Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach

Borah, Pratikshya; Sharma, Eshan; Kaur, Amarjot; Chandel, Girish; Mohapatra, Trilochan; Kapoor, Sanjay; Khurana, Jitendra P.

doi:10.1038/srep42131

Cited by 58 publications

(48 citation statements)

References 84 publications

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“…Overexpression of OsBURP16 enhanced sensitivity to cold, salinity and drought stresses compared with controls [8]. Reduced violaxanthin de-epoxidase, LOC_Os04g31040, is instrumental in the regulation of xanthophyll cycle which can reduce ROS damage to cell structure [9,10].…”

Section: Module 7 the Third Pcmentioning

confidence: 99%

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

Campbell

et al. 2018

Preprint

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In many applications, such as gene co-expression network analyses, data arises with a huge number of covariates while the size of sample is comparatively small. To improve the accuracy of prediction, variable selection is often used to get a sparse solution by forcing coefficients of variables contributing less to the observed response variable to zero. Various algorithms were developed for variable selection, but LASSO is well known for its statistical accuracy, computational feasibility and broad applicability to adaptation. In this project, we applied LASSO to the gene co-expression network of rice with salt stress to discover key gene interactions for salt-tolerance related phenotypes. The dataset we have is a high-dimensional one, having 50K genes from 100 samples, with the issue of multicollinearity for fitting linear regression -the expression level of genes in the same pathway tends to be highly correlated. The property of LASSO with sparse parameters is naturally suitable to identify gene interactions of interest in this dataset. After biologically functional modules in the coexpression network was identified, the major changed expression patterns were further selected by LASSO regression to establish a linear relationship between gene expression profiles and physiological responses, such as sodium/potassium condenses, with salt stress. Five modules of intensively co-expressed genes, from 45 to 291 genes, were identified by our method with significant P-values, which indicate these modules are significantly associated with physiological responses to stress. Genes in these modules have functions related to ion transport, osmotic adjustment, and oxidative tolerance. For example, LOC_Os7g47350 and LOC_Os07g37320 are co-expressed gene in the same module 15. Both are ion transporter genes and have higher gene expression levels for rice with low sodium levels with salt stress.

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Section: Module 7 the Third Pcmentioning

confidence: 99%

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

Campbell

et al. 2018

Preprint

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“…Moreover, phytohormone signaling and Ca 2+ signaling were also highlighted in transcript pro ling and revealed the cross-talk among phytohormone signaling pathways (Kim et al 2018;LY et al 2014). In addition, a large number of transcription factor families, like WRKY, bZIP, and MYB, were identi ed involved in ABA-mediated signaling transduction under abiotic stresses (Borah et al 2017;Okay et al 2014). However, the molecular mechanism of drought tolerance/sensitive still need to be further investigation.…”

Section: Introductionmentioning

confidence: 99%

Identification of key modules and hub genes regulating drought stress response in rice drought sensitive line PY6 by weighted gene co-expression network analysis

Yu¹,

Liu²,

Wu³

et al. 2020

Preprint

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Background: Drought stress is an adverse factor with deleterious effects on several facets of rice growth. However, the mechanism underlying drought resistance in rice remains unclear. In order to genetically understand the potential molecular mechanism for drought response in rice, a drought sensitive Chromosome Segment Substitution Line (CSSL) PY6, which was constructed by the introgression of genomic segments of drought sensitive variety LAMBAYEQUE1 into drought-resistance variety PR403 via backcrossing, was used to map the QTL locus dss-1 for its sensitive phenotype, and to reveal the impact of dss-1 on the transcriptional profiling of PY6 via RNA-seq and WGCNA (weighted gene co-expression network analysis) analysis. Results: The genetic linkage analysis showed that dss-1 was located on the short arm of chromosome 1 of rice. In contrast to PR403, the over-accumulation of H 2 O 2 and MDA that might result in drought sensitive phenotype was observed in PY6 under drought stress. In the analysis of RNA-seq data, the identified differentially expressed genes (DEGs) mainly enriched in photosynthesis-related GO terms and exhibited a down-regulation pattern of their expressions in both PY6 and PR403 in response to drought stress, indicating that the photosynthesis was greatly inhibited in rice. Further WGCNA analysis constructed a co-expression network with 26 gene modules in which 4 and 3 modules that were highly correlated with H 2 O 2 and MDA, respectively. Likewise, the GO analysis of the differentially expressed hub genes (DEHGs) enriched in H 2 O 2 -correlated modules showed that the photosynthesis related GO terms were consistently over-represented. Furthermore, functional annotation of DEHGs in H 2 O 2 and MDA correlated modules revealed a cross talk between abiotic and biotic stresses. This was reflected by the differential expression alterations of hub genes which were annotated as encoding MYBs, laccases, WRKYs, and PRs family proteins, and ZFP36 were notably observed between PY6 and PR403 in response drought stress. Conclusions: Collectively, we speculated that drought-induced the inhibition of photosynthesis lead to the accumulation of H 2 O 2 and MDA that can trigger the reprogramming the profiling of transcriptome in rice. This included the differential regulation of hub genes that involve in ROS eliminated pathways to prevent the damage of rice plants from oxidative stress.

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“…Mutant lines indicated tolerance to drought in a selection processes, it should be showing relationship between phenotype and genotype. Based on reports from QTL and molecular data showed that a key gene has immediate response to drought and other biotic stressed Samota et al, 2017;Borah et al, 2017;Prince et al, 2015). The plant's phenotype showed tolerance to drought can be observed such as panicle length and fertile grains, roots length.…”

Section: Introductionmentioning

confidence: 99%

Drought Tolerance and Evaluation of Genetic Changes in Rice Mutant Lines

Amsal¹,

Ishak-ishak²

2018

American Journal of Applied Sciences

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The genetic improvement of rice through mutation induction to obtain drought resistance is essential for stable and adequate rice production would enable us to anticipate the rice yield-reducing effects of global warming. The aim of this research was to evaluate the rice mutant lines showing tolerance to drought condition and their genetic relationship using SSR markers. Mutant lines were obtained by irradiation of Mira-1 rice variety at primordial state by 25 and 50 Gy doses. Twenty numbers of M4 rice mutant lines, cv. Mira-1 as wild type, cv. Gajah mungkur as positive control and cv. IR64 as negative control were chosen in this study were planted in PVC cylinders in the green house. The result showed that the agronomic trait of rice mutant lines were better than their wild type. Root length of 17 number of mutant lines are longer than their wild type and Gajah mungkur, the longest root obtain was 71.5 cm on 7J4 rice mutant line compared to Mira-1 only which was 25 cm. The number of lateral roots and seeds content per panicle higher than their wild type and positive control. Based on SSR marker linked to root depth, DRO1 showed that 12 numbers of mutant lines polymorphic and changing of genetic of mutant lines which was indicating the mutant lines were tolerant to drought compared to their wild type. The molecular information of rice mutant lines is essential for further development of a new superior variety of rice, which would be an improvement of the variety already existed.

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Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach

Cited by 58 publications

References 84 publications

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

Identification of key modules and hub genes regulating drought stress response in rice drought sensitive line PY6 by weighted gene co-expression network analysis

Drought Tolerance and Evaluation of Genetic Changes in Rice Mutant Lines

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