A tripartite approach identifies the major sunflower seed albumins
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We have used a combination of genomic, transcriptomic, and proteomic approaches to identify the napin-type albumin genes in sunflower and define their contributions to the seed albumin pool.
Seed protein content is determined by the expression of what are typically large gene families. A major class of seed storage proteins is the napin-type, water soluble albumins. In this work we provide a comprehensive analysis of the napin-type albumin content of the common sunflower (Helianthus annuus) by analyzing a draft genome, a transcriptome and performing a proteomic analysis of the seed albumin fraction. We show that although sunflower contains at least 26 genes for napin-type albumins, only 15 of these are present at the mRNA level. We found protein evidence for 11 of these but the albumin content of mature seeds is dominated by the encoded products of just three genes. So despite high genetic redundancy for albumins, only a small sub-set of this gene family contributes to total seed albumin content. The three genes identified as producing the majority of sunflower seed albumin are potential future candidates for manipulation through genetics and breeding.
KeywordsHigh Performance Liquid Chromatography Draft Genome Sunflower Seed Seed Storage Protein Helianthus Annuus
A.S.J. is supported by an International Postgraduate Research Scholarship and an Australian Postgraduate Award. B.F. was supported by Australian Research Council grant DP120103369. J.R. and J.S.M. are supported by Australian Research Council Future Fellowships FT130100890 and FT120100013, respectively. Authors would like to acknowledge Prof. Loren Rieseberg (University of British Columbia) for providing access to a draft sunflower genome, the BAC/EST Resource Center of the Arizona Genomics Institute (University of Arizona) and David Kudrna for H. annuus cDNA clones and the Compositae Genome Project website (http://cgpdb.ucdavis.edu/) supported by the USDA IFAFS Programme and NSF Plant Genome Programme for EST data. The authors also thank Michelle Colgrave, Nicolas Taylor, Richard Jacoby and Mark Condina for valuable advice on proteomics. This work was supported by Australian Research Council grant DP130101191.
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Conflict of interest
The authors declare that they have no conflicting interests.
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