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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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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....
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RNA-seq03:21

RNA-seq

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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...
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Related Experiment Video

Updated: Mar 19, 2026

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
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Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation

Manabu Watanabe1, Junko Kusano1, Shinsaku Ohtaki1

  • 1Life Technologies Japan Ltd., a part of Thermo Fisher Scientific. 4-2-8 Shibaura, Minato-ku Tokyo 108-0023, Japan.

Applied & Translational Genomics
|June 14, 2016
PubMed
Summary

This study presents a novel single-cell identification and cancer gene profiling method using massively parallel sequencing. The technique successfully distinguishes individual cancer cells from bulk populations, addressing sample heterogeneity in genomic analysis.

Keywords:
HeterogeneityLaser capture microdissectionSemiconductor-based sequencingSingle cell identification

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Area of Science:

  • Genomics
  • Molecular Biology
  • Cancer Research

Background:

  • Understanding single-cell biology is crucial for accurate genomic analysis.
  • Tumor sample heterogeneity poses a significant challenge in cancer research.
  • Next-generation sequencing combined with single-cell methods offers potential solutions.

Purpose of the Study:

  • To develop and validate a single-cell identification method.
  • To enable seamless cancer gene profiling from single cells.
  • To overcome limitations imposed by sample heterogeneity in mutation detection.

Main Methods:

  • Single-cell capture using laser capture microdissection (LCM).
  • Whole genome amplification (WGA) of single cells and bulk populations.
  • Multiplex PCR (AmpliSeq™ SNP HID panel) for cell identification using 136 SNPs.
  • Parallel mutation profiling of 50 cancer-related genes using a hotspot panel.
  • Semiconductor-based massively parallel sequencing.

Main Results:

  • The method successfully identified and profiled a single A549 cancer cell.
  • Genotype concordance probability for cell identification reached 10^31-35.
  • Sequence coverage for single cells was lower than bulk populations, attributed to WGA or allele dropout.
  • Comparative analysis confirmed successful discrimination of a single cell from a bulk population.

Conclusions:

  • The developed approach provides a powerful tool for single-cell analysis.
  • This method effectively addresses tumor sample heterogeneity in somatic mutation detection.
  • Enables precise genomic profiling at the single-cell level for cancer research.