scholarly journals Correction to Supporting Information for Rohrback et al., Submegabase copy number variations arise during cerebral cortical neurogenesis as revealed by single-cell whole-genome sequencing

2018 ◽  
Vol 115 (48) ◽  
pp. E11428-E11428
Keyword(s):  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variations ◽  
Whole Genome ◽  
Cortical Neurogenesis

scholarly journals Submegabase copy number variations arise during cerebral cortical neurogenesis as revealed by single-cell whole-genome sequencing

2018 ◽  
Vol 115 (42) ◽  
pp. 10804-10809 ◽  
Author(s):  
Suzanne Rohrback ◽  
Craig April ◽  
Fiona Kaper ◽  
Richard R. Rivera ◽  
Christine S. Liu ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Cortical Development ◽  
Building Blocks ◽  
Copy Number Variations ◽  
Whole Genome ◽  
Mature Brain ◽  
The Brain

Somatic copy number variations (CNVs) exist in the brain, but their genesis, prevalence, forms, and biological impact remain unclear, even within experimentally tractable animal models. We combined a transposase-based amplification (TbA) methodology for single-cell whole-genome sequencing with a bioinformatic approach for filtering unreliable CNVs (FUnC), developed from machine learning trained on lymphocyte V(D)J recombination. TbA–FUnC offered superior genomic coverage and removed >90% of false-positive CNV calls, allowing extensive examination of submegabase CNVs from over 500 cells throughout the neurogenic period of cerebral cortical development in Mus musculus. Thousands of previously undocumented CNVs were identified. Half were less than 1 Mb in size, with deletions 4× more common than amplification events, and were randomly distributed throughout the genome. However, CNV prevalence during embryonic cortical development was nonrandom, peaking at midneurogenesis with levels triple those found at younger ages before falling to intermediate quantities. These data identify pervasive small and large CNVs as early contributors to neural genomic mosaicism, producing genomically diverse cellular building blocks that form the highly organized, mature brain.

scholarly journals MBRS-59. SINGLE-CELL WHOLE-GENOME SEQUENCING DISSECTS INTRA-TUMOURAL GENOMIC HETEROGENEITY AND CLONAL EVOLUTION IN CHILDHOOD MEDULLOBLASTOMA

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii408-iii408
Author(s):  
Marina Danilenko ◽  
Masood Zaka ◽  
Claire Keeling ◽  
Stephen Crosier ◽  
Rafiqul Hussain ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Single Cell Analysis ◽  
Mutational Analysis ◽  
Single Cells ◽  
Clonal Evolution ◽  
Whole Genome ◽  
Clinically Significant

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.

Abstract 2739: Low-pass whole genome sequencing detects copy number variations in circulating tumor DNA

2017 ◽  
Author(s):  
Xiaoji Chen ◽  
Jill M. Spoerke ◽  
Kathryn Yoh ◽  
Walter C. Darbonne ◽  
Ling-Yuh Huw ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Circulating Tumor Dna ◽  
Copy Number Variations ◽  
Whole Genome ◽  
Low Pass ◽  
Tumor Dna

Defining the heterogeneity landscape of pancreatic cancer copy number alterations.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15776-e15776
Author(s):  
Timour Baslan ◽  
Jie Wu ◽  