Single-cell isolation from cell suspensions and whole genome amplification from single cells to provide templates for CGH analysis

2007 ◽  
Vol 2 (12) ◽  
pp. 3173-3184 ◽  
Author(s):  
Jochen B Geigl ◽  
Michael R Speicher
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Cell Isolation ◽  
Cell Suspensions ◽  
Whole Genome ◽  
Genome Amplification ◽  
Single Cell Isolation

scholarly journals Combined Molecular Genetic and Cytogenetic Analysis from Single Cells after Isothermal Whole-Genome Amplification

2011 ◽  
Vol 57 (7) ◽  
pp. 1032-1041 ◽  
Author(s):  
Thomas Kroneis ◽  
Jochen B Geigl ◽  
Amin El-Heliebi ◽  
Martina Auer ◽  
Peter Ulz ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Molecular Genetic ◽  
Target Cells ◽  
Whole Genome ◽  
Single Cell Level ◽  
Cell Level ◽  
Genome Amplification

BACKGROUND Analysis of chromosomal aberrations or single-gene disorders from rare fetal cells circulating in the blood of pregnant women requires verification of the cells' genomic identity. We have developed a method enabling multiple analyses at the single-cell level that combines verification of the genomic identity of microchimeric cells with molecular genetic and cytogenetic diagnosis. METHODS We used a model system of peripheral blood mononuclear cells spiked with a colon adenocarcinoma cell line and immunofluorescence staining for cytokeratin in combination with DNA staining with the nuclear dye TO-PRO-3 in a preliminary study to define candidate microchimeric (tumor) cells in Cytospin preparations. After laser microdissection, we performed low-volume on-chip isothermal whole-genome amplification (iWGA) of single and pooled cells. RESULTS DNA fingerprint analysis of iWGA aliquots permitted successful identification of all analyzed candidate microchimeric cell preparations (6 samples of pooled cells, 7 samples of single cells). Sequencing of 3 single-nucleotide polymorphisms was successful at the single-cell level for 20 of 32 allelic loci. Metaphase comparative genomic hybridization (mCGH) with iWGA products of single cells showed the gains and losses known to be present in the genomic DNA of the target cells. CONCLUSIONS This method may be instrumental in cell-based noninvasive prenatal diagnosis. Furthermore, the possibility to perform mCGH with amplified DNA from single cells offers a perspective for the analysis of nonmicrochimeric rare cells exhibiting genomic alterations, such as circulating tumor cells.

scholarly journals Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

2017 ◽  
Author(s):  
Tamir Biezuner ◽  
Ofir Raz ◽  
Shiran Amir ◽  
Lilach Milo ◽  
Rivka Adar ◽  
...  
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Targeted Sequencing ◽  
Whole Genome ◽  
Genome Coverage ◽  
Genome Amplification ◽  
Cell Experiment ◽  
Commercial Kits ◽  
Genomic Regions

AbstractAdvances in biochemical technologies have led to a boost in the field of single cell genomics. Observation of the genome at a single cell resolution is currently achieved by pre-amplification using whole genome amplification (WGA) techniques that differ by their biochemical aspects and as a result by biased amplification of the original molecule. Several comparisons between commercially available single cell dedicated WGA kits (scWGA) were performed, however, these comparisons are costly, were only performed on selected scWGA kit and more notably, are limited by the number of analyzed cells, making them limited for reproducibility analysis. We benchmarked an economical assay to compare all commercially available scWGA kits that is based on targeted sequencing of thousands of genomic regions, including highly mutable genomic regions (microsatellites), from a large cohort of human single cells (125 cells in total). Using this approach, we could analyze the genome coverage, the reproducibility of genome coverage and the error rate of each kit. Our experimental design provides an affordable and reliable comparative assay that simulates a real single cell experiment. Results demonstrate the needfor a dedicated kit selection depending on the desired single cell assay.

scholarly journals SureTypeSC - A Random Forest and Gaussian Mixture predictor of high confidence genotypes in single cell data

2018 ◽  
Author(s):  
Ivan Vogel ◽  
Robert C. Blanshard ◽  
Eva R. Hoffmann
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Snp Array ◽  
Lineage Tracing ◽  
Whole Genome ◽  
High Confidence ◽  
High Quality ◽  
Genome Amplification

