Masahide Seki

This study introduces TISCA2 and IncepTIS to map and predict stress-responsive translation initiation sites, revealing tissue-specific patterns and enabling engineered mRNA 5' leaders.

This study identifies calmodulin as a host factor that accelerates HSV-1 gene-expression tempo, increasing virus-producing cells and protecting mice from lethal infection.

The paper maps lineage trajectories and gene regulatory networks of cardiopharyngeal neural crest cells in mice, identifying a Hox-Meis-regulated transition associated with cardiac cushion development.

This study identifies PER proteins' role in regulating circadian alternative splicing in the liver using long-read RNA sequencing and mass spectrometry.

The paper shows that in mouse male germ cells, promoter chromatin states are shaped by H3K4me3 density and H3K27me3 dynamics, influencing gene expression during development.

This study shows that astrocytic C3 production exacerbates neuronal mitochondrial dysfunction and necroptosis in tauopathy models, and that anserine can mitigate these effects.

The paper identifies molecular mechanisms driving the divergence of adult neural stem cells and ependymal cells during embryogenesis through single-cell transcriptomic analysis.

The paper introduces iSCseq, a method that captures subcellular transcriptomic changes in living cells, revealing new osteoclast subsets and subcellular connections.

The paper uses multimodal analysis to reveal cardiac neural crest lineage diversity and gene regulatory networks involved in their differentiation.

The paper analyzes single-cell immune data from healthy individuals to reveal cell diversity and daily fluctuations, showing how immune responses vary between individuals and over time.

This study develops Dyrec-seq to measure transcription and RNA degradation rates simultaneously, revealing their relationship to gene function and response to stimuli.

The paper identifies a novel class of structural aberrations in lung cancers using long-read sequencing and shows their occurrence in vivo and in cancer-related genes.

MoMI-G is a web-based genome browser for visualizing structural variants and other genomic annotations, enabling intuitive exploration of large and nested variants.

The paper develops a computational method to detect microbial contaminants in NGS data and assesses their functional impact on host molecular pathways.