Masaru Koido

Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expression in unmeasured regions and tissues can enhance biologists' histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE, and confirmed its performance using the spatial-transcriptome profiles and immunohistochemi

Genome-wide association studies (GWAS) have identified genetic variations associated with adverse drug effects in pharmacogenomics (PGx) research. However, interpreting the biological implications of these associations remains a challenge. This review highlights 2 promising post-GWAS methods for PGx. First, we discuss the polygenic architecture of the PGx traits, especially for drug-induced liver injury. Experimental modelling using multiple donors' human primary hepatocytes and human liver orga

Mitochondria can be involved in regulating cellular stress response to hypoxia and tumor growth, but little is known about that mechanistic relationship. Here, we show that mitochondrial deficiency severely retards tumor xenograft growth with impairing hypoxic induction of HIF-1 transcriptional activity. Using mtDNA-deficient ρ0 cells, we found that HIF-1 pathway activation was comparable in slow-growing ρ0 xenografts and rapid-growing parental xenografts. Interestingly, we found that ex vivo ρ0

It has been difficult to elucidate the structure of gene regulatory networks under anticancer drug treatment. Here, we developed an algorithm to highlight the hub genes that play a major role in creating the upstream and downstream relationships within a given set of differentially expressed genes. The directionality of the relationships between genes was defined using information from comprehensive collections of transcriptome profiles after gene knockdown and overexpression. As expected, among

Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation qual