Functional & Integrative Genomics

, Volume 18, Issue 6, pp 627–644 | Cite as

Transcriptome profiling of short-term response to chilling stress in tolerant and sensitive Oryza sativa ssp. Japonica seedlings

  • Matteo ButiEmail author
  • Marianna Pasquariello
  • Domenico Ronga
  • Justyna Anna Milc
  • Nicola Pecchioni
  • Viet The Ho
  • Chiara Pucciariello
  • Pierdomenico Perata
  • Enrico Francia
Original Article


Low temperature is a major factor limiting rice growth and yield, and seedling is one of the developmental stages at which sensitivity to chilling stress is higher. Tolerance to chilling is a complex quantitative trait, so one of the most effective approaches to identify genes and pathways involved is to compare the stress-induced expression changes between tolerant and sensitive genotypes. Phenotypic responses to chilling of 13 Japonica cultivars were evaluated, and Thaibonnet and Volano were selected as sensitive and tolerant genotypes, respectively. To thoroughly profile the short-term response of the two cultivars to chilling, RNA-Seq was performed on Thaibonnet and Volano seedlings after 0 (not stressed), 2, and 10 h at 10 °C. Differential expression analysis revealed that the ICE-DREB1/CBF pathway plays a primary role in chilling tolerance, mainly due to some important transcription factors involved (some of which had never been reported before). Moreover, the expression trends of some genes that were radically different between Thaibonnet and Volano (i.e., calcium-dependent protein kinases OsCDPK21 and OsCDPK23, cytochrome P450 monooxygenase CYP76M8, etc.) suggest their involvement in low temperature tolerance too. Density of differentially expressed genes along rice genome was determined and linked to the position of known QTLs: remarkable co-locations were reported, delivering an overview of genomic regions determinant for low temperature response at seedling stage. Our study contributes to a better understanding of the molecular mechanisms underlying rice response to chilling and provides a solid background for development of low temperature-tolerant germplasm.


Oryza sativa Chilling tolerance Short-term response RNA-Seq Differentially expressed genes 



Thanks are due to Marco Moretto and Paolo Sonego (Fondazione Edmund Mach, San Michele all’Adige ITALY) for their precious help with RNA-Seq data treatment.

Author contributions

MP, DR, VTH, and CP performed rice plants phenotiping, RNA extractions and RT-qPCR. MB and JAM performed the RNA-Seq analysis. MB wrote the manuscript. EF, NP, and PP conceived the experiment, participated in the interpretation and discussion of results, and contributed to the writing of the paper.

Funding information

This work was supported by Progetto AGER, grant n° 2010-2369—Integrated Genetic And Genomic Approaches For New Italian Rice Breeding Strategies (RISINNOVA).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10142_2018_615_MOESM1_ESM.xlsx (10 kb)
Online Resource 1 Primers used for RT-qPCR. (XLSX 9 kb)
10142_2018_615_Fig7_ESM.png (32 kb)
Online Resource 2

Statistical analysis of electrolytic leakage (EL%) measured in not stressed plants (ctrl) and 2, 7, 14 days after chilling exposure for Experiment 1. Dashed lines inside boxes represent the average value for the 13 cultivars. Significant differences were derived from unbalanced ANOVA and reported on the figure (n.s., not significant; ***, p < 0.001). (PNG 32 kb)

10142_2018_615_MOESM2_ESM.tif (87 kb)
High Resolution Image (TIF 86 kb)
10142_2018_615_MOESM3_ESM.xlsx (11 kb)
Online Resource 3 Size (bp) and normalization factors (calculated with EdgeR according to each library size) for the 18 RNA-Seq libraries. (XLSX 11 kb)
10142_2018_615_MOESM4_ESM.xlsx (6.2 mb)
Online Resource 4 Normalized reads counts for active genes in Thaibonnet and Volano RNA libraries. (XLSX 6378 kb)
10142_2018_615_MOESM5_ESM.png (29 kb)
Online Resource 5 Multi-dimensional scaling (MDS) plots for Thaibonnet (a) and Volano (b) RNA libraries generated with EdgeR to measure gene expression differences (three biological replicates for 0, 2 and 10 h of chilling stress for each genotype). (PNG 29 kb)
10142_2018_615_MOESM6_ESM.xlsx (10.5 mb)
Online Resource 6 EdgeR differential expression analysis results for all the active genes of Thaibonnet and Volano rice genotypes for 2 and 10 h of chilling stress compared to control samples. (XLSX 10721 kb)
10142_2018_615_MOESM7_ESM.xlsx (1012 kb)
Online Resource 7 List of the rice genes that are differentially expressed in at least one of the four stress combinations (Thaibonnet/Volano; 2/10 h of stress) compared to controls. Position on the genome, description and log2 Fold Change resulting from EdgeR analysis are reported for each gene. Empty cells on log2FC columns mean that the gene is not regulated on the correspondent RNA-Seq set. (XLSX 1011 kb)
10142_2018_615_Fig8_ESM.png (296 kb)
Online Resource 8

