Harukazu Suzuki

xcore: an R package for inference of gene expression regulators

xcore is an R package that models transcription factor activity using ChIP-seq signatures and gene expression data, demonstrating improved biological relevance in case studies.

Antisense oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types

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.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

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.

Master Transcription Factors Regulate the DNA Methylation Landscape During Hepatocyte Differentiation

The paper identifies transcription factors that regulate DNA methylation dynamics during hepatocyte differentiation, revealing GATA6's role in DNA demethylation and chromatin activation.

Recounting the FANTOM Cage Associated Transcriptome

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.

Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

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.

Evidence of transcription at polyT short tandem repeats

The paper investigates transcription initiation at polyT short tandem repeats (STRs) using CAGE data and develops a deep learning model to predict STR-associated transcription with high accuracy.

Combinatorial perturbation analysis reveals divergent regulations of mesenchymal genes during epithelial-to-mesenchymal transition

The paper uses combinatorial perturbations to study EMT gene regulation, finding that mesenchymal genes show diverse dependencies on TGF-β and ZEB1, with functional differences in motility and cancer survival.

Transcriptionally induced enhancers in the macrophage immune response to Mycobacterium tuberculosis infection

The paper identifies transcriptionally induced enhancers in macrophages infected with Mycobacterium tuberculosis and links them to immune gene activation.

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

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.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

The paper identifies shared expression patterns of genetic variants across tissues and cell types, enabling fine mapping of disease-associated variants and revealing key cell types involved in disease pathogenesis.

Genome-wide profiling of transcribed enhancers during macrophage activation

The paper identifies transcribed enhancers in mouse macrophages during activation and shows their association with gene expression and inflammation-related transcription factors.

Single-cell transcriptomes of fluorescent, ubiquitination-based cell cycle indicator cells

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.

IRNdb: The database of immunologically relevant non-coding RNAs.

IRNdb is a database of immunologically relevant non-coding RNAs that integrates experimentally supported interactions and annotations to aid in studying ncRNA regulation in the immune system.