Our lab aims to determine epigenomic and transcriptomic changes in a 17comprehensive manner in various models by applying the most advanced available technologies, such as single-cell genomics. Such information will be utilized to gain insights into various biological questions at the molecular level.Construction of a Mouse Ageing Atlas with single-cell genomicsInflammation is a major hallmark of ageing. To determine whether the pres-ence of the microbiota is contributing to the increase in inflammation that is observed with age (termed ‘inflammaging’), we are generating single-cell ge-nomic (5’ scRNA-seq and scATAC-seq) datasets of various tissues from both SPF and germ-free mice at various ages, as well as lipidomics (in collaboration with the Arita lab, IMS), metabolomics and microbiome (in collaboration with the Ohno lab, IMS). Such a rich collection of multi-omics datasets will likely provide us with an unbiased insight at many different levels, including the ef-fect of the microbiome, into the complex biological phenomena of ageing. Our preliminary analysis of the completed datasets from 8 different tissues captures increased inflammation signatures with old age at the transcriptomic level, which are in fact reduced in the germ-free mice that completely lack microbes. This indeed suggests that the microbiota contributes to inflammaging.Development of UniverSC: a flexible cross-platform single-cell data processing pipelineSingle-cell RNA-sequencing analysis to quantify RNA molecules in indi-vidual cells has become popular as it can obtain a large amount of information from each experiment. We have developed UniverSC (https://github.com/minoda-lab/universc), a universal single-cell RNA-seq data processing tool that supports any UMI-based platform. Our command-line tool enables consistent and comprehensive integration, comparison and evaluation across data gen-erated from a wide range of platforms. In an effort to democratize single-cell analysis, UniverSC is also available through Docker as well as GUI (graphical user interface).Figure: Construction of a Mouse Ageing Atlas with single-cell genomics and UniverSC: a flex-ible cross-platform single-cell data processing pipelineLeft: 5’ scRNA-seq data from 8 mouse tissues obtained from young (2 months) and old (19 months) SPF (specific pathogen-free) or GF (germ-free) mice are combined and displayed.Right: The pipeline and the GUI for UniverSC are shown.Recent Major PublicationsKelly ST, Battenberg K, Hetherington NA, Hayashi M, Minoda A. UniverSC: a flexible cross-platform single-cell data processing pipeline. BioRxiv doi: https://doi.org/10.1101/2021.01.19.427209 (2021)Augusto RC, Rey O, Cosseau C, Chaparro C, Vidal-Dupiol J, Allienne JF, Duval D, Pinaud S, Tönges S, Andriantsoa R, Luquet E, Aubret F, Dia Sow M, David P, Thomson V, Joly D, Gomes Lima M, Federico D, Danchin E, Minoda A, Grunau C. A simple ATAC-seq protocol for population epigenetics. Wellcome Open Res 5, 121 (2021)Ramilowski 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)Invited presentationsMinoda A. “Determining the state of type 2 innate im-mune response in the lung in old age” Japanese Society for Immunology (Online) December 2021Minoda A. “Mouse Ageing Promoter Atlas: effect of the microbiota on ageing” Human Cell Atlas Asia (Online) November 2021Minoda A. “Single cell RNA-seq analysis towards un-derstanding ageing” The 57th Annual Meeting of Liver Cancer Study Group of Japan (Online) July 2021Minoda A. “Tissue ageing dissected by single cell RNA-seq” Okinawa Institute of Science and Technology Graduate University (Okinawa, Japan) March 2021Minoda A. “Tissue ageing dissected by single cell RNA-seq” Biology Departmental Seminar, University of Ala-bama at Birmingham (Online) February 2021Laboratory for Cellular EpigenomicsTeam Leader: Aki Minoda
元のページ ../index.html#23