William James Greenleaf

This study shows that chromatin remodeling in engram neurons during memory storage alters their transcriptional responses to future experiences, dampening further information storage.

The paper investigates chromatin state transitions during epigenetic memory formation by analyzing single-cell gene expression and chromatin structure changes after repressor recruitment and release.

This study identifies the epigenetic signature and key transcription factors regulating human antigen-specific Tr1 cells, revealing their unique biology and potential for therapeutic applications.

The paper introduces and benchmarks two droplet-based single-nucleus assays for chromatin accessibility and gene expression, showing they are cost-effective and produce high-quality data.

The paper tests enhancer-promoter compatibility using improved assays, finding that promoter responsiveness, not enhancer rank order, determines activation sensitivity.

TwinC predicts trans-chromosomal DNA contacts using DNA sequence and provides insights into their functional mechanisms.

This study develops lipid nanoparticles (LNPs) for spleen-targeted RNA delivery without altering charge, showing improved splenic accumulation and distinct transcriptomic effects compared to conventional LNPs.

This study identifies how genetic and environmental factors shape the human immune cell epigenome through differential methylation and chromatin accessibility changes.

This study links in vitro transcription factor affinities to in vivo single-molecule chromatin states using thermodynamic models and experimental data for KLF1.

This study shows that many premalignant colorectal polyps contain multiple genetic lineages, indicating polyclonal origins rather than single-cell expansion.

The paper designs compact RNA sensors for complex functions of multiple inputs using crowdsourced designs and an algorithm, achieving applications like tuberculosis diagnosis.

The paper uses a single-cell multi-omic atlas and deep learning to identify cis-regulatory elements and genetic drivers of heart development and disease.

The paper identifies age-related microbiome metabolites that alter RNA splicing and chromatin accessibility in the mouse brain using metabolomics, transcriptomic, and multi-omic approaches.

The paper identifies HBO1 and MLL1 complexes as key tumor suppressors in lung cancer using in vivo functional screens of epigenetic regulators.

This paper develops beCasKAS, a method to directly detect off-target base editor activity in primary cells, revealing distinct off-target profiles and enabling risk stratification of edits.

The paper presents a single cell multiomic atlas of human lung development, identifying regulatory elements and gene programs, and linking genetic variants to pulmonary function.

The paper analyzes the epigenomic changes in innate immune cells after influenza virus infection and finds coordinated rewiring of the epigenetic landscape.

The paper presents a multimodal epigenome atlas of human immune cells exposed to viral and chemical agents, revealing epigenetic changes in transcription factor binding sites and cytokine networks.

The paper identifies a disease-associated motor neuron state in a mouse ALS model that precedes cell death and links it to human ALS genetic risk factors.

This study shows that cancer cell phagocytosis by macrophages induces an anti-inflammatory gene regulatory program, promoting immunosuppression and tumor growth.

The paper develops RoboATAC, an automated ATAC-seq method, to study how TF dosage affects chromatin accessibility and gene expression, finding that DNA sequence predicts dosage sensitivity and nucleosome positioning patterns vary by TF.

The paper introduces a high-resolution single-molecule chromatin accessibility mapping method to quantify transcription factor occupancy and co-accessibility in human cell lines.

The paper presents a single-cell multi-omics atlas of human development and uses deep learning to analyze regulatory DNA motifs and their impact on chromatin accessibility and gene expression.

The paper updates and reevaluates evidence for nuclear transcription factor occupancy over the mitochondrial genome using expanded ChIP-seq data and deep learning models.

BPCells enables scalable single-cell RNA-seq and ATAC-seq analysis on modest hardware by using disk-backed streaming algorithms and compressed formats.

The paper introduces KAS-ATAC, a method combining KAS-seq and ATAC-seq to simultaneously measure chromatin accessibility and single-stranded DNA, revealing insights into transcription and regulatory elements in the human genome.

Learning and removing Tn5/DNase-I sequence bias lets a small base-resolution CNN (ChromBPNet) recover TF motifs and footprints from accessibility data and rival Enformer at predicting chromatin QTL effects.

The paper uses spatial CODEX experiments to show early colorectal cancer microenvironment changes in FAP, including CAFs, immune suppression, and beta-catenin nuclear translocation.

This paper identifies transcription-replication conflict as a vulnerability in ecDNA-containing cancers and demonstrates that CHK1 inhibition selectively kills these tumors.