10.22376/ijpbs.2019.10.1.p1-12 Volume 12 Issue 2 2021 (April-June) Rice ( lessThan i greaterThan Oryza sativa L. lessThan /i greaterThan ) is a major staple crop in India as well as it is consumed in other parts of world. It is feeding about 50% of the world's population as well as has a chief contribution in Indian economy. It is one of the most grown crops in India. Rice production is affected because of various biotic and abiotic factors. These factors lead to decrease in crop yield as well as it affects rice omics and lead to various disease (sheath blight, rice BLAST, etc.). Previous works and papers show that bacterial, fungal and viral pathogens are constantly destroying the rice yields and it is affecting the crop from germinating stage. Omics study is helping in prediction, identification, and modification of disease. Omics techniques such as genomics, transcriptomics, proteomics, epigenomics, etc., are helpful in prediction of disease. Disease can be predicted in the initial stage of crop development. Using, transcriptomics disease prediction in rice is nowadays very easy and through this we can decrease the chance of crop damage and maximise its productivity. Bioinformatics tools and databases are applied for study of disease prediction models. Datasets are generated after conducting various experiments which helps researchers to find out disease affecting crops at genetic level. Nowadays, many crops are modified genetically to improve disease resistance (Genetically Modified Crops). These datasets are stored in different rice databases (gramene, international rice information system, etc). These databases can be utilized in the creation of GM crops using bioinformatic tools like clustal omega, SRS, etc. Simran Jeet Kaur, Shivam Bhardwaj and Rashmi Rameshwari Oryza sativa, Rice production, Omics, Datasets, Genetic diseases 22-32