Proteomic analysis reveals response of differential wheat (Triticum aestivum L.) genotypes to oxygen deficiency stress View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Rui Pan, Dongli He, Le Xu, Meixue Zhou, Chengdao Li, Chu Wu, Yanhao Xu, Wenying Zhang

ABSTRACT

BACKGROUND: Waterlogging is one of the main abiotic stresses that limit wheat production. Quantitative proteomics analysis has been applied in the study of crop abiotic stress as an effective way in recent years (e.g. salt stress, drought stress, heat stress and waterlogging stress). However, only a few proteins related to primary metabolism and signal transduction, such as UDP - glucose dehydrogenase, UGP, beta glucosidases, were reported to response to waterlogging stress in wheat. The differentially expressed proteins between genotypes of wheat in response to waterlogging are less-defined. In this study, two wheat genotypes, one is sensitive to waterlogging stress (Seri M82, named as S) and the other is tolerant to waterlogging (CIGM90.863, named as T), were compared in seedling roots under hypoxia conditions to evaluate the different responses at proteomic level. RESULTS: A total of 4560 proteins were identified and the number of differentially expressed proteins (DEPs) were 361, 640, 788 in S and 33, 207, 279 in T in 1, 2, 3 days, respectively. These DEPs included 270 common proteins, 681 S-specific and 50 T-specific proteins, most of which were misc., protein processing, DNA and RNA processing, amino acid metabolism and stress related proteins induced by hypoxia. Some specific proteins related to waterlogging stress, including acid phosphatase, oxidant protective enzyme, S-adenosylmethionine synthetase 1, were significantly different between S and T. A total of 20 representative genes encoding DEPs, including 7 shared DEPs and 13 cultivar-specific DEPs, were selected for further RT-qPCR analysis. Fourteen genes showed consistent dynamic expression patterns at mRNA and protein levels. CONCLUSIONS: Proteins involved in primary metabolisms and protein processing were inclined to be affected under hypoxia stress. The negative effects were more severe in the sensitive genotype. The expression patterns of some specific proteins, such as alcohol dehydrogenases and S-adenosylmethionine synthetase 1, could be applied as indexes for improving the waterlogging tolerance in wheat. Some specific proteins identified in this study will facilitate the subsequent protein function validation and biomarker development. More... »

PAGES

60

References to SciGraph publications

  • 2017-01. Physiological mechanism of programmed cell death aggravation and acceleration in wheat endosperm cells caused by waterlogging in ACTA PHYSIOLOGIAE PLANTARUM
  • 2010-03. Proteome analysis of soybean roots under waterlogging stress at an early vegetative stage in JOURNAL OF BIOSCIENCES
  • 1994-05. Differential accumulation of S-adenosylmethionine synthetase transcripts in response to salt stress in PLANT MOLECULAR BIOLOGY
  • 2014-03. Influence of seedling age and nitrogen application on photosynthesis and yield of rice (Oryza sativa) grown under waterlogged condition in INDIAN JOURNAL OF PLANT PHYSIOLOGY
  • 2010-12. Proteome analysis of soybean leaves, hypocotyls and roots under salt stress in PROTEOME SCIENCE
  • 2015-02. Tolerance of wheat to vegetative stage soil waterlogging is conditioned by both constitutive and adaptive QTL in EUPHYTICA
  • 2010-11. Comparative proteomics analysis of differentially expressed proteins in soybean cell wall during flooding stress in AMINO ACIDS
  • 2007-06. A proteomic screen and identification of waterlogging-regulated proteins in tomato roots in PLANT AND SOIL
  • 2018-01. iTRAQ-based comparative proteomic analysis provides insights into somatic embryogenesis in Gossypium hirsutum L. in PLANT MOLECULAR BIOLOGY
  • 2017-12. Elucidation of the molecular responses to waterlogging in Sesbania cannabina roots by transcriptome profiling in SCIENTIFIC REPORTS
  • 2014-07. Adverse weather conditions for European wheat production will become more frequent with climate change in NATURE CLIMATE CHANGE
  • 2018-03. Trends in plant research using molecular markers in PLANTA
  • 2014-01. Effects of nitrogen spraying on the post-anthesis stage of winter wheat under waterlogging stress in ACTA PHYSIOLOGIAE PLANTARUM
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12864-018-5405-3

    DOI

    http://dx.doi.org/10.1186/s12864-018-5405-3

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111507921

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30658567


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