A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms
Abstract
:1. Introduction
2. Effects of Salinity on Rice
2.1. Morphological Effects on Rice under Salinity
2.2. Physiology, Biochemistry and Molecular Response of Rice under Salinity Stress
3. Adaptive Mechanisms of Salinity Tolerance in Rice
4. Omics Platforms Used for Rice Improvement
4.1. Genomics
Parents | QTLs Number | Different Stage | References |
---|---|---|---|
Pokkali × IR29 | 23 | Seedlings | [84] |
Nonabokra × Koshihikari | 11 | Seedlings | [85] |
Ahlemi Tarom × Neda | 73 | Seedlings | [86] |
Capsule × BRRI dhan29 | 27 | Seedlings | [87] |
Pokkali × Bengal | 50 | Seedlings | [82] |
Hasawi × IR29 | 34 | Seedlings | [88] |
Kalarata × Azucena | 13 | Seedlings | [89] |
Nonabokra × Jupiter | 33 | Seedlings | [90] |
Dianjingyou × Sea Rice 86 | 1 | Seedlings | [91] |
CSR27 × MI48 | 25 | Seedlings, vegetative and reproductive | [92] |
OM7347 × OM5629 | 9 | Seedlings, vegetative and reproductive | [93] |
Horkuch × IR29 | 14 | Seedlings and reproductive | [94] |
Cheriviruppu8 × Pusa Bashmati 1 | 16 | Reproductive | [95] |
Pokkali × IR36 | 6 | Maturity | [96] |
CSR27 × MI48 | 8 | Maturity | [97] |
Jiucaiqing × IR26 | 16 | Germination | [98] |
Wujiaozhan × Nipponbare | 13 | Germination | [99] |
4.2. Transcriptomics
4.3. Proteomics
4.4. Metabolomics
4.5. Phenomics
Omic Approach | Techniques | Description | References |
---|---|---|---|
Genomics | Map-based sequencing | Rice genome sequence. | [81] |
Illumina-seq | 213 and 436 transcript tags of shoot and root were differentially expressed in response to salt. | [256] | |
Genome-wide meta-analysis | 3449 DEGs were detected in rice tissues. Surprisingly, 23 possible-candidate salinity responsive genes for yield and ion homeostasis were discovered. | [257] | |
Mutation breeding | Rice mutants improve salt tolerance. | [119,121,123,124] | |
Illumina-seq | DMRs enhance salt tolerance. | [131] | |
Genetic engineering | Developed salinity tolerant rice mutants through CRISPR-cas9. | [258,259] | |
Transcriptomics | DNA microarray | 486 salt-responsive ESTs identified from rice shoot. | [148] |
RNA-seq | Several salt-inducible genes have been identified | [152,153] | |
RNA-seq | In hybrid rice LYP9 and from its two parents, salt- induced DEGs were found to be 8292, 8037 and 631, respectively. This research provided a new perspective on heterosis mechanisms in salinity tolerance. | [154] | |
RNA-seq | More transporters, ion and sugar-related transports were also identified from Mulai roots to have a role in the control of salt tolerance. | [166] | |
RNA-seq | Identify genetic SSR markers that will help in marker- assisted breeding to improve the agronomic traits under different stress conditions. | [163] | |
RNA-seq | Identified important genes regulated during salt stress in rice, such as OsSOS1, OsHKT1;5, OsHKT2;1, OsNHX1, OsAKT1, OsNRT1;2, OsTPC1, OsCDPK7, OsARP, OsMAPK5, 44 and OsSERF1. | [76] | |
Proteomics | 2-DE | Six salt responsive proteins identified | [181] |
2-DE and MALDI-TOF MS | During salt stress, 57 responsive proteins were regulated, among them several are novel salt responsive proteins. | [182] | |
2-DE and LC-MS/MS | Four proteins were identified, among them 2 proteins, involved in salt stress response and the ubiquitin 26S proteasome system. | [183] | |
2-D and MALDI-TOF MS | 11 proteins were found to be differentially expressed. Most of them were new to being involved in rice salt response. | [185] | |
2-DE | 40 uniquely upregulated proteins were identified under ABA+salt stress. | [187] | |
iTRAQ | Identified 5340 proteins, among them differentially expressed proteins involved in salt stress regulation and response to oxidation–reduction; photosynthesis and carbohydrate metabolisms. | [192] | |
iTRAQ | Identified more than 2000 proteins in both root and shoot of salt-tolerant elite line FL478, during the early salinity stage. Among the identified proteins, some proteins are potential candidates, involved in the amino acid synthesis, antioxidant stress, and maintenance of mitochondrial activity, metabolism and Calvin cycle. | [193] | |
iTRAQ | Identified 4598 proteins; among them, 279 were up- and downregulated and involved in oxidative phosphorylation, photosynthesis, phenylpropanoid biosynthesis, posttranslational modification and energy metabolism. | [194] | |
Metabolomics | GC-MS | Metabolic profiling of ice seeds. | [215,216,217,218] |
GC-MS | Rice metabolic profiling. | [219] | |
H-NMR | Five conserved salts responsive metabolic markers were identified. | [220] | |
H-NMR | Significant accumulation of sugar and amino acids under stress conditions. | [221] | |
GC-MS | Characterised 92 primary metabolites in both shoots and roots in rice under stress and control conditions. Among them, 11 metabolites including amino acid and sugar significantly increased in tolerant varieties at the time of salt treatments. | [222] | |
GC-MS | Two signalling molecules serotonin and gentisic acid are two significant biomarker compounds produced in tolerant varieties that contribute to NaCl tolerance | [224] | |
