Genome-Wide Detection of Single-Nucleotide and Copy-Number Variations of a Single Human Cell
Open accessAbstract
Single-Cell Sequencing: With the rapid progress in sequencing technologies, single-cell sequencing is now possible, promising insight into how cell-to-cell heterogeneity affects biological behavior. Achieving adequate genome coverage remains a challenge because single-cell sequencing relies on genome amplification that is prone to sequence bias. Zong et al. (p. 1622 ) report a new amplification method: multiple annealing and looping-based amplification cycles that allowed 93% genome coverage for a human cell. This coverage facilitated accurate detection of point mutations and copy number variations. Lu et al. (p. 1627 ) used the method to sequence 99 sperm cells from a single individual. Mapping the meiotic crossovers revealed a nonrandom distribution with a reduced recombination rate near transcription start sites.
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Rapid technological advances have enabled genome-wide profiling of RNA, DNA, protein, epigenetic modifications, chromatin accessibility, and other molecular events in single cells.
“rapid technological advances have enabled genome-wide profiling of RNA7–10, DNA11–17, protein18–21, epigenetic modifications22–26, chromatin accessibility27,28, and other molecular events29 in single cells.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [12]
MALBAC produces short amplicons (0.5-1.5 kb) compared to multiple displacement amplification (MDA) (10-50 kb amplicons).
“MALBAC produces short amplicons (0.5–1.5kb) compared to multiple displacement amplification (MDA) (10–50 kb amplicons) (Dean et al., 2002; Zhang et al., 2015; Zong et al., 2012)”
From Resolving rates of mutation in the brain using single-neuron genomics (2016) · cites this paper as Zong et al., 2012
These peaks and troughs often occur in the same locations as in MALBAC single cells from an unrelated study by Zong et al. (2012), suggesting that this non-uniformity in genome amplification is inherent to MALBAC.
“These peaks and troughs often occur in the same locations as in MALBAC single cells from an unrelated study by Zong et al. (2012) (Figure 4A), suggesting that this non-uniformity in genome amplification is inherent to MALBAC.”
From Resolving rates of mutation in the brain using single-neuron genomics (2016) · cites this paper as Zong et al. (2012)
Upton et al. single neurons have mean MAPD scores of 0.53 ± 0.16 (SD), compared to MAPD 0.18 ± 0.06 for MALBAC-amplified single cells from Zong et al. (2012) and MAPD 0.33 ± 0.06 for MDA-amplified single neurons from Evrony et al. (2015).
“Upton et al. single neurons have mean MAPD scores of 0.53 ± 0.16 (SD), compared to MAPD 0.18 ± 0.06 for MALBAC-amplified single cells from Zong et al. (2012) and MAPD 0.33 ± 0.06 for MDA-amplified single neurons from Evrony et al. (2015).”
From Resolving rates of mutation in the brain using single-neuron genomics (2016) · cites this paper as Zong et al. (2012)
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Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., Land, S. J., Lu, X., & Ruden, D. M. (2012) · Fly · doi:10.4161/fly.19695 · Cited by 11,816 · see citing works
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,216 · see citing works
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877 · see citing works
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066 · see citing works
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441 · see citing works
Genetic instabilities in human cancers
Lengauer, C., Kinzler, K. W., & Vogelstein, B. (1998) · Nature · doi:10.1038/25292 · Cited by 4,168 · cited 2× · see citing works
“Such dynamic variations are reflected in the genomic heterogeneity among a population of cells, which demands characterization of genomes at the single cell level (4-6).”
