Biology subjects

Lawrence, J. E. G.

Publications and source records attributed to Lawrence, J. E. G..

3 recordsLinked to original sources

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 The HDCA integrates published and unpublished single cell/nucleus RNAseq atlases across prenatal organs, and includes a newly generated, spatially resolved, multimodal cell atlas of intact human embryos.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↗

bioRxiv2023

Single cell transcriptomics reveals chondrocyte differentiation dynamics in vivo and in vitro

The consistent production of in vitro chondrocytes that faithfully recapitulate in vivo development would be of great benefit for musculoskeletal disease modelling and regenerative medicine. Current efforts are often limited by off-target differentiation, resulting in a heterogeneous product. Furthermore, the lack of comparison to human embryonic tissue, precludes detailed evaluation of in vitro cells. Here, we perform single-cell RNA sequencing of embryonic long bones dissected from first trimester hind limbs from a range of gestational ages. We combine this with publicly available data to form a detailed atlas of endochondral ossification, which we then use to evaluate a series of published in vitro chondrogenesis protocols, finding substantial variability in cell states produced by each. We apply single-nuclear RNA sequencing to one protocol to enable direct comparison between in vitro and in vivo, and perform trajectory alignment between the two to reveal differentiation dynamics at the single-cell level, shedding new light on off-target differentiation in vitro. Using this information, we inhibit the activity of FOXO1, a transcription factor predicted to be active in embryonic bone development and in chondrogenic cells in vitro, and increase chondrocyte transcripts in vitro. This study therefore presents a new framework for evaluating tissue engineering protocols, using single-cell data from human development to drive improvement and bring the prospect of true engineered cartilage closer to reality.

bioengineering↗

bioRxiv2023

WebAtlas pipeline for integrated single cell and spatial transcriptomic data

Single cell and spatial transcriptomics illuminate complementary features of tissues. However, online dissemination and exploration of integrated datasets is challenging due to the heterogeneity and scale of data. We introduce the WebAtlas pipeline for user-friendly sharing and interactive navigation of integrated datasets. WebAtlas unifies commonly used atlassing technologies into the cloud-optimised Zarr format and builds on Vitessce to enable remote data navigation. We showcase WebAtlas on the developing human lower limb to cross-query cell types and genes across single cell, sequencing- and imaging-based spatial transcriptomic data.

bioinformatics↗