrossRefGoogle Scholar
  37. Rabilloud T (2002) Two-dimensional gel electrophoresis in proteomics: old, old fashioned, but it still climbs up the mountains. Proteomics 2:3–10PubMedCrossRefGoogle Scholar
  38. Rostoks N, Mudie S, Cardle L, Russell J, Ramsay L, Booth A, Svensson J, Wanamaker S, Walia H, Rodriguez E, Hedley P, Liu H, Morris J, Close T, Marshall D, Waugh R (2005) Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress. Mol Genet Genomics 274:515–527PubMedCrossRefGoogle Scholar
  39. Saldanha AJ (2004) Java Treeview-extensible visualization of microarray data. Bioinformatics 20:3246–3248PubMedCrossRefGoogle Scholar
  40. Schlesier B, Mock H-P (2006) Protein isolation and 2-D electrophoretic separation. In: Sanchez-Serrano J, Salinas J (eds) Arabidopsis protocols. Humana, NJ, pp 381–391CrossRefGoogle Scholar
  41. Shewry PR, Halford NG (2002) Cereal seed storage proteins: structures, properties and role in grain utilization. J Exp Bot 53:947–958PubMedCrossRefGoogle Scholar
  42. Shewry PR, Tatham AS (1990) The prolamin storage proteins of cereal seeds—structure and evolution. Biochem J 267:1–12PubMedGoogle Scholar
  43. Stylianou IM, Affourtit JP, Shockley KR, Wilpan RY, Abdi FA, Bhardwaj S, Rollins J, Churchill GA, Paigen B (2008) Applying gene expression, proteomics and single-nucleotide polymorphism analysis for complex trait gene identification. Genetics 178:1795–1805PubMedCrossRefGoogle Scholar
  44. 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 92:191–203CrossRefGoogle Scholar
  45. Touzet P, Morin C, Damerval C, Leguilloux M, Zivy M, Devienne D (1995) Characterizing allelic proteins for genome mapping in maize. Electrophoresis 16:1289–1294PubMedCrossRefGoogle Scholar
  46. Tuberosa R, Salvi S, Sanguineti MC, Landi P, MacCaferri M, Conti S (2002) Mapping QTLs regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot 89:941–963PubMedCrossRefGoogle Scholar
  47. van Mechelen JR, Schuurink RC, Smits M, Graner A, Douma AC, Sedee NJA, Schmitt NF, Valk BE (1999) Molecular characterization of two lipoxygenases from barley. Plant Mol Biol 39:1283–1298PubMedCrossRefGoogle Scholar
  48. Varshney RK, Graner A, Sorrells ME (2005) Genomics-assisted breeding for crop improvement. Trends Plant Sci 10:621–630PubMedCrossRefGoogle Scholar
  49. Vij S, Tyagi AK (2007) Emerging trends in the functional genomics of the abiotic stress response in crop plants. Plant Biotechnol J 5:361–380PubMedCrossRefGoogle Scholar
  50. Westbrook JA, Yan JX, Wait R, Welson SY, Dunn MJ (2001) Zooming-in on the proteome: very narrow-range immobilised pH gradients reveal more protein species and isoforms. Electrophoresis 22:2865–2871PubMedCrossRefGoogle Scholar
  51. Witzel K, Surabhi G-K, Jyothsnakumari G, Sudhakar C, Matros A, Mock H-P (2007) Quantitative proteome analysis of barley seeds using ruthenium(II)-tris-(bathophenanthroline-disulphonate) staining. J Proteome Res 6:1325–1333PubMedCrossRefGoogle Scholar
  52. Zhu H, Briceno G, Dovel R, Hayes PM, Liu BH, Liu CT, Ullrich SE (1999) Molecular breeding for grain yield in barley: an evaluation of QTL effects in a spring barley cross. Theor Appl Genet 98:772–779CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Katja Witzel
    • 1
    • 2
  • Christof Pietsch
    • 1
    • 3
  • Marc Strickert
    • 1
    • 4
  • Andrea Matros
    • 1
  • Marion S. Röder
    • 1
  • Winfriede Weschke
    • 1
  • Ulrich Wobus
    • 1
  • Hans-Peter Mock
    • 1
    Email author
  1. 1.Leibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
  2. 2.Institute of Plant Nutrition and Soil ScienceChristian-Albrechts-UniversityKielGermany
  3. 3.KWS LOCHOW GMBHEinbeckGermany
  4. 4.University of SiegenSiegenGermany

Personalised recommendations