BackgroundThe landscape of somatic copy-number alteration across human cancers
Beroukhim, R., Mermel, C. H., Porter, D., Wei, G., Raychaudhuri, S., Donovan, J., Barretina, J., Boehm, J. S., Dobson, J., Urashima, M., et al. (2010) · Nature · doi:10.1038/nature08822 · Cited by 4,017 · see citing works
Isolation of rare circulating tumour cells in cancer patients by microchip technology
Nagrath, S., Sequist, L. V. D., Maheswaran, S., Bell, D. W., Irimia, D., Ulkus, L., Smith, M. R., Kwak, E. L., Digumarthy, S. R., Muzikansky, A., et al. (2007) · Nature · doi:10.1038/nature06385 · Cited by 3,565 · see citing works
Tumour evolution inferred by single-cell sequencing
Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., et al. (2011) · Nature · doi:10.1038/nature09807 · Cited by 2,598 · see citing works
Distant metastasis occurs late during the genetic evolution of pancreatic cancer
Yachida, S., Jones, S., Bozic, I., Antal, T., Leary, R., Fu, B., Kamiyama, M., Hruban, R. H., Eshleman, J. R., Nowak, M. A., et al. (2010) · Nature · doi:10.1038/nature09515 · Cited by 2,502 · see citing works
Massive genomic rearrangement acquired in a single catastrophic event during cancer development
Stephens, P. J., Greenman, C. D., Fu, B., Yang, F., Bignell, G. R., Mudie, L. J., Pleasance, E. D., Lau, K. W., Beare, D., Stebbings, L. A., et al. (2011) · Cell · doi:10.1016/j.cell.2010.11.055 · Cited by 2,414 · see citing works
Genomic instability — an evolving hallmark of cancer
Negrini, S., Gorgoulis, V. G., & Halazonetis, T. D. (2010) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2858 · Cited by 2,397 · see citing works
Drake, J. W., Charlesworth, B., Charlesworth, D., & Crow, J. F. (1998) · Genetics · doi:10.1093/genetics/148.4.1667 · Cited by 1,932 · see citing works
Telenius, H., Carter, N. P., Bebb, C., Nordenskjöld, M., Ponder, B. A. J., & Tunnacliffe, A. (1992) · Genomics · doi:10.1016/0888-7543(92)90147-k · Cited by 1,420 · see citing works
The patterns and dynamics of genomic instability in metastatic pancreatic cancer
Campbell, P. J., Yachida, S., Mudie, L. J., Stephens, P. J., Pleasance, E. D., Stebbings, L. A., Morsberger, L. A., Latimer, C., McLaren, S., Lin, M.-L., et al. (2010) · Nature · doi:10.1038/nature09460 · Cited by 1,317 · see citing works
Maternal Plasma DNA Sequencing Reveals the Genome-Wide Genetic and Mutational Profile of the Fetus
Lo, Y. M. D., Chan, K. C. A., Sun, H., Chen, E. Z., Jiang, P., Lun, F. M. F., Zheng, Y. W. L., Leung, T. Y., Lau, T. K., Cantor, C. R., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3001720 · Cited by 1,102 · see citing works
Analysis of Genetic Inheritance in a Family Quartet by Whole-Genome Sequencing
Roach, J. C., Glusman, G., Smit, A. F. A., Huff, C. D., Hubley, R., Shannon, P. T., Rowen, L., Pant, K. P., Goodman, N., Bamshad, M., et al. (2010) · Science · doi:10.1126/science.1186802 · Cited by 1,084 · see citing works
Dean, F. B., Nelson, J. R., Giesler, T. L., & Lasken, R. S. (2001) · Genome Research · doi:10.1101/gr.180501 · Cited by 1,070 · see citing works
Whole genome amplification from a single cell: implications for genetic analysis.
