William James Greenleaf

The paper introduces Spear-ATAC, a high-throughput scATAC-seq protocol that identifies regulatory networks in cancer by analyzing chromatin accessibility and sgRNA spacer sequences from thousands of cells.

This study examines the 3D genome organization of dinoflagellates, finding that transcription-induced supercoiling drives domain-scale structure without chromatin loops.

The paper introduces a method to profile off-target specificity of CRISPR enzymes using ssDNA mapping, applicable to both catalytically dead and active Cas9 variants.

The paper uses single-cell data to show a continuum of cell state and composition changes from polyps to colorectal cancer, identifying stem-like cells and regulatory markers.

ArchR, an HDF5-backed R suite for end-to-end scATAC-seq analysis, outpaces SnapATAC and Signac and processes over 1.2 million simulated cells within 8 h on a laptop.

The paper uses single-cell epigenomic data to identify functional SNPs associated with Alzheimer's and Parkinson's disease, revealing novel gene-disease associations and regulatory mechanisms.

This study profiles single-nucleus transcriptomes of adult mouse spinal motor neurons to identify transcriptional subtypes and their functional roles.

This paper introduces SMAC-seq, a method for long-range chromatin accessibility mapping in eukaryotes, and demonstrates its application in yeast.

A crowdsourced RNA design approach discovers efficient, reversible molecular sensors that couple small molecule inputs to protein binding and fluorogenic outputs.

The paper maps stimulation-responsive chromatin changes in immune cells and identifies variants linked to autoimmunity.

The paper identifies off-target effects in CRISPR-Cas9 screens for non-coding elements and shows that strict filtering with specificity scores improves the identification of essential regulatory regions.

The paper uses scATAC-seq to analyze chromatin accessibility in immune cell development and tumor microenvironments, identifying regulatory elements and trajectories associated with cell differentiation and therapy response.

This paper develops a single-cell multi-omic framework to identify malignant regulatory signatures in mixed phenotype acute leukemia by analyzing transcriptomic and epigenetic data.

The paper analyzes cell cycle dynamics in human pluripotent stem cells primed for differentiation using RNA-sequencing and identifies PI3K signaling's role in early differentiation states.

The paper demonstrates a high-throughput platform for protein function assays using a DNA sequencing chip, quantifying antibody binding and enzyme activity with high throughput.

Perturb-ATAC combines CRISPR perturbations with single-cell ATAC-seq to identify gene regulatory networks in human cells.

The paper develops a PCA-based method to improve genetic interaction detection in CRISPR screens and identifies co-functional gene pairs that refine cancer cell network understanding.

The paper introduces Pi-ATAC, a method combining single-cell chromatin and proteomic profiling, revealing hypoxia's role in shaping the regulome in tumor cells.

This study identifies factors that determine Satb1 binding-site selectivity, showing its preference for nucleosome-dense regions and its mechanosensitive interactions with DNA.

The paper develops a high-throughput single-cell ATAC-seq method and applies it to cluster PBMCs by hematopoietic cell type.

This study identifies the Gatad2a-Chd4-Mbd3 subcomplex of the NuRD complex as a key inhibitor of naive pluripotency, showing that its disruption enables deterministic reprogramming of somatic cells to iPSCs.

This paper introduces scABC, an R package for unsupervised clustering of scATAC-seq data to classify cell types based on open chromatin regions.

MAVRIC is a nonparametric method that quantifies variance explained by covariates and performs differential analysis on various genomics and epigenomics data types.

This paper introduces ChAR-seq, a method to map RNA-to-DNA contacts genome-wide, identifying chromatin-bound RNA targets such as nascent transcripts and trans-associated RNAs.

This study shows that the INO80 chromatin-remodelling complex coordinates metabolic homeostasis with cell division in S. cerevisiae by regulating periodic gene expression.

This study uses ATAC-seq in C. elegans to identify dynamic chromatin accessibility changes, revealing novel enhancers and a regulatory factor involved in development.

This paper uses HiChIP to map enhancer-promoter interactions in primary human cells, linking disease-associated DNA variants to their target genes.

This paper maps high-resolution epigenetic and biosynthetic changes during reprogramming of fibroblasts to iPSCs, identifying two gene modules regulated by different mechanisms.

Omni-ATAC improves ATAC-seq by reducing background noise and enabling analysis of frozen tissues, revealing disease-associated DNA element activities in human brain structures.

chromVAR analyzes sparse scATAC-seq data to estimate motif-associated accessibility changes and cluster profiles while controlling technical biases.