IMR Press / FBL / Volume 27 / Issue 10 / DOI: 10.31083/j.fbl2710295
Open Access Original Research
Imputation of Human Primary Osteoblast Single Cell RNA-Seq Data Identified Three Novel Osteoblastic Subtypes
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1 Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, 410081 Changsha, Hunan, China
2 Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA
3 School of Basic Medical Science, Central South University, 410008 Changsha, Hunan, China
4 Xiangya Nursing School, Central South University, 410013 Changsha, Hunan, China
5 Department of Orthopedics, Xiangya Hospital, Central South University, 410008 Changsha, Hunan, China
6 Department of Orthopedics and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, 410008 Changsha, Hunan, China
7 Center of Reproductive Health, System Biology and Data Information, Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, 410081 Changsha, Hunan, China
*Correspondence: (Li-Jun Tan); (Hong-Wen Deng)
These authors contributed equally.
Academic Editor: Elisa Belluzzi
Front. Biosci. (Landmark Ed) 2022, 27(10), 295;
Submitted: 25 May 2022 | Revised: 1 July 2022 | Accepted: 14 July 2022 | Published: 31 October 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: Recently, single-cell RNA sequencing (scRNA-seq) technology was increasingly used to study transcriptomics at a single-cell resolution, scRNA-seq analysis was complicated by the “dropout”, where the data only captures a small fraction of the transcriptome. This phenomenon can lead to the fact that the actual expressed transcript may not be detected. We previously performed osteoblast subtypes classification and dissection on freshly isolated human osteoblasts. Materials and Methods: Here, we used the scImpute method to impute the missing values of dropout genes from a scRNA-seq dataset generated on freshly isolated human osteoblasts. Results: Based on the imputed gene expression patterns, we discovered three new osteoblast subtypes. Specifically, these newfound osteoblast subtypes are osteoblast progenitors, and two undetermined osteoblasts. Osteoblast progenitors showed significantly high expression of proliferation related genes (FOS, JUN, JUNB and JUND). Analysis of each subtype showed that in addition to bone formation, these undetermined osteoblasts may involve osteoclast and adipocyte differentiation and have the potential function of regulate immune activation. Conclusions: Our findings provided a new perspective for studying the osteoblast heterogeneity and potential biological functions of these freshly isolated human osteoblasts at the single-cell level, which provides further insight into osteoblasts subtypes under various (pathological) physiological conditions.

single-cell RNA sequencing (scRNA-seq)
osteoblast heterogeneity
immune regulation
osteoclast differentiation
adipose differentiation
Fig. 1.
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