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7 November 2018 Drought-responsive protein identification in developing grains of a wheat–Haynaldia villosa 6VS/6AL translocation line
Ruomei Wang, Jisu Wu, Xiong Deng, Dongmiao Liu, Yueming Yan
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Abstract

Drought is a widespread abiotic stress that has a detrimental effect on both yield and quality of wheat. Discovery and utilisation of drought-resistant gene resources from wheat-related species may help to mitigate effects of drought and decrease yield loss. In this study, we used a comparative proteome approach to identify potential drought-resistance proteins from a wheat (Triticum aestivum L.)–Haynaldia villosa (L.) Schur 6VS/6AL translocation line. Drought experiments showed that introgression of the H. villosa 6VS chromosome short arm into common wheat cultivar Yangmai 5 through 6VS/6AL translocation led to better drought resistance. Two-dimensional difference gel electrophoresis (2D-DIGE) identified 99 differentially accumulated protein (DAP) spots in the wheat–H. villosa 6VS/6AL translocation line, 42 of which were specifically present or showed a significantly upregulated accumulation. Of these, 20 DAPs representing 19 unique proteins in the wheat–H. villosa 6VS/6AL translocation line were upregulated under drought stress. These proteins were mainly involved in defence–stress, energy metabolism, carbon metabolism, nitrogen metabolism, and protein metabolism or folding. Protein–protein interaction analysis of key DAPs displayed a complex interaction network that synergistically regulated drought response. Dynamic transcriptional expression analysis revealed the differential expression of six key DAP genes involved in drought-stress response in the protein–protein interaction network. Our results indicated that H. villosa may have gene resources for wheat drought-resistance improvement.

© CSIRO 2018
Ruomei Wang, Jisu Wu, Xiong Deng, Dongmiao Liu, and Yueming Yan "Drought-responsive protein identification in developing grains of a wheat–Haynaldia villosa 6VS/6AL translocation line," Crop and Pasture Science 69(12), 1182-1196, (7 November 2018). https://doi.org/10.1071/CP18303
Received: 26 June 2018; Accepted: 1 October 2018; Published: 7 November 2018
KEYWORDS
2D-DIGE
grain development
PPI network
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