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A decade ago, gene sequencing was still defined by scarcity. Instruments were concentrated in elite labs. Large studies were rare. Budgets dictated ambition. Today, genomics looks less like a boutique research tool and more like public infrastructure—scaled, automated, globally distributed. MGI’s 10-year trajectory offers a lens into how that shift happened—and why it matters.
“Over the past decade, lower cost and greater scale have shifted genomics from isolated experiments to shared infrastructure,” says Duncan Yu, president of MGI. That phrase—shared infrastructure—captures the transformation more clearly than any performance benchmark.
In 2018, MGI launched the T7 sequencer, capable at the time of processing up to 60 human genomes per day. The milestone wasn’t just about throughput; it signaled a new operational mindset. Sequencing at scale, Yu argues, “is not simply doing the same thing more times. It introduces challenges in workflow, consistency, maintenance, and data handling.”
Those challenges are invisible to most outside the lab, but they are what enable population-scale genomics. Over the past decade, national initiatives have expanded from tens of thousands of samples to hundreds of thousands of genomes. That leap required platforms that ran continuously, predictably, and accurately. “This is what allows genomics to support national programs, large population initiatives,” Yu says.
Cost has been the most public battleground. Launched in 1990, the Human Genome Project required 13 years and nearly $3 billion. By 2007, sequencing had dropped to roughly $1,000 per genome—still too high for most clinical settings. Sustained engineering drove even more economic improvements in sequencing. “By pushing costs down sustainably, we helped shift genomics from small, selective studies to population-scale research, where entirely new questions can be asked,” Yu explains.
Affordability alone, however, does not democratize science. Deployment does. Over the past decade, MGI expanded globally—not just by shipping systems, but by building local capacity. “Access means global deployment, local training, service support,” Yu says. “We’ve spent years working with partners around the world to ensure sequencing capacity is not concentrated in a few regions, but can be built and sustained locally.”
This redistribution of capability changes where innovation happens. When sequencing is locally available, researchers can tackle region-specific diseases, agricultural resilience, or environmental risks without outsourcing core analysis abroad. “By lowering structural barriers, sequencing has become part of everyday scientific and public infrastructure,” Yu adds.
Technology evolution followed that philosophy. In 2022, MGI introduced new platforms, including the self-luminous sequencing–based E25 and the fast mid-throughput G99, emphasizing flexibility alongside performance. In 2023, the launch of T20x2 pushed throughput to a new level—up to 50,000 whole genomes per year—at a record-breaking cost profile of less than $100. By 2025, benchtop and ultra-high-throughput systems such as T1+ and T7+ reflected a design priority: faster turnaround without sacrificing scalability. Moreover, the sub-$100 milestone crossed a psychological threshold: sequencing could move from selective research into routine health infrastructure.
Yet Yu is careful to shift attention away from individual machines. “When people talk about genomics, they often think about machines or breakthroughs,” he says. “But an open ecosystem and infrastructure are something different. It means sequencing is no longer an exception or a privilege, but a dependable foundation for science, healthcare, and public decision-making.”
Artificial intelligence (AI) has become essential to that foundation. As datasets ballooned, AI-driven quality control and variant detection moved from experimental to indispensable. Looking forward, Yu sees AI’s role expanding beyond the speed of analysis. “We expect AI to help connect sequencing data with other data types and be well integrated into sustainable, trusted sequencing ecosystems,” he says.
In February 2026, MGI expanded its genomics footprint with the acquisitions of STOmics and CycloneSeq, adding spatiotemporal multi-omics and nanopore sequencing to its portfolio. The move positions MGI Tech as the only provider uniting short-read, long-read, and stereo-seq spatial transcriptomics in one ecosystem. Researchers have often stitched together platforms from different vendors, risking reagent mismatches, calibration drift, workflow friction, and data silos. Those cracks widen at scale, driving redundant validation and operational drag. By consolidating technologies, MGI offers labs a coherent framework that blends throughput, structural insight, and spatial context, enabling flexible strategy without rebuilding infrastructure at every stage. The goal is not just to read genomes faster, but to integrate layers of biological insight into cohesive systems that can serve healthcare and research at scale.
The past decade proved that sequencing could be made faster and cheaper. The deeper achievement was structural: turning genomics into durable infrastructure. If the next decade succeeds, sequencing will not be a headline-grabbing breakthrough. It will be something more powerful—ordinary, embedded, and everywhere it needs to be.
