EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput...

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Long non-coding RNAs (lncRNAs) are crucial in biological processes, but identifying functional ones requires curated data.
• The initial EVLncRNAs database (pre-May 2016) served as a valuable resource for experimentally validated functional lncRNAs (EVlncRNAs).
• Extensive research on lncRNAs has been published since the first release, necessitating an updated comprehensive database.

Purpose of the Study:

• To update and expand the EVLncRNAs database with experimentally validated functional lncRNAs (EVlncRNAs) and their associated data.
• To incorporate new categories of lncRNAs, including structural, exosomal, circular, and resistance-related types.
• To improve data accessibility and analysis through enhanced visualization tools and bioinformatics resources.

Main Methods:

• Manual curation of 19,245 lncRNA-related articles published between May 2016 and May 2020.
• Expansion of annotated EVlncRNAs, disease associations, and interaction records.
• Integration of new data categories and validation against retracted or fake articles.

Main Results:

• A substantial increase in annotated EVlncRNAs (260%), lncRNA-disease associations (484%), and interaction records (537%).
• Addition of new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 resistant lncRNAs.
• Development of an interactive visual network for exploring lncRNA-related interactions and integration with new bioinformatics tools.

Conclusions:

• EVLncRNAs 2.0 provides a significantly enriched and validated resource for functional lncRNA research.
• The database facilitates deeper insights into lncRNA roles in health and disease.
• Enhanced usability and new features empower researchers in the lncRNA field.