New software makes gene editing technology simpler

Researchers, including those of Indian-origin, have developed a software that can quickly identify most effective ways to target genes with a powerful gene editing tool.
The advance could facilitate new discoveries in gene therapies and basic genetics research, researchers said.
Researchers at Harvard University and the University of California, San Diego, simplified a laborious part of the gene editing process using the CRISPR/Cas9 system - choosing the best components to match specific gene targets.
"We've taken a step towards making the CRISPR/Cas9 system more robust," said co-first author Prashant Mali, assistant professor at the UC San Diego Jacobs School of Engineering.

CRISPR/Cas9 is a relatively new genome engineering tool that targets a particular segment of DNA in living cells - such as a gene mutation - and replaces it with a new genetic sequence.
This technology ultimately has applications in gene therapies for genetic disorders such as sickle cell anemia and cystic fibrosis.

The CRISPR/Cas9 system has two components - a short "guide RNA" with a sequence matching a particular gene target, and a large protein called Cas9 that cuts DNA precisely at that target. Researchers can change the guide RNA sequence to match the new gene target.
However, finding the best guide RNA match for a specific gene target is a labour-intensive process. Researchers might need to test numerous candidates of guide RNAs before finding the most active guide RNA.

To decipher what makes certain guide RNAs better than others, the team evaluated a library containing thousands of guide RNAs against a library containing thousands of corresponding gene targets.
Using the data and patterns from these thousands of gene targeting experiments, the team developed a new matchmaking software that predicts and ranks the best guide RNA matches for any given gene target.
"From these experiments, we were able to find features in the guide RNAs that worked and in those that didn't work. We built a computational model that accounts for all these different features," said co-first author Raj Chari, a research fellow working in the lab of Professor George Church in the Department of Genetics at Harvard Medical School.

"The end product is an interactive software for users to find guide RNAs that are predicted to be highly specific and highly active for their gene targets," Chari said.
"We hope to minimise the time and work in finding the most successful guide RNA sequence for a gene target, which will be helpful for finding new gene therapies," said Chari.
The research was published in the journal Nature Methods.