An Improved 1-D SDS–PAGE Method for the Identification of Three Bread Wheat «Waxy» Proteins

Zhao, Xiaochun; Sharp, P. J.

doi:10.1006/jcrs.1996.0019

Cited by 84 publications

(59 citation statements)

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“…Starch granules were extracted from mature and developing wheat kernels according to procedure described by Zhao and Sharp (1996) with the exception of the steeping step, which was only done with mature seeds. Extracted starch (10 mg) was resuspended in 150 L of sample buffer …”

Section: Isolation Of Starch Granule Proteins and Sds-page Analysismentioning

confidence: 45%

Isolation of a cDNA Encoding a Granule-Bound 152-Kilodalton Starch-Branching Enzyme in Wheat

et al. 2000

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Screening of a wheat (Triticum aestivum) cDNA library for starch-branching enzyme I (SBEI) genes combined with 5Ј-rapid amplification of cDNA ends resulted in isolation of a 4,563-bp composite cDNA, Sbe1c. Based on sequence alignment to characterized SBEI cDNA clones isolated from plants, the SBEIc predicted from the cDNA sequence was produced with a transit peptide directing the polypeptide into plastids. Furthermore, the predicted mature form of SBEIc was much larger (152 kD) than previously characterized plant SBEI (80-100 kD) and contained a partial duplication of SBEI sequences. The first SBEI domain showed high amino acid similarity to a 74-kD wheat SBEI-like protein that is inactive as a branching enzyme when expressed in Escherichia coli. The second SBEI domain on SBEIc was identical in sequence to a functional 87-kD SBEI produced in the wheat endosperm. Immunoblot analysis of proteins produced in developing wheat kernels demonstrated that the 152-kD SBEIc was, in contrast to the 87-to 88-kD SBEI, preferentially associated with the starch granules. Proteins similar in size and recognized by wheat SBEI antibodies were also present in Triticum monococcum, Triticum tauschii, and Triticum turgidum subsp. durum.

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Section: Isolation Of Starch Granule Proteins and Sds-page Analysismentioning

confidence: 45%

Isolation of a cDNA Encoding a Granule-Bound 152-Kilodalton Starch-Branching Enzyme in Wheat

et al. 2000

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“…Starch granules were purified from mature seeds and starch granule proteins were separated by SDS-PAGE following the method reported in Zhao and Sharp (1996) with some modifications (Mohammadkhani et al, 1999). Protein bands were visualized by silver staining.…”

Section: Detection Of Ftgbssi Protein By Sodium Dodecyl Sulfate Polyasupporting

confidence: 40%

Identification and characterization of granule bound starch synthase I (GBSSI) gene of tartary buckwheat (Fagopyrum tataricum Gaertn.)

Wang

Feng

et al. 2014

Gene

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“…However, this procedure is time consuming, not suitable for commercial grades of wheat with a narrow range of amylose content, and often does not yield definitive results for the identification of partial waxy lines [7]. Rather than applying chemical methods to determine the amylose content of wheat, characterizing waxy and partial waxy wheat lines according to the number of active GBSS genes by detection of the different GBSS isoforms through protein analysis has been formulated using SDS-PAGE [8], ELISA [9], or multiplex PCR techniques [10]. However, these methods are expensive, complex, time consuming and not amenable to either wheat breeding programs or to the various stages of wheat marketing and production.…”

Section: Introductionmentioning

confidence: 43%

Classification of the waxy condition of durum wheat by near infrared reflectance spectroscopy using wavelets and a genetic algorithm

Lavine

Mirjankar

Delwiche

2014

Microchemical Journal

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a b s t r a c t a r t i c l e i n f oNear infrared (NIR) reflectance spectroscopy has been applied to the problem of differentiating four genotypes of durum wheat: 'waxy', Wx A1 null null, wx-B1 null and wild type. The test data consisted of 95 NIR reflectance spectra of wheat samples obtained from a USDA-ARS wheat breeding program. A two-step procedure for pattern recognition analysis of NIR spectral data was employed. First, the wavelet packet transform [14,15] was applied to the NIR reflectance data using wavelet filters at different scales to extract and separate low-frequency signal components from high frequency noise components. By applying these filters, each reflectance spectrum was decomposed into wavelet coefficients that represented the sample's constituent frequencies. Second, wavelet coefficients characteristic of the waxy condition of the wheat samples were identified using a genetic algorithm for pattern recognition. The pattern recognition GA employed both supervised and unsupervised learning to identify wavelet coefficients that optimized clustering of the spectra by genotype in a plot of the two largest principal components of the data. By sampling key feature subsets, scoring their PC plots, and tracking those genotypes and samples that were difficult to classify, the pattern recognition GA was able to identify a set of wavelet coefficients whose PC plot showed clustering of the wheat samples on the basis of their 'waxy' condition. Object validation was also performed to assess the predictive ability of the proposed NIR method to identify the 'waxy' condition of the wheat. An overall classification success rate of 78% was achieved for the spectral data.

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An Improved 1-D SDS–PAGE Method for the Identification of Three Bread Wheat «Waxy» Proteins

Cited by 84 publications

References 0 publications

Isolation of a cDNA Encoding a Granule-Bound 152-Kilodalton Starch-Branching Enzyme in Wheat

Isolation of a cDNA Encoding a Granule-Bound 152-Kilodalton Starch-Branching Enzyme in Wheat

Identification and characterization of granule bound starch synthase I (GBSSI) gene of tartary buckwheat (Fagopyrum tataricum Gaertn.)

Classification of the waxy condition of durum wheat by near infrared reflectance spectroscopy using wavelets and a genetic algorithm

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