Biology subjects

Lee, J. T. H.

Publications and source records attributed to Lee, J. T. H..

9 recordsLinked to original sources

bioRxiv2026

A multimodal interrogation of Broca's area in the pediatric and adult human brain

Language is a defining trait of our species, and disruptions in language acquisition can have profound consequences to the individuals affected. Uncovering the neurodevelopmental basis of this complex trait requires detailed molecular and cellular insights into the neocortical areas that support linguistic abilities. Here we performed joint gene expression and chromatin accessibility profiling at single-nucleus resolution (10x Genomics Single cell Multiome) and spatial transcriptomic profiling (Xenium high-plex in situ spatial transcriptomics) of Brocas area alongside adjacent motor cortical areas. We profiled individuals from different ancestries (European and African) and developmental stages (infancy, childhood, adolescence, and adulthood). We provide a high-resolution dissection of the cellular and molecular architecture of Brocas and motor cortical areas across early life stages and anchor the trajectories to the cellular states found in the adult human brain. We identify distinct area- and stage-specific cellular signatures, including a prominent role of glia populations and interneuron subtypes contributing to cytoarchitectonic specializations. Using longitudinal single cell spatial transcriptomic profiling, we orthogonally validate our consensus cell taxonomy and spatially resolve layer enrichment of neuronal and astrocyte subtypes that distinguish Brocas area and motor cortex. We also uncover cell type-specific molecular signatures that distinguish cell developmental trajectories in these cortical areas, including an early molecular code established by differential expression of cadherin genes that might contribute to area-specific intercellular communication. We also identify cell type-specific vulnerabilities to language- related neurodevelopmental and neuropsychiatric disorders, with selective susceptibility of particular somatostatin-positive interneuron subtypes to ASD/ADHD. Finally, evolutionary analysis of differentially accessible regions between Brocas area and motor cortex suggests that genetic mutations that might have contributed to the emergence of linguistic abilities accumulated over the course of million years following the divergence of human and chimpanzee lineages. Together, our study provides a comprehensive molecular, cellular and spatial definition of Brocas area and motor cortex, laying the groundwork for investigations into unique aspects of human cognition and related neurodevelopmental and neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

An integrated single cell and spatial omics atlas of human prenatal development

Single cell genomics has enabled analysis of human prenatal development at unprecedented resolution. However, most studies have relied on dissociated tissues during restricted windows of development, limiting insights into how spatially distributed networks of cells, and multicellular niches emerge and adapt to distinct organ microenvironments in situ. Moreover, existing human developmental atlases have not yet been harmonised, and we thus lack a comprehensive catalogue of known cell types in the developing human body. Here, we introduce the Human Developmental Cell Atlas (HDCA), a unified structural, cellular and molecular resource for prenatal human development. The HDCA integrates published and unpublished single cell/nucleus RNAseq atlases across prenatal organs, and includes a newly generated, spatially resolved, multimodal cell atlas of intact human embryos. Spanning 4-22 post conceptional weeks, capturing embryonic and early to mid fetal stages, the HDCA contains [~]4.6 million cells/nuclei which resolve into [~]450 cell types, explorable with a bespoke web portal. For a global overview of the human embryos multicellular communities, we applied unsupervised deep learning to our intact human embryo spatial data, charting 114 tissue niches that are structural and signalling hubs for the cellular interactions of the embryo. Guided by these niches, we profiled cellular networks over space and time, not examinable using single-organ atlases. In so doing, we revealed tissue-specific fibroblast patterning from previously undescribed mesenchyme progenitors, early diversification of organ-specific blood capillaries and lymphatic vasculature, emergence of neural crest cell fates, the formation of placode-and neural crest-derived peripheral sensory neurons, and how tissue niches guide peripheral neuron maturation and axonal migration. The HDCA thus serves as a comprehensive step towards a comprehensive understanding of human prenatal development, and a template towards unravelling the biology of congenital disorders.

developmental biology↗

bioRxiv2026

Federated single-cell QTL meta-analysis reveals novel disease mechanisms

Genetic effects on gene expression are often cell type-specific and obscured in bulk analyses. To resolve this context-dependent regulation, we performed a federated cis-eQTL meta-analysis across 12 PBMC datasets (2,032 individuals, 2.5 million cells). Across six immune cell types, we identified cis-eQTLs for 6,592 genes and fine-mapped 14,985 independent loci. Notably, the 42% of eQTLs that were undetected in a bulk eQTL study on 43,301 whole blood samples also showed stronger enrichment for disease GWAS loci. We further identified three genome-wide significant and 65 suggestive loci affecting the abundance of (rare) immune cell types and validated these using previously reported hematological GWAS and bulk-derived trans-eQTLs. Integrating single-cell cis-eQTLs with bulk trans-eQTLs enabled us to anchor 6,382 trans-eGenes (37.2% novel) to upstream regulators and reconstruct directed gene regulatory relationships. For example, a hemorrhoidal disease-associated variant showed a CD4+ T cell-specific cis-eQTL on BACH1 that colocalized with 45 immune and metabolic trans-eGenes. These results demonstrate the power of single-cell QTL meta-analysis in interpreting complex trait genetics.

