Proteomic Data Integration Highlights Central Actors Involved in Einkorn (Triticum monococcum ssp. monococcum) Grain Filling in Relation to Grain Storage Protein Composition

被引:4
作者
Bancel, Emmanuelle [1 ,2 ]
Bonnot, Titouan [1 ,2 ,5 ]
Davanture, Marlene [3 ]
Alvarez, David [1 ,2 ]
Zivy, Michel [3 ]
Martre, Pierre [1 ,2 ,6 ]
Dejean, Sebastien [4 ]
Ravel, Catherine [1 ,2 ]
机构
[1] Univ Clermont Auvergne, INRA, UMR GDEC, Clermont Ferrand, France
[2] Clermont Auvergne Univ, Genet Divers & Ecophysiol Cereals, UMR1095, Clermont Ferrand, France
[3] Univ Paris Sud, Univ Paris Saclay, CNRS, UMR GQE,INRA,Agro ParisTech, Gif Sur Yvette, France
[4] Univ Toulouse, CNRS, UMR5219, Inst Math Toulouse, Toulouse, France
[5] Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA
[6] Univ Montpellier, Montpellier SupAgro, INRA, LEPSE, Montpellier, France
来源
FRONTIERS IN PLANT SCIENCE | 2019年 / 10卷
关键词
albumin-globulin; data integration; nitrogen; proteomic; grain development; storage protein; sulfur; Triticum monococcum; GENE-EXPRESSION; GLUTAMINE-SYNTHETASE; SULFUR FERTILIZATION; WHEAT; NITROGEN; QUALITY; ACCUMULATION; ASSOCIATION; TOOL; ENDOSPERM;
D O I
10.3389/fpls.2019.00832
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Albumins and globulins (AGs) of wheat endosperm represent about 20% of total grain proteins. Some of these physiologically active proteins can influence the synthesis of storage proteins (SPs) (gliadins and glutenins) and consequently, rheological properties of wheat flour and processing. To identify such AGs, data, (published by Bonnot et al., 2017) concerning abundance in 352 AGs and in the different seed SPs during grain filling and in response to different nitrogen (N) and sulfur (S) supply, were integrated with mixOmics R package. Relationships between AGs and SPs were first unraveled using the unsupervised method sparse Partial Least Square, also known as Projection to Latent Structure (sPLS). Then, data were integrated using a supervised approach taking into account the nutrition and the grain developmental stage. We used the block.splda procedure also referred to as DIABLO (Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies). These approaches led to the identification of discriminant and highly correlated features from the two datasets (AGs and SPs) which are not necessarily differentially expressed during seed development or in response to N or S supply. Eighteen AGs were correlated with the quantity of SPs per grain. A statistical validation of these proteins by genetic association analysis confirmed that 5 out of this AG set were robust candidate proteins able to modulate the seed SP synthesis. In conclusion, this latter result confirmed that the integrative strategy is an adequate way to reduce the number of potentially relevant AGs for further functional validation.
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页数:14
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