Benny Bergman

All organisms have many genes, but not all of them are expressed at the same time. Organisms constantly have to regulate which genes are active and which are not. DNA methylations—little molecules that are attached to specific nucleotides of DNA, usually cytosine and sometimes adenine, stop cells from expressing the affected genes—have a very important role in gene regulation. Unfortunately, we don’t currently have precise ways to detect and map them. There are multiple types of methylations that are attached to different nucleotides and regulate different aspects of genes. DNA Sequencing is the process of sequencing the nucleotides in DNA, finding out what the DNA order is. Nanopore sequencing measures the electric current of nucleotides in DNA. The goal of this paper was to create an effective way to detect DNA methylations. The unique way nanopore sequencing processes data could allow for very accurate detection of DNA methylations. In this paper, researchers created a method of DNA methylation detection using nanopore sequencing by comparing measurements of the same nucleotides that have different methylations. They then created a machine learning program to determine differences in the modification types, as well as the methylation type for each variation in the signal by comparing the differences in each pulse. The methylation detection system they created was very accurate and was able to greatly improve on pre-existing methods. They used this new method of methylation detection to improve other methods such as binning (a process to get the full understanding of the genome by breaking up and reassembling the genome)and mapping genomes. Their detection method is the most efficient and effective method for determining methylations on cytosine. When a disease is being studied, we will now be able to obtain the complete genome with all the DNA modifications of the disease, which will allow for a better understanding of the disease to help create cures.