Iqbal Zahra, Iqbal Mohammed Shariq, Khan M Iqbal R, Ansari Mohammad Israil
Molecular Crop Research Unit, Department of Biochemistry, Chulalongkorn University, Bangkok, Thailand.
Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow, India.
Front Plant Sci. 2021 Oct 15;12:741419. doi: 10.3389/fpls.2021.741419. eCollection 2021.
Rice () 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 rice trait improvement and stress management are described.
水稻是世界上近一半人口的重要主食作物。包括非生物和生物胁迫在内的具有挑战性的环境条件对水稻的品质和产量产生负面影响。为了确保为前所未有的不断增长的世界人口提供粮食供应,改良水稻作物至关重要。在这个时代,“组学”技术已被广泛用于破译水稻中的调控机制和细胞复杂性。组学技术的进步为可靠探索参与水稻性状发育的遗传资源提供了强大平台。基因组学、转录组学、蛋白质组学和代谢组学等组学学科为在最佳和胁迫环境下实现水稻所需的改良做出了重大贡献。本综述概述了基础和应用多组学技术为改良水稻优良性状提供的新编排。本文还提供了组学应用的当前情况目录,以了解这种重要作物在产量提高和各种环境胁迫方面的情况。此外,还描述了数据科学领域中用于分析大数据以及检索与水稻性状改良和胁迫管理相关信息的合适数据库。