Elena Prigmore

This study creates a comprehensive spatial atlas of the human ovarian cortex, revealing molecular mechanisms of primordial follicle activation and follicle niche organization.

Human Developmental Cell Atlas integrates ~4.6 million cells/nuclei from 4-22 post-conception weeks into 454 refined cell types and maps 114 spatial niches across 6PCW whole-embryo sections.

This study creates a single-cell multiomics atlas of B cell development in prenatal and adult bone marrow and in vitro models, identifying novel cell subsets and molecular signatures.

This study uses single-cell transcriptomics to compare in vitro and in vivo chondrocyte differentiation, identifies off-target differentiation, and improves in vitro protocols by inhibiting FOXO1.

The paper creates a regulon atlas mapping TF activity across human cell types and uses it to link disease signatures to cell types and TFs, improving disease risk locus analysis.

The paper identifies a spatiotemporal cancer cell trajectory in glioblastoma that explains tumor heterogeneity across regions and subclones.

The paper examines the transcriptional evolution of myeloid leukaemia in Down syndrome by analyzing single-cell RNA sequencing data from patient samples and fetal tissues.

The paper maps the spatial organization of the human thymus across developmental stages using a multimodal atlas and identifies key cellular and molecular features of T cell development.

The paper constructs a high-resolution single-cell reference atlas of the human endometrium, identifying cell types, states, and signaling networks, and links them to endometriosis.

The paper identifies Th2-like malignant cells in CTCL supported by a B cell-rich microenvironment through single-cell and spatial transcriptomics analysis.

This study creates a spatially resolved single-cell multiomics atlas of human trophoblast differentiation in early pregnancy, revealing key regulatory programs and cell-cell communication events involved in EVT invasion and arterial transformation.

The paper identifies cancer cells from single cell transcriptomes by using allelic imbalances to accurately separate cancer from non-cancer cells.

This study creates a single-cell and single-nucleus transcriptomic atlas of human skeletal muscle ageing, revealing mechanisms in muscle stem cells, myofibers, and the microenvironment.

The paper identifies genetic and chemotherapeutic causes of germline hypermutation by analyzing genome-wide sequences of families with rare genetic diseases.

The paper identifies a distinct developmental state in KMT2A-rearranged infant B-cell acute lymphoblastic leukemia using single-cell transcriptome analysis.

This study maps the temporal and spatial dynamics of the human endometrium using single-cell and spatial reference maps, identifying key signaling pathways regulating cell fate in vivo and in vitro.

InDelible detects cryptic structural variants in exome sequencing data, improving diagnostic yield for developmental disorders by identifying variants missed by standard methods.

This study uses single-cell RNA-sequencing to analyze fetal bone marrow development and identifies disruptions in hematopoiesis in Down syndrome.

The paper identifies retrotransposition events in developmental disorders using exome sequencing data from the DDD study and shows their evolutionary constraints.

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

The paper estimates the contribution of recessive coding variants to developmental disorders using exome data from 7,448 families, finding low prevalence in European ancestry but higher in Pakistani ancestry.