AbstractMotivationAccurate genotyping of DNA from a single cell is required for applications such asde novomutation detection, linkage analysis and lineage tracing. However, achieving high precision genotyping in the single cell environment is challenging due to the errors caused by whole genome amplification. Two factors make genotyping from single cells using single nucleotide polymorphism (SNP) arrays challenging. The lack of a comprehensive single cell dataset with a reference genotype and the absence of genotyping tools specifically designed to detect noise from the whole genome amplification step. Algorithms designed for bulk DNA genotyping cause significant data loss when used for single cell applications.ResultsIn this study, we have created a resource of 28.7 million SNPs, typed at high confidence from whole genome amplified DNA from single cells using the Illumina SNP bead array technology. The resource is generated from 104 single cells from two cell lines that are available from the Coriell repository. We used mother-father-proband (trio) information from multiple technical replicates of bulk DNA to establish a high quality reference genotype for the two cell lines on the SNP array. This enabled us to develop SureTypeSC - a two-stage machine learning algorithm that filters a substantial part of the noise, thereby retaining the majority of the high quality SNPs. SureTypeSC also provides a simple statistical output to show the confidence of a particular single cell genotype using Bayesian [email protected]

scholarly journals Accurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands

2021 ◽  
Vol 118 (8) ◽  
pp. e2013106118
Author(s):  
Dong Xing ◽  
Longzhi Tan ◽  
Chi-Han Chang ◽  
Heng Li ◽  
X. Sunney Xie
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Human Sperm ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Amplification ◽  
Human Blood Cells ◽  
Human Neurons

Single-nucleotide variants (SNVs), pertinent to aging and disease, occur sporadically in the human genome, hence necessitating single-cell measurements. However, detection of single-cell SNVs suffers from false positives (FPs) due to intracellular single-stranded DNA damage and the process of whole-genome amplification (WGA). Here, we report a single-cell WGA method termed multiplexed end-tagging amplification of complementary strands (META-CS), which eliminates nearly all FPs by virtue of DNA complementarity, and achieved the highest accuracy thus far. We validated META-CS by sequencing kindred cells and human sperm, and applied it to other human tissues. Investigation of mature single human neurons revealed increasing SNVs with age and potentially unrepaired strand-specific oxidative guanine damage. We determined SNV frequencies along the genome in differentiated single human blood cells, and identified cell type-dependent mutational patterns for major types of lymphocytes.

scholarly journals SureTypeSC—a Random Forest and Gaussian mixture predictor of high confidence genotypes in single-cell data

2019 ◽  
Vol 35 (23) ◽  
pp. 5055-5062 ◽  
Author(s):  
Ivan Vogel ◽  
Robert C Blanshard ◽  
Eva R Hoffmann
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Supplementary Information ◽  
De Novo Mutation ◽  
Whole Genome ◽  
High Confidence ◽  
High Quality ◽  
Genome Amplification

Abstract Motivation Accurate genotyping of DNA from a single cell is required for applications such as de novo mutation detection, linkage analysis and lineage tracing. However, achieving high precision genotyping in the single-cell environment is challenging due to the errors caused by whole-genome amplification. Two factors make genotyping from single cells using single nucleotide polymorphism (SNP) arrays challenging. The lack of a comprehensive single-cell dataset with a reference genotype and the absence of genotyping tools specifically designed to detect noise from the whole-genome amplification step. Algorithms designed for bulk DNA genotyping cause significant data loss when used for single-cell applications. Results In this study, we have created a resource of 28.7 million SNPs, typed at high confidence from whole-genome amplified DNA from single cells using the Illumina SNP bead array technology. The resource is generated from 104 single cells from two cell lines that are available from the Coriell repository. We used mother–father–proband (trio) information from multiple technical replicates of bulk DNA to establish a high quality reference genotype for the two cell lines on the SNP array. This enabled us to develop SureTypeSC—a two-stage machine learning algorithm that filters a substantial part of the noise, thereby retaining the majority of the high quality SNPs. SureTypeSC also provides a simple statistical output to show the confidence of a particular single-cell genotype using Bayesian statistics. Availability and implementation The implementation of SureTypeSC in Python and sample data are available in the GitHub repository: https://github.com/puko818/SureTypeSC Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Accurate Genomic Variant Detection in Single Cells with Primary Template-Directed Amplification

2020 ◽  
Author(s):  
Veronica Gonzalez ◽  
Sivaraman Natarajan ◽  
Yuntao Xia ◽  
David Klein ◽  
Robert Carter ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Variant Calling ◽  
Whole Genome ◽  
Genome Amplification ◽  
Genome Wide ◽  
Variant Detection ◽  
Genomic Variant

