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Data-driven techniques enhance understanding of cell division

Research from Umeå University paves the way for a quantitative data analysis method to study the cell division process in individual cells. The improved resolution will promote advanced cell analysis in the human body, especially in cases of incorrect cell division such as in the context of cancer. The research is in Nucleic Acids Research.

"The aim is to discover new unexpected biological patterns. We did not get the results we expected! But the study fortunately gave us a better understanding of the genome and how it can be measured when sequencing using transposons, a type of genetically modified mobile gene sequence.

"The transposons behave differently during cell division and this can be used, among other things, to follow the cell division process", says Johan Henriksson, research fellow at the Department of Molecular Biology at Umeå University.

Every organ in the body is built from a large number of different cells, each of which performs different functions. Therefore, it is important to be able to study the cells individually. Even in the early stages of biological science, this was possible using microscopy, but it was limited to studying a maximum of five or ten genes at a time.

Advanced single-cell methods began to be used in the 2010s and have revolutionized the ability to efficiently count a large number of information-bearing molecules in the cell. The method relies on sequencing to study all (more than 20,000) genes in a single cell. Nowadays, it is also possible to study millions of cells, one at a time, and this generates an enormous amount of data.

Studies of single cells do not need to be based on a hypothesis because no prior selection of genes is needed. This is called a "data-driven" approach, in that the collected data rather than a hypothesis guides the research direction and results.

"The aim is to discover new unexpected biological patterns, which can lead to new research questions", says Henriksson. "However, this comes with two major problems: We are now simply drowning in data and the technology is expensive."

This was an important driving force for the research project that Henriksson and his group started. Questions they asked themselves were: If the method is so expensive, how can it be used in a better way? What else can we tell from the data that we had not thought of before?

One theory was that it would be possible to measure the length of telomeres—DNA structures that form the ends of our chromosomes and protect them. Every time a cell divides, the telomeres become shorter. When they become too short, the cell can no longer divide; it becomes inactive or the genome is damaged, which can transform it into a cancer cell.

However, the project did not go as planned. The initial analysis of the data looked promising, but the more data that was analyzed, the more contradictions were noticed.

"After an intensive hunt for data from other labs, which can now be easily downloaded and compared, our team became desperate. Instead, we began to focus on investigating which other biological factors could affect the telomere length measurement", says Henriksson.

The data analysis forced the researchers to pay close attention to details in previous research on telomeres. For example, the expected sequence of human telomeres—repeated DNA sequences of TTAGGG—is also found in other parts of the genome. Furthermore, the telomere is not a perfect repeat of TTAGGG, or a repeat at all. Rather, the telomere model is now so dated and oversimplified that it may actually be counterproductive.

Advanced sequencing technology has provided new data on the telomere sequence, but it is complex and difficult to interpret. The interpretation is also affected by how the measurement is performed. Henriksson believes that the technique for analyzing genomes from single cells (ATAC-seq) needs to be reevaluated. ATAC-seq uses a type of genetically modified mobile gene sequence, called a transposon, to cut up the DNA into small pieces that can be sequenced.

"Based on some rather complicated experiments, it turned out that the transposon neither duplicates local DNA as previous research suggests, nor does it seem to chop up the telomere as much as other parts of the genome. Measuring telomere length was simply not possible with this approach", says Henriksson.

In another study, the researchers have already used the measurement method to locate a new, unexplored state in T cells that appears to be interesting for immunotherapy, a type of cancer treatment where the body's own immune system is used to fight cancer.