Nucleic Acids Research, 20 November, 2025, DOI：https://doi.org/10.1093/nar/gkaf1132

NONCODE v7.0: updated lncRNA resource integrating scRNA-seq data encompassing immune baseline, development, and disease

Hongjie Liu, Yongsan Yang, Xin Le, Kai Gao, Jingjia Liu, Youfen Fan, Xiaoxi Zeng, Runsheng Chen, Jianjun Zheng, Yi Zhao

Abstract

The rapid advancement of single-cell multi-omics technologies, typified by single-cell RNA sequencing (scRNA-seq), has provided systematic methodologies for dissecting gene expression heterogeneity within cell populations. However, long noncoding RNAs (lncRNAs) research is hindered by a lack of databases covering diverse tissues, disease contexts, and integrated multi-dimensional single-cell annotations. To address this gap, we updated NONCODE v7.0 (available at https://v7.noncode.org/) through the integration of scRNA-seq data, enabling systematic analysis of lncRNA expression. NONCODE v7.0 incorporates 2061 human scRNA-seq samples from 229 datasets, covering a spectrum of 6 categories, with 3 core ones including Physiological Control as an immune baseline, Physiological Development, and Pathological Disease. Following standardized quality control and processing, the database encompasses 14 million high-quality cells and annotates 94?843 lncRNAs (98.5% of human lncRNAs in NONCODE v6.0). Furthermore, we extended the database through the integration of single-cell-tailored functional modules, encompassing data query and retrieval, interactive visualization (including cell composition, UMAP/t-SNE clustering, marker gene heatmaps, and lncRNA expression profiles), and comparative analysis functionalities. The analytical module facilitates the identification of cell-type-specific differentially expressed (DE) lncRNAs across distinct disease states, thus establishing a foundational resource platform to facilitate the advancement of downstream functional investigations into lncRNAs.

Article link：https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkaf1132/8328556#supplementary-data