Evidence map›Paper›PMID 36793138›Full record

ArticleHuman genomics2023

Regulon active landscape reveals cell development and functional state changes of human primary osteoblasts in vivo.

Shengran Wang, Yun Gong, Zun Wang, Xianghe Meng, Zhe Luo, Christopher J Papasian, Jonathan Greenbaum, Yisu Li, Qilan Liang, Yiping Chen and 10 more

Open access · goldAbstract read
In one paragraph

Article in Human genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 3 institutions in 2 countries.

Shengran WangCenter for System Biology, Data Sciences and Reproductive Health, School of Basic Medical Science, Central South University, Changsha, 410008, China.
Yun GongTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, 1440 Canal St., Suite 1610, New Orleans, LA, 70112, USA.
Zun WangXiangya School of Nursing, Central South University, Changsha, 410013, China.
Xianghe MengCenter for System Biology, Data Sciences and Reproductive Health, School of Basic Medical Science, Central South University, Changsha, 410008, China.
Zhe LuoTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, 1440 Canal St., Suite 1610, New Orleans, LA, 70112, USA.
Christopher J PapasianDepartment of Biomedical Sciences, School of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
Jonathan GreenbaumTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, 1440 Canal St., Suite 1610, New Orleans, LA, 70112, USA.
Yisu LiDepartment of Cell and Molecular Biology, Tulane University School of Science and Engineering, Tulane University, New Orleans, LA, 70112, USA.
Qilan LiangDepartment of Cell and Molecular Biology, Tulane University School of Science and Engineering, Tulane University, New Orleans, LA, 70112, USA.
Yiping ChenDepartment of Cell and Molecular Biology, Tulane University School of Science and Engineering, Tulane University, New Orleans, LA, 70112, USA.
Xiaohua LiLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Human Normal University, Changsha, 410081, China.
Qiu XiangCenter for System Biology, Data Sciences and Reproductive Health, School of Basic Medical Science, Central South University, Changsha, 410008, China.
Hiuxi ZhangLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Human Normal University, Changsha, 410081, China.
Ying LiuLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Human Normal University, Changsha, 410081, China.
Liang ChengDepartment of Orthopaedics and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
Yihe HuDepartment of Orthopedics, Xiangya Hospital, Central South University, Changsha, 410008, China.
Lijun TanLaboratory of Molecular and Statistical Genetics, College of Life Sciences, Human Normal University, Changsha, 410081, China.
Hui ShenTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, 1440 Canal St., Suite 1610, New Orleans, LA, 70112, USA.
Hongmei XiaoInstitute of Reproductive and Stem Cell Engineering, Center of Reproductive Health, School of Basic Medical Science, Central South University, 172 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan Province, People's Republic of China. hmxiao@csu.edu.cn.
Hongwen DengTulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, 1440 Canal St., Suite 1610, New Orleans, LA, 70112, USA. hdeng2@tulane.edu.
Tulane University · USCentral South University · CNUniversity of Missouri–Kansas City · US

Funding

Characterization and functional assessment of a novel population of Wnt/beta-catenin driven adopocytes.R01DK128907 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI CHEN, YIPING, WANG, QIONG ANNABEL · 2021 to 2024
$2.0M
NIDDK NIH HHS R01 DK128907
6 · The paper itself

Abstract

backgroundWhile transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro.

resultsWe identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts.

conclusionsThis is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

Indexed as

OsteoblastsRegulonCell DifferentiationGene Expression RegulationHumansBone metabolismCell-specific networkOsteoblastSingle-cell RNA sequencingTranscription factor

Identifiers

PMID36793138
PMCPMC9930257
OpenAlexW4321004353

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.