UW researchers deploy DNA Typewriter in mouse zygote. October 12, 2026 Tour Colleges 3:42 am Health Researchers have used a molecular genome-editing tool called DNA Typewriter to reconstruct the cellular family tree of a developing mouse embryo, tracking 1.28 million cells over 13.5 days of gestation and mapping how a single fertilized egg multiplies into specialized tissues and organs. Order DNA Kits The mammalian body begins as a single fertilized egg. Tracing how that founding cell divides into millions of specialized descendants has long challenged developmental biology. While scientists mapped the complete cell lineage of a transparent roundworm in 1983, generating a comprehensive cell fate map for a mammal that develops hidden in utero was out of reach until now. Two independent research groups turned to genome-editing technology to record cellular divisions directly inside living embryos using DNA-modifying methods. University of Washington team uses DNA Typewriter. Jay Shendure is the scientific director of the Seattle Hub for Synthetic Biology and a professor at the University of Washington School of Medicine. The team injected the components of a tracking system called DNA Typewriter directly into a fertilized mouse egg, allowing the embryo to grow for 13.5 days - equivalent to roughly two-thirds of normal gestation and reaching the stage of organogenesis, when complex organs take shape. The technology functions much like an airplane black box for embryonic development. The group achieved this latest breakthrough by employing a tracking method named DNA Typewriter, which was developed by Junhong Choi and Jay Shendure. As the cell divides, each daughter cell inherits the sequence of previous stamps. Find Rare Items Writing the record is only half the problem. Haedong Kim The updated design allows the sequential genetic stamps to preserve a running log of each division event without fully severing the DNA or erasing earlier records. Tracing cells back to two founding divisions. From that single embryo, the researchers reconstructed a time-calibrated lineage tree comprising 1.28 million transcriptionally profiled cells, which corresponds to roughly 10 percent of all cells in a two-week-old mouse. The Seattle Hub for Synthetic Biology - a collaborative effort between the Allen Institute, UW Medicine, and Biohub - detailed the milestone as the largest cell lineage tree ever assembled for any mammal. The recording captured a fortuitous edit right after the fertilized egg split in half, creating two independent daughter lineages within the same embryo. When the researchers analyzed these two branches, they found that one branch produced more descendants than the other, but both founding branches contributed almost equal ratios of diverse cell types. Study Biology Independent research groups apply parallel methods. In independent research published in the journal Cell, a separate team led by molecular biologist Jonathan Weissman of the Massachusetts Institute of Technology used a complementary genome-editing tool. Weissman's team introduced prime-editing instructions and 35 target DNA sites into mouse embryonic stem cells, which they then injected into developing mouse embryos at the four- to eight-cell stage. While Shendure's DNA Typewriter logged divisions sequentially onto an inserted tape from the zygote stage onward, Weissman's team installed heritable genetic marks at multiple sites across the genome as stem cells integrated into the growing embryo. Both methods produced high-resolution cell fate maps that allowed investigators to trace when specific lineages - such as neural crest cells - committed to their specialized biological functions. Application to cancer and congenital disease. Mapping the normal trajectory from a single zygote to millions of cells provides a reference model for studying developmental abnormalities. By analyzing the timing of lineage splits, scientists can pinpoint when developmental processes go awry and how congenital malformations, genetic disorders, and cancer arise. Because tumors develop when individual cells accumulate mutations and their descendants proliferate, tracking lineages in this manner could inform the design of therapeutic cells and illuminate how stem cell therapies engraft after transplantation.

Google, Meta join $1.8 billion effort to build ai-powered virtual human cell. Google and Meta are joining a $1.8 billion international effort to generate the biological data needed to build AI models capable of predicting how human cells respond to drugs, genetic changes and other conditions. The initiative, led by nonprofit Biohub, brings together technology companies, U.S. government agencies and research institutions in an effort to create a large, open biological data resource. Google DeepMind, Isomorphic Labs and Meta are collectively committing $300 million, while the U.S. Department of Energy plans to provide more than $500 million over five years. The expanded effort was announced Wednesday as researchers increasingly look to artificial intelligence to speed up drug discovery and improve understanding of complex diseases. Building a predictive model of human cells. The project, known as the Virtual Biology Initiative, aims to measure how cells respond to a much wider range of genetic, chemical, environmental and other changes than scientists can currently study at scale. Researchers will use the resulting information to train AI systems designed to predict cellular behavior. The long term goal is a virtual cell that could allow scientists to conduct some experiments digitally before moving promising ideas into physical laboratories. Biohub said the combined commitment of funding, data, computing resources and measurement technology represents the largest coordinated effort so far to create AI ready biological data. The initiative builds on Biohub's earlier $500 million commitment. The nonprofit was founded by Meta CEO Mark Zuckerberg and Priscilla Chan and has focused on using biomedical research and technology to accelerate work on human disease. Google, Meta bring AI expertise to biology. Google DeepMind, Isomorphic Labs and Meta are providing $300 million to the expanded initiative. Their involvement brings major AI and computational resources to a project that depends on collecting and processing enormous amounts of biological information. The Department of Energy will contribute more than $500 million over five years through laboratory measurement, modeling and computation. The National Institutes of Health will also coordinate existing datasets and repositories developed through more than $500 million in earlier federal funding. Those resources are expected to help researchers standardize biological information so it can be used to train AI models more effectively. The first large scale dataset is expected within about a year, while Biohub aims to develop more capable predictive models over the next five years. Drug discovery is a major target. The project could have significant implications for pharmaceutical research if the models eventually become accurate enough to predict how cells respond to potential treatments. Drug development can take