Analysis of Peanut Leaf Proteome

R. Ramesh, Prashanth Suravajhala, T. Pechan

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    Resumé

    Peanut (Arachis hypogaea) is one of the most important sources of plant protein. Current selection of genotypes requires molecular characterization of available populations. Peanut genome database has several EST cDNAs which can be used to analyze gene expression. Analysis of proteins is a direct approach to define function of their associated genes. Proteome analysis linked to genome sequence information is critical for functional genomics. However, the available protein expression data is extremely inadequate. Proteome analysis of peanut leaf was conducted using two-dimensional gel electrophoresis in combination with sequence identification using MALDI/TOF to determine their identity and function related to growth, development and responses to stresses. Peanut leaf proteins were resolved into 300 polypeptides with pI values between 3.5 and 8.0 and relative molecular masses from 12 to 100 kDa. A master leaf polypeptide profile was generated based on the consistently expressed protein pattern. Proteins present in 205 spots were identified using GPS software and Viridiplantae database (NCBI). Identity of some of these proteins included RuBisCO, glutamine synthetase, glyoxisomal malate dehydrogenase, oxygen evolving enhancer protein and tubulin. Bioinformatical analyses showed that there are 133 unique protein identities. They were categorized into 10 and 8 groups according to their cellular compartmentalization and biological functionality, respectively. Enzymes necessary for carbohydrate metabolism and photosynthesis dominated in the set of identified proteins. The reference map derived from a drought-tolerant cv.Vemana should serve as the basis for further investigations of peanut physiology such as detection of expressed changes due to biotic and abiotic stresses, plant development. Furthermore, the leaf proteome map will lead to development of protein markers for cultivar identification at seedling stage of the plant. Overall, this study will contribute to improve our understanding of plant genetics and metabolism, and overall assist in the selection and breeding programs geared toward crop improvement.
    OriginalsprogEngelsk
    TidsskriftJournal of Proteome Research
    Vol/bind9
    Udgave nummer5
    Sider (fra-til)2236-2254
    ISSN1535-3893
    DOI
    StatusUdgivet - 2010

    Emneord

      Citer dette

      Ramesh, R., Suravajhala, P., & Pechan , T. (2010). Analysis of Peanut Leaf Proteome. Journal of Proteome Research, 9(5), 2236-2254. https://doi.org/10.1021/pr901009n
      Ramesh, R. ; Suravajhala, Prashanth ; Pechan , T. / Analysis of Peanut Leaf Proteome. I: Journal of Proteome Research. 2010 ; Bind 9, Nr. 5. s. 2236-2254.
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      title = "Analysis of Peanut Leaf Proteome",
      abstract = "Peanut (Arachis hypogaea) is one of the most important sources of plant protein. Current selection of genotypes requires molecular characterization of available populations. Peanut genome database has several EST cDNAs which can be used to analyze gene expression. Analysis of proteins is a direct approach to define function of their associated genes. Proteome analysis linked to genome sequence information is critical for functional genomics. However, the available protein expression data is extremely inadequate. Proteome analysis of peanut leaf was conducted using two-dimensional gel electrophoresis in combination with sequence identification using MALDI/TOF to determine their identity and function related to growth, development and responses to stresses. Peanut leaf proteins were resolved into 300 polypeptides with pI values between 3.5 and 8.0 and relative molecular masses from 12 to 100 kDa. A master leaf polypeptide profile was generated based on the consistently expressed protein pattern. Proteins present in 205 spots were identified using GPS software and Viridiplantae database (NCBI). Identity of some of these proteins included RuBisCO, glutamine synthetase, glyoxisomal malate dehydrogenase, oxygen evolving enhancer protein and tubulin. Bioinformatical analyses showed that there are 133 unique protein identities. They were categorized into 10 and 8 groups according to their cellular compartmentalization and biological functionality, respectively. Enzymes necessary for carbohydrate metabolism and photosynthesis dominated in the set of identified proteins. The reference map derived from a drought-tolerant cv.Vemana should serve as the basis for further investigations of peanut physiology such as detection of expressed changes due to biotic and abiotic stresses, plant development. Furthermore, the leaf proteome map will lead to development of protein markers for cultivar identification at seedling stage of the plant. Overall, this study will contribute to improve our understanding of plant genetics and metabolism, and overall assist in the selection and breeding programs geared toward crop improvement.",
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      author = "R. Ramesh and Prashanth Suravajhala and T. Pechan",
      year = "2010",
      doi = "10.1021/pr901009n",
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      Ramesh, R, Suravajhala, P & Pechan , T 2010, 'Analysis of Peanut Leaf Proteome' Journal of Proteome Research, bind 9, nr. 5, s. 2236-2254. https://doi.org/10.1021/pr901009n

      Analysis of Peanut Leaf Proteome. / Ramesh, R.; Suravajhala, Prashanth; Pechan , T.

