Microarray dataset of transgenic rice overexpressing Abp57

Tan, Lay Wen; Tan, Cheng Seng; Rahman, Zuraida Ab; Goh, Hoe-Han; Ismail, Ismanizan; Zainal, Zamri

doi:10.1016/j.dib.2017.07.047

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Previous studies demonstrated that transgenic rice harbour stress-related genes such as NHX1 (vacuolar Na + /H + antiporter) [ 276 ], ADC (arginine decarboxylase) [ 277 ], Calcineurin , CBF3 (C-repeat element binding factor 3) [ 278 ], codA (choline oxidase) [ 279 ], HVA1 (LEA protein) [ 280 ], OsCDPK7 (regulatory factor) [ 49 ], OsMAPK5 (mitogen-activated protein kinase) [ 281 ], SOD2 (plasma membrane Na + /H + antiporter) [ 282 ] and TPSP (trehalose-6-phosphate synthase and phosphatase) [ 283 ] to enhance abiotic stress tolerance, especially salinity and drought. A recent study also found that the overexpression salt-responsive gene OsPP1a [ 284 ], OsASR1 [ 285 ], Abp57 [ 286 ], SIDP361 [ 287 ], OsSUV3 [ 288 ] and PDH45 [ 289 ] contribute to salinity tolerance in rice. As seen above, significant progress has been achieved in improving abiotic-stress-tolerant transgenic rice.…”

Section: Modernise Breeding Approaches For Rice Salinity Improvementmentioning

confidence: 99%

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Ullah

Abdullah‐Zawawi

Zainal-Abidin

et al. 2022

Plants

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Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

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Section: Modernise Breeding Approaches For Rice Salinity Improvementmentioning

confidence: 99%

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Ullah

Abdullah‐Zawawi

Zainal-Abidin

et al. 2022

Plants

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“…The robust multiarray analysis (RMA) method was applied to ensure that the relative log expression signal (RLE) was comparable between samples. The microarray experiment was then previously deposited into the NCBI by [21] and is accessible through the NCBI GEO DataSets (DOI: https:// www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE99055, accessed on 1 June 2017) [22].…”

Section: Gene Expression Profiling Differentially Expressed Genes (De...mentioning

confidence: 99%

“…To further support the reliability of our Abp57-OE microarray data in drought, the coexpression module analysis was carried out using the CEMiTool R package version 1.20 [30]. The published microarray dataset, under the accession number GSE99055, was employed as a discovery set [21]. In this study, the correlation method of Pearson was selected to transform the gene expression matrix (m × n) into an adjacency matrix, where m denotes as genes and n represents the samples.…”

Section: Construction Of Gene Co-expression Network Modulesmentioning

confidence: 99%

An Integration of Transcriptomic Data and Modular Gene Co-Expression Network Analysis Uncovers Drought Stress-Related Hub Genes in Transgenic Rice Overexpressing OsAbp57

et al. 2022

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Auxin receptor plays a significant role in the plant auxin signalling pathway in response to abiotic stress. Recently, we found that transgenic rice overexpressing ABP57 had higher drought tolerance than the wild-type cultivar, MR219, due to the fact of its enhanced leaf photosynthetic rate and yields under drought stress. We performed a microarray study on this line to investigate the underlying mechanisms contributing to the observed phenotype. After microarray data filtering, 3596 genes were subjected to modular gene co-expression network (mGCN) development using CEMiTool, an R package. We identified highly related genes in 12 modules that could act to specific responses towards drought or any of the abiotic stress types. Gene set enrichment and overrepresentation analyses for modules extracted two highly upregulated modules that are involved in drought-related biological processes such as transmembrane transport of metal ions and response to oxidative stress. Finally, 123 hub genes were identified in all modules after integrating co-expression information with physical interaction data. In addition, the interplay of significant pathways between the metabolism of chlorophyll and flavonoid and the signalling pathways of MAPK, IAA, and SA inferred the concurrent involvement of stress tolerance response. Collectively, our findings seek new future directions for breeding strategies in rice tolerant improvements.

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Microarray dataset of transgenic rice overexpressing Abp57

Cited by 2 publications

References 2 publications

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

An Integration of Transcriptomic Data and Modular Gene Co-Expression Network Analysis Uncovers Drought Stress-Related Hub Genes in Transgenic Rice Overexpressing OsAbp57

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