Julia A. Belk

The paper isolates and characterizes two postnatal human neural stem cell subsets, showing their fate biases and decline in frequency over time.

This study uses somatic mutations to track marrow-derived cell infiltration into the human brain, finding widespread microglia replenishment and a protective link between clonal hematopoiesis and Alzheimer's disease.

A genome-wide plasmid screen, Retain-seq, identifies thousands of CpG-rich promoter-like human elements that tether episomes to mitotic chromosomes, shape ecDNA structure, and lose function when methylated.

The paper identifies cis-regulatory elements and transcription factors controlling FOXP3 expression in human Tregs and Tconvs, revealing mechanisms that restrict FOXP3 to Tregs in mice.

The paper shows that ecDNA-borne PVT1 fusions stabilize oncogenic mRNAs by interacting with SRSF1, enhancing RNA stability and supporting MYC dependency in cancer.

This study identifies a STAG2-PAXIP1/PAGR1 tumor-suppressive axis in lung cancer by showing their combined role in suppressing oncogenic KRAS-driven tumorigenesis.

This study introduces CRISPRai, a bidirectional epigenetic editing system, to investigate gene regulation hierarchies and interactions in T cells and hematopoietic lineage transcription factors.

This study shows that Xist ribonucleoprotein complexes drive sex-biased autoimmunity in males, leading to autoimmune pathology and reprogramming of immune cells to resemble female patterns.

The paper develops PACER to infer clonal expansion rates from single timepoint data and identifies TCL1A activation as a mediator of clonal hematopoiesis fitness.

The paper uses CRISPR screens to identify mucins as key host factors that restrict SARS-CoV-2 infection in human lung cells.

This paper introduces ENTER-seq, a method using engineered lentiviral particles to systematically discover receptor-ligand interactions and map TCR specificity in single cells.

TCR-BERT uses self-supervised transfer learning on unlabeled T-cell receptor sequences to learn representations that improve antigen-binding prediction, specificity clustering, and computational TCR sequence design.