Haopeng Yu

Piwi-interacting RNAs are a type of small noncoding RNA that have various functions. piRBase is a manually curated resource focused on assisting piRNA functional analysis. piRBase release v3.0 is committed to providing more comprehensive piRNA related information. The latest release covers >181 million unique piRNA sequences, including 440 datasets from 44 species. More disease-related piRNAs and piRNA targets have been collected and displayed. The regulatory relationships between piRNAs and targets have been visualized. In addition to the reuse and expansion of the content in the previous version, the latest version has additional new content, including gold standard piRNA sets, piRNA clusters, piRNA variants, splicing-junction piRNAs, and piRNA expression data. In addition, the entire web interface has been redesigned to provide a better experience for users. piRBase release v3.0 is free to access, browse, search, and download at http://bigdata.ibp.ac.cn/piRBase.

Yin Yang 1 (YY1) regulates early embryogenesis and adult tissue formation. However, the role of YY1 in stem cell regulation remains unclear. YY1 has a Polycomb group (PcG) protein-dependent role in mammalian cells. The PcG-independent functions of YY1 are also reported, although their underlying mechanism is still undefined. This paper reports the role of YY1 and BAF complex in the OCT4-mediated pluripotency network in mouse embryonic stem cells (mESCs). The interaction between YY1 and BAF complex promotes mESC proliferation and pluripotency. Knockdown of Yy1 or Smarca4, the core component of the BAF complex, downregulates pluripotency markers and upregulates several differentiation markers. Moreover, YY1 enriches at both promoter and super-enhancer regions to stimulate transcription. Thus, this study elucidates the role of YY1 in regulating pluripotency through its interaction with OCT4 and the BAF complex and the role of BAF complex in integrating YY1 into the core pluripotency network.

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.