Our mission is to understand the origins and functions of non-coding transcription in human genome, with a focus on long non-coding RNAs and enhancer RNAs. We have been at the forefront of annotating these non-coding RNAs using large-scale in-house transcriptomic datasets (e.g. FANTOM consortium). We also integrate our in-house datasets with public epigenomic and genetic (e.g. GWAS and eQTL) datasets to gain insights into the roles of non-coding RNAs in human diseases. Our team is primarily composed of bioinformatic analysts specialized in transcriptomics, but we are working closely with experimental biologists to provide bioinformatics support on technology development (e.g. single-cell transcriptomics), as well as participating other collaborative projects (e.g. Human Cell Atlas). Our research focuses on the following areas: 1) Integrating genetic data with population-scale single-cell and bulk transcriptomic/epigenomic data (i.e. GWAS and eQTL) to gain insights into human diseases, in particular autoimmune diseases; 2) In vitro modeling neurodegeneration using patient derived iPSC at population-scale; 3) Cohort scale single-cell profiling of tumor transcriptome and somatic mutation;
The successful candidate will be responsible for analyzing the population-scale single-cell transcriptomic and epigenomic datasets generated from neurodegeneration, autoimmune diseases or cancer cohorts. These analyses include but not limit to unsupervised cell clustering, cell-types annotation, single-cell eQTL, cell-type specific enrichment of GWAS signal, gene co-expression network and beyond. These projects highlight the integration of genetic data with single-cell RNA-Seq/ATAC-Seq data to identify active functional non-coding elements across cell-types, aiming 1) to elucidate the roles of non-coding elements in diseases, and 2) to facilitate the interpretation of causality of non-coding variants in human disease predisposition. The candidate is expected to apply the most cutting-edge computational and statistical methods for single-cell omics and genetics to construct personalized (based on genetic variations) gene regulatory networks, which would ultimately provide guidance for precision medicine in the future. Candidates with interests in single-cell omics, human genetics, neurodegeneration and autoimmune diseases are encouraged to apply.
The primary affiliation of this position is Hiroshima University, Graduate School of Integrated Sciences for Life. The successful candidate will be also affiliated to RIKEN Center for Integrative Medical Sciences, Laboratory for Genome Information Analysis, as a visiting researcher. Regular travels between Hiroshima University in Higashi-Hiroshima and RIKEN at Yokohama are expected.