Genetic Manipulation of Mammary Gland Development and Lactation

  • Darryl L. Hadsell
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 554)


The mammalian genome is believed to contain some 30,000 to 40,000 different genes. Of these an estimated 42% have no known function. Genetically engineered mouse models (GEMM) have been a powerful tool available for determining gene function in vivo. In the mammary gland, a variety of genetic engineering approaches have been applied successfully to understanding the importance of specific gene products to mammary gland development and lactation. Our own laboratory has applied genetically engineered mice to facilitate understanding of the regulation of mammary gland development and lactation by insulin-like growth factors (IGF) and by the transcription factor, upstream stimulatory factor (USF-2). Our studies on transgenic mice that overexpress IGF-I have demonstrated the importance of IGF-dependent signaling pathways to maintenance of mammary epithelial cells during the declining phase of lactation. Our analysis of early developmental processes in mammary tissue from mice that carry a targeted mutation in the IGF-I receptor gene suggests that IGF-dependent stimulation of cell cycle progression is more important to early mammary gland development than potential antiapoptotic effects. Lastly, our studies on mice that carry a targeted mutation of the Usf2 gene have demonstrated that this gene is necessary for normal lactation and have highlighted the importance of this gene to the maintenance of protein synthesis. These studies, as well as studies of others, have highlighted both the strengths and limitations inherent in the use of GEMM. Limitations serve as the driving force behind development of new experimental strategies and genetic engineering schemes that will allow for a full understanding of gene function within the mammary gland.


Mammary Gland Milk Yield Mouse Mammary Tumor Virus Mammary Gland Development Upstream Stimulatory Factor 
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 Science+Business Media New York 2004

Authors and Affiliations

  • Darryl L. Hadsell
    • 1
  1. 1.The USDA/ARS Children’s Nutrition Research Center, Department of PediatricsBaylor College of MedicineHoustonUSA

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