Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

被引:22
作者
Iqbal, Zahra [1 ]
Iqbal, Mohammed Shariq [2 ]
Khan, M. Iqbal R. [3 ]
Ansari, Mohammad Israil [4 ]
机构
[1] Chulalongkorn Univ, Dept Biochem, Mol Crop Res Unit, Bangkok, Thailand
[2] Amity Univ Uttar Pradesh, Amity Inst Biotechnol, Lucknow, Uttar Pradesh, India
[3] Jamia Hamdard, Dept Bot, New Delhi, India
[4] Univ Lucknow, Dept Bot, Lucknow, Uttar Pradesh, India
关键词
genomics; metabolomics; omics; proteomics; rice; stress; transcriptomics; ORYZA-SATIVA L; ZINC-FINGER PROTEIN; GENOME-WIDE ASSOCIATION; COMPARATIVE PROTEOMIC ANALYSIS; DATABASE RAP-DB; TRANSCRIPTION FACTOR; GRAIN-YIELD; GENE-EXPRESSION; SALINITY TOLERANCE; DROUGHT TOLERANCE;
D O I
10.3389/fpls.2021.741419
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-a-vis rice trait improvement and stress management are described.
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页数:31
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