Zhang, L., Cui, X., Schmitt, K., Hubert, R., Navidi, W. C., & Arnheim, N. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.13.5847 · Cited by 897 · see citing works
Single-Cell Exome Sequencing Reveals Single-Nucleotide Mutation Characteristics of a Kidney Tumor
Xu, X., Hou, Y., Yin, X., Bao, L., Tang, A., Song, L., Li, F., Tsang, S., Wu, K., Wu, H., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.025 · Cited by 667 · see citing works
Variation in genome-wide mutation rates within and between human families
the 1000 Genomes Project (2011) · Nature Genetics · doi:10.1038/ng.862 · Cited by 581 · see citing works
Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm
Hou, Y., Song, L., Zhu, P., Zhang, B., Tao, Y., Xu, X., Li, F., Wu, K., Liang, J., Shao, D., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.028 · Cited by 541 · see citing works
Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm
Wang, J., Fan, H. C., Behr, B. R., & Quake, S. R. (2012) · Cell · doi:10.1016/j.cell.2012.06.030 · Cited by 511 · see citing works
Central dogma at the single-molecule level in living cells
Li, G., & Xie, X. S. (2011) · Nature · doi:10.1038/nature10315 · Cited by 442 · see citing works
Self-citationSequencing genomes from single cells by polymerase cloning
Zhang, K., Martiny, A. C., Reppas, N. B., Barry, K., Malek, J. A., Chisholm, S. W., & Church, G. M. (2006) · Nature Biotechnology · doi:10.1038/nbt1214 · Cited by 411 · see citing works
Noninvasive Whole-Genome Sequencing of a Human Fetus
Kitzman, J. O., Snyder, M. W., Ventura, M., Lewis, A. P., Qiu, R., Simmons, L. E., Gammill, H. S., Rubens, C. E., Santillan, D. A., Murray, J. C., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3004323 · Cited by 410 · see citing works
Whole-genome molecular haplotyping of single cells
Fan, H. C., Wang, J., Potanina, A., & Quake, S. R. (2010) · Nature Biotechnology · doi:10.1038/nbt.1739 · Cited by 364 · see citing works
Multiple Mutation Analyses in Single Tumor Cells with Improved Whole Genome Amplification
Dietmaier, W., Hartmann, A., Wallinger, S., et al. (1999) · American Journal Of Pathology · doi:10.1016/s0002-9440(10)65254-6 · Cited by 256 · see citing works
Identification and correction of systematic error in high-throughput sequence dataPreprint
Meacham, F., Boffelli, D., Dhahbi, J. M., Martin, D. I. K., Singer, M., & Pachter, L. S. (2011) · Nature Precedings · doi:10.1186/1471-2105-12-451 · Cited by 240 · see citing works
Digital MDA for enumeration of total nucleic acid contamination
Blainey, P. C., & Quake, S. R. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1074 · Cited by 123 · see citing works
SW480, a p53 Double-mutant Cell Line Retains Proficiency for Some p53 Functions
Rochette, P. J., Bastien, N., Lavoie, J., Guérin, S. L., & Drouin, R. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.06.033 · Cited by 100 · see citing works
Hanson, E., & Ballantyne, J. (2005) · Analytical Biochemistry · doi:10.1016/j.ab.2005.08.017 · Cited by 73 · see citing works
Direct, genome-wide assessment of DNA mutations in single cells
Gundry, M. C., Li, W., Maqbool, S. B., & Vijg, J. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr949 · Cited by 70 · see citing works
MacArthur, D. (2012) · Nature · doi:10.1038/487427a · Cited by 49 · see citing works
Genetic instability favoring transversions associated with ErbB2-induced mammary tumorigenesis
Liu, S., Liu, W., Jakubczak, J. L., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.052710299 · Cited by 27 · see citing works
Whole genome amplification using single‐primer PCR
Lao, K., Xu, N. L., & Straus, N. A. (2008) · Biotechnology Journal · doi:10.1002/biot.200700253 · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Single-cell chromatin accessibility reveals principles of regulatory variation
Buenrostro, J. D., Wu, B., Litzenburger, U. M., Ruff, D., Gonzales, M. L., Snyder, M. P., Chang, H. Y., & Greenleaf, W. J. (2015) · Nature · doi:10.1038/nature14590 · Cited by 2,308 · see citing works
The Technology and Biology of Single-Cell RNA Sequencing
Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C., & Teichmann, S. A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.005 · Cited by 1,487 · see citing works
Single-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334 · see citing works
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works
Clonal evolution in breast cancer revealed by single nucleus genome sequencing
Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., Chen, K., Scheet, P., Vattathil, S., Liang, H., et al. (2014) · Nature · doi:10.1038/nature13600 · Cited by 1,029 · see citing works
Scaling single-cell genomics from phenomenology to mechanism
Tanay, A., & Regev, A. (2017) · Nature · doi:10.1038/nature21350 · Cited by 792 · see citing works
Revealing the vectors of cellular identity with single-cell genomics
Wagner, A., Regev, A., & Yosef, N. (2016) · Nature Biotechnology · doi:10.1038/nbt.3711 · Cited by 632 · see citing works
Plaks, V., Koopman, C. D., & Werb, Z. (2013) · Science · doi:10.1126/science.1235226 · Cited by 722 · see citing works
Goodrich, J. K., Di Rienzi, S. C., Poole, A. C., Koren, O., Walters, W. A., Caporaso, J. G., Knight, R., & Ley, R. E. (2014) · Cell · doi:10.1016/j.cell.2014.06.037 · Cited by 714 · see citing works
Hou, Y., Guo, H., Cao, C., Li, X., Hu, B., Zhu, P., Wu, X., Wen, L., Tang, F., Huang, Y., et al. (2016) · Cell Research · doi:10.1038/cr.2016.23 · Cited by 647 · see citing works
Design and Analysis of Single-Cell Sequencing Experiments
Grün, D., & van Oudenaarden, A. (2015) · Cell · doi:10.1016/j.cell.2015.10.039 · Cited by 536 · see citing works
Benzodiazepines: use, abuse, and consequences.
