Literature DB >> 26741407

Highly multiplexed targeted DNA sequencing from single nuclei.

Marco L Leung1,2, Yong Wang1, Charissa Kim1,2, Ruli Gao1, Jerry Jiang1, Emi Sei1, Nicholas E Navin1,2,3.   

Abstract

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.

Entities:  

Mesh:

Year:  2016        PMID: 26741407      PMCID: PMC4807405          DOI: 10.1038/nprot.2016.005

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  35 in total

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Journal:  Nature       Date:  2011-03-13       Impact factor: 49.962

3.  Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients.

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Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-09       Impact factor: 11.205

Review 4.  Tumor heterogeneity: causes and consequences.

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Journal:  Biochim Biophys Acta       Date:  2009-11-18

Review 5.  Single cell analysis of cancer genomes.

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Journal:  Curr Opin Genet Dev       Date:  2014-02-26       Impact factor: 5.578

6.  High-throughput droplet digital PCR system for absolute quantitation of DNA copy number.

Authors:  Benjamin J Hindson; Kevin D Ness; Donald A Masquelier; Phillip Belgrader; Nicholas J Heredia; Anthony J Makarewicz; Isaac J Bright; Michael Y Lucero; Amy L Hiddessen; Tina C Legler; Tyler K Kitano; Michael R Hodel; Jonathan F Petersen; Paul W Wyatt; Erin R Steenblock; Pallavi H Shah; Luc J Bousse; Camille B Troup; Jeffrey C Mellen; Dean K Wittmann; Nicholas G Erndt; Thomas H Cauley; Ryan T Koehler; Austin P So; Simant Dube; Klint A Rose; Luz Montesclaros; Shenglong Wang; David P Stumbo; Shawn P Hodges; Steven Romine; Fred P Milanovich; Helen E White; John F Regan; George A Karlin-Neumann; Christopher M Hindson; Serge Saxonov; Bill W Colston
Journal:  Anal Chem       Date:  2011-10-28       Impact factor: 6.986

7.  Future medical applications of single-cell sequencing in cancer.

Authors:  Nicholas Navin; James Hicks
Journal:  Genome Med       Date:  2011-05-31       Impact factor: 11.117

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9.  Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

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Journal:  Nature       Date:  2012-11-28       Impact factor: 49.962

10.  Clonal evolution in breast cancer revealed by single nucleus genome sequencing.

Authors:  Yong Wang; Jill Waters; Marco L Leung; Anna Unruh; Whijae Roh; Xiuqing Shi; Ken Chen; Paul Scheet; Selina Vattathil; Han Liang; Asha Multani; Hong Zhang; Rui Zhao; Franziska Michor; Funda Meric-Bernstam; Nicholas E Navin
Journal:  Nature       Date:  2014-07-30       Impact factor: 49.962

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  21 in total

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2.  Scalable whole-genome single-cell library preparation without preamplification.

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Review 3.  Genome evolution in ductal carcinoma in situ: invasion of the clones.

Authors:  Anna K Casasent; Mary Edgerton; Nicholas E Navin
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Review 5.  Advancing Cancer Research and Medicine with Single-Cell Genomics.

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Journal:  Cancer Cell       Date:  2020-04-13       Impact factor: 31.743

Review 6.  Tumour heterogeneity and metastasis at single-cell resolution.

Authors:  Devon A Lawson; Kai Kessenbrock; Ryan T Davis; Nicholas Pervolarakis; Zena Werb
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7.  SCARLET: Single-cell tumor phylogeny inference with copy-number constrained mutation losses.

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Journal:  Cell Syst       Date:  2020-04-22       Impact factor: 10.304

Review 8.  Building a lineage from single cells: genetic techniques for cell lineage tracking.

Authors:  Mollie B Woodworth; Kelly M Girskis; Christopher A Walsh
Journal:  Nat Rev Genet       Date:  2017-01-23       Impact factor: 53.242

9.  Multimodal detection of protein isoforms and nucleic acids from mouse pre-implantation embryos.

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10.  Systematic assessment of the performance of whole-genome amplification for SNP/CNV detection and β-thalassemia genotyping.

Authors:  Fei He; Wanjun Zhou; Ren Cai; Tizhen Yan; Xiangmin Xu
Journal:  J Hum Genet       Date:  2018-02-13       Impact factor: 3.172

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