AbstractImprovements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here we present primary template-directed amplification (PTA), a new isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the new types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a new tool for mapping genome-wide interactions of mutagens with single living human cells at base pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate whole genome amplification, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.

scholarly journals Evaluation of whole genome amplification and bioinformatic methods for the characterization of Leishmania genomes at a single cell level

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hideo Imamura ◽  
Pieter Monsieurs ◽  
Marlene Jara ◽  
Mandy Sanders ◽  
Ilse Maes ◽  
...  
Keyword(s):  
Single Cell ◽  
Leishmania Donovani ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Second Step ◽  
Whole Genome ◽  
Dna Testing ◽  
Cell Level ◽  
Genome Amplification

Abstract Here, we report a pilot study paving the way for further single cell genomics studies in Leishmania. First, the performances of two commercially available kits for Whole Genome Amplification (WGA), PicoPLEX and RepliG were compared on small amounts of Leishmania donovani DNA, testing their ability to preserve specific genetic variations, including aneuploidy levels and SNPs. We show here that the choice of WGA method should be determined by the planned downstream genetic analysis, PicoPLEX and RepliG performing better for aneuploidy and SNP calling, respectively. This comparison allowed us to evaluate and optimize corresponding bio-informatic methods. As PicoPLEX was shown to be the preferred method for studying single cell aneuploidy, this method was applied in a second step, on single cells of L. braziliensis, which were sorted by fluorescence activated cell sorting (FACS). Even sequencing depth was achieved in 28 single cells, allowing accurate somy estimation. A dominant karyotype with three aneuploid chromosomes was observed in 25 cells, while two different minor karyotypes were observed in the other cells. Our method thus allowed the detection of aneuploidy mosaicism, and provides a solid basis which can be further refined to concur with higher-throughput single cell genomic methods.

scholarly journals Comparison of seven single cell whole genome amplification commercial kits using targeted sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tamir Biezuner ◽  
Ofir Raz ◽  
Shiran Amir ◽  
Lilach Milo ◽  
Rivka Adar ◽  
...  
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Genomic Sequence ◽  
Single Cells ◽  
Targeted Sequencing ◽  
Whole Genome ◽  
Cell Level ◽  
Genome Amplification ◽  
Commercial Kits ◽  
Commercial Kit

AbstractAdvances in whole genome amplification (WGA) techniques enable understanding of the genomic sequence at a single cell level. Demand for single cell dedicated WGA kits (scWGA) has led to the development of several commercial kit. To this point, no robust comparison of all available kits was performed. Here, we benchmark an economical assay, comparing all commercially available scWGA kits. Our comparison is based on targeted sequencing of thousands of genomic loci, including highly mutable regions, from a large cohort of human single cells. Using this approach we have demonstrated the superiority of Ampli1 in genome coverage and of RepliG in reduced error rate. In summary, we show that no single kit is optimal across all categories, highlighting the need for a dedicated kit selection in accordance with experimental requirements.

scholarly journals Evaluation of whole genome amplification and bioinformatic methods for the characterization of Leishmania genomes at a single cell level

2020 ◽  
Author(s):  
Hideo Imamura ◽  
Marlene Jara ◽  
Pieter Monsieurs ◽  
Mandy Sanders ◽  
Ilse Maes ◽  
...  
Keyword(s):  
Single Cell ◽  
Leishmania Donovani ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Second Step ◽  
Whole Genome ◽  
Dna Testing ◽  
Cell Level ◽  
Genome Amplification

AbstractHere, we report a pilot study paving the way for further single cell genomics studies in Leishmania. First, the performances of two commercially available kits for Whole Genome Amplification (WGA), PicoPlex and RepliG was compared on small amounts of Leishmania donovani DNA, testing their ability to preserve specific genetic variations, including aneuploidy levels and SNPs. We show here that the choice of WGA method should be determined by the planned downstream genetic analysis, Picoplex and RepliG performing better for aneuploidy and SNP calling, respectively. This comparison allowed us to evaluate and optimize corresponding bio-informatic methods. As PicoPlex was shown to be the preferred method for studying single cell aneuploidy, this method was applied in a second step, on single cells of L. braziliensis, which were sorted by fluorescence activated cell sorting (FACS). Even sequencing depth was achieved in 28 single cells, allowing accurate somy estimation. A dominant karyotype with three aneuploid chromosomes was observed in 25 cells, while two different minor karyotypes were observed in the other cells. Our method thus allowed the detection of aneuploidy mosaicism, and provides a solid basis which can be further refined to concur with higher-throughput single cell genomic methods.

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