      I: Journal of Proteome Research, Bind 9, Nr. 5, 2010, s. 2236-2254.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

      TY - JOUR

      T1 - Analysis of Peanut Leaf Proteome

      AU - Ramesh, R.

      AU - Suravajhala, Prashanth

      AU - Pechan , T.

      PY - 2010

      Y1 - 2010

      N2 - Peanut (Arachis hypogaea) is one of the most important sources of plant protein. Current selection of genotypes requires molecular characterization of available populations. Peanut genome database has several EST cDNAs which can be used to analyze gene expression. Analysis of proteins is a direct approach to define function of their associated genes. Proteome analysis linked to genome sequence information is critical for functional genomics. However, the available protein expression data is extremely inadequate. Proteome analysis of peanut leaf was conducted using two-dimensional gel electrophoresis in combination with sequence identification using MALDI/TOF to determine their identity and function related to growth, development and responses to stresses. Peanut leaf proteins were resolved into 300 polypeptides with pI values between 3.5 and 8.0 and relative molecular masses from 12 to 100 kDa. A master leaf polypeptide profile was generated based on the consistently expressed protein pattern. Proteins present in 205 spots were identified using GPS software and Viridiplantae database (NCBI). Identity of some of these proteins included RuBisCO, glutamine synthetase, glyoxisomal malate dehydrogenase, oxygen evolving enhancer protein and tubulin. Bioinformatical analyses showed that there are 133 unique protein identities. They were categorized into 10 and 8 groups according to their cellular compartmentalization and biological functionality, respectively. Enzymes necessary for carbohydrate metabolism and photosynthesis dominated in the set of identified proteins. The reference map derived from a drought-tolerant cv.Vemana should serve as the basis for further investigations of peanut physiology such as detection of expressed changes due to biotic and abiotic stresses, plant development. Furthermore, the leaf proteome map will lead to development of protein markers for cultivar identification at seedling stage of the plant. Overall, this study will contribute to improve our understanding of plant genetics and metabolism, and overall assist in the selection and breeding programs geared toward crop improvement.

      AB - Peanut (Arachis hypogaea) is one of the most important sources of plant protein. Current selection of genotypes requires molecular characterization of available populations. Peanut genome database has several EST cDNAs which can be used to analyze gene expression. Analysis of proteins is a direct approach to define function of their associated genes. Proteome analysis linked to genome sequence information is critical for functional genomics. However, the available protein expression data is extremely inadequate. Proteome analysis of peanut leaf was conducted using two-dimensional gel electrophoresis in combination with sequence identification using MALDI/TOF to determine their identity and function related to growth, development and responses to stresses. Peanut leaf proteins were resolved into 300 polypeptides with pI values between 3.5 and 8.0 and relative molecular masses from 12 to 100 kDa. A master leaf polypeptide profile was generated based on the consistently expressed protein pattern. Proteins present in 205 spots were identified using GPS software and Viridiplantae database (NCBI). Identity of some of these proteins included RuBisCO, glutamine synthetase, glyoxisomal malate dehydrogenase, oxygen evolving enhancer protein and tubulin. Bioinformatical analyses showed that there are 133 unique protein identities. They were categorized into 10 and 8 groups according to their cellular compartmentalization and biological functionality, respectively. Enzymes necessary for carbohydrate metabolism and photosynthesis dominated in the set of identified proteins. The reference map derived from a drought-tolerant cv.Vemana should serve as the basis for further investigations of peanut physiology such as detection of expressed changes due to biotic and abiotic stresses, plant development. Furthermore, the leaf proteome map will lead to development of protein markers for cultivar identification at seedling stage of the plant. Overall, this study will contribute to improve our understanding of plant genetics and metabolism, and overall assist in the selection and breeding programs geared toward crop improvement.

      KW - 2-D electrophoresis

      KW - leaves

      KW - MALDI

      KW - peanut

      KW - proteins

      KW - sequencing

      U2 - 10.1021/pr901009n

      DO - 10.1021/pr901009n

      M3 - Journal article

      VL - 9

      SP - 2236

      EP - 2254

      JO - Journal of Proteome Research

      JF - Journal of Proteome Research

      SN - 1535-3893

      IS - 5

      ER -