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A nanowell-based sequencing technique bridging the gap between genetic and epigenetic profiling: wellDA-seq

Date: April 18, 2025

Author: Takara Bio Blog Team

Categories: Research News

Single-cell profiling is transforming our understanding of breast cancer

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As a result it is now possible to map the intricate dance between genetics and epigenetics within a single cell by leveraging approaches beyond unimodal measurements.

Globally, breast cancer is among the most diagnosed cancers, with varying subtypes and complexities. To unravel these intricacies, Wang et al. (2024) developed nanowell DNA&ATAC sequencing (wellDA-seq), the first high-resolution method capable of simultaneously mapping genomic and epigenomic profiles in thousands of individual cells. This breakthrough has enhanced our knowledge of tumor evolution and promises to transform our understanding of this disease.


How wellDA-seq works

At the heart of this innovation is a nanowell-based sequencing technique. The compartmentalization of single cells in nanowells allows wellDA-seq to fully remove chromatin from genomic DNA, for high-resolution whole genome profiling in addition to measuring chromatin accessibility. It utilizes two distinct transposomes for separate labeling of open chromatin regions and the genomic DNA, maintaining cell integrity throughout the process. The technique simultaneously tags open and closed chromatin regions in single cells, providing resolution of genome-wide copy number alterations (CNAs) and chromatin accessibility.


Elucidating breast cancer heterogeneity

Bridging the gap between genetic and epigenetic profiling, wellDA-seq offers insights into how specific genetic mutations influence chromatin accessibility and identifies epithelial cell-of-origin in breast cancer cells, a major challenge in understanding breast cancer evolution. This dual profiling capability uncovered key dynamics, revealing that ancestral cancer cells in estrogen receptor-positive (ER+) breast cancers arise from luminal hormone-responsive (LumHR) epithelial cells, one of the three epithelial cell types in normal breast tissue. The study showed that as breast cancer evolves, cancer cells lose their original epithelial characteristics—a discovery that sheds light on cancer dedifferentiation and progression.


A glimpse at the findings

  1. Uncommon events in normal tissues: rare aneuploid cells were identified in normal breast tissue, showcasing somatic CNAs like chromosome 1q gain and 10q loss.
  2. Tumor microenvironment insights: somatic changes were detected in non-epithelial cells, such as T-cells and pericytes, highlighting the complexity of the tumor ecosystem and suggesting broader genomic instability beyond cancer cells.
  3. Genomic alterations influence chromatin accessibility: over 80% of chromatin accessibility changes in cancer cells were linked to CNAs, emphasizing the interplay between genetic alterations and epigenomic remodeling. 

Cancer and beyond: a tool for all of biology

The advent of wellDA-seq is a transformative step in single-cell analysis and cancer research. This technology provides an understanding of tumor evolution and cellular dynamics in two different dimensions, far surpassing the capabilities of unimodal methods. While the current wellDA-seq findings are based on a limited cohort, they pave the way for larger studies that could transform how we approach cancer diagnostics and treatment.

While wellDA-seq's initial application is in breast cancer, the technology has the potential to span far beyond, including immunology and neuroscience, promising to deepen our understanding of cellular behavior in both disease and health.

Ready to explore wellDA-seq? Learn more about the potential of this highly scalable approach and how it can redefine research across multiple disciplines.


Reference

Wang K, et al. Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer. bioRXiv September 10, 2024.


Takara bio products used in this exciting research

ICELL8® cx Single-Cell dispensing system

ICELL8 350v nanowell chips

CellSelect® Software

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