ArticleBMC bioinformatics2017
RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Transcriptomic responses under combined bacterial blight and drought stress in rice reveal potential genes to improve multi-stress tolerance.BMC plant biology · 2022Pooled it
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice.Database : the journal of biological databases and curation · 2024Article
- Integration of miRNA dynamics and drought tolerant QTLs in rice reveals the role of miR2919 in drought stress response.BMC genomics · 2023Article
- Meta-Analysis of Microarray Data and Their Utility in Dissecting the Mapped QTLs for Heat Acclimation in Rice.Plants (Basel, Switzerland) · 2023Article
- Article
- Genomics and transcriptomics to protect rice (Frontiers in plant science · 2022Review
- Overexpression of a DUF740 family gene (Frontiers in plant science · 2022Article
- Genome Editing: A Promising Approach for Achieving Abiotic Stress Tolerance in Plants.International journal of genomics · 2022Review
- Integration of Dual Stress Transcriptomes and Major QTLs from a Pair of Genotypes Contrasting for Drought and Chronic Nitrogen Starvation Identifies Key Stress Responsive Genes in Rice.Rice (New York, N.Y.) · 2021Article
- RiceMetaSysB: a database of blast and bacterial blight responsive genes in rice and its utilization in identifying key blast-resistant WRKY genes.Database : the journal of biological databases and curation · 2019Article
- Article
- Whole Genome Characterization of a Few EMS-Induced Mutants of Upland Rice Variety Nagina 22 Reveals a Staggeringly High Frequency of SNPs Which Show High Phenotypic Plasticity Towards the Wild-Type.Frontiers in plant science · 2018Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice.
resultsRiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search.
conclusionsThe aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.