DNA Typewriter records cells’ history in early mouse embryo
Inserted into a fertilized mouse egg genome, the tape then tracked the lineage of 1.3 million embryonic cells up to late organ development.
Scientists have succeeded in reconstructing the family tree of cells in a developing mouse embryo. They recorded cells’ relationships, starting when the fertilized egg first split in two and ending after the body with organs took shape. That period lasted 13.5 days. (Full gestation in mice is 19 to 21 days.)
The study results appeared Oct. 8, 2026 in Science.
“We are interested in tracking how cells’ early ancestry in an embryo influences their later fates. Exploring cell lineages helps decode normal development. Such research could eventually advance knowledge about congenital malformations, neurodevelopmental conditions, genetic disorders or cancer,” said Dr. Jay Shendure, professor of genome sciences at the University of Washington School of Medicine in Seattle and a Howard Hughes Medical Institute Investigator.
He and Dr. Chengxiang Qiu, a molecular and systems biologist at Dartmouth College in New Hampshire, are co-senior authors of the Science paper.
Their team’s most recent milestone was reached by using a tracking technology called DNA Typewriter, invented by Shendure and Junhong Choi, who is at Sloan Kettering Cancer Center.
The team inserted a newly redesigned tape into the fertilized mouse egg genome to tap into the mouse’s DNA as a recording medium. The redesign makes the tape’s record easier to read back out of individual cells. As cells divide and take on different characteristics to build the embryo, the DNA Typewriter remains inside each cell’s own genetic material. It serves like a keeper of a ship’s log.
“Think of it like an actual typewriter, except it types onto a cell's own DNA instead of paper,” explained Haedong Kim, a co-first author of the study and a postdoctoral scientist in genome sciences at UW Medicine, the Seattle Hub for Synthetic Biology and the Howard Hughes Medical Institute. “Every time a cell divides, it strikes one new character onto the next blank line — always in order, never overwriting what's already there. Because the characters are always filled in sequence, that sequence itself spells out the cell's division history.”
These codes can then be recovered in a cell’s progeny. Shared DNA Typewriter markings tell scientists which groups of cells had an ancestor cell in common.
"Writing the record is only half the problem. You also have to read it back out of each cell, so we redesigned the tape to make that easier," said Kim.
The complexity of a mammal’s body has challenged scientists who try to accurately trace the lineage of the vast numbers and types of cells in a developing mouse. Decades ago, other scientists accomplished such a feat in a tiny roundworm. But that transparent creature has a simple internal structure with comparatively few cells. Attempts to trace a mouse’s embryonic cell lineage with older technologies produced vital data but a more fragmentary view.
Also, the older methods that cut DNA can leave scars, according to researchers. In addition, they are harsher on the cells and often erase earlier records. They run out of recording capacity fast. Because they place marks in no particular order, the timeline must be guessed afterward.
“DNA Typewriter avoids all of this,” said Kim. “It writes without fully severing the DNA, keeps recording relatively steadily, and writes everything in strict order, so we can record cell lineages at much higher resolution for a longer time.”
The research team attempted this recording in 100 fertilized mouse eggs and ended up with 10 embryos to examine. In Embryo No. 3, the recording system was clearly switched on and had gathered the richest history, according to the scientists. They turned their full analysis to it.
Their study resulted in several new insights. One stemmed from a fortuitous catch immediately after the fertilized mouse egg split in half.
“Our recording captured a clear, permanent mark distinguishing the two very first cells, letting us trace nearly every cell we profiled from the embryo back to one or the other,” said Kim. “One of these two founding cells did go on to produce more descendants than the other, but they produced diverse cell types at almost equal ratios.”
Another finding: By analyzing the recordings, the scientists could pinpoint when, during development, each cell type first broke off on its own separate path.
The scientists showed that these kinds of family trees of development could help them understand when cells pick their jobs, with results consistent with findings accrued over decades of study, but here measured in a single mouse.
“Blood cells and the retina committed relatively early, while the skin's outer layer didn't commit until noticeably later,” they said. “Cell fate wasn't locked in all at once. Different cell types settled into their identity on their own separate schedules, some early and some late.
Looking at the overall study, Kim said: “This kind of large-scale developmental recording gives scientists a map of how one cell becomes a whole body — which helps explain how organs form correctly, how that process can go wrong in birth defects, and how abnormal cell growth drives cancer. As stem cell engineering advances, this kind of recording can also help guide how we engineer cells for therapeutic use.”
The other co-first authors on the study were Qi Yu and Sophie Seidel of the UW School of Medicine’s Department of Genome Sciences and at the Seattle Hub for Synthetic Biology, where Shendure is the lead scientific director. Shendure is also the scientific director of the UW Medicine Brotman Baty Institute for Precision Medicine and of the Allen Institute for Cell Lineage Tracing.
This work was supported by the Seattle Hub for Synthetic Biology, a collaboration between the Allen Institute, BioHub and University of Washington School of Medicine (CZIF2023-008738); Paul G. Allen Frontiers Group’s Allen Discovery Center for Cell Lineage Tracing; UW Medicine Brotman Baty Institute for Precision Medicine; Washington Research Foundation; National Institutes of Health (R00HG012973 and P30CA008748); Damon Runyon Cancer Research Foundation (DFS-64-24); Searle Scholars Award (SSP-2025-101); Dartmouth’s Center for Quantitative Biology National Institute of General Medical Sciences grant (P20GM130454) and Swiss National Science Foundation (239394).
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