Takeya Kasukawa

The paper identifies repeat element-anchored enhancer-promoter interactions (REEPIs) in hormone-resistant breast cancer and links them to transcriptional adaptation and regulatory reprogramming.

The paper introduces nucCAGE and PRIME to identify active cis-regulatory elements with high sensitivity and applies them to create a cell-type-resolved CRE atlas.

The paper maps RNA-chromatin interactions in human prefrontal cortex, revealing co-regulatory changes linked to brain evolution and disease pathways.

The paper identifies new gene products and transcript isoforms in macrophage differentiation and activation, revealing how alternative promoters influence innate immune functions.

The paper integrates enhancer-promoter interactions and RNA-DNA contacts to show RNA's role in modulating cis-regulatory networks during neural differentiation.

The paper develops a machine learning method to identify cis-regulatory element profiles and their sequence features during neuronal differentiation using single-cell ATAC-seq and RNA-seq data.

The paper identifies trans-contacting intronic RNAs (TIRs) in neuronal cells that form nuclear scaffolds called introsomes, influencing 3D genome organization and gene expression.

This study maps transcription start sites and active enhancers in Galleria mellonella larvae during fungal infection and treatment using LQ-ssCAGE.

The paper identifies 3UTR-derived capped RNAs, showing they are abundant and originate from AGO2-mediated cleavage at G-quadruplexes, with implications for APP protein regulation.

This paper introduces CFC-seq and SALA to sequence non-poly(A) RNAs, identifies 39,425 novel transcriptional units, and reveals a genomic code governing enhancer RNA fate based on promoter architecture.

The paper evaluates the impact of different Cell Ranger versions on single-cell gene expression data, finding significant variations in cell barcode processing, gene expression, and clustering results.

The paper constructs a single-cell atlas of transcribed cis-regulatory elements in the human genome, revealing gene regulation patterns and trait-gene relationships across cell populations.

The paper performs knockdown of 200 lncRNAs in human iPS cells, identifies 36 with growth inhibition, and finds molecular phenotypes in 29.3% of cases, with higher agreement in molecular than cell growth phenotypes across cell types.

The paper develops a functional annotation workflow for insect transcriptomes, improving annotation of both protein and ncRNA sequences and integrating expression data, applied to stick insects and silkworms.

The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.

DECCODE identifies small molecules that enhance cell reprogramming and conversion using transcriptional data and drug profiles.

The paper identifies cis-interacting lncRNAs and their targets using RNA-chromatin and Hi-C data across 18 human cell types.

The paper uses single-cell RNA sequencing and C1 CAGE to identify distinct phases of pluripotency during the naive-to-primed transition in mice.

The paper presents FC-R2, an expanded transcriptome atlas of over 109,000 genes, including lncRNAs, and demonstrates its utility in analyzing gene expression across normal and diseased human samples.

The paper evaluates mapping strategies for CAGE reads to determine 5'-end sequences of mRNAs and long-noncoding RNAs, finding that strategy choice affects alignment accuracy and biological interpretation.

RADICL-seq maps genome-wide RNA-chromatin interactions in intact nuclei, revealing general and cell type-specific patterns of transcript occupancy and the role of transcription in chromatin structure.

The paper shows that pluripotent stem cells undergo a mesenchymal-epithelial transition (MET) before losing pluripotency, which is distinct from the gastrulation EMT and regulated by integrin-mediated cell-matrix interactions.

The paper introduces SkewC, a method to identify poor quality cells in scRNA-seq by analyzing gene coverage skewness, and validates it across 37,993 cells from 15 protocols.

C1 CAGE detects transcription start sites and enhancer activity in lung cancer cells, revealing subpopulations with distinct responses to TGF-β and enhancer RNA dynamics.

The paper enhances the FANTOM5 expression atlas by associating gene-orphan promoter regions with their transcripts using CAGEscan.

The paper generates a single-cell RNA-seq dataset of HeLa cells labeled with Fucci reporters and provides an open workflow for data processing and quality control.