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SUM-seq: Ultra-High-Throughput Single-Cell Gene Profiling

February 26, 2026
in Medicine
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In the rapidly evolving landscape of single-cell genomics, a groundbreaking technique known as Single-cell Ultra-high-throughput Multiplexed Sequencing (SUM-seq) is poised to redefine how scientists explore the intricate tapestry of gene regulation within individual cells. Presented in a recent protocol paper spearheaded by Yildiz, Lobato-Moreno, Claringbould, and colleagues, this innovative methodology revolutionizes the joint profiling of chromatin accessibility and gene expression in single nuclei, marrying scalability with cost-efficiency in an unprecedented manner. As cellular heterogeneity remains a paramount challenge in understanding developmental biology, disease mechanisms, and therapeutic responses, SUM-seq emerges as a beacon of precision and throughput, enabling researchers to dissect complex gene regulatory networks with newfound depth.

At its core, SUM-seq integrates the power of in situ barcoding specific to both accessible DNA regions and mRNA within individual nuclei, followed by droplet-based microfluidic barcoding. This sophisticated combinatorial approach introduces a multiplexing dimension previously unattainable, allowing multiple samples to be processed simultaneously in a single run. The ingenuity lies in its capacity to resolve droplets that encapsulate more than one nucleus, overcoming a notorious bottleneck in droplet microfluidics where multinucleated droplets confound data purity and interpretation. The consequent multiomic library preparation is not only robust but exquisitely scalable, accommodating the growing demand for large-scale single-cell atlasing projects and dynamic perturbation screens without compromising data quality.

When placed in context with existing multimodal assays for chromatin accessibility and transcriptome profiling, SUM-seq’s throughput and multiplexing capabilities are strikingly superior. Traditional methodologies often grapple with limitations such as lower cell capture rates, increased per-sample costs, and reduced flexibility when scaling to complex experimental designs involving multiple time points or treatment conditions. SUM-seq addresses these challenges head-on, providing a toolkit that dramatically expands the number of nuclei and samples analyzed in a single experiment. This leap in efficiency heralds a new era where large and diverse cellular populations from heterogeneous tissues can be interrogated thoroughly, accelerating discoveries in diverse fields ranging from immunology to oncology.

Of particular interest to researchers aiming to decode gene regulatory landscapes, SUM-seq simultaneously uncovers chromatin accessibility patterns—which reflect regulatory element activity—and gene expression profiles within the very same nucleus. This dual-layer insight paves the way for comprehensive modeling of cis-regulatory interactions that govern cell state transitions and phenotypic diversity. By mapping these epigenetic and transcriptomic features in tandem at a single-cell resolution, SUM-seq enables the construction of integrated gene regulatory networks with unprecedented fidelity, thereby enriching our understanding of cellular identity and functional heterogeneity.

SUM-seq’s methodological finesse extends into the realm of experimental design and sample preparation, accommodating a broad spectrum of sample types and experimental settings. The protocol offers detailed guidance on nuclei isolation, barcoding optimization, and droplet microfluidics parameters to ensure reproducibility and high data integrity. Moreover, the assay is optimized for completion within a remarkably short timeframe—approximately two to three days from sample collection to library preparation—and sequencing followed by only a single day for data processing. This rapid turnaround time is particularly advantageous in scenarios where timely data generation is critical, such as clinical diagnostics or iterative perturbation experiments.

The protocol’s accessibility is another commendable aspect, strategically crafted so that researchers equipped with general molecular biology expertise can implement it effectively. While prior exposure to single-cell assays is recommended to maximize success, the user-friendly design lowers the entry barrier for laboratories seeking to adopt cutting-edge multiomic profiling without necessitating overly specialized skill sets or prohibitively expensive equipment. This democratization of technology empowers a wider scientific community to harness high-resolution single-cell data for hypothesis generation and validation.

Crucially, SUM-seq addresses longstanding issues inherent to droplet-based approaches—issues that include sample cross-contamination and data deconvolution challenges arising from the multiplication of nuclei within single droplets. By introducing in situ barcoding strategies tailored to both accessible chromatin and transcriptomic content, the method meticulously preserves sample identity while capturing high-fidelity multiomic signatures. This technical nuance is instrumental in resolving complexities associated with heterogeneous or multinucleated samples, further expanding the assay’s utility.

