TY - JOUR T1 - Functional annotation of human long noncoding RNAs using chromatin conformation data JF - bioRxiv DO - 10.1101/2021.01.13.426305 SP - 2021.01.13.426305 AU - Saumya Agrawal AU - Tanvir Alam AU - Masaru Koido AU - Ivan V. Kulakovskiy AU - Jessica Severin AU - Imad Abugessaisa AU - Andrey Buyan AU - Josee Dostie AU - Masayoshi Itoh AU - Naoto Kondo AU - Yunjing Li AU - Mickaƫl Mendez AU - Jordan A. Ramilowski AU - Ken Yagi AU - Kayoko Yasuzawa AU - Chi Wai Yip AU - Yasushi Okazaki AU - Michael M. Hoffman AU - Lisa Strug AU - Chung Chau Hon AU - Chikashi Terao AU - Takeya Kasukawa AU - Vsevolod J. Makeev AU - Jay W. Shin AU - Piero Carninci AU - Michiel JL de Hoon Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/01/13/2021.01.13.426305.abstract N2 - Transcription of the human genome yields mostly long non-coding RNAs (lncRNAs). Systematic functional annotation of lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. Currently, 95% of human lncRNAs have no functional characterization. Using chromatin conformation and Cap Analysis of Gene Expression (CAGE) data in 18 human cell types, we systematically located genomic regions in spatial proximity to lncRNA genes and identified functional clusters of interacting protein-coding genes, lncRNAs and enhancers. Using these clusters we provide a cell type-specific functional annotation for 7,651 out of 14,198 (53.88%) lncRNAs. LncRNAs tend to have specialized roles in the cell type in which it is first expressed, and to incorporate more general functions as its expression is acquired by multiple cell types during evolution. By analyzing RNA-binding protein and RNA-chromatin interaction data in the context of the spatial genomic interaction map, we explored mechanisms by which these lncRNAs can act.Competing Interest StatementThe authors have declared no competing interest. ER -