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Small Noncoding RNA Signatures for Determining the Developmental Potential of an Embryo at the Morula Stage.

Angelika V TimofeevaYulia DrapkinaIvan FedorovVitaliy ChagovetsNataliya MakarovaMaria ShaminaElena KalininaGennady Sukhikh
Published in: International journal of molecular sciences (2020)
As part of the optimization of assisted reproductive technology programs, the aim of the study was to identify key small noncoding RNA (sncRNA) molecules that participate in maternal-to-zygotic transition and determine development potential and competence to form a healthy fetus. Small RNA deep sequencing followed by quantitative real-time RT-PCR was used to profile sncRNAs in 50 samples of spent culture medium from morula with different development potentials (no potential (degradation/developmental arrest), low potential (poor-quality blastocyst), and high potential (good/excellent quality blastocyst capable of implanting and leading to live birth)) obtained from 27 subfertile couples who underwent in vitro fertilization. We have shown that the quality of embryos at the morula stage is determined by secretion/uptake rates of certain sets of piRNAs and miRNAs, namely hsa_piR_011291, hsa_piR_019122, hsa_piR_001311, hsa_piR_015026, hsa_piR_015462, hsa_piR_016735, hsa_piR_019675, hsa_piR_020381, hsa_piR_020485, hsa_piR_004880, hsa_piR_000807, hsa-let-7b-5p, and hsa-let-7i-5p. Predicted gene targets of these sncRNAs included those globally decreased at the 8-cell-morula-blastocyst stage and critical to early embryo development. We show new original data on sncRNA profiling in spent culture medium from morula with different development potential. Our findings provide a view of a more complex network that controls human embryogenesis at the pre-implantation stage. Further research is required using reporter analysis to experimentally confirm interactions between identified sncRNA/gene target pairs.
Keyphrases
  • single cell
  • high resolution
  • public health
  • endothelial cells
  • pregnant women
  • gene expression
  • mass spectrometry
  • stem cells
  • physical activity
  • cell proliferation
  • weight loss
  • artificial intelligence
  • quality improvement