# LnCeVar 2.0: an updated resource and web tools for genomic variations disrupting ceRNA networks from single-cell/spatial transcriptomics data

## TL;DR

LnCeVar 2.0 is an updated database that explores how genomic variations affect RNA networks using single-cell and spatial transcriptomics data.

## Contribution

The database introduces expanded data, improved tools, and 3D visualization for analyzing SNV–ceRNA events in disease contexts.

## Key findings

- The database includes 5,218,062 SNV–ceRNA events across 2,673,603 cells/spots linked to disease processes.
- New tools like CeVarSC3D and CeVarST3D enable 3D visualization of SNV effects on RNA networks and cell states.
- The database supports high-resolution investigation of regulatory mechanisms in complex diseases.

## Abstract

LnCeVar 2.0 (available at http://bio-bigdata.hrbmu.edu.cn/LnCeVar or http://www.bio-bigdata.net/LnCeVar) is an updated database investigating genomic variations that disrupt competing endogenous RNA (ceRNA) networks via single-cell and spatial transcriptomics. Enhancements include expanded data and improved features: (i) 16 937 experimentally supported cancer biomarkers as well as 5785 validated ceRNA interactions and single nucleotide variant (SNV)–ceRNA events, manually curated and linked to key cancer pathogenic processes; (ii) 812 single-cell RNA sequencing/spatial transcriptomics RNA sequencing datasets covering 102 diseases, clinical treatments (e.g. chemotherapy, immunotherapy), and normal tissues; (iii) 5 218 062 single-cell- and spatial-specific SNV–ceRNA events across 2 673 603 cells/spots, with cellular functional perturbation networks; (iv) 5 comprehensive and 12 mini tools for multilevel cross talk analysis and 3D visualization; and (v) novel inference of SNV effects on cell types, states, and functions at single-cell and spatial levels. LnCeVar 2.0 features a user-friendly interface for searching, browsing, and analyzing data. For instance, the CeVarState interface illustrates how SNV–ceRNA events influence cell states during developmental processes, revealing interactions that determine cell fate. The CeVarSC3D and CeVarST3D tools perform multilevel cross talk analyses of SNVs, ceRNA networks, and cell states in disease pathology, providing interactive 3D visualizations. Overall, we anticipate that the updated database will facilitate the high-resolution investigation of SNV–ceRNA networks and advance our understanding of the regulatory mechanisms in complex disease ecosystems.

Graphical Abstract