Identifying unique regulatory elements related to polymorphic imprinting and gestational aging in the placenta

胎盘在怀孕期间生长并附着在子宫壁上。它通过脐带将母亲和婴儿联系起来。它的主要目的是为婴儿提供生长所需的所有营养和氧气，同时清除婴儿血液中的废物和二氧化碳。如果胎盘发育或功能不正常，可能会导致妊娠并发症，对婴儿产生巨大后果，不是在分娩后立即发生，而是在以后的生活中。细胞是胎盘等复杂组织的基本单位。不同细胞类型的细胞表型和功能有很大差异。正是我们基因的编码和活动(称为表达)最终决定了产生哪些细胞及其行为方式。这是通过对DNA进行“表观遗传”修改来实现的。一种形式的表观遗传调控是通过用甲基标记基因组的某些区域来实现的，这些区域往往充当基因表达的半永久阻断。然而，DNA甲基化并不是单独起作用的，有不同的相互作用机制有助于表观遗传调节。近年来，一类被称为印记基因的基因被证明对胎盘的发育和功能是必不可少的。这些独特的调控基因在表观遗传学上是“开启”的，并且只在母体或父体复制中表达，而不是两者都表达。胎盘是令人着迷的，因为它具有独特的表观遗传学特征，与所有其他组织相比，DNA甲基化明显较少，这在怀孕期间会发生微妙的变化。这种独特的低甲基化状态对表观遗传信息的附加层的层级影响尚未被研究。此外，胎盘含有数百个在其他组织中没有的独特印记基因，这些基因的表达通常随着怀孕而减少，且不依赖于DNA甲基化。这表明其他表观遗传机制是导致观察到的下调的原因。由于我们不知道胎盘内健康衰老的机制，我们对这一现象的理解受到了阻碍。在这个应用中，我们试图了解胎盘中的甲基化如何在怀孕的不同时间点影响其他表观遗传标记，以及这最终如何影响印记基因的表达(目标1.1-1.2)。为了实现这一点，我们将利用并在某些情况下改进最新的技术，以确定基因组的哪个区域与不同的表观遗传特征相关，以及这如何影响发育(目标2.1和3)。此外，由于我们预计样本中的可变性和细胞类型特定的特征，我们将分析分离的单细胞，使我们能够识别在“大量”胎盘活检中不明显的模式(目标2.2)。为了确保在我们以前经验的基础上获得最大的成功机会，我们建立了一个团队，成员包括厄勒姆研究所英国国家能力基因组学技术开发的研究人员和数据分析的计算专家。在使用极其强大的计算机和专门的计算机程序进行分析之后(目标2.3)，我们将比较不同时间和不同细胞类型的胎盘数据，以确定对与妊娠相关的表达变化重要的区域，特别是印记基因，随后我们将移除或改变这些区域以确定功能(目标4)。

The placenta grows during pregnancy and is attached to the wall of the womb. It links the mother to the baby via the umbilical cord. Its main purpose is to supply the baby with all nutrients and oxygen required for growth, whilst removing waste products and carbon dioxide from the baby's blood. If the placenta does not develop or function correctly, this can lead to pregnancy complications that have huge consequences for the baby, not immediately following delivery, but later in life. Cells are the fundamental unit of complex tissues such as the placenta. Cell phenotype and function are very different between the different cell types. It is the code and activity (referred to as expression) of our genes that are ultimately responsible for defining which cells are produced and how they behave. This is achieved by 'epigenetic' modifications to the DNA. One form of epigenetic regulation is achieved by marking certain regions of the genome with methyl groups that tend to act as a semi-permanent block for gene expression. However, DNA methylation does not act alone, there are different interactive mechanisms that help in epigenetic regulation. In recent years a class of genes, known as imprinted genes, have been shown to be essential for placenta development and function. These uniquely regulated genes are epigenetically turned "on" and expressed solely from the maternal or paternal copy, but not both. The placenta is fascinating as it has a unique epigenetic profile having significantly less DNA methylation compared to all other tissues, which subtly changes during pregnancy. The hierarchical consequences of this unique hypomethylated state on the addition layers of epigenetic information have not been investigated. Furthermore, the placenta harbours hundreds of unique imprinted genes not found in other tissues, the expression of which generally decrease with gestation in a DNA methylation independent manner. This suggests other epigenetic mechanisms are responsible for the observed downregulation. Our understanding of this phenomenon has been hindered by the fact we do not know the mechanisms responsible for healthy aging within the placenta. In this application, we seek to understand how methylation in placenta influences other epigenetic marks at different time point in pregnancy and how this ultimately impacts on imprinted gene expression (Objectives 1.1-1.2). To achieve this, we will utilize, and in some cases improve, the latest technologies to identify which area of the genome are associated with different epigenetic signatures and how this influence development (Objectives 2.1 & 3). Furthermore, since we anticipate variability and cell-type specific signatures within our samples, we will profile isolated single-cells, allowing for us to identify patterns which would not be evident in "bulk" placenta biopsies (Objective 2.2). To ensure maximum chance of success building of our previous experiences, we have established a team that includes researchers responsible for technical development at the UK National Capability in Genomics at the Earlham Institute and computational experts for data analysis. Following the analysis using extremely powerful computers and specialised computer programs (Objective 2.3) we will compare our placenta-derived data across time, and within difference cells- types, to identify regions important for gestation-age related expression changes, especially for imprinted genes, which we will subsequently be remove or alter to determine functionality (Objective 4).