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Plet1 is an epigenetically regulated cell surface protein that provides essential cues to direct trophoblast stem cell differentiation.

ABSTRACT: Gene loci that are hypermethylated and repressed in embryonic (ESCs) but hypomethylated and expressed in trophoblast (TSCs) stem cells are very rare and may have particularly important roles in early developmental cell fate decisions, as previously shown for Elf5. Here, we assessed another member of this small group of genes, Placenta Expressed Transcript 1 (Plet1), for its function in establishing trophoblast lineage identity and modulating trophoblast differentiation. We find that Plet1 is tightly repressed by DNA methylation in ESCs but expressed on the cell surface of TSCs and trophoblast giant cells. In hypomethylated ESCs that are prone to acquire some trophoblast characteristics, Plet1 is required to confer a trophoblast-specific gene expression pattern, including up-regulation of Elf5. Plet1 displays an unusual biphasic expression profile during TSC differentiation and thus may be pivotal in balancing trophoblast self-renewal and differentiation. Furthermore, overexpression and CRISPR/Cas9-mediated knockout in TSCs showed that high Plet1 levels favour differentiation towards the trophoblast giant cell lineage, whereas lack of Plet1 preferentially induces syncytiotrophoblast formation. Thus, the endogenous dynamics of Plet1 expression establish important patterning cues within the trophoblast compartment by promoting differentiation towards the syncytiotrophoblast or giant cell pathway in Plet1-low and Plet1-high cells, respectively.

SUBMITTER: Murray A

PROVIDER: S-EPMC4848516 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Plet1 is an epigenetically regulated cell surface protein that provides essential cues to direct trophoblast stem cell differentiation.

Murray Alexander A Sienerth Arnold R AR Hemberger Myriam M

Scientific reports 20160428

Gene loci that are hypermethylated and repressed in embryonic (ESCs) but hypomethylated and expressed in trophoblast (TSCs) stem cells are very rare and may have particularly important roles in early developmental cell fate decisions, as previously shown for Elf5. Here, we assessed another member of this small group of genes, Placenta Expressed Transcript 1 (Plet1), for its function in establishing trophoblast lineage identity and modulating trophoblast differentiation. We find that Plet1 is tig ...[more]

PMID: 27121762

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Project description:BackgroundMethylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis.ResultsOur two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes.ConclusionsOur results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

Dataset Information

Plet1 is an epigenetically regulated cell surface protein that provides essential cues to direct trophoblast stem cell differentiation.

Publications

Plet1 is an epigenetically regulated cell surface protein that provides essential cues to direct trophoblast stem cell differentiation.

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