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DOI 10.1186/s12864-017-4378-y

Медицинская библиотека · BMC genomics · 2017

Genes uniquely expressed in human growth plate chondrocytes uncover a distinct regulatory network.

Li Bing, Balasubramanian Karthika, Krakow Deborah, Cohn Daniel H

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Аннотация

BACKGROUND

Chondrogenesis is the earliest stage of skeletal development and is a highly dynamic process, integrating the activities and functions of transcription factors, cell signaling molecules and extracellular matrix proteins. The molecular mechanisms underlying chondrogenesis have been extensively studied and multiple key regulators of this process have been identified. However, a genome-wide overview of the gene regulatory network in chondrogenesis has not been achieved.

RESULTS

In this study, employing RNA sequencing, we identified 332 protein coding genes and 34 long non-coding RNA (lncRNA) genes that are highly selectively expressed in human fetal growth plate chondrocytes. Among the protein coding genes, 32 genes were associated with 62 distinct human skeletal disorders and 153 genes were associated with skeletal defects in knockout mice, confirming their essential roles in skeletal formation. These gene products formed a comprehensive physical interaction network and participated in multiple cellular processes regulating skeletal development. The data also revealed 34 transcription factors and 11,334 distal enhancers that were uniquely active in chondrocytes, functioning as transcriptional regulators for the cartilage-selective genes.

CONCLUSIONS

Our findings revealed a complex gene regulatory network controlling skeletal development whereby transcription factors, enhancers and lncRNAs participate in chondrogenesis by transcriptional regulation of key genes. Additionally, the cartilage-selective genes represent candidate genes for unsolved human skeletal disorders.

Для цитирования: Li Bing, Balasubramanian Karthika, Krakow Deborah, Cohn Daniel H. Genes uniquely expressed in human growth plate chondrocytes uncover a distinct regulatory network.. BMC genomics. 2017. DOI: 10.1186/s12864-017-4378-y.

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