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FoxA2 and p53 regulate the transcription of HSD17B1 in ovarian granulosa cells of pigs.

Xiaolong YuanXiaofeng ZhouXiwu QiaoQi WuZhixiang YaoYao JiangHao ZhangZhe ZhangXilong WangJiaqi Li
Published in: Reproduction in domestic animals = Zuchthygiene (2020)
The oestrogens have been highly implicated in the fertility of female animals. It is widely known that the oestrogens are primarily synthetized by the ovarian granulosa cells (GCs), and the final and essential step of this process is to catalyse the oestrone to the more active oestradiol by the protein coded by hydroxysteroid 17-beta dehydrogenase 1 (HSD17B1) gene. However, the molecular mechanism regarding the transcription of HSD17B1 remains to be fully elucidated in ovarian GCs. In this study, the 5'-deletion, luciferase assay and chromatin immunoprecipitation (ChIP) were utilized to explore the molecular regulation of transcription of HSD17B1 with the porcine ovarian GCs as the cellular model. After the deletions with -2105 to -1754 bp, -1753 to -1429 bp, -1430 to -1081 bp and -1082 to -730 bp, the relative luciferase activity of HSD17B1 promoter did not change significantly, but the deletion of -731 to -332 bp significantly increased the relative luciferase activity of HSD17B1 promoter, and an insertion (GTTT) that might raise the transcription of HSD17B1 was identified at -401 bp of HSD17B1. These findings suggested the region from -731 to +38 bp was the core promoter of HSD17B1, and the region between -731 to -332 bp might be a silence element for HSD17B1. Furthermore, the forkhead box A2 (FoxA2) directly bound at -412 to -401 bp to negatively but p53 bound at -383 to -374 bp to positively regulate the transcription and translation of HSD17B1 in ovarian GCs. These findings will improve our understanding on HSD17B1-mediated oestrogens and provide useful information for further investigations into fertility of females.
Keyphrases
  • transcription factor
  • gene expression
  • dna methylation
  • high throughput
  • healthcare
  • genome wide
  • skeletal muscle
  • insulin resistance
  • type diabetes
  • binding protein
  • social media