An integrated single-cell atlas of the skeleton from development through adulthood

Abstract

The recent growth of single-cell transcriptomics has turned single-cell RNA sequencing (scRNA-seq) into a near-routine experiment. Breakthroughs in improving scalability have led to the creation of organism-wide transcriptomic datasets, aiming to comprehensively profile the cell types and states within an organism throughout its lifecycle. To date however, the skeleton remains a majorly underrepresented organ system in organism-wide atlases. Considering how the skeleton not only serves as the central framework of the vertebrate body but is also the home of the hematopoietic niche and a central player in major metabolic and homeostatic processes, this presents a major deficit in current reference atlas projects. To address this issue, we integrated seven separate scRNA-seq datasets containing skeletal cells and their developmental precursors, generating an atlas of over 800,000 cells. This skeletal cell atlas describes cells across the mesenchymal lineage from the induction of the limb field to adult bone, encompassing 50 different cell states. In addition, the original datasets were reannotated, enabling the discovery of novel, highly specific marker genes, some of which we have validated in vivo by whole-mount in situ hybridization. Furthermore, expanding the repertoire of available time points and cell types within a single dataset allowed for more complete analyses of cell-cell communication or in silico perturbation studies. Taken together, we present a missing piece in the current atlas mapping efforts, which will be of value to researchers in the fields of skeletal biology, hematopoiesis, metabolism and regenerative medicine.

Why Animal Experiments Are Still Indispensable in Bone Research: A Statement by the European Calcified Tissue Society

“…Computer models now allow the first predictions of loss and maybe gain of functions of genes on cellular differentiation patterns in bone biology, providing an excellent tool to decide whether a genetic animal experiment is likely to reveal a phenotype and thus a functional explanation of novel factors in bone growth and physiology. ( 66 ) However, credibility assessment requires the availability of high‐quality dedicated data that cannot be sourced sufficiently from the currently available in vitro models or human clinical studies. The goal can only be to use the best possible combination of methodology that involves scientific rigorousness and considers ethical awareness and restrictions to understand fundamental biology and develop advanced treatment options for bone diseases.…”

“…These data‐driven models allow insight into basic biology as well as clinical variation. One example is the development of the skeletal cell atlas ( 66 ) bringing together all available murine single‐cell RNA sequencing data sets into a comprehensive framework, making use of open‐source bioinformatics codes. This atlas provides a physiological blueprint of the limb development process and a platform to investigate in silico, for example, the effects of genetic mutations and knockouts.…”

A ligand-receptor interactome atlas of the zebrafish

“…Zebrafish single-cell RNAseq datasets are used to explore the developmental ligand-receptor interactome (Campbell et al, 2021; Herpelinck et al, 2022; Holler et al, 2021; Hu et al, 2022). However, a bottleneck in using such tools is in the dependence on orthologous mammalian ligand-receptor interactome data while ignoring zebrafish-specific data (Farnsworth et al, 2020; Farrell et al, 2018).…”

“…Zebrafish single-cell RNAseq datasets are used to explore the developmental ligand-receptor interactome [23][24][25]50 . However, a bottleneck in using such tools is in the dependence on incomplete orthologous mammalian ligand-receptor classifications and mammalian ligand-receptor interactome records 51,52 .…”

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas

“…To circumvent this, advances in scRNA-seq data analysis and integration [54][55][56][57] have led to the creation of so-called "atlases". Atlases have become an invaluable tool as they provide new insights beyond individual datasets [58][59][60][61][62] , such as description of cellular landscape in health and disease 60,61,[63][64][65][66][67][68][69] and comparison across animal or in vitro models and corresponding human datasets [70][71][72] . Whilst previous efforts have been made to compare the results of multiple islet scRNA-seq studies 27,47,73 , a comprehensive integrated atlas of mouse pancreatic islet cells across biological conditions and datasets with sufficient power to identify cell states is still missing.…”