CHANGE-seq: a novel, simple and scalable method to understand genome editors

Molecular circularization of DNA highlights regions of genetic variation, but also locates therapeutic targets. By converting purified human genomic DNA from a linear to circular form, scientists are able to see DNA regions that are most likely to be affected by genome editors.

Genome editors are a transformative technology with the capability to change the DNA within living cells. They hold great promise both as tools for basic research and as genomic medicines, where a patient’s own cells could be modified to become a ‘living drug’ to treat conditions like sickle cell disease and cancer.

CRISPR-Cas9 nucleases are small molecular scissors that can be programmed to cut DNA at precise locations in the human genome. The DNA breaks can be repaired by your cells’ natural DNA repair pathways by processes that enable the correction or disruption of genes. However, genome editors like CRISPR-Cas9 can make mistakes and cut the DNA at unintended locations. If the DNA in our cells accumulates mutations in the wrong places, there is increased risk that the cells could become cancerous.

Playing tag (mentation) in genome editing

In my lab at St. Jude, we developed a new method called CHANGE-seq which enables us to see precisely where genome editing nucleases like CRISPR-Cas9 are cutting within the human genome. If you’ve ever tried to find a friend in a crowded place, you know it can be hard to find them unless they stand out by wearing a bright scarf or carrying a colorful umbrella.

Similarly, CHANGE-seq works by making DNA cut by CRISPR-Cas9 genome editors stand out through a process called molecular circularization. It shares this principle with an earlier approach we developed called CIRCLE-seq, but is much simpler to perform by leveraging a process called tagmentation. With CHANGE-seq, first we convert purified human genomic DNA from a linear to a circular form. After treating this circularized DNA with CRISPR-Cas9, only DNA that has been cut open will have new ends that stand out from uncut DNA circles and can be sequenced and mapped to the human genome. In this way, CHANGE-seq enables quick, sensitive, discovery of DNA regions that are most likely to be affected by genome editors.

Locating specific therapeutic targets and genetic variations

To advance genome editing therapeutics, we need to pick the most effective and specific targets. CHANGE-seq can help by providing an experimental method to evaluate hundreds of sites to find the very best ones. For example, using CHANGE-seq, we were able to analyze over a hundred targets in human primary T-cells (an important immune cell that is being developed for cancer immunotherapies) and find a number of highly specific and active targets. We uncovered factors that distinguish specific from non-specific targets and developed machine learning methods based on the large-scale datasets to predict unintended off-target activity.

CHANGE-Seq can also be used to understand the effects of individual genetic variation on genome editing. There are approximately 4-5 million positions in the genome where DNA sequences differ between each person, making them unique. In the context of treatments that require editing the genome, it is important to understand how this naturally occurring variation can alter the response to these therapies.

Genome editing technologies have been around for over twenty years. The beauty of CRISPR-Cas9 genome editors is the simplicity in which any user may adopt and program them. CHANGE-seq is a powerful new technique because, similarly, it now enables anyone that wishes to understand the genome-wide activity of these amazing tools to do so.

About the author

Shengdar Tsai, PhD, is an assistant member in the Hematology Department. View full bio.

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