Though genes are commonly thought of as stretches of DNA that contain 12instructions for building a protein, less than 2% of the human genome consists of protein-coding regions, while the remaining 98% is non-coding. Nevertheless, 76% of the human genome is transcribed, typically in a highly cell type-dependent fashion, generating a wide variety of non-coding RNAs. As most genetic variants associated with disease are located in such non-coding re-gions, understanding the biological role of non-coding RNAs is of fundamental importance. However, 95% of non-coding genes currently do not have a func-tional annotation.Non-coding RNAs localized to the cell nucleus are particularly interesting as they may be involved in transcriptional control of nearby genes. We analyzed sequencing data from Hi-C, a chromosome conformation capture protocol that detects pairs of DNA segments in close physical proximity, to understand the 3D structure of the human genome in the nucleus across 18 cell types. This al-lowed us to assign cell type-specific functional categories to most non-coding RNAs based on their physical association with functionally annotated protein-coding genes. We found that non-coding RNAs typically have specialized func-tions in specific cells initially, but during evolution expand their functionality to more general biological roles in multiple cell types. All functional annotations of non-coding RNAs generated by our analysis are provided to the community through ZENBU-Reports, a scientific visualization system for genome-wide data.Next, we focus our attention to understanding the mechanism of regula-tion in the cell nucleus. In a collaborative effort with other RIKEN teams, we are currently developing experimental methods to visualize the 3D structure of chromatin in the nucleus using electron microscopy and to identify specific regulatory DNA sites and RNA molecules in these images.Figure: Example of the functional annotation generated for non-coding RNA ENSG00000272462, including associ-ated protein-coding genes, their expression correlation with the non-coding RNA and gene ontology categories assigned to this non-coding RNA in each cell type.Recent Major PublicationsRamilowski JA, Yip CW, Agrawal S, Chang JC, Ciani Y, Kulakovskiy IV, Mendez M, Ooi JLC, Ouyang JF, Parkinson N, Petri A, Roos L, Severin J, Yasuzawa K, Abugessaisa I, Akalin A, Antonov IV, Arner E, Bonetti A, Bono H, Borsari B, Brombacher F, Cameron CJ, Cannistraci CV, Cardenas R, Cardon M, Chang H, Dostie J, Ducoli L, Favorov A, Fort A, Garrido D, Gil N, Gimenez J, Guler R, Handoko L, Harshbarger J, Hasegawa A, Hasegawa Y, Hashimoto K, Hayatsu N, Heutink P, Hirose T, Imada EL, Itoh M, Kacz-kowski B, Kanhere A, ..., De Hoon M, Shin JW, Carninci P. Functional annotation of human long noncoding RNAs via molecular phenotyping. Genome Res 30, 1060-1072 (2020)Alam T, Agrawal S, Severin J, Young RS, Andersson R, Arner E, Hasegawa A, Lizio M, Ramilowski JA, Abuges-saisa I, Ishizu Y, Noma S, Tarui H, Taylor MS, Lassmann T, Itoh M, Kasukawa T, Kawaji H, Marchionni L, Sheng G, Forrest ARR, Khachigian LM, Hayashizaki Y, Carninci P, De Hoon MJL. Comparative transcriptomics of primary cells in vertebrates. Genome Res 30, 951-961 (2020)Bonetti A, Agostini F, Suzuki AM, Hashimoto K, Pascarel-la G, Gimenez J, Roos L, Nash AJ, Ghilotti M, Cameron CJF, Valentine M, Medvedeva YA, Noguchi S, Agirre E, Kashi K, Samudyata, Luginbühl J, Cazzoli R, Agrawal S, Luscombe NM, Blanchette M, Kasukawa T, De Hoon M, Arner E, Lenhard B, Plessy C, Castelo-Branco G, Orlando V, Carninci P. RADICL-seq identifies general and cell type-specific principles of genome-wide RNA-chromatin interactions. Nat Commun 11, 1018 (2020)Invited presentationsAgrawal S. “The biological role of long noncoding RNAs in human cells inferred from chromatin conformation data” The ENCODE Research Applications and Users Meeting (Barcelona, Spain) October 2020De Hoon M. “FANTOM: Functional annotation of the mammalian genome” Genomics Winter School, Future Biotech Winter Retreat 2020 (Novosibirsk, Russia) Febru-ary 2020Laboratory for Applied Computational GenomicsTeam Leader: Michiel de Hoon
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