The human genome is a dull sequence of letters but the information of how to form the different cells in our body is encoded through these very letter in our genome. Each cell type is characterised by its distinct epigenome, a makeup of the genome composed of many different proteins that leave “open” or “closed” different parts of the genome. And with the simple addition of punctuation marks we can read and understand the meaning of that apparently dull sequence of letters.
This is the task accomplished by the epigenome, which is composed of chemical changes on the DNA that allow us and the cell to understand how to read and interpret the genome. For this reason, studying the epigenome is important to understanding how development can give rise to the large variety of cell types forming tissues and organs, all starting from a single cell and a single genome.
In a recent study by researchers at the Newcastle University, have developed a bioinformatics method that allows the automatic analysis of multiple epigenomes to identify the genomic locations where the necessary makeup changes to form both healthy and diseased cell types.
Dr Daniel Rico, Research Fellow at Newcastle University’s Institute of Cellular Medicine, said: “We have the
technology to reveal the different epigenomic makeups and this is generating a significant amount of data. We can seriously talk about “big data” in epigenomics research. However, the main bottleneck is to translate all this data into useful information to get insight into biological mechanisms. The new method that we have developed will allow researchers to identify the key regions in the genome that show differential makeups depending of the cell types. As many diseases are associated to disease-specific epigenomic makeups, this method will be particularly useful to identify the key regions in the genome where the makeup deviates from the healthy state. This will allow the development of new disease biomarkers and, hopefully, open a new path for developing therapies targeting the epigenomes.”The study published in Nucleic Acids Research details the method allowing the integration of a variety of epigenomic datasets to classify different samples and automatically identify genomic regions in which changes affect the definition of cell type.
Enrique Carrillo-de-Santa-Pau, co-first author of the study, from the Spanish National Cancer Research Centre, said: “The development of this type of methods is very important. Up to now differences between cell types had mostly been characterised at the levels of genes that are either switched on or off, that is the final product of the epigenomic regulation, but we did not know where the switches for these genes were (encoded in the epigenome). This acquired knowledge is fundamental to enable new therapies based on acting on the correct switches in cases where the cell loses control in diseases such as cancer. Understanding this level of regulation will take us one step further in the personalised medicine agenda.”
It is hoped that this method will allow scientists to identify new epigenetic biomarkers, which may help in the formulation of personalised medicine diagnosis and treatment.
