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Gene network modules associated with abiotic stress response in tolerant rice genotypes identified by transcriptome meta-analysis

Abstract

Abiotic stress tolerance is a complex trait regulated by multiple genes and gene networks in plants. A range of abiotic stresses are known to limit rice productivity. Meta-transcriptomics has emerged as a powerful approach to decipher stress-associated molecular network in model crops. However, retaining specificity of gene expression in tolerant and susceptible genotypes during meta-transcriptome analysis is important for understanding genotype-dependent stress tolerance mechanisms. Addressing this aspect, we describe here “abiotic stress tolerant” (ASTR) genes and networks specifically and differentially expressing in tolerant rice genotypes in response to different abiotic stress conditions. We identified 6,956 ASTR genes, key hub regulatory genes, transcription factors, and functional modules having significant association with abiotic stress–related ontologies and cis-motifs. Out of the 6956 ASTR genes, 73 were co-located within the boundary of previously identified abiotic stress trait–related quantitative trait loci. Functional annotation of 14 uncharacterized ASTR genes is proposed using multiple computational methods. Around 65% of the top ASTR genes were found to be differentially expressed in at least one of the tolerant genotypes under different stress conditions (cold, salt, drought, or heat) from publicly available RNAseq data comparison. The candidate ASTR genes specifically associated with tolerance could be utilized for engineering rice and possibly other crops for broad-spectrum tolerance to abiotic stresses.

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Acknowledgements

The authors would like to thank the Indian Council of Agricultural Research (ICAR) for supporting this work through the ICAR-sponsored project on the National Initiative on Climate Resilient Agriculture (NICRA) project. VC was supported by NASF (ICAR) grant No. Phen 2015/2011-12. Cis-element GRN analysis was performed using Computational facilities provided by the BTISNET program of the DBT, Govt. of India Grant No. BT/BI/04/069/2006. Use of computational resources of Bioinformatics Center, NII, and New Delhi for TRANSFAC analysis is gratefully acknowledged.

Author information

SS, VC, and KCB conceived and designed the experiments. SS performed the experiments and analyzed the data. SS, SKL, and GY interpreted the data. AKa performed computational analysis. SKM and AKu performed promoter extraction and cis-regulatory element in ASTR-GCN genes. SS, VC, DMP, GY, SKL, MD, and KCB wrote the paper. All authors read and approved the final manuscript.

Correspondence to Viswanathan Chinnusamy or Kailash Chander Bansal.

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Fig. S1

Node degree distribution of abiotic stress tolerant (ASTR) genes network in rice. (PDF 137 kb)

Fig. S2

Functional association of identified motifs in the abiotic stress tolerant (ASTR) genes modules in rice. (PDF 162 kb)

Fig. S3

(a) Bar plot shows the frequency of ASTR genes categorized in two groups; (1) ASTR gene differentially expressed in more than 1 experiment (in dark brown bar color) and (2) ASTR genes differentially expressed in one or in none of the experiments (in light brown bar color) plotted over the different categories (range from 2 to 17) of ranking from our microarray data shows on x-axis. Figure shows top ranking ASTR genes are in the top bin from RNAseq data as well. (b) Heatmap showing log2 fold change expression of ASTR genes in different tolerant cultivar under different stress condition in rice from publicly available RNAseq data (Shen et al. 2014; Shankar et al. 2016; Yoo et al. 2017; Zhang et al. 2017a, b; Chen et al. 2017; Cohen et al. 2017; Formentin et al. 2018) (Quantitative data is given in Table S8). Samples information in detailed in column name, formatted as stress name, then tissue type separated by “.” and then cultivar information in “( )”. Note that heat stress data showing here (very few) is for ASTR genes uniquely differentially expressed in heat stress tolerant genotype only. (PDF 37 kb)

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Smita, S., Katiyar, A., Lenka, S.K. et al. Gene network modules associated with abiotic stress response in tolerant rice genotypes identified by transcriptome meta-analysis. Funct Integr Genomics 20, 29–49 (2020). https://doi.org/10.1007/s10142-019-00697-w

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Keywords

  • Rice (Oryza sativa)
  • Gene network module
  • Abiotic stress
  • QTLs
  • Tolerant genotype
  • Meta-analysis
  • Transcriptome