Theoretical and Applied Genetics

, Volume 118, Issue 7, pp 1321–1337 | Cite as

Mapping and proteomic analysis of albumin and globulin proteins in hexaploid wheat kernels (Triticum aestivum L.)

  • Marielle Merlino
  • Philippe Leroy
  • Christophe Chambon
  • Gérard Branlard
Original Paper


Albumins and globulins of wheat endosperm represent 20% of total kernel protein. They are soluble proteins, mainly enzymes and proteins involved in cell functions. Two-dimensional gel immobiline electrophoresis (2DE) (pH 4-7) × SDS-Page revealed around 2,250 spots. Ninety percent of the spots were common between the very distantly related cultivars ‘Opata 85’ and ‘Synthetic W7984’, the two parents of the International Triticeae Mapping Initiative (ITMI) progeny. ‘Opata’ had 130 specific spots while ‘Synthetic’ had 96. 2DE and image analysis of the soluble proteins present in 112 recombinant inbred lines of the F9-mapped ITMI progeny enabled 120 unbiased segregating spots to be mapped on 21 wheat (Triticum aestivum L. em. Thell) chromosomes. After trypsic digestion, mapped spots were subjected to MALDI-Tof or tandem mass spectrometry for protein identification by database mining. Among the ‘Opata’ and ‘Synthetic’ spots identified, many enzymes have already been mapped in the barley and rice genomes. Multigene families of Heat Shock Proteins, beta-amylases, UDP-glucose pyrophosphorylases, peroxydases and thioredoxins were successfully identified. Although other proteins remain to be identified, some differences were found in the number of segregating proteins involved in response to stress: 11 proteins found in the modern selected cultivar ‘Opata 85’ as compared to 4 in the new hexaploid `Synthetic W7984’. In addition, ‘Opata’ and ‘Synthetic’ differed in the number of proteins involved in protein folding (2 and 10, respectively). The usefulness of the mapped enzymes for future research on seed composition and characteristics is discussed.


Segregation Distortion Wheat Kernel Kernel Protein Wheat Endosperm International Triticeae Mapping Initiative 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Isabelle Hamon and the team laboratory are gracefully acknowledged for their precious help in this study.

Supplementary material

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Supplementary material 1 (XLS 106 kb)
122_2009_983_MOESM2_ESM.xls (166 kb)
Supplementary material 2 (XLS 166 kb)
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Supplementary material 3 (XLS 183 kb)


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Marielle Merlino
    • 1
  • Philippe Leroy
    • 1
  • Christophe Chambon
    • 2
  • Gérard Branlard
    • 1
  1. 1.INRA UMR 1095Clermont-FerrandFrance
  2. 2.INRA UR 370, PFEM-Plateau ProtéomiqueSaint-Genès-ChampanelleFrance

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