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Updated: Jun 10, 2025

Using In Vivo and Tissue and Cell Explant Approaches to Study the Morphogenesis and Pathogenesis of the Embryonic and Perinatal Aorta
Published on: September 12, 2017
Transcriptional regulation of postnatal aortic development
D Weiss1, N Yeung2, A B Ramachandra3
1Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Mechanical & Materials Engineering, University of Denver, Denver, CO, USA.
None:
The aorta exhibits tremendous changes in geometry, composition, and mechanical properties during postnatal development. These changes are necessarily driven by transcriptional changes, both genetically programmed and mechano-responsive, but there has not been a careful comparison of time-course changes in the transcriptional profile and biomechanical phenotype. Here, we show that the greatest period of differential gene expression in the normal postnatal mouse aorta occurs prior to weaning at three weeks of age though with important evolution of many transcripts thereafter. We identify six general temporal patterns, including transcripts that monotonically decrease to lower or increase to higher steady state values as well as those that either peak or dip prior to or near weaning. We show that diverse transcripts within individual groupings correlate well over time, and that sub-sets of these groups correlate well with the developmental progression of different biomechanical metrics that are expected to be involved in mechano-sensing. In particular, expression of genes for elastin and elastin-associated glycoproteins tend to correlate well with the ratio of systolic-to-diastolic stress whereas genes for collagen fibers correlate well with the daily rate of change of systolic stress and genes for mechano-sensing proteins tend to correlate well with the systolic stress itself. We conclude that different groupings of genes having different temporal expression patterns correlate well with different measures of the wall mechanics, hence emphasizing a need for age-dependent, gene-specific computational modeling of postnatal development.
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