Assembling a typical family tree can take a lot of work, but imagine if your family contained billions of members rather than hundreds. That’s the challenge facing researchers studying embryonic development, who delve into the cells that come from a sole ancestor — a fertilized egg — but form everything from skin to brain tissue.
Two studies published this month represent a major step toward being able to retrace these byzantine histories at a single-cell level of detail.
“People have been studying how embryos develop for hundreds of years,” said James Gagnon, a developmental biologist at the University of Utah who was not involved in either study. “These papers are getting us to the point where we’re ready to learn stuff about general principles of animal development.”
Both efforts employ a system known as prime editing, which makes it possible to insert specific DNA marks at defined sites in the genome. Once those are introduced into an embryonic cell, the sequences will be retained in the developing cell. When it divides, the two resulting “daughter cells” keep the same genomic marks — but will then go on to accumulate new ones as well. These are then also passed on to their descendants, and so on.
DNA sequencing ultimately reveals the accumulated marks in each embryonic cell and enables researchers to computationally reconstruct developmental history based on their patterns.
In the latest studies, both teams worked with embryonic mice and used prime editing to insert various short sequences comprising different combinations of the four nucleotide letters (A, G, T and C) that form DNA. (Even a short sequence can produce a lot of diversity; a three-nucleotide marker, for example, can encompass 64 different combinations.)
One of the studies, led by genomics researcher Jay Shendure at the University of Washington and published in Science, builds on a technique developed by his group in 2022 called DNA Typewriter. It ensures each new marker is incorporated in sequential order. “That creates sort of a linear progression of time,” which makes the subsequent reconstruction process simpler, Shendure explained in an interview.
He and colleagues started with a fertilized egg, tracing the cellular lineages in a single mouse embryo after 13½ days of development — more than halfway through the developmental process, when “you’ve got the basis of most organs and things like that,” he noted. They then assembled a massive family tree tracing the descent of nearly 1.3 million cells — only 10 percent of the total but sufficient to map the origins of many cell and tissue types.
The second study, led by investigator Jonathan Weissman at the Whitehead Institute for Biomedical Research in Massachusetts and published in Cell, used an alternative prime-editing-based method called PEtracer. This analysis was narrower in scope — a 2½-day window of development — but included 16 embryos from across that span of time. Within each, Weissman’s group typically recorded the lineages of nearly half of the cells, finding consistent developmental trajectories that establish the mouse’s overall body plan and lead to the formation of the heart and other organs.
Neither technique currently captures the whole picture of embryonic development, but the two studies suggest a clear road forward.
“Having that ‘movie’ of development of a mouse … is something that still lies ahead of us, but I feel much more confident we’re going to get there,” Shendure said. This same lineage-tracing toolbox could also be used to reveal how many disease processes unfold, such as tumor growth and metastasis. The goal is ultimately to utilize such findings to better understand the same processes in human beings.
It may be some time before extensive lineage maps based on DNA Typewriter and PEtracer become accessible to labs without substantial financial and technical resources. But both research groups have made their published data available online, and as with the Human Genome Project — an immense consortium-led effort that soon became an invaluable resource for global research — Gagnon is optimistic that the reference material generated by these early efforts will be a tide that raises all boats in the developmental biology field.
“For me, that’s the fun thing — trying to think of how these types of datasets empower science in many labs,” he said.
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