years and requires extensive laboratory and clinical testing. A reliable virtual cell could help researchers identify promising drug candidates earlier, prioritize experiments and reduce some of the time and cost involved in testing biological hypotheses. However, researchers still face major challenges. Existing biological datasets do not capture enough of the enormous range of conditions that cells can experience, meaning the initiative must generate new measurements at a much larger scale. The goal is not simply to create another AI system. Researchers need models that can make predictions about biological conditions they have not previously encountered and then produce results that can be validated in real laboratory experiments. Open data could expand research access. Biohub says the biological datasets generated through the initiative will eventually become publicly available, although commercial partners will receive an initial period of access before the information is released more broadly. That approach is intended to give participating companies an opportunity to develop models while preserving a wider scientific resource for researchers. The initiative also reflects growing competition to apply AI beyond language, images and software development. Technology companies and research organizations are increasingly investing in systems designed to model physical and biological processes. For Google and Meta, the project provides an opportunity to apply their computing and AI capabilities to one of the most difficult areas of scientific research. For biomedical researchers, the value will depend on whether larger datasets and increasingly capable models can produce predictions that hold up outside the computer. The effort therefore represents a major investment in the infrastructure needed for AI-driven biology, rather than a completed virtual human cell. Its success will ultimately depend on the quality of the biological data and how accurately AI models can translate those measurements into useful predictions. Could AI-powered virtual cells eventually help scientists discover treatments faster and reduce the time needed to test new drugs? Follow EVTV Online for more updates on artificial intelligence, technology, science and major developments shaping the future. Keep reading in this section Recommended explainers. Picked by the EVTV newsroom Get EVTV in your inbox. The daily briefing on Venezuela and U.S. news that matters. Follow EVTV. Latest updates on this topic. Most recent coverage · #Google Share your take with the EVTV community. By submitting you accept its comment policy: be respectful, no insults or spam. Comments are reviewed before appearing.

Trump unveils $6 billion US science push. In short. The announcements came at the White House's Science: A New Golden Age Summit, where President Donald Trump outlined an ambitious programme to strengthen American leadership in emerging technologies. Learn Hindi Created On: 9 Oct 2026 9:30 AM IST Share: Washington: The Trump administration unveiled more than $6 billion in science and technology initiatives, bringing together federal agencies, technology companies, universities and philanthropies to accelerate research in artificial intelligence, quantum computing, nuclear-powered space exploration and biomedical science. The announcements came at the White House's Science: A New Golden Age Summit, where President Donald Trump outlined an ambitious programme to strengthen American leadership in emerging technologies. According to a White House fact sheet, the initiatives include $2.4 billion in computing resources and technology support from 11 industry partners for the Genesis Mission, which seeks to use superintelligence to accelerate scientific discoveries. Nvidia committed $1 billion, followed by AMD with $500 million and OpenAI with $200 million. Anthropic and Google pledged $150 million each, while other participants included Amazon Web Services, Micron and several technology infrastructure companies. Discover more News Subscription Service Local News Updates ePaper Access The contributions will support more than 15 federal agencies working on scientific challenges in energy, healthcare, space and other fields. "Today marks the most transformative day for the American scientific enterprise since the reshaping of the Federal research ecosystem following World War II," White House science adviser Michael Kratsios said. "The efforts announced today will channel billions of dollars across our science ecosystem to realize the new scientific opportunities that now exist," he added. The administration also announced a $1 billion investment involving universities, industry and the state of Georgia to expand scientific computing infrastructure and workforce training. More than 14 universities across 10 states will participate in a regional computing consortium, while five universities in North and South Carolina will establish another research computing hub. The National Science Foundation and Department of Energy announced more than $100 million for advanced scientific instruments and autonomous laboratories. In quantum computing, the Energy Department launched a $215 million competition aimed at developing fault-tolerant quantum computers capable of solving scientifically relevant problems. NASA and the Energy Department also announced plans to develop nuclear-powered spacecraft and lunar energy systems. The projects include Space Reactor-1, a nuclear-powered spacecraft intended for a Mars mission in 2028, and Lunar Reactor-1, a proposed nuclear fission reactor on the Moon. Biomedical research received another major push, with the National Institutes of Health, Energy Department and Biohub launching a $1.8 billion initiative to develop virtual models of cells and biological systems. The programme aims to improve predictions of how diseases develop and how biological systems respond to potential treatments. The administration also announced a $100 million Genesis Mission Fellowship to support accelerated doctoral programmes combining artificial intelligence with scientific and engineering disciplines. Discover more Business News Analysis Technology News Updates Entertainment News Other initiatives include opportunities for gifted school students, early-career researchers and scientists working outside conventional research institutions. A new X-Labs Consortium will receive more than $310 million in industry and philanthropic commitments to support multidisciplinary research teams. The White House said the announcements build on earlier federal investments, including a $5 billion commitment supporting the Genesis Mission and a $1.5 billion National Science Foundation initiative for independent research laboratories. The initiatives reflect the administration's emphasis on using advanced computing and artificial intelligence to accelerate scientific research while strengthening domestic technical expertise. The White House described the programme as a partnership among government, industry, universities and philanthropy, with the objective of maintaining American technological leadership and developing a new generation of scientists and engineers.