Saved in:
Bibliographic Details
Main Authors: Theunis, Koen, Vanuytven, Sebastiaan, Claes, Irene, Geurts, Jarne, Rambow, Florian, Brown, Daniel, Van Der Haegen, Michiel, Marin-Bejar, Oskar, Rogiers, Aljosja, Van Raemdonck, Nina, Leucci, Eleonora, Demeulemeester, Jonas, Sifrim, Alejandro, Marine, Jean-Christophe, Voet, Thierry
Format: Artículo científico
Language:en
Published: Nucleic acids research 2025
Subjects:
Online Access:https://pubmed.ncbi.nlm.nih.gov/40138718/
Tags: Add Tag
No Tags, Be the first to tag this record!
Table of Contents:
  • Single-cell genome and transcriptome sequencing without upfront whole-genome amplification reveals cell state plasticity of melanoma subclones. Theunis, Koen Vanuytven, Sebastiaan Claes, Irene Geurts, Jarne Rambow, Florian Brown, Daniel Van Der Haegen, Michiel Marin-Bejar, Oskar Rogiers, Aljosja Van Raemdonck, Nina Leucci, Eleonora Demeulemeester, Jonas Sifrim, Alejandro Marine, Jean-Christophe Voet, Thierry Single-Cell Analysis Melanoma Humans Animals Transcriptome Mice Cell Plasticity Cell Line, Tumor Gene Expression Profiling Genome, Human DNA Copy Number Variations Genomics Single-cell multi-omics methods enable the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at single-cell and pseudo-bulk levels compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method that explores genetic alterations and their functional consequences in single cells at scale.