Woods, J. H., Katz, J. L., & Winger, G. (1992) · Pharmacological Reviews · doi:10.1016/s0031-6997(25)00468-5 · Cited by 560 · see citing works
Guo, H., Zhu, P., Wu, X., Li, X., Wen, L., & Tang, F. (2013) · Genome Research · doi:10.1101/gr.161679.113 · Cited by 518 · see citing works
Single-cell multiomics: technologies and data analysis methods
Lee, J., Hyeon, D. Y., & Hwang, D. (2020) · Experimental & Molecular Medicine · doi:10.1038/s12276-020-0420-2 · Cited by 524 · see citing works
Spatially resolved transcriptomics and beyond
Crosetto, N., Bienko, M., & van Oudenaarden, A. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3832 · Cited by 509 · see citing works
Integrated genome and transcriptome sequencing of the same cell
Dey, S. S., Kester, L., Spanjaard, B., Bienko, M., & van Oudenaarden, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3129 · Cited by 502 · see citing works
Single-cell analysis tools for drug discovery and development
Heath, J. R., Ribas, A., & Mischel, P. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2015.16 · Cited by 473 · see citing works
Single-cell multiomics: multiple measurements from single cells
Macaulay, I. C., Ponting, C. P., & Voet, T. (2017) · Trends in Genetics · doi:10.1016/j.tig.2016.12.003 · Cited by 451 · see citing works
Ni, X., Zhuo, M., Su, Z., Duan, J., Gao, Y., Wang, Z., Zong, C., Bai, H., Chapman, A. R., Zhao, J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320659110 · Cited by 454 · see citing works
Self-citationMulticlonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing
Casasent, A. K., Schalck, A., Gao, R., Sei, E., Long, A., Pangburn, W., Casasent, T., Meric-Bernstam, F., Edgerton, M. E., & Navin, N. E. (2018) · Cell · doi:10.1016/j.cell.2017.12.007 · Cited by 411 · see citing works
Single Cell Genomics: Advances and Future Perspectives
Macaulay, I. C., & Voet, T. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004126 · Cited by 384 · see citing works
Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells
Guo, F., Li, L., Li, J., Wu, X., Hu, B., Zhu, P., Wen, L., & Tang, F. (2017) · Cell Research · doi:10.1038/cr.2017.82 · Cited by 374 · see citing works
Ubiquitous L1 Mosaicism in Hippocampal Neurons
Upton, K. R., Gerhardt, D. J., Jesuadian, J. S., Richardson, S. R., Sánchez-Luque, F. J., Bodea, G. O., Ewing, A. D., Salvador-Palomeque, C., van der Knaap, M. S., Brennan, P. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.03.026 · Cited by 320 · see citing works
Sequencing thousands of single-cell genomes with combinatorial indexing
Vitak, S. A., Torkenczy, K. A., Rosenkrantz, J. L., Fields, A. J., Christiansen, L., Wong, M. H., Carbone, L., Steemers, F. J., & Adey, A. (2017) · Nature Methods · doi:10.1038/nmeth.4154 · Cited by 294 · see citing works
Cai, X., Evrony, G. D., Lehmann, H. S., Elhosary, P. C., Mehta, B. K., Poduri, A., & Walsh, C. A. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.07.043 · Cited by 318 · see citing works
Genome analyses of single human oocytes
Hou, Y., Fan, W., Yan, L., Li, R., Lian, Y., Huang, J., Li, J., Xu, L., Tang, F., Xie, X. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.11.040 · Cited by 302 · see citing works
Self-citationBreast tumours maintain a reservoir of subclonal diversity during expansion
Minussi, D. C., Nicholson, M. D., Ye, H., Davis, A., Wang, K., Baker, T., Tarabichi, M., Sei, E., Du, H., Rabbani, M., et al. (2021) · Nature · doi:10.1038/s41586-021-03357-x · Cited by 256 · see citing works
