Since researchers first succeeded in mapping the human genome back in 2003, the technological development has moved at warp speed, and the process, which at that time took several years and billions of dollars, can now be performed in a few days. In the Klaus Hansen research group at the Biotech Research & Innovation Centre, University of Copenhagen, researchers have developed a new type of software, which enables a much faster analysis and interpretation of the vast amounts of data provided by sequencing technology.
“The amount of information that a genome researcher creates and which makes the basis of his scientific work has grown a million times during the last two decades. Today, the challenge does not consist in creating the data, but in exploring them and deducing meaningful conclusions. We believe that this analytical tool, which we have called “EaSeq” can help researchers in doing so,” said Associate Professor Klaus Hansen.
ChIP sequencing — an insight into the workflow of human cells
The EaSeq software has been developed for analysis of so called ChIP sequencing. DNA sequencing is used for mapping the sequence of the base pairs, which our DNA consists of, and ChIP sequencing is a derived method in which the sequences are used to determine the presence of different cell components in the genome at a given time.
“Roughly speaking, ChIP sequencing can be compared to a microscope, which enables us to observe the presence of different cell components in the entire genome at a given time. The method is still quite young and holds the potential to be applied within many more scientific fields, which can benefit from understanding how healthy and pathological cells control and uses genes,” said Associate Professor Mads Lerdrup.
Better analytical tools means a broader range of applications
While ChIP sequencing has made it possible to produce enormous amounts of data very fast, the analysis of these data has — until now — been a tedious process. Most of the analytical software being used requires knowledge of computer programming and researchers have, therefore, been dependent on specialists in order to decode and analyze their data. EaSeq offers a far more visual and intuitive alternative, which makes it possible for biomedical researchers to study and test hypotheses using their own data. This means that, instead of waiting for weeks for others to carry out an analysis, researchers will be able to perform the analyses themselves in a matter of hours.
Today, DNA sequencing is gaining ground within the clinical area where it is e.g. being used for diagnosis and targeting of treatment within the cancer area. The developers of EaSeq see similar perspectives for ChIP sequencing in the clinical work and, in that context, strong analytical tools will be pivotal.
“The DNA sequence itself tells us very little about how cells actual decodes the DNA and, to understand this, we need to map out which cell components are present in different parts of the genome at a specific time. It is our hope that we, by increasing feasibility, can enable researchers to faster uncover such knowledge and apply it clinically,” said Associate professor Mads Lerdrup.
The research project has been financed by the Danish National Research Foundation and the results have been published in the journal Nature Structural & Molecular Biology.
