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Temporal and Tissue-Specific Control of Gene Expression in the Peri-Implantation Mouse Embryo Through Electroporation of dsRNA

  • Miguel L. Soares
  • Maria-Elena Torres-Padilla

The delivery of nucleic acids into embryos — either DNA molecules for transient expression or double-stranded RNA for gene silencing by RNA interference (RNAi) — remains a challenging aspect of functional studies on live organisms. Electroporation has long been a standard method for the active transfer of the nega tively charged nucleic acids into mammalian cells (Andreason and Evans, 1988). This technique employs electric pulses to create transient pores in the cytoplasmic membrane through which the nucleic acids are actively delivered. It was not until the conditions for culture of whole embryos became consistent, however, that it has been applied successfully for transfection of mouse concepti.

Nucleic acids delivery by electroporation has been achieved at various stages of mouse embryonic development. Conditions for successful electroporation in pre implantation stages have been established and optimized allowing whole-embryo tar geting of zygotes, morulae and blastocysts (Grabarek et al., 2002; Soares et al., 2005). Post-implantation embryos have undergone the procedure from as early as embryonic day (E) 5.25 up to E13.0 (Calegari et al., 2002; Mellitzer et al., 2002; Holm et al., 2007; Soares et al., 2008). This temporal specificity is particularly useful when study ing signaling pathways at work within relatively small time windows in development. In early post-implantation development, for instance, just before gastrulation, signal ing events shaping the establishment of the body axes of the mouse conceptus have been studied by temporal-specific electroporation of dsRNA (Soares et al., 2008).

Keywords

Inner Cell Mass Preimplantation Embryo Visceral Endoderm Parietal Endoderm Extraembryonic Ectoderm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2009

Authors and Affiliations

  1. 1.Department of PhysiologyDevelopment and Neuroscience, University of CambridgeCambridgeUK

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