Cell lineage analysis in human brain using endogenous retroelements
Evrony, G. D., Lee, E., Mehta, B. K., Benjamini, Y., Johnson, R. M., Cai, X., Yang, L., Haseley, P., Lehmann, H. S., Park, P. J., et al. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.028 · Cited by 269 · see citing works
<i>EGFR</i> Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287 · see citing works
Challenges in measuring and understanding biological noise
Eling, N., Morgan, M. D., & Marioni, J. C. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0130-6 · Cited by 247 · see citing works
Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer
Akdemir, K. C., Le, V. T., Chandran, S., Li, Y., Verhaak, R. G., Beroukhim, R., Campbell, P. J., Chin, L., Dixon, J. R., Futreal, P. A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-019-0564-y · Cited by 283 · see citing works
Single-cell sequencing techniques from individual to multiomics analyses
Kashima, Y., Sakamoto, Y., Kaneko, K., Seki, M., Suzuki, Y., & Suzuki, A. (2020) · Experimental & Molecular Medicine · doi:10.1038/s12276-020-00499-2 · Cited by 270 · see citing works
Building a lineage from single cells: genetic techniques for cell lineage tracking
Woodworth, M. B., Girskis, K. M., & Walsh, C. A. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.159 · Cited by 236 · see citing works
Gole, J., Gore, A., Richards, A., Chiu, Y.-J., Fung, H.-L., Bushman, D., Chiang, H.-I., Chun, J., Lo, Y.-H., & Zhang, K. (2013) · Nature Biotechnology · doi:10.1038/nbt.2720 · Cited by 238 · see citing works
Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity
Liu, L., Liu, C., Quintero, A., Wu, L., Yuan, Y., Wang, M., Cheng, M., Leng, L., Xu, L., Dong, G., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08205-7 · Cited by 243 · see citing works
Frequent loss of heterozygosity in CRISPR-Cas9–edited early human embryos
Alanis-Lobato, G., Zohren, J., McCarthy, A., Fogarty, N. M. E., Kubikova, N., Hardman, E., Greco, M., Wells, D., Turner, J. M. A., & Niakan, K. K. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2004832117 · Cited by 234 · see citing works
Single-cell transcriptome sequencing: recent advances and remaining challenges
Liu, S., & Trapnell, C. (2016) · F1000Research · doi:10.12688/f1000research.7223.1 · Cited by 230 · see citing works
Hoang, M. L., Kinde, I., Tomasetti, C., McMahon, K. W., Rosenquist, T. A., Grollman, A. P., Kinzler, K. W., Vogelstein, B., & Papadopoulos, N. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607794113 · Cited by 224 · see citing works
LINE-1 Evasion of Epigenetic Repression in Humans
Sanchez-Luque, F. J., Kempen, M.-J. H. C., Gerdes, P., Vargas-Landin, D. B., Richardson, S. R., Troskie, R.-L., Jesuadian, J. S., Cheetham, S. W., Carreira, P. E., Salvador-Palomeque, C., et al. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.05.024 · Cited by 161 · see citing works
Resolving rates of mutation in the brain using single-neuron genomics
Evrony, G. D., Lee, E., Park, P. J., & Walsh, C. A. (2016) · eLife · doi:10.7554/elife.12966 · Cited by 163 · see citing works
Calibrating genomic and allelic coverage bias in single-cell sequencing
Zhang, C.-Z., Adalsteinsson, V. A., Francis, J., Cornils, H., Jung, J., Maire, C., Ligon, K. L., Meyerson, M., & Love, J. C. (2015) · Nature Communications · doi:10.1038/ncomms7822 · Cited by 112 · see citing works
Recent advances in single-cell sequencing technologies
