SUMMARY: Currently, gene information available for Oryza sativa species is located in various online heterogeneous data sources. Moreover, methods of access are also diverse, mostly web-based and sometimes query APIs, which might not always be straightforward for domain experts. The challenge is to collect information quickly from these applications and combine it logically, to facilitate scientific research. We developed a Python package named PyRice, a unified programing API to access all supported databases at the same time with consistent output. PyRice design is modular and implements a smart query system, which fits the computing resources to optimize the query speed. As a result, PyRice is easy to use and produces intuitive results. AVAILABILITY AND IMPLEMENTATION: https://github.com/SouthGreenPlatform/PyRice. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Eukaryotic gene transcription is a complex process, which requires the orchestrated recruitment of a large number of proteins, such as sequence-specific DNA binding factors, chromatin remodelers and modifiers, and general transcription machinery, to regulatory regions. Previous works have shown that these regulatory proteins favor specific organizational theme along promoters. Details about how they cooperatively regulate transcriptional process, however, remain unclear. We developed a method to reconstruct a Bayesian network (BN) model representing functional relationships among various transcriptional components. The positive/negative influence between these components was measured from protein binding and nucleosome occupancy data and embedded into the model. Application on S.cerevisiae ChIP-Chip data showed that the proposed method can recover confirmed relationships, such as Isw1-Pol II, TFIIH-Pol II, TFIIB-TBP, Pol II-H3K36Me3, H3K4Me3-H3K14Ac, etc. Moreover, it can distinguish colocating components from functionally related ones. Novel relationships, e.g., ones between Mediator and chromatin remodeling complexes (CRCs), and the combinatorial regulation of Pol II recruitment and activity by CRCs and general transcription factors (GTFs), were also suggested. CONCLUSION: protein binding events during transcription positively influence each other. Among contributing components, GTFs and CRCs play pivotal roles in transcriptional regulation. These findings provide insights into the regulatory mechanism.