Welcome To RiceRegMap!

RiceRegMap is based on rice 1-2mm young panicle, contains 275 RNA-seq data from representative cultivars and 219 ATAC-seq data from 219 of these populations, alongside high quality genomic variations. By meticulously dissecting these data, we pinpointed 30,869 expressed genes in the panicle and delineated 58,249 open chromatin regions (OCRs), which were further stratified into 736,242 bins for sophisticated analysis. This foundation of data was enriched with additional RNA-seq and ATAC-seq profiles from a selection of rice varieties, along with pertinent phenotypic data, to create a multi-dimensional map of rice's molecular landscape.

The establishment of RiceRegMap represents a significant leap forward in the exploration of gene expression regulation and the identification of key functional variations in rice. This comprehensive database is a testament to the power of multi-omics approaches, integrating a wealth of population-based genomic, transcriptomic, and chromatin accessibility data to unravel the intricate networks governing gene expression in rice.

Employing a Local Expression and Chromatin Accessibility Association Study (Local-eCAAS), we adeptly associated gene expression with the chromatin state of flanking regions, identifying a staggering 70% of the panicle-expressed genes as having significant cis-regulatory regions. This approach was further refined to distinguish cis- and trans-accessibility components within the chromatin structure, leading to the identification of 438,169 bins with pronounced cis-heritability. These findings were instrumental in pinpointing the regulatory elements that govern gene expression.

By leveraging cutting-edge tools such as caTWAS and FIMO scans of known transcription factors (TFs) motifs, RiceRegMap provided the aspects of upstream factors that govern gene regulation. The innovative TF→Bin_i→Target Genes strategy employed in this research facilitated the construction of a downstream regulatory target list, with each candidate downstream target assigned a SECAS score based on a multitude of data points, including association degree, co-expression, bin accessibility, and proximity to the target gene's transcription start site (TSS).

RiceRegMap also delved into local genomic variations, associating gene expression levels and bin accessibility with variations within ±100 kb regions and overlaying this with known TF Motif information to identify key cis-variations. A Bayesian colocalization analysis strategy was adeptly utilized to uncover key variations influencing multiple molecular phenotypes, providing a robust data framework and theoretical underpinning for understanding the impact of genomic variations.

RiceRegMap stands as a beacon for rice functional genomics research, offering online access to gene regulation and variation data, and equipping researchers with tools such as co-localization analysis and eCAAS enrichment. This database is poised to accelerate the elucidation of complex gene expression regulatory networks and propel rice functional genomics research into a new era of discovery and understanding.

Data Source

RiceRegMap is a database that contains population based 275 RNA-seq data and 219 ATAC-seq data of rice 1-2mm young panicle.

RiceRegMap enables online access to gene regulation and variation data, supporting the clarification of rice gene functions and mechanisms. It supports online queries for gene cis-regulatory regions, expression regulatory relationships, and key functional variations.

Comments or Questions

For any questions please send email to JingJ@webmail.hzau.edu.cn or weibo.xie@mail.hzau.edu.cn.

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Citations

Researchers who wish to use RiceRegMap are encouraged to refer to our publication:

Ming L, Fu D, Wu Z, Zhao H, Xu X, Xu T, Xiong X, Li M, Zheng Y, Li G, Yang L, Xia C, Zhou R, Liao K, Yu Q, Chai W, Li S, Liu Y, Wu X, Mao J, Wei J, Li X, Wang L, Wu C and Xie W. Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks. Nature Communications, 2023, 14:7501.

Zhao H, Li J, Yang L, Qin G, Xia C, Xu X, Su Y, Liu Y, Ming L, Chen L-L, Xiong L and Xie W. An inferred functional impact map of genetic variants in rice. Molecular Plant. 2021, 14: 1584–1599.