genetics↗

bioRxiv2025

Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics

Metabolism supplies energy, building blocks, and signaling molecules vital for cell function and communication, but methods to directly measure it at single-cell and/or spatial resolutions remain technically challenging and inaccessible for most researchers. Single-cell and spatial transcriptomics offer high-throughput data alternatives with a rich ecosystem of computational tools. Here, we present scCellFie, a computational framework to infer metabolic activities from human and mouse transcriptomic data at single-cell and spatial resolution. Applied to [~]30 million cell profiles, we generated a comprehensive metabolic atlas across human organs, identifying organ- and cell-type-specific activities. In the endometrium, scCellFie reveals metabolic programs contributing to healthy tissue remodeling during the menstrual cycle, with temporal patterns replicated in data from in vitro cultures. We also uncover disease-associated metabolic alterations in endometriosis and endometrial carcinoma, linked to proinflammatory macrophages, and metabolite-mediated epithelial cell communication, respectively. Ultimately, scCellFie provides a scalable toolbox for extracting interpretable metabolic functionalities from transcriptomic data.

bioinformatics↗

bioRxiv2025

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

cancer biology↗

bioRxiv2025

A conserved differentiation program facilitates inhibitory neuron production in the developing mouse and human cerebellum

Understanding the molecular mechanisms driving lineage decisions and differentiation during development is challenging in complex systems with a diverse progenitor pool, such as the mammalian cerebellum. Importantly, how different transcription factors cooperate to generate neural diversity and the gene regulatory mechanisms that drive neuron production, especially during the late stages of cerebellar development are poorly understood. Here, we used single cell RNA-sequencing (scRNA-seq) to investigate the developmental trajectories of Nestin-expressing progenitors (NEPs) in the neonatal mouse cerebellum. We identified FOXO1 as a key regulator of NEP-to-inhibitory neuron differentiation, acting directly downstream of ASCL1. Genome occupancy and functional experiments using primary NEPs showed that both ASCL1 and FOXO1 regulate neurogenesis genes during differentiation while independently regulating proliferation and survival, respectively. Furthermore, we demonstrated that WNT signalling promotes the transition from an ASCL1+ to a FOXO1+ cellular state. Finally, we showed that the role of WNT signalling in promoting neuron production via FOXO1 is conserved in primary human NEPs. By resolving how cerebellar interneurons differentiate, our findings could have implications for cerebellar disorders such as spinocerebellar ataxia, where cerebellar interneurons are overproduced.

developmental biology↗

bioRxiv2023

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.

pathology↗

bioRxiv2023

Mining alternative splicing patterns in scRNA-seq data using scASfind

Single-cell RNA-seq is widely used for transcriptome profiling, but most analyses have focused on gene-level events, with much less attention devoted to alternative splicing. Here, we present scASfind, a novel computational method to allow for quantitative analysis of cell type-specific splicing events. scASfind utilizes an efficient data structure to store the percent spliced-in value for each splicing event. This makes it possible to exhaustively search for patterns among all differential splicing events, allowing us to identify marker events, mutually exclusive events, and large blocks of exons that are specific to one or more cell types. These methods allow researchers to compare cells based on isoforms rather than genes, thereby enabling more nuanced characterization of cell types and states. We demonstrate the advantages of scASfind on two mouse and one human datasets, identifying differences across the several key genes that cannot be detected using gene expression alone.

bioinformatics↗

bioRxiv2019

Fast searches of large collections of single cell data using scfind

Single cell technologies have made it possible to profile millions of cells, but for these resources to be useful they must be easy to query and access. To facilitate interactive and intuitive access to single cell data we have developed scfind, a search engine for cell atlases. Using transcriptome data from mouse cell atlases we show how scfind can be used to evaluate marker genes, to perform in silico gating, and to identify both cell-type specific and housekeeping genes. Moreover, we have developed a subquery optimization routine to ensure that long and complex queries return meaningful results. To make scfind more user friendly and accessible, we use indices of PubMed abstracts and techniques from natural language processing to allow for arbitrary queries. Finally, we show how scfind can be used for multi-omics analyses by combining single-cell ATAC-seq data with transcriptome data.

bioinformatics↗