Box plots representing the log2(Fold Change) statistical distribution for DEGs of Thaibonnet (red) and Volano (blue), clustered by their expression trend: (a) genes up-regulated after 2 and 10 h of stress; (b) genes up-regulated only after 2 h of stress; (c) genes up-regulated only after 10 h of stress; (d) genes down-regulated after 2 and 10 h of stress; (e) genes down-regulated only after 2 h of stress; (f) genes down-regulated only after 10 h of stress. Whiskers above and below the boxes indicate the 10th and the 90th percentiles. (PNG 296 kb)

10142_2018_615_MOESM8_ESM.tif (66 kb)
High Resolution Image (TIF 65 kb)
10142_2018_615_MOESM9_ESM.xlsx (18 kb)
Online Resource 9 List of QTLs found in Gramene and in bibliography. For each QTL, relative trait, linkage group (LG), genetic position in cM (where available), associated markers, physical position in Japonica rice genome in bp, number of genes included in the QTL that are differentially expressed in at least one experiment (Thaibonnet/Volano and 2/10 h) are reported. (XLSX 17 kb)
10142_2018_615_MOESM10_ESM.xlsx (1.2 mb)
Online Resource 10 GO-enrichment analysis results for DEGs of Thaibonnet and Volano rice genotypes for 2 and 10 h of chilling stress. For each GO term, over- and under-represented p-value, number of DE genes (numDEInCat), total genes (numInCat), ontology and term name are included. (XLSX 1190 kb)
10142_2018_615_MOESM11_ESM.xlsx (41 kb)
Online Resource 11 List of the GO terms enriched (p < 0.05) in at least one of the 4 analyzed DEGs sets (Thaibonnet/Volano and 2/10 h). For each GO term, p-value for each DEGs set, ontology and GO term name are reported. Empty cells on p-value columns means that the GO term is not significantly enriched in the correspondent DEGs set. (XLSX 40 kb)
10142_2018_615_MOESM12_ESM.png (80 kb)
Online Resource 12 MapMan regulation overview of the genes that are up-regulated at 2 h in Volano, but only at 10 h in Thaibonnet. Genes are binned to MapMan functional categories and the values are represented as the log2-transformed values. Blue squares indicates up-regulated genes. (PNG 79 kb)
10142_2018_615_MOESM13_ESM.xls (37 kb)
Online Resource 13 Genes binned by MapMan to “Transcription Factor” among genes that are up-regulated at 2 h and 10 h in Volano, but only at 10 h in Thaibonnet. (XLS 37 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Matteo Buti
    • 1
    Email author
  • Marianna Pasquariello
    • 2
  • Domenico Ronga
    • 1
  • Justyna Anna Milc
    • 1
    • 3
  • Nicola Pecchioni
    • 3
    • 4
  • Viet The Ho
    • 5
    • 6
  • Chiara Pucciariello
    • 5
  • Pierdomenico Perata
    • 5
  • Enrico Francia
    • 1
    • 3
  1. 1.BIOGEST-SITEIAUniversity of Modena and Reggio EmiliaReggio EmiliaItaly
  2. 2.Department of Crop GeneticsJohn Innes CentreNorwichUK
  3. 3.Department of Life SciencesUniversity of Modena and Reggio EmiliaReggio EmiliaItaly
  4. 4.Cereal Research CentreCouncil for Agricultural Research and EconomicsFoggiaItaly
  5. 5.PlantLabScuola Superiore Sant’AnnaPisaItaly
  6. 6.Ho Chi Minh City University of Food IndustryHo Chi MinhVietnam

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