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RNA-seq

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...

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Updated: Jul 17, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics.

Jinhyun Kim¹, Sungsik Kim², Huiran Yeom³

¹Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea.

Nature Communications

|August 29, 2023

Summary

This summary is machine-generated.

Barcoded Multiple Displacement Amplification (bMDA) enhances spatial genomics by enabling high-coverage DNA analysis of multiple samples simultaneously. This scalable technique aids in understanding cancer cell evolution within specific tissue microenvironments.

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Last Updated: Jul 17, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

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Published on: January 7, 2020

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Published on: August 11, 2011

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Area of Science:

Genomics
Cancer Research
Molecular Biology

Background:

Understanding the spatial distribution of genetic mutations within tumors is crucial for deciphering cellular heterogeneity and tumor evolution.
Existing methods like Multiple Displacement Amplification (MDA) provide high genome coverage but lack the multiplexing capacity for large-scale spatial genomic studies.

Purpose of the Study:

To introduce barcoded Multiple Displacement Amplification (bMDA), a novel technique for high-coverage genomic analysis of low-input DNA with enhanced multiplexing capabilities.
To overcome bottlenecks in spatial genomics by streamlining library preparation for simultaneous analysis of multiple samples.

Main Methods:

Development and implementation of barcoded Multiple Displacement Amplification (bMDA), integrating cell barcoding directly into the MDA process.
Application of bMDA to triple-negative breast cancer tissues for integrative spatial analysis.
Comprehensive analysis of genomic alterations including copy number variations, single nucleotide variations, structural variations, and kataegis signatures within spatial microniches.

Main Results:

bMDA successfully achieved high-coverage genomic analysis from low-input DNA samples.
The technique significantly improved multiplexing capabilities, enabling simultaneous analysis of multiple spatial regions.
Integrative spatial analysis of triple-negative breast cancer revealed subclonal evolutionary relationships within distinct microniches.

Conclusions:

bMDA is a scalable technology that overcomes key limitations in current spatial genomics approaches.
This method facilitates detailed assessment of genomic alterations and subclonal architecture in a spatial context.
bMDA holds significant potential to advance the field of spatial genomics and cancer research.