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Volume 50 Issue 4
Apr.  2023
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Deciphering the chromatin spatial organization landscapes during BMMSC differentiation

doi: 10.1016/j.jgg.2023.01.009
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We would like to acknowledge the assistance of Prof. Gang Cao (Huazhong Agricultural University) and his colleagues for their advice regarding the analysis of DLO Hi-C data. We would like to thank Chengling Liu and Leilei Zhan (Medical Research Center, Wuhan GeneCreate Biological Engineering Co., Ltd.) for their assistance with sequenced data analysis. We sincerely thank Ms. Jin Liu for her contribution to themanuscript. This work was supported in part by the National Natural Science Foundation of China, grant no. 31960136, and the Yunnan health training project for high-level talents. Yunnan Key Laboratory of Innovative Application of Traditional Chinese Medicine, grant no. 202105AG070032. Kunming University of Science and Technology &

the First People’s Hospital of Yunnan Province Joint Special Project on Medical Research, grant no. KUSTKH2022002Z, and 2021 Center of Yunnan Orthopedics and Sports Rehabilitation Clinical Medical Research, grant no. 2022YJZX-GK04, and the 2023 Project of Yunnan Basic Research, grant no. 202201AT070079 and 202201AT070285.

  • Received Date: 2022-11-03
  • Accepted Date: 2023-01-18
  • Rev Recd Date: 2023-01-18
  • Publish Date: 2023-04-30
  • The differentiation imbalance in bone marrow mesenchymal stem cells (BMMSCs) is critical for the development of bone density diseases as the population ages. BMMSCs are precursor cells for osteoblasts and adipocytes; however, the chromatin organization landscapes during BMMSC differentiation remain elusive. In this study, we systematically delineate the four-dimensional genome and dynamic epigenetic atlas of BMMSCs by RNA sequencing, assay for transposase-accessible chromatin sequencing, and high-throughput chromosome conformation capture. The structure analyses reveal 17.5% common and 28.5%–30% specific loops among BMMSCs, osteoblasts, and adipocytes. The subsequent correlation of genome-wide association studies and expression quantitative trait locus (eQTL) data with multi-omics analysis reveal 274 genes and 3634 single nucleotide polymorphisms (SNPs) associated with bone degeneration and osteoporosis (OP). We hypothesize that SNP mutations affect transcription factor (TF) binding sites, thereby affecting changes in gene expression. Furthermore, 26 motifs, 260 TFs, and 291 SNPs are identified to affect the eQTL. Among these genes, DAAM2, TIMP2, and TMEM241 are found to be essential for diseases such as bone degeneration and OP and may serve as potential drug targets.
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