GC-MS | A total of 84 metabolites were identified including amino acid, sugar, organic acid and other small molecular components. | [225] | |
Phenomics | RGB and fluorescence images | A combined technique was applied for the screening of different salt tolerance traits of rice. | [246] |
IR thermal images | Used to examine rice phenotyping under a salt stress environment. | [247] | |
Automated imaging | Identify significant traits for subsequent QTL analysis, to deeper understand the genetic mechanisms driving RSA. | [248] | |
X-ray tomography | Used to quantify the response of rice RSA to the soil environment. | [249] | |
RGB and fluorescence images | Investigate the complex salinity tolerance in Australian wild rice species. | [251] |
5. Modernise Breeding Approaches for Rice Salinity Improvement
5.1. Marker-Assisted Selection (MAS)
5.2. Transgenic Approach
5.3. Genome Editing
5.4. Machine Learning (ML)
6. Integration of Omics and Role of Bioinformatics for Rice Improvement
7. Conclusions
8. Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Database | Description | Web Tool/URL |
---|---|---|
RAP-DB | Rice genomics database | https://rapdb.dna.affrc.go.jp (accessed on 10 October 2021) |
RiceXPro | Expression profile database of rice | https://ricexpro.dna.affrc.go.jp (accessed on 10 October 2021) |
NCBI GEO | National Center for Biotechnology Information Gene Expression Omnibus | https://ncbi.nlm.nih.gov/geo (accessed on 10 October 2021) |
QlicRice | Stress related QTLs data mining tool | https://nabg.iasri.res.in:8080/qlic-rice (accessed on 10 October 2021) |
STIFDB2 | Plant stress-related data mining tool | https://caps.ncbs.res.in/stifdb2 (accessed on 10 October 2021) |
TENOR | Comprehensive mRNA-seq database of rice under environmental stress conditions | https://tenor.dna.affrc.go.jp (accessed on 10 October 2021) |
Genevestgator | Transcriptomics database for investigating gene expression in a wide range of biological situations | https://genevestigator.com (accessed on 2 September 2021) |
CSRDB | Small RNA database for cereals | https://sundarlab.ucdavis.edu/smrnas (accessed on 10 October 2021) |
RiceSRTFDB | Rice stress-related TF database | https://nipgr.res.in/RiceSRTFDB (accessed on 10 October 2021) |
Stress2TF | A manually curated database of transcription factor regulation in plants response to stress | https://csgenomics.ahau.edu.cn/Stress2TF (accessed on 10 October 2021) |
PSPDB | Stress-related protein database for plants | https://bioclues.org/pspdb (accessed on 10 October 2021) |
OryzaGenome | Integrated biological and genomics database | https://viewer.shigen.info/oryzagenome2detail (accessed on 15 October 2021) |
Ricebase | Combining molecular marker, pedigree and whole-genome-based data tool | https://ricebase.org (accessed on 10 October 2021) |
Gramene | A comprehensive data library for comparative genomics studies | https://gramene.org (accessed on 15 October 2021) |
Phytozome | Plant Comparative Genomics Portal | https://phytozome.net (accessed on 12 February 2020) |
Ensembl Plants | Integrated tool for plant genomics data mining, interpreting and visualising | https://plants.ensembl.org (accessed on 12 February 2020) |
PlantPReS | Plant proteome database | https://proteome.ir (accessed on 17 October 2021) |
Plant Reactome | Genome, transcriptome, proteome and integrated metabolic pathways | https://plants.reactome.org (accessed on 12 February 2020) |
PlantGDB | Resources for plant genomics | https://plantgdb.org (accessed on 17 October 2021) |
GabiPD | Integrative omics database | https://gabipd.org (accessed on 17 October 2021) |
PMND | A vast network of databases on plant metabolic pathways | https://plantcyc.org (accessed on 17 October 2021) |
RicyerDB | Integrated genomics and proteomics database | https://server.malab.cn/Ricyer (accessed on 13 October 2021) |
CARMO | Integrative omics database | https://bioinfo.sibs.ac.cn/carmo (accessed on 13 October 2021) |
PTools | Integrative omics database | https://omictools.com/ptools/tool (accessed on 13 October 2021) |
Gromacs | Database of genomics, proteomics and metabolomics | https://omictools.com/gromacs/tool (accessed on 13 October 2021) |
STRING | PPI network analysis containing functional association | https://string-db.org (accessed on 9 January 2020) |
PANTHER | Analysis of proteins based on evolutionary relationships | https://pantherdb.org (accessed on 13 October 2021) |
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Ullah, M.A.; Abdullah-Zawawi, M.-R.; Zainal-Abidin, R.-A.; Sukiran, N.L.; Uddin, M.I.; Zainal, Z. A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms. Plants 2022, 11, 1430. https://doi.org/10.3390/plants11111430
Ullah MA, Abdullah-Zawawi M-R, Zainal-Abidin R-A, Sukiran NL, Uddin MI, Zainal Z. A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms. Plants. 2022; 11(11):1430. https://doi.org/10.3390/plants11111430
Chicago/Turabian StyleUllah, Mohammad Asad, Muhammad-Redha Abdullah-Zawawi, Rabiatul-Adawiah Zainal-Abidin, Noor Liyana Sukiran, Md Imtiaz Uddin, and Zamri Zainal. 2022. "A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms" Plants 11, no. 11: 1430. https://doi.org/10.3390/plants11111430