
Mammalian preimplantation embryos provide an excellent opportunity to study temporal and spatial gene expression in whole mount in situ hybridization (WISH). However, large-scale studies are made difficult by the size of the embryos ( approximately 60mum diameter) and their fragility. We have developed a chamber system that allows parallel processing of embryos without the aid of a microscope. We first selected 91 candidate genes that were transcription factors highly expressed in blastocysts, and more highly expressed in embryonic (ES) than in trophoblast (TS) stem cells. We then used the WISH to identify 48 genes expressed predominantly in the inner cell mass (ICM) and to follow several of these genes in all seven preimplantation stages. The ICM-predominant expressions of these genes suggest their involvement in the pluripotency of embryonic cells. This system provides a useful tool to a systematic genome-scale analysis of preimplantation embryos.
Mice, Blastocyst, Animals, Computational Biology, Gene Expression Regulation, Developmental, Genetic Testing, Genomics, In Vitro Techniques, In Situ Hybridization
Mice, Blastocyst, Animals, Computational Biology, Gene Expression Regulation, Developmental, Genetic Testing, Genomics, In Vitro Techniques, In Situ Hybridization
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 71 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
