Interactive analysis and assessment of single-cell copy-number variations

Garvin, Tyler; Aboukhalil, Robert; Kendall, Jude; Baslan, Timour; Atwal, Gurinder S.; Hicks, James; Wigler, Michael; Schatz, Michael C.

doi:10.1038/nmeth.3578

Cited by 242 publications

(331 citation statements)

References 29 publications

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“…As an additional confirmation of the deletion variant, we subjected a portion of the MDA-amplified single cell genomic DNA that was used for SLAV-seq to shallow whole genome sequencing. Consistent with previous reports 24 , we observed high variability in the normalized read count per 500kb bin across the genome [coefficient of variation (SD/mean) of 0.65, 0.77 and 1.01 for samples 48, 53, and 153, respectively] due to unequal amplification from single cell whole genome amplification. Nevertheless, we observed a reduction in normalized read counts at position chr7:108.7–109.5MB, consistent with the SLAV found in that position in sample 153 (Fig 4A, right).…”

Section: L1 Sequences Are Hotspots For Somatic Cnvs That Are Createdsupporting

confidence: 91%

L1-associated genomic regions are deleted in somatic cells of the healthy human brain

et al. 2016

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The healthy human brain is a mosaic of varied genomes. L1 retrotransposition is known to create mosaicism by inserting L1 sequences into new locations of somatic cell genomes. Using a machine learning-based, single-cell sequencing approach, we discovered that Somatic L1-Associated Variants (SLAVs) are actually composed of two classes: L1 retrotransposition insertions and retrotransposition-independent L1-associated variants. We demonstrate that a subset of SLAVs are, in fact, somatic deletions generated by L1 endonuclease cutting activity. Retrotransposition- independent rearrangements within inherited L1s resulted in the deletion of proximal genomic regions. These rearrangements were resolved by microhomology-mediated repair, which suggests that L1-associated genomic regions are hotspots for somatic copy number variants in the brain and therefore a heritable genetic contributor to somatic mosaicism. We demonstrate that SLAVs are present in crucial neural genes, such as DLG2/PSD93, and affect between 44–63% of cells of the cells in the healthy brain.

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Section: L1 Sequences Are Hotspots For Somatic Cnvs That Are Createdsupporting

confidence: 91%

L1-associated genomic regions are deleted in somatic cells of the healthy human brain

et al. 2016

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“…For each sample, read counts per bin were normalized proportionally to make the total read counts to 1 million, followed by GC content adjustment for each bin. Sample codes for this analysis have been published previously [33,34]. Median values of each bin read counts of WBC controls were used to exclude low coverage bins from downstream analyses (<100 reads).…”

Section: Methodsmentioning

confidence: 99%

“…Ratios between test samples and WBC controls were calculated and reported after Log2 transformation. Chromosomal segments were predicted using R Bioconductor package DNAcopy (alpha = 0.05), see the sample code from the literature [33,34] which determined break points where DNA copy number changed. LSTs were calculated as number of chromosomal breaks between adjacent regions of at least 10 Mb.…”

Section: Methodsmentioning

confidence: 99%

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis

et al. 2016

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Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.

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“…Then, the clean sequence reads are aligned to the human reference genome (hg38) with Burrows-Wheeler aligner MEM (22), ordered and indexed using SAMtools (23). The copy number alteration (CNA) status of a single cell is analyzed using Ginkgo (24). Briefly, the mapped reads are binned by chromosome position, normalized for GC biases and other amplification artifacts, and then segmented to identify chromosome regions with consistent copy number status.…”

Section: Bioinformatic Analysismentioning

confidence: 99%

Detection of Urothelial Bladder Carcinoma via Microfluidic Immunoassay and Single-Cell DNA Copy-Number Alteration Analysis of Captured Urinary-Exfoliated Tumor Cells

Chen

et al. 2018

Cancer Research

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The increasing incidence of bladder cancer and its high rate of recurrence over a 5-year period necessitate the need for diagnosis and surveillance amelioration. Cystoscopy and urinary cytology are the current tools, and molecular techniques such as BTA stat, NMP22, survivin mRNA, and urovysion FISH have attracted attention; however, they suffer from insufficient sensitivity or specificity. We developed a novel microfluidic approach for harvesting intact urinary-exfoliated tumor cells (UETC), either individually or in clusters, in a clean and segregated environment, which is crucial to minimize crosscontamination and misreads. To reliably and accurately identify UETC, our quantitative immunoassay involved concurrent use of two oncoproteins CK20 and CD44v6 antigen. CK20 is an intermediate filament protein overexpressed in urothelial tumors, and CD44v6 is a membrane adhesion molecule closely associated with cell invasion, tumor progression, and metastatic spread. Single-cell whole-genome sequencing on 12 captured UETCs and copy number alteration analysis showed that 11/12 (91.7%) of the immunofluorescence-identified UETCs possessed genomic instability. A total of 79 patients with bladder cancer and 43 age-matched normal controls (NC) were enrolled in the study. We detected considerably higher UETC counts in patients with bladder cancer versus the NC group [53.3 (10.7-1001.9) vs. 0.0 (0-3.0) UETCs/10 mL; P < 0.0001]. For bladder cancer detection, a stratified 10-fold cross-validation of training data reveals an overall predictive accuracy of 0.84 [95% confidence interval (CI), 0.76-0.93] with an 89.8% (95% CI, 71.5%-86.4%) for sensitivity and 71.5% (95% CI, 59.7%-83.3%) for specificity. Overall, the microfluidic immunoassay demonstrates increased sensitivity and specificity compared with other techniques for the detection of bladder cancer.Significance: A unique and promising diagnostic assay for bladder cancer is proposed with potential clinical utility as a complement for cytology. Cancer Res; 78(14); 4073-85. Ó2018 AACR.

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Interactive analysis and assessment of single-cell copy-number variations

Cited by 242 publications

References 29 publications

L1-associated genomic regions are deleted in somatic cells of the healthy human brain

L1-associated genomic regions are deleted in somatic cells of the healthy human brain

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis

Detection of Urothelial Bladder Carcinoma via Microfluidic Immunoassay and Single-Cell DNA Copy-Number Alteration Analysis of Captured Urinary-Exfoliated Tumor Cells

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