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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Automating ChIP-seq Experiments to Generate Epigenetic Profiles on 10,000 HeLa Cells
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Cell2Read: an automated workflow to generate sequencing-ready DNA libraries from human cell suspensions.

Kathryn Whitehead1, Sarah Planchak1, Trinity Williams1

  • 1Center for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.

Biology Methods & Protocols
|December 30, 2025
PubMed
Summary

Cell2Read automates cell lysis and sample preparation for next-generation sequencing (NGS), enabling high-quality DNA analysis from as few as 1500 cells. This novel method ensures reproducible results for diverse cell types, crucial for genomic research and diagnostics.

Keywords:
DNA extraction automationautomated DNA library preparationcancer cell detectioncell lysishigh-throughput genomicslow-input sequencingoncology diagnostics

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Area of Science:

  • Genomics
  • Molecular Biology
  • Biotechnology

Background:

  • Next-generation sequencing (NGS) requires efficient sample preparation, especially from limited cell inputs.
  • Current methods can be labor-intensive and may struggle with low cell numbers or diverse sample types.
  • Automated solutions are needed to improve reproducibility and accessibility in genomic analysis.

Purpose of the Study:

  • To introduce and validate Cell2Read, a novel automated workflow for integrated cell lysis and sample preparation for NGS.
  • To assess the performance of Cell2Read with low cell inputs and various cell types.
  • To evaluate the method's suitability for analyzing heterogeneous cell populations, including those relevant to oncology.

Main Methods:

  • Development of an automated platform integrating cell lysis, DNA extraction, and library preparation.
  • Optimization of diffusion kinetics and thermal geometries for low-input cell processing.
  • Testing across multiple human cell lines (HepG2, Caov3, HEY A8, OVCAR 8, MDA-MB-231) and primary cells.
  • Evaluation of sequencing integrity, DNA yield, quality scores, GC bias, and alignment rates.
  • Assessment of performance with heterogeneous cell suspensions, including spiked cancer cells.

Main Results:

  • Cell2Read successfully processed cell suspensions as low as 1500 cells without compromising sequencing integrity.
  • Consistent DNA yield (≥10 ng) and high sequencing quality (alignment rates >95% for ≥3125 cells) were achieved.
  • The method demonstrated reproducibility across diverse cell types and comparable performance to manual protocols.
  • Non-biased sequencing of heterogeneous cell suspensions was achieved, with DNA representation proportional to cancer cell concentration.
  • The system yielded high-quality genomic data from low-input samples, suitable for clinical diagnostics and research.

Conclusions:

  • Cell2Read provides a technically validated, scalable, and automated solution for NGS sample preparation.
  • The workflow significantly expands accessibility to genomic analysis from low-input human samples.
  • Its robustness and reproducibility make it ideal for oncology research and clinical diagnostics.
  • Cell2Read ensures high-quality, unbiased sequencing data, supporting accurate genomic profiling.