Biology subjects

Ji, A. L.

Publications and source records attributed to Ji, A. L..

4 recordsLinked to original sources

bioRxiv2025

A single-cell spatial transcriptomic census of human skin anatomy

The skin is the largest human organ and a site of significant disease burden, yet its cellular and molecular organization across the body are largely undefined. Here, we construct a spatially-resolved single-cell atlas of 1.2 million cells from normal adult human skin to localize 45 cell types across 15 anatomic sites. We define principles of organ-wide cell composition, including axes of cell diversity and specialization, and distinguish site-enriched cell types. Each body site is comprised of 10 multicellular neighborhoods that define cell-cell communication. Notably, we identify a perivascular neighborhood enriched for immune-stromal crosstalk with features resembling a homeostatic immune niche similar to skin-associated lymphoid tissue. Finally, mapping these neighborhoods onto skin disease reveals pathogenic neighborhood disruptions, including pan-disease immune alterations in the perivascular neighborhood. We present a framework charting the skins multiscale spatial organization across a molecular to macroanatomic scale. This work advances our understanding of organ-wide skin cellular organization and communication, and its architectural disruption in disease. HIGHLIGHTSO_LIHuman skin MERFISH spatial atlas of 1.2 million cells from 114 samples and 22 donors C_LIO_LICellular diversity varies along a central to peripheral body site spatial axis C_LIO_LI10 multicellular neighborhoods define skin microanatomy and homeostatic interactions C_LIO_LIHuman skin diseases feature spatial and transcriptional neighborhood remodeling C_LI

genomics↗

bioRxiv2022

Visualizing somatic alterations in spatial transcriptomics data of skin cancer

Tools to visualize genetic alterations within tissues remain underdeveloped despite the growth of spatial transcriptomic technologies, which measure gene expression in different regions of tissues. Since genetic alterations can be detected in RNA-sequencing data, we explored the feasibility of observing somatic alterations in spatial transcriptomics data. Extracting genetic information from spatial transcriptomic data would illuminate the spatial distribution of clones and allow for correlations with regional changes in gene expression to support genotype-phenotype studies. Recent work demonstrates that copy number alterations can be inferred from spatial transcriptomics data1. Here, we describe new software to further enhance the inference of copy number from spatial transcriptomics data. Moreover, we demonstrate that single nucleotide variants are also detectable in spatial transcriptomic data. We applied these approaches to map the location of point mutations, copy number alterations, and allelic imbalances in spatial transcriptomic data of two cutaneous squamous cell carcinomas. We show that both tumors are dominated by a single clone of cells, suggesting that their regional variations in gene expression2 are likely driven by non-genetic factors. Furthermore, we observe mutant cells in histologically normal tissue surrounding one tumor, which were not discernible upon histopathologic evaluation. Finally, we detected mono-allelic expression of immunoglobulin heavy chains in B-cells, revealing clonal populations of plasma cells surrounding one tumor. In summary, we put forward solutions to add the genetic dimension to spatial transcriptomic datasets, augmenting the potential of this new technology.

genomics↗

bioRxiv2021

The spatial landscape of clonal somatic mutations in benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

genomics↗

bioRxiv2018

Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks

Here we present Perturb-ATAC, a method which combines multiplexed CRISPR interference or knockout with genome-wide chromatin accessibility profiling in single cells, based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by assay of transposase-accessible chromatin with sequencing (ATAC-seq). We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in [~]4,300 single cells, encompassing more than 63 unique genotype-phenotype relationships. Perturb-ATAC in human B lymphocytes uncovered regulators of chromatin accessibility, TF occupancy, and nucleosome positioning, and identified a hierarchical organization of TFs that govern B cell state, variation, and disease-associated cis-regulatory elements. Perturb-ATAC in primary human epidermal cells revealed three sequential modules of cis-elements that specify keratinocyte fate, orchestrated by the TFs JUNB, KLF4, ZNF750, CEBPA, and EHF. Combinatorial deletion of all pairs of these TFs uncovered their epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions. Thus, Perturb-ATAC is a powerful and general strategy to dissect gene regulatory networks in development and disease.\n\nHighlightsO_LIA new method for simultaneous measurement of CRISPR perturbations and chromatin state in single cells.\nC_LIO_LIPerturb-ATAC reveals regulatory factors that control cis-element accessibility, trans-factor occupancy, and nucleosome positioning.\nC_LIO_LIPerturb-ATAC reveals regulatory modules of coordinated trans-factor activity in B lymphoblasts.\nC_LIO_LIKeratinocyte differentiation is orchestrated by synergistic activities of co-binding TFs on cis-elements.\nC_LI

genomics↗