Highly multiplexed targeted DNA sequencing from single nuclei

Nature Protocols

Volumn 11, Issue 2, 2016, Pages 214-235

  Leung, Marco L ^a,b   Wang, Yong ^a   Kim, Charissa ^a,b   Gao, Ruli ^a   Jiang, Jerry ^a   Sei, Emi ^a   Navin, Nicholas E ^a,b  

^a UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^b UNIVERSITY OF TEXAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALLELE; ALLELIC DROPOUT RATE; ARTICLE; BREAST CANCER CELL LINE; CONTROLLED STUDY; DNA BARCODING; DNA LIBRARY; DNA SEQUENCE; FLUORESCENCE ACTIVATED CELL SORTING; GENE AMPLIFICATION; GENETIC VARIABILITY; HUMAN; HUMAN CELL; HUMAN TISSUE; MULTIPLE DISPLACEMENT AMPLIFICATION; NEXT GENERATION SEQUENCING; PRIORITY JOURNAL; SINGLE CELL DNA SEQUENCING; SINGLE NUCLEOTIDE VARIANT; CELL NUCLEUS; HIGH THROUGHPUT SEQUENCING; PROCEDURES; SINGLE CELL ANALYSIS; TIME FACTOR;

CELL NUCLEUS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; SEQUENCE ANALYSIS, DNA; SINGLE-CELL ANALYSIS; TIME FACTORS;

EID: 84961369572     PISSN: 17542189     EISSN: 17502799     Source Type: Journal    
DOI: 10.1038/nprot.2016.005     Document Type: Article

References (35)

1. Koboldt, D.C., Steinberg, K.M., Larson, D.E., Wilson, R.K. & Mardis, E.R. The next-generation sequencing revolution and its impact on genomics. Cell 155, 27-38 (2013).
2. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61-70 (2012).
3. Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330-337 (2012).
4. Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519-525 (2012).
5. Fu, W. et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493, 216-220 (2013).
6. Navin, N. & Hicks, J. Future medical applications of single-cell sequencing in cancer. Genome Med. 3, 31 (2011).
7. Marusyk, A. & Polyak, K. Tumor heterogeneity: causes and consequences. Biochim. Biophys. Acta 1805, 105-117 (2010).
8. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883-892 (2012).
9. Marusyk, A., Almendro, V. & Polyak, K. Intra-tumour heterogeneity: a looking glass for cancer? Nat. Rev. Cancer 12, 323-334 (2012).
10. Gawad, C., Koh, W. & Quake, S.R. Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics. Proc. Natl. Acad. Sci. USA 111, 17947-17952 (2014).
11. Yu, C. et al. Discovery of biclonal origin and a novel oncogene SLC12A5 in colon cancer by single-cell sequencing. Cell Res. 24, 701-712 (2014).
12. Ni, X. et al. Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients. Proc. Natl. Acad. Sci. USA 110, 21083-21088 (2013).
13. Li, Y. et al. Single-cell sequencing analysis characterizes common and cell-lineage-specific mutations in a muscle-invasive bladder cancer. Gigascience 1, 12 (2012).
14. Hou, Y. et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148, 873-885 (2012).
15. Xu, X. et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell 148, 886-895 (2012).
16. Wang, Y. & Navin, N.E. Advances and applications of single-cell sequencing technologies. Mol. Cell 58, 598-609 (2015).
17. Navin, N.E. Cancer genomics: one cell at a time. Genome Biol. 15, 452 (2014).
18. Van Loo, P. & Voet, T. Single cell analysis of cancer genomes. Curr. Opin. Genet. Dev. 24, 82-91 (2014).
19. Saliba, A.E., Westermann, A.J., Gorski, S.A. & Vogel, J. Single-cell RNA-seq: advances and future challenges. Nucleic Acids Res. 42, 8845-8860 (2014).
20. Sandberg, R. Entering the era of single-cell transcriptomics in biology and medicine. Nat. Methods 11, 22-24 (2014).
21. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90-94 (2011).
22. Baslan, T. et al. Genome-wide copy number analysis of single cells. Nat. Protoc. 7, 1024-1041 (2012).
23. Wang, Y. et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512, 155-160 (2014).
24. Leung, M.L., Wang, Y., Waters, J. & Navin, N.E. SNES: single-nucleus exome sequencing. Genome Biol. 16, 55 (2015).
25. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).
26. Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357-359 (2012).
27. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297-1303 (2010).
28. Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842 (2010).
29. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
30. Ng, P.C. & Henikoff, S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 31, 3812-3814 (2003).
31. Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248-249 (2010).
32. Navin, N.E. Delineating cancer evolution with single-cell sequencing. Sci. Transl. Med. 7, 296fs229 (2015).
33. Zong, C., Lu, S., Chapman, A.R. & Xie, X.S. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338, 1622-1626 (2012).
34. Hindson, B.J. et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal. Chem. 83, 8604-8610 (2011).
35. Chen, K. et al. Clinical actionability enhanced through deep targeted sequencing of solid tumors. Clin. Chem. 61, 544-553 (2015).