Gestational ageing in the placenta

Characterising the epigenome of the human placenta

Project Summary.

Led by:

David Monk, UEA School of Biological Sciences

Research Team:

UEA School of Biological Sciences

Earlham Institute Macaulay and Haerty Groups

Earlham Institute Genomics Pipelines

Funded by:

UKRI Biotechnology and Biological Sciences Research Council BB/V016156/1


The human placenta links a growing baby to its mother, providing oxygen and nutrients while removing waste and carbon dioxide. If this vital organ does not develop or function correctly, the consequences can be significant.

In order to understand what happens when things go wrong, we must first understand normal development. Gene expression dictates which cells are produced where in the placenta and how those cells behave over time.

Expression is regulated by various modifications to both the DNA and the scaffolding structures which hold it in place. These modifications are epigenetic – molecular additions which do not change the DNA code itself but do change the way the code behaves. As yet, there has been no systematic characterisation of the normal epigenetic modifications in the placenta during development.

One of these epigenetic modifications involves bolting molecules, known as methyl groups, onto specific sites in the DNA. This modification is called methylation and directly impacts gene expression - how much the DNA will ultimately be expressed as proteins or other functional molecules, such as regulatory RNA.

This project will paint a very detailed picture of methylation in the placenta, from early to late pregnancy, and how this might impact gene expression and influence other epigenetic marks.

The work involves a series of experiments to assess changes in the placental epigenome throughout gestation. The intention is to create an exhaustive profile of the placenta’s development, which can be used as a basis for comparison in later biomedical research.


Impact statement.

The group is planning to produce consensus epigenetic maps for early and late placenta samples. These datasets will allow the identification of these important functional regulatory elements, many of which are anticipated to change during gestation.

Bioinformatic analyses could reveal the temporal epigenetic and expression profiles for imprinted genes. This will allow novel regulatory elements to be defined and characterised.

In the longer term, this project will generate large amounts of novel data, allowing the visualisation of the placenta epigenome on an unprecedented scale. This data will have wide-ranging potential biomedical applications.