Wen, L., & Tang, F. (2022) · Precision Clinical Medicine · doi:10.1093/pcmedi/pbac002 · Cited by 127 · see citing works
Preimplantation Genetic Testing for Monogenic Disorders
De Rycke, M., & Berckmoes, V. (2020) · Genes · doi:10.3390/genes11080871 · Cited by 140 · see citing works
SNES: single nucleus exome sequencing
Leung, M. L., Wang, Y., Waters, J., & Navin, N. E. (2015) · Genome Biology · doi:10.1186/s13059-015-0616-2 · Cited by 112 · see citing works
Single-cell mutational profiling and clonal phylogeny in cancer
Potter, N. E., Ermini, L., Papaemmanuil, E., Cazzaniga, G., Vijayaraghavan, G., Titley, I., Ford, A., Campbell, P., Kearney, L., & Greaves, M. (2013) · Genome Research · doi:10.1101/gr.159913.113 · Cited by 107 · see citing works
Somatic Mutagenesis in Mammals and Its Implications for Human Disease and Aging
Zhang, L., & Vijg, J. (2018) · Annual Review of Genetics · doi:10.1146/annurev-genet-120417-031501 · Cited by 108 · see citing works
Calçada, D., Vianello, D., Giampieri, E., Sala, C., Castellani, G., de Graaf, A., Kremer, B., van Ommen, B., Feskens, E., Santoro, A., et al. (2014) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2014.01.004 · Cited by 97 · see citing works
Comparison of whole genome amplification techniques for human single cell exome sequencing
Borgström, E., Paterlini, M., Mold, J. E., Frisen, J., & Lundeberg, J. (2017) · PLOS ONE · doi:10.1371/journal.pone.0171566 · Cited by 77 · see citing works
Brown, A. J., Snapkov, I., Akbar, R., Pavlović, M., Miho, E., Sandve, G. K., & Greiff, V. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me00071b · Cited by 59 · see citing works
Lodato, M. A., & Walsh, C. A. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz191 · Cited by 56 · see citing works
Rethinking liquid biopsy: Microfluidic assays for mobile tumor cells in human body fluids
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- Authors
- Zong, C., Lu, S., Chapman, A. R., & Xie, X. S.
- Affiliations
- Harvard University (US)
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
- Corresponding author
- Zong, Chenghang
- Chapman, Alec R.
- Xie, X. Sunney
- Venue
- Science
- Published
- 2012-12-21
- Volume
- 338
- Issue
- 6114
- Pages
- 1622-1626
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3600412
- OpenAlex
- W2064977507
- Cited by
- 1,154
- References
- 37
- Citations by year
- 2026: 53 · 2025: 56 · 2024: 67 · 2023: 81 · 2022: 102 · 2021: 92 · 2020: 68 · 2019: 107 · 2018: 77 · 2017: 116 · 2016: 86 · 2015: 93 · 2014: 89 · 2013: 59 · 2012: 3
- FWCI
- 25.82
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- Bill and Melinda Gates Foundation (OPP42867)
- Peking University
- National Institutes of Health
- National Human Genome Research Institute (RC2HG005613, R01HG005097, HG005097-1, HG005613-01)
- National Institute of General Medical Sciences (T32GM008313, GM008313)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- single-cell genomics, copy number variation, single nucleotide variants, MALBAC, cancer cell lines, single-cell sequencing, genome coverage
- MeSH terms
- Adenocarcinoma, DNA, Neoplasm, Humans, Colorectal Neoplasms, Genome, Human, Point Mutation, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Nucleic Acid Amplification Techniques, Cell Line, Tumor, DNA Copy Number Variations, Single-Cell Analysis, High-Throughput Nucleotide Sequencing, Mutation Rate
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