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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Identifying novel regulators of placental development using time-series transcriptome data.

Ha Th Vu1,2, Haninder Kaur1, Kelby R Kies1,2

  • 1Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, USA.

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|January 9, 2023
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This study reveals novel regulators of early placental development by analyzing gene networks in mouse embryos. These findings offer insights into placental function and potential therapeutic targets.

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Area of Science:

  • Developmental Biology
  • Genomics
  • Molecular Biology

Background:

  • The placenta is crucial for fetal development, supplying oxygen and nutrients.
  • Early placental development regulatory mechanisms and gene interaction networks are poorly understood.
  • Identifying key genes and networks is essential for understanding placental function.

Purpose of the Study:

  • To identify genes with timepoint-specific expression during early mouse placental development.
  • To infer gene interaction networks and analyze highly connected modules.
  • To predict novel regulators of placental development and validate their function.

Main Methods:

  • RNA-sequencing of mouse fetal placenta at embryonic days 7.5, 8.5, and 9.5.
  • Bioinformatic analysis to infer gene interaction networks and identify network modules.
  • Identification of hub genes and neighboring genes within modules.
  • Experimental validation of candidate regulators in the HTR-8/SVneo cell line.

Main Results:

  • Identified timepoint-specific gene network modules associated with distinct developmental processes.
  • Discovered modules with expression profiles similar to specific human placental cell populations.
  • Predicted novel candidate regulators, four of which were confirmed to regulate cell migration.

Conclusions:

  • Network analysis of bulk RNA-sequencing data can predict novel regulators of placental development.
  • Identified candidate regulators are expressed in specific placental cell types and influence placental functions.
  • The findings provide valuable insights into the transcriptional landscape of early placental development.