Unknown

Dataset Information

0

Single-Cell RNA Sequencing of Calvarial and Long-Bone Endocortical Cells.


ABSTRACT: Single-cell RNA sequencing (scRNA-Seq) is emerging as a powerful technology to examine transcriptomes of individual cells. We determined whether scRNA-Seq could be used to detect the effect of environmental and pharmacologic perturbations on osteoblasts. We began with a commonly used in vitro system in which freshly isolated neonatal mouse calvarial cells are expanded and induced to produce a mineralized matrix. We used scRNA-Seq to compare the relative cell type abundances and the transcriptomes of freshly isolated cells to those that had been cultured for 12 days in vitro. We observed that the percentage of macrophage-like cells increased from 6% in freshly isolated calvarial cells to 34% in cultured cells. We also found that Bglap transcripts were abundant in freshly isolated osteoblasts but nearly undetectable in the cultured calvarial cells. Thus, scRNA-Seq revealed significant differences between heterogeneity of cells in vivo and in vitro. We next performed scRNA-Seq on freshly recovered long bone endocortical cells from mice that received either vehicle or sclerostin-neutralizing antibody for 1 week. We were unable to detect significant changes in bone anabolism-associated transcripts in immature and mature osteoblasts recovered from mice treated with sclerostin-neutralizing antibody; this might be a consequence of being underpowered to detect modest changes in gene expression, because only 7% of the sequenced endocortical cells were osteoblasts and a limited portion of their transcriptomes were sampled. We conclude that scRNA-Seq can detect changes in cell abundance, identity, and gene expression in skeletally derived cells. In order to detect modest changes in osteoblast gene expression at the single-cell level in the appendicular skeleton, larger numbers of osteoblasts from endocortical bone are required. © 2020 American Society for Bone and Mineral Research.

SUBMITTER: Ayturk UM 

PROVIDER: S-EPMC8265023 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC8134068 | biostudies-literature
| S-EPMC6323125 | biostudies-literature
| S-BSST603 | biostudies-other
| S-EPMC5810423 | biostudies-literature
| S-EPMC11328938 | biostudies-literature
| S-EPMC8421549 | biostudies-literature
| S-EPMC10178277 | biostudies-literature
| S-EPMC8613180 | biostudies-literature
| S-EPMC8579438 | biostudies-literature
| S-EPMC8762313 | biostudies-literature