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Evaluating DNA methylation and gene expression variability in the human term placenta
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文摘
Obtaining representative samples from a term placenta for gene-expression studies is confounded by both within placental heterogeneity and sampling effects such as sample location and processing time. Epigenetic processes involved in the regulation of gene expression, such as DNA methylation, may show similar variability, but are less well studied. Therefore, we investigated the nature of within and between- placenta variation in gene expression and DNA methylation of genes that were chosen for being differentially expressed or methylated by cell type within the placenta.

Methods

In total, two or more samples from each of 38 normal term placentae were utilized. The expression levels of CDH1, CDH11, ID2, PLAC1 and KISS1 were evaluated by real-time PCR. DNA methylation levels of LINE1 elements and CpGs within the promoter regions of KISS1, PTPN6, CASP8, and APC were similarly quantified by pyrosequencing.

Results

Despite considerable sample-to-sample variability within each placenta, the within-placenta correlation for both gene expression and methylation was significant for each studied gene. Most of this variability was not due to sample location. However, between placental differences in gene expression were inflated by the dramatic effect of processing time (0–24 h) on mRNA levels, particularly for PLAC1 and KISS1 (both expressed in the apical syncytiotrophoblast). In contrast, DNA methylation levels remained relatively constant over this same time period.

Conclusion

Due to extensive site-to-site variability, multiple sampled sites are needed to accurately represent a placenta for molecular studies. Furthermore, mRNA quantitation of some genes may be hampered by its rapid degradation post-delivery (and possibly perinatally) and thus processing time should be considered in such analyses. Within-placenta correlations in expression and methylation from unrelated genes raise the possibility that methylation and expression variation may potentially reflect cell composition differences between samples rather than true differences occurring at the cellular level.

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