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Gene editing
Making precise, targeted changes to a genome's DNA sequence.
Gene editing is making precise, targeted changes to a genome’s DNA sequence. Rather than adding a whole new gene at random, an editor finds one chosen spot in the three billion letters of a genome and rewrites it — correcting a mutation, switching a letter, or turning a gene off. The genome stops being a read-only archive and becomes something you can write to.
How it works
The workhorse is CRISPR-Cas9: a short guide RNA is programmed to match a target DNA site, and the Cas9 nuclease it carries cuts both strands there. The cell’s own repair machinery then patches the break — and in the process introduces the intended edit. Because the guide is just a piece of RNA, retargeting the tool to a new site is as easy as changing a sequence.
From that base, a derivative ladder makes editing more precise. Base editing (from David Liu’s lab) chemically converts one DNA letter to another with no double-strand break, avoiding the messy cut. Prime editing (Anzalone and Liu, 2019) works like search-and-replace, using an extended guide to write new sequence directly — more versatile than base editing. Epigenome editing goes further still, changing whether a gene is expressed without altering the underlying sequence at all.
Why it matters (for bio × AI)
Gene editing is the write-tool for biology, the counterpart to reading sequence. In little more than a decade it went from a 2012 discovery (Jennifer Doudna and Emmanuelle Charpentier, Nobel Prize 2020) to approved therapies, including one for sickle cell disease. AI enters at every step: designing guide RNAs, predicting off-target cuts, and optimizing delivery into cells. It also leans on variant-effect prediction — knowing which edits are safe or beneficial before you make them.
Related
See the central dogma for how DNA’s information becomes function, and variant-effect prediction for judging which changes to a sequence matter.