Daytime soybean transcriptome fluctuations during water deficit stress View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Fabiana Aparecida Rodrigues, Renata Fuganti-Pagliarini, Juliana Marcolino-Gomes, Thiago Jonas Nakayama, Hugo Bruno Correa Molinari, Francisco Pereira Lobo, Frank G Harmon, Alexandre Lima Nepomuceno

ABSTRACT

BACKGROUND: Since drought can seriously affect plant growth and development and little is known about how the oscillations of gene expression during the drought stress-acclimation response in soybean is affected, we applied Illumina technology to sequence 36 cDNA libraries synthesized from control and drought-stressed soybean plants to verify the dynamic changes in gene expression during a 24-h time course. Cycling variables were measured from the expression data to determine the putative circadian rhythm regulation of gene expression. RESULTS: We identified 4866 genes differentially expressed in soybean plants in response to water deficit. Of these genes, 3715 were differentially expressed during the light period, from which approximately 9.55% were observed in both light and darkness. We found 887 genes that were either up- or down-regulated in different periods of the day. Of 54,175 predicted soybean genes, 35.52% exhibited expression oscillations in a 24 h period. This number increased to 39.23% when plants were submitted to water deficit. Major differences in gene expression were observed in the control plants from late day (ZT16) until predawn (ZT20) periods, indicating that gene expression oscillates during the course of 24 h in normal development. Under water deficit, dissimilarity increased in all time-periods, indicating that the applied stress influenced gene expression. Such differences in plants under stress were primarily observed in ZT0 (early morning) to ZT8 (late day) and also from ZT4 to ZT12. Stress-related pathways were triggered in response to water deficit primarily during midday, when more genes were up-regulated compared to early morning. Additionally, genes known to be involved in secondary metabolism and hormone signaling were also expressed in the dark period. CONCLUSIONS: Gene expression networks can be dynamically shaped to acclimate plant metabolism under environmental stressful conditions. We have identified putative cycling genes that are expressed in soybean leaves under normal developmental conditions and genes whose expression oscillates under conditions of water deficit. These results suggest that time of day, as well as light and temperature oscillations that occur considerably affect the regulation of water deficit stress response in soybean plants. More... »

PAGES

505

References to SciGraph publications

  • 2008-08. Global transcriptome analysis reveals circadian regulation of key pathways in plant growth and development in GENOME BIOLOGY
  • 2010-01. Genome sequence of the palaeopolyploid soybean in NATURE
  • 2014-12. Circadian oscillatory transcriptional programs in grapevine ripening fruits in BMC PLANT BIOLOGY
  • 2000-08. Arabidopsis thaliana germin-like proteins: common and specific features point to a variety of functions in PLANTA
  • 2010-12. Coordination of the maize transcriptome by a conserved circadian clock in BMC PLANT BIOLOGY
  • 2002-05. A soybean gene encoding a proline-rich protein is regulated by salicylic acid, an endogenous circadian rhythm and by various stresses in THEORETICAL AND APPLIED GENETICS
  • 2008-12. Validation of internal control for gene expression study in soybean by quantitative real-time PCR in BMC MOLECULAR BIOLOGY
  • 2010-12. Identification and analysis of the germin-like gene family in soybean in BMC GENOMICS
  • 1999-07. The Atger3 promoter confers circadian clock-regulated transcription with peak expression at the beginning of the night in PLANT MOLECULAR BIOLOGY
  • 1998-12. Arabidopsis thaliana contains a large family of germin-like proteins: characterization of cDNA and genomic sequences encoding 12 unique family members in PLANT MOLECULAR BIOLOGY
  • 2009-11. The BURP domain protein AtUSPL1 of Arabidopsis thaliana is destined to the protein storage vacuoles and overexpression of the cognate gene distorts seed development in PLANT MOLECULAR BIOLOGY
  • 1999-05. Treatment with 24-epibrassinolide, a brassinosteroid, increases the basic thermotolerance of Brassica napus and tomato seedlings in PLANT MOLECULAR BIOLOGY
  • 1998-09. A conserved BURP domain defines a novel group of plant proteins with unusual primary structures in MOLECULAR GENETICS AND GENOMICS
  • 2009-06. Genome-wide identification of BURP domain-containing genes in rice reveals a gene family with diverse structures and responses to abiotic stresses in PLANTA
  • 2010-12. Genome-scale identification of Soybean BURP domain-containing genes and their expression under stress treatments in BMC PLANT BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12864-015-1731-x

    DOI

    http://dx.doi.org/10.1186/s12864-015-1731-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1022451482

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26149272


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