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Translation of Tudor-SN, a novel terminal oligo-pyrimidine (TOP) mRNA, is regulated by the mTORC1 pathway in cardiomyocytes.

Shihu GanChao SuJinzheng MaMingxia LiuXiaoteng CuiLingbiao XinYuanyuan RenXingjie GaoLin GeMinxin WeiJie Yang
Published in: RNA biology (2020)
The mechanisms that regulate cell-cycle arrest of cardiomyocytes during heart development are largely unknown. We have previously identified Tudor staphylococcal nuclease (Tudor-SN) as a cell-cycle regulator and have shown that its expression level was closely related to cell-proliferation capacity. Herein, we found that Tudor-SN was highly expressed in neonatal mouse myocardia, but it was lowly expressed in that of adults. Using Data Base of Transcription Start Sites (DBTSS), we revealed that Tudor-SN was a terminal oligo-pyrimidine (TOP) mRNA. We further confirmed that the translational efficiency of Tudor-SN mRNA was controlled by the mammalian target of rapamycin complex 1 (mTORC1) pathway, as revealed via inhibition of activated mTORC1 in primary neonatal mouse cardiomyocytes and activation of silenced mTORC1 in adult mouse myocardia; additionally, this result was recapitulated in H9c2 cells. We also demonstrated that the downregulation of Tudor-SN in adult myocardia was due to inactivation of the mTORC1 pathway to ensure that heart growth was in proportion to that of the rest of the body. Moreover, we revealed that Tudor-SN participated in the mTORC1-mediated regulation of cardiomyocytic proliferation, which further elucidated the correlation between Tudor-SN and the mTORC1 pathway. Taken together, our findings suggest that the translational efficiency of Tudor-SN is regulated by the mTORC1 pathway in myocardia and that Tudor-SN is involved in mTORC1-mediated regulation of cardiomyocytic proliferation and cardiac development.
Keyphrases
  • cell proliferation
  • cell cycle
  • cell cycle arrest
  • signaling pathway
  • heart failure
  • pi k akt
  • transcription factor
  • single cell
  • binding protein
  • atrial fibrillation
  • left ventricular
  • deep learning