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Integrated genome and transcriptome sequencing of the same cell

Single-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transc... Full description

Journal Title: Nature biotechnology 2015, Vol.33 (3), p.285
Main Author: Dey, Siddharth S
Other Authors: Kester, Lennart , Spanjaard, Bastiaan , Bienko, Magda , van Oudenaarden, Alexander
Format: Electronic Article Electronic Article
Language: English
Subjects:
DNA
ID: ISSN: 1087-0156
Zum Text:
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title: Integrated genome and transcriptome sequencing of the same cell
format: Article
creator:
  • Dey, Siddharth S
  • Kester, Lennart
  • Spanjaard, Bastiaan
  • Bienko, Magda
  • van Oudenaarden, Alexander
subjects:
  • Cell Line, Tumor
  • DNA
  • Gene Expression Regulation
  • Genome
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Journal Article
  • Research Support, Non-U.S. Gov't
  • RNA, Messenger
  • Single-Cell Analysis
  • Transcriptome
ispartof: Nature biotechnology, 2015, Vol.33 (3), p.285
description: Single-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transcriptome heterogeneity. We describe a quasilinear amplification strategy to quantify genomic DNA and mRNA from the same cell without physically separating the nucleic acids before amplification. We show that the efficiency of our integrated approach is similar to existing methods for single-cell sequencing of either genomic DNA or mRNA. Further, we find that genes with high cell-to-cell variability in transcript numbers generally have lower genomic copy numbers, and vice versa, suggesting that copy number variations may drive variability in gene expression among individual cells. Applications of our integrated sequencing approach could range from gaining insights into cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissues.
language: eng
source:
identifier: ISSN: 1087-0156
fulltext: no_fulltext
issn:
  • 1087-0156
  • 1546-1696
url: Link


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titleIntegrated genome and transcriptome sequencing of the same cell
creatorDey, Siddharth S ; Kester, Lennart ; Spanjaard, Bastiaan ; Bienko, Magda ; van Oudenaarden, Alexander
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descriptionSingle-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transcriptome heterogeneity. We describe a quasilinear amplification strategy to quantify genomic DNA and mRNA from the same cell without physically separating the nucleic acids before amplification. We show that the efficiency of our integrated approach is similar to existing methods for single-cell sequencing of either genomic DNA or mRNA. Further, we find that genes with high cell-to-cell variability in transcript numbers generally have lower genomic copy numbers, and vice versa, suggesting that copy number variations may drive variability in gene expression among individual cells. Applications of our integrated sequencing approach could range from gaining insights into cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissues.
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abstractSingle-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transcriptome heterogeneity. We describe a quasilinear amplification strategy to quantify genomic DNA and mRNA from the same cell without physically separating the nucleic acids before amplification. We show that the efficiency of our integrated approach is similar to existing methods for single-cell sequencing of either genomic DNA or mRNA. Further, we find that genes with high cell-to-cell variability in transcript numbers generally have lower genomic copy numbers, and vice versa, suggesting that copy number variations may drive variability in gene expression among individual cells. Applications of our integrated sequencing approach could range from gaining insights into cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissues.