ArticlePhysiological genomics2011
Identification of maternally regulated fetal gene networks in the placenta with a novel embryo transfer system in mice.
Article in Physiological genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
10 authors.
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Abstract
The mechanisms for provisioning maternal resources to offspring in placental mammals involve complex interactions between maternally regulated and fetally regulated gene networks in the placenta, a tissue that is derived from the zygote and therefore of fetal origin. Here we describe a novel use of an embryo transfer system in mice to identify gene networks in the placenta that are regulated by the mother. Mouse embryos from the same strain of inbred mice were transferred into a surrogate mother either of the same strain or from a different strain, allowing maternal and fetal effects on the placenta to be separated. After correction for sex and litter size, maternal strain overrode fetal strain as the key determinant of fetal weight (P < 0.0001). Computational filtering of the placental transcriptome revealed a group of 81 genes whose expression was solely dependent on the maternal strain [P < 0.05, false discovery rate (FDR) < 0.10]. Network analysis of this group of genes yielded highest statistical significance for pathways involved in the regulation of cell growth (such as insulin-like growth factors) as well as those involved in regulating lipid metabolism [such as the low-density lipoprotein receptor-related protein 1 (LRP1), LDL, and HDL], both of which are known to play a role in fetal development. This novel technique may be generally applied to identify regulatory networks involved in maternal-fetal interaction and eventually help identify molecular targets in disorders of fetal growth.
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