A major European genomics service provider is adopting cutting-edge sequencing technology that could transform how researchers access genetic data at unprecedented scale. BaseClear, a Netherlands-based genomics company with over 30 years of experience, has become the first Ultima Certified Service Provider in Europe, launching sequencing services on Ultima Genomics' UG200 Platform. This partnership marks a significant shift in making high-throughput, cost-effective DNA sequencing accessible across the continent.

What Makes This Sequencing Platform Different?

The UG200 Platform represents a new generation of sequencing architecture designed to handle what researchers call "AI-scale" biological data generation. Unlike conventional sequencing technologies that force scientists to choose between breadth, depth, and frequency of genetic analysis, Ultima's approach dramatically lowers the cost per sample while increasing throughput. This matters because modern genomics research increasingly depends on analyzing massive datasets to train artificial intelligence models that can predict biological outcomes and discover new treatments.

BaseClear's adoption of this technology comes at a pivotal moment. The company was selected by Basecamp Research to serve as the service provider for the Trillion-Gene Atlas, an ambitious initiative designed to generate and model biological data at trillion-gene scale using Ultima's platform. To put that in perspective, a trillion genes represents an enormous volume of genetic information that would have been economically unfeasible to sequence just a few years ago.

How Will This Expand Access to Genomic Research?

BaseClear's automated workflow integrates sample receipt, genomic extraction, library preparation, sequencing, and data delivery into a single streamlined process powered by Ultima's platform. This comprehensive offering opens doors for researchers working across multiple domains who need large-scale genetic data:

• Biomarker Discovery: Identifying genetic markers that predict disease risk or treatment response in patient populations.
• Cell and Gene Therapy: Analyzing genetic sequences to develop and validate new cellular and genetic treatments.
• Vaccine Development: Generating genomic data to understand pathogen genetics and optimize vaccine design.
• Industrial Biotechnology: Discovering enzymes and biological pathways for manufacturing and chemical production.
• Clinical Research: Conducting large-scale pharmacogenomic studies to understand how genetics influence drug response.
• Transcriptomics and Single-Cell Analysis: Examining gene expression patterns in individual cells and tissue samples.
• Whole-Genome Sequencing: Sequencing complete genomes for germline and somatic (cancer) analysis.

The timing of this partnership is significant because European researchers have historically faced barriers to accessing the latest sequencing technologies at scale. By establishing BaseClear as a certified service provider, Ultima is directly addressing the infrastructure gap that has limited large-scale genomics initiatives on the continent.

Why Are Archived Tumor Samples Getting New Attention?

While BaseClear's partnership focuses on generating new data, another major development is unlocking genetic information from samples that have been stored for decades. PacBio and Covaris have jointly developed an integrated workflow that enables long-read sequencing of formalin-fixed, paraffin-embedded (FFPE) tissue samples, the most abundant resource in cancer research. These archived specimens, collected routinely during clinical care and often linked to detailed patient records, represent an enormous untapped resource for genomics research.

The challenge has been that FFPE preservation damages and fragments DNA, making it incompatible with long-read sequencing technologies that traditionally require longer, intact DNA molecules. The new workflow combines Covaris' truXTRAC extraction technology with PacBio's AmpliFi and Kinnex workflows to recover high-quality nucleic acids and reconstruct sequencing-ready material from degraded samples.

"FFPE samples have been largely untouched by long-read sequencing," explained Amit Patel, Senior Director of Product Marketing at PacBio.

Amit Patel, Senior Director of Product Marketing, PacBio

In validation studies, this workflow detected more than 11,000 structural variants per sample while also supporting extensive variant phasing, revealing genomic information that conventional short-read sequencing often misses. With an estimated one billion FFPE samples stored in hospitals, pathology labs, and biobanks worldwide, many dating back decades, this breakthrough could transform how researchers study cancer genetics and disease progression.

How Are Universities Integrating AI Into Genomics Research?

Beyond industry partnerships, academic institutions are investing heavily in AI-enabled genomics research. Penn State's Huck Institutes of the Life Sciences awarded nine interdisciplinary seed grants for 2026-27, with multiple projects specifically focused on using artificial intelligence to understand biological systems at scale.

One particularly relevant project involves developing an AI framework to identify how plants respond to environmental changes. Researchers led by Paul Gauthier are combining physiological measurements, metabolomics data, and artificial intelligence to understand how crop plants like maize and wheat adapt to variations in light, temperature, and carbon dioxide. Another team, led by Qunhua Li, is developing AI tools to analyze live-cell microscopy data, enabling researchers to track dynamic cellular processes that control gene activity in real time.

"The Huck Seed Grant program is designed to foster collaborations across disciplines and colleges," said Christina Grozinger, Publius Vergilius Maro Professor of Entomology and director of the Huck Institutes of the Life Sciences.

Christina Grozinger, Publius Vergilius Maro Professor of Entomology and Director, Huck Institutes of the Life Sciences

These academic initiatives reflect a broader trend: the convergence of genomics, artificial intelligence, and biology is creating new opportunities to understand life at scales previously impossible to study. Whether it's generating trillion-gene datasets for AI training, unlocking archived tumor samples, or using machine learning to predict gene regulation in living cells, the infrastructure and tools for AI-scale biology research are rapidly maturing.

For researchers and clinicians, this convergence means faster access to genomic insights, lower costs for large-scale studies, and the ability to revisit historical samples with modern analytical tools. For patients, it could accelerate the discovery of new treatments and enable more personalized medicine based on individual genetic profiles.