The scalability and cost-effectiveness of SUM-seq hold transformative potential for large-scale biological endeavors. Projects such as the Human Cell Atlas or other tissue-centric atlases, which demand the processing of thousands to millions of cells across diverse conditions and subjects, stand to benefit immensely. Given the ability to multiplex numerous samples within a single experimental batch, researchers can now execute time-course studies or perturbation screens with high statistical power and biological resolution—ushering in more nuanced and data-rich insights into dynamic cellular responses.

In the sphere of data analysis, the protocol guides users through best practices for processing the complex multiomic data streams generated. Integrative computational frameworks tailored for chromatin accessibility and gene expression analyses enable the extraction of biologically meaningful patterns and regulatory relationships. This synergy between wet-lab innovation and computational rigor reinforces SUM-seq’s position as a holistic platform for single-cell systems biology.

A fascinating aspect of SUM-seq is its adaptability to diverse biological questions and experimental needs. Whether investigating developmental trajectories in embryonic tissues, immune cell activation in inflammatory contexts, or tumor heterogeneity in oncology, the simultaneous capture of epigenomic and transcriptomic layers offers a panoramic view of cellular function. Such detailed molecular portraits facilitate the identification of novel regulatory elements, transcription factor networks, and cell type-specific expression programs that might otherwise remain obscured in bulk analyses.

Moreover, by substantially reducing costs relative to existing multiomic approaches, SUM-seq not only expands accessibility but also encourages more extensive experimental replication and validation—key practices for ensuring reproducibility and robustness in scientific research. Institutions and consortia aiming to build comprehensive cellular atlases can leverage this cost-effectiveness to maximize sample breadth and depth, fueling discoveries that traverse species, disease states, and environmental exposures.

Looking ahead, the potential applications of SUM-seq are vast and varied. Its compatibility with nuclei from frozen or fixed tissues positions it as a valuable tool for retrospective studies and biobanking efforts, where sample preservation methods often preclude traditional cell-based assays. By overcoming these sample constraints, researchers can unlock hidden treasures in archived specimens with fresh genomic insights.

As single-cell technology continues to mature, methodologies like SUM-seq exemplify the commitment to convergence—bringing together multiple layers of molecular information in a unified, scalable, and cost-effective manner. This convergence is a leap toward comprehensively understanding the regulatory codes embedded within cellular genomes, ultimately informing precision medicine and targeted therapies.

In closing, the SUM-seq protocol, articulated with clarity and depth by Yildiz and colleagues, is more than a methodological advance; it is a paradigm shift in single-cell multiomic profiling. By balancing innovation with practicality, it equips the scientific community with a powerful instrument to chart the molecular choreography of life at the cellular level. As researchers begin to embrace and deploy SUM-seq across diverse biological inquiries, we can anticipate a surge in discoveries that illuminate the complexities of cellular identity, function, and disease with unprecedented clarity.


Subject of Research: Single-cell multimodal profiling of chromatin accessibility and gene expression to dissect gene regulatory networks and cellular heterogeneity.

Article Title: Single-cell ultra-high-throughput multiplexed chromatin accessibility and gene expression sequencing (SUM-seq).

Article References:
Yildiz, U., Lobato-Moreno, S., Claringbould, A. et al. Single-cell ultra-high-throughput multiplexed chromatin accessibility and gene expression sequencing (SUM-seq). Nat Protoc (2026). https://doi.org/10.1038/s41596-025-01310-0

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41596-025-01310-0

Tags: cellular heterogeneity analysischromatin accessibility in single nucleicombinatorial in situ barcodingdroplet-based microfluidic barcodinggene regulatory networks single-cellmultiomic single-cell analysismultiplexed single-cell sequencingscalable single-cell genomicssingle-cell developmental biology researchsingle-cell gene expression profilingsingle-cell ultra-high-throughput multiplexed sequencingSUM-seq protocol
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