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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Bioinformatics approaches to single-blastomere transcriptomics.

Leila Taher1, Martin J Pfeiffer2, Georg Fuellen3

  • 1Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.

Molecular Human Reproduction
|September 21, 2014
PubMed
Summary
This summary is machine-generated.

Single-cell transcriptomics reveals gene expression networks in early mouse development. This technology allows detailed analysis of cell identity and transitions during preimplantation embryo development.

Keywords:
embryo developmentgene regulationlineage decisionsnetwork biologysingle-cell transcriptomics

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Area of Science:

  • Developmental Biology
  • Genomics
  • Molecular Biology

Background:

  • Mouse preimplantation development involves lineage decisions from a totipotent zygote.
  • Previous studies analyzed spatio-temporal gene expression and genetic manipulations up to the blastocyst stage.
  • Broader overviews of gene expression networks distinguishing cells within an embryo were previously limited.

Purpose of the Study:

  • To review the current state of single-cell transcriptomics in mouse preimplantation embryos.
  • To summarize recent findings from pioneering studies in the field.
  • To investigate cell transitions using PluriNetWork and ExprEssence based on published data.

Main Methods:

  • Whole genome amplification methodology.
  • Microfluidics-based quantitative reverse transcription polymerase chain reaction (RT-PCR).
  • Analysis of published data using PluriNetWork and ExprEssence.

Main Results:

  • Single-cell transcriptomics enables comprehensive analysis of gene expression in individual blastomeres.
  • Pioneering studies have provided new insights into cell identity and differentiation.
  • Investigated cell transitions reveal dynamic gene expression patterns during development.

Conclusions:

  • Single-cell transcriptomics is a powerful tool for understanding early mammalian development.
  • This technology advances our knowledge of lineage decisions and cell fate determination.
  • Future research can further elucidate complex gene regulatory networks in embryos.