Dataset Information

Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI).

ABSTRACT: Single-cell genomics is important for biology and medicine. However, current whole-genome amplification (WGA) methods are limited by low accuracy of copy-number variation (CNV) detection and low amplification fidelity. Here we report an improved single-cell WGA method, Linear Amplification via Transposon Insertion (LIANTI), which outperforms existing methods, enabling micro-CNV detection with kilobase resolution. This allowed direct observation of stochastic firing of DNA replication origins, which differs from cell to cell. We also show that the predominant cytosine-to-thymine mutations observed in single-cell genomics often arise from the artifact of cytosine deamination upon cell lysis. However, identifying single-nucleotide variations (SNVs) can be accomplished by sequencing kindred cells. We determined the spectrum of SNVs in a single human cell after ultraviolet radiation, revealing their nonrandom genome-wide distribution.

SUBMITTER: Chen C

PROVIDER: S-EPMC5538131 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI).

Chen Chongyi C Xing Dong D Xing Dong D Tan Longzhi L Li Heng H Zhou Guangyu G Huang Lei L Xie X Sunney XS

Science (New York, N.Y.) 20170401 6334

Single-cell genomics is important for biology and medicine. However, current whole-genome amplification (WGA) methods are limited by low accuracy of copy-number variation (CNV) detection and low amplification fidelity. Here we report an improved single-cell WGA method, Linear Amplification via Transposon Insertion (LIANTI), which outperforms existing methods, enabling micro-CNV detection with kilobase resolution. This allowed direct observation of stochastic firing of DNA replication origins, wh ...[more]

PMID: 28408603

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Project description:Combining whole genome amplification (WGA) methods with novel laser-based microdissection techniques has made it possible to exploit recent progress in molecular knowledge of cancer development and progression. However, WGA of one or a few cells has not yet been optimized and systematically evaluated for samples routinely processed in tumor pathology. We therefore studied the value of established WGA protocols in comparison to an improved PEP (I-PEP) PCR method in defined numbers of flow-sorted and microdissected tumor cells obtained both from frozen as well as formalin-fixed and paraffin-embedded tissue sections. In addition, the feasibility of I-PEP-PCR for mutation analysis was tested using clusters of 50-100 unfixed tumor cells obtained by touch preparation of ten breast carcinomas by conventional sequencing of exon 7 and 8 of the p53 gene. Finally, immunocytochemically stained microdissected single disseminated tumor cells from bone marrow aspirates were investigated with respect to mutations in codon 12 of Ki-ras by restriction fragment length polymorphism (RFLP)-PCR after I-PEP-PCR. The modified I-PEP-PCR protocol was superior to the original PEP-PCR and DOP-PCR protocols concerning amplification of DNA from one cell (efficiency rate I-PEP-PCR 40% versus PEP-PCR 15% and DOP-PCR 30%) and five cells (efficiency rate I-PEP-PCR 100% versus PEP-PCR 33% and DOP-PCR 20%). Preamplification by I-PEP allowed 100% sequence accuracy in > 4000 sequenced base pairs and Ki-ras mutation detection in isolated single disseminated tumor cells. For reliable microsatellite analysis of I-PEP-preamplified DNA, at least 10 unfixed cells from fluorescence-activated cell sorting, 10 cells from frozen tissue, or at least 30 cells from formalin-fixed and paraffin-embedded tissue sections were required. Thus, I-PEP-PCR allowed multiple reliable microsatellite analyses suited for microsatellite instability and losses of heterozygosity and mutation analysis even at the single cell level, rendering this technique a powerful new tool for molecular analyses in diagnostic and experimental tumor pathology.

Dataset Information

Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI).

Publications

Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI).

Similar Datasets

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