2025 Trends: NGS

The Next Generation Sequencing (NGS) field has been in constant flux since a wave of newcomers entered the field several years ago that changed the game. The startups offered sequencing users new technology options that they didn’t have previously. Now, things have settled down a bit, and the companies (both old and new) have been busy carving out their niches in the genomics community. But what will next year bring for NGS? Are customers going to want tools that provide multiple readouts, easier library prep, or better data handling capabilities? Here, we asked six companies to share their perspectives, in their own words, on what trends we can expect in 2025.

Driving Insights Through Innovation and Informatics

In the year ahead, the life science industry’s focus on informatics is going to intensify. NGS has advanced dramatically because of investments to bring down the cost of sequencing, enable whole-genome sequencing, and introduce the use of multiomics.

Today, lab capabilities are no longer a primary bottleneck to new breakthroughs–but gleaning biological insight from the mountains of data generated in the lab can be a significant barrier.

Whole-genome sequencing, multiomics, and multi-modal data integration promise a deeper understanding of biology than has ever been possible before. But only if sequencing and multiomic data can be organized, analyzed, and deciphered.

This is why the next frontier of innovation for our industry will be centered on the ability to bring together multi-modal data into an accurate and digestible set of actionable insights.

Labs need tools for:

• Storing, organizing, and formatting large amounts of multiomic data in a way that is easily accessible to downstream tools and cost effective.

• Advanced secondary analysis algorithms to convert raw data into biological signals such as variant calls, protein expression values, methylation fractions, or spatial transcriptomic images.

• AI models and tertiary analysis tools that generate research conclusions by probing high-dimensional datasets.

These needs are essential for large omics initiatives and population genomics studies. For example, the Alliance for Genomic Discovery, launched in 2022, is generating and analyzing hundreds of thousands of genomes to create genomic, multimodal phenotypic, and multiomic data to discover highly actionable therapeutic targets and accelerate breakthroughs.

As we at Illumina continue to focus on the needs of labs and researchers around the world, we know that it’s not just the sequencing but the entire workflow that will unlock the next big discoveries. Informatics is a huge part of that workflow and we’ll continue to invest in software innovation to drive the most powerful insights available.

A New Phase of Multiomic Analysis

In 2025, population-scale genome studies will begin expanding to an entirely new phase of multiomic analysis enabled by direct interrogation of molecules. Unlike past studies based on a molecular proxy, such as cDNA for transcriptomes or bisulfite conversion for methylomes, direct analysis of RNA and epigenomes will add to DNA sequencing data to enable a more sophisticated understanding of native biology in these extremely large cohorts.

Scientists going forward will be able to start unlocking new, actionable insights into health and disease from efforts such as the UK Biobank’s recent investment in building a unique epigenomic data set based on DNA from 50,000 participants. Ultimately, this approach will unlock the potential to drive more routine adoption of precision medicine in mainstream healthcare than would ever have been possible with information gleaned from genomic data alone.

Spatial Biology and Other New Frontiers

The year 2025 will see a shift into in situ sequencing of cells in tissue, expanding the capabilities of current spatial biology methods and empowering a new wave of biological insights. Direct sequencing of genomic variations such as cancer mutations, gene edits, and immune receptor sequences in single cells within their native spatial context in tissue will allow researchers to explore complex cellular interactions and disease mechanisms with unparalleled biological precision.

2025 is poised to be a breakthrough year for spatial biology, with new high-throughput sequencing-based technologies enabling large-scale, cost-effective studies. With increased throughput and dramatic cost reduction, we expect to see more routine 3D spatial studies to comprehensively assess cellular interactions in the tissue microenvironment. Importantly, large-scale spatial multiomic studies on clinically characterized FFPE samples will unlock routine translational and clinical research.

Integration of AI into multiomic datasets on characterized clinical samples will enable a foundational bridge with routine pathology. Models trained on larger application-specific datasets will provide critical insights for researchers to dramatically accelerate biomarker discovery, refine diagnostic processes, and guide the development of more effective, targeted therapies.

Speed, flexibility, and user experience will become paramount as new clinical sequencing applications move beyond central hubs. We will continue to see the decentralization of new rapid clinical sequencing applications, moving the testing closer to internal expertise at institutions. 

Multiomics and AI Analytics

The year 2025 will mark a revolution in genomics, driven by the power of multiomics and artificial intelligence. Multiomics—the integration of genetic, epigenetic, and transcriptomic data from the same sample—offers a comprehensive perspective on biology, bridging the gap between genotype and phenotype. By combining these insights with AI-powered analytics, researchers can unravel complex biological mechanisms, accelerating breakthroughs in rare diseases, cancer, and population health. This synergy is making previously unanswerable scientific questions accessible and redefining the possibilities in genomics.

The progress of long-read sequencing over the past decade has been extraordinary.  RNA is also a key component of this revolution.

In 2025, multiomics will become the new standard for research. By integrating genetic, epigenetic, and transcriptomic data with HiFi accuracy, scientists can uncover the full complexity of biological systems—transforming our understanding of health, disease, and the possibilities for intervention. PacBio’s innovations ensure that the future of genomics is truly multiomic, accessible, and transformative.

Higher Quality Data at Lower Cost

The ability to do more with less has been extremely impactful across the research community. We are entering an era where more “omics” is now possible, and sequencing needs to be both high quality and affordable to enable researchers to explore further with more breadth and depth. AI and machine learning will have a profound impact on our industry in helping to accelerate biomarker discoveries, identify new pathways for drug development and offer a more defined path towards precision medicine. The intersection of NGS and AI/ML will be critical towards the generation of large datasets that will be required to drive AI-scale breakthroughs and for which the cost of sequencing data will be paramount.

We are entering a world in which clinical NGS will become standard of care across the entire patient care continuum. As the cost of sequencing continues to drop to even below the $100 genome, clinical testing labs will be even more motivated for the opportunity to develop new and transform existing assays that enable more breadth and depth with better economics. The development, validation, and accessibility of liquid biopsy assays to improve outcomes for patients with cancer will require technologies that can provide lower limits of detection at the part-per-million level to find the ‘needle in a haystack’ without added cost.

Easy accessibility to cost-effective sequencing will be important in driving this next wave of genomics at scale. We see labs consolidating to more efficient NGS workflows and that provide more high-quality data coupled with lower cost.

NGS Evolution Empowers AI-Assisted Discovery

The future of NGS is shifting toward commoditization. Current NGS methods primarily focus on identifying changes within the genome. However, our biology—and consequently our diseases—are much more complex than nucleotide variations suggest. New tools are being rapidly developed and implemented to offer vital additional insights into biological processes, which will ultimately revolutionize drug discovery.

The next evolution of NGS is an accessible, fully integrated system to capture complete biological pictures built on the foundation of sequencing. Breakthroughs require us to respect biological nuance and demand platforms that assay all types of molecules, including DNA, RNA, proteins, metabolites, and lipids, in their native context, in a time- and space-dependent manner. Understanding the interactions between these molecules and the dynamics of biology with a systematic view is the next summit, one we are quickly approaching.

The current state of art is taking soft steps towards multiomics, using multiple segmented approaches among several biological samples at different time-points, making it expensive to collect the large-scale, accurate, and unified data that is required for AI to build better predicative models. We are boldly moving towards a future where fast, affordable, and accurate integrated multiomics measurements from the same sample and the same instrument become the new standard. This progress will significantly enhance our understanding of biology and empower AI-assisted discovery with reliable and consistent data obtained from single biological samples, and thus bring efficiency to the drug discovery and development process.

Accessible integrated multiomics represents the future of applied sequencing as we know it. This evolved form of discovery is significantly different from the relatively flat NGS, but as scientists, we don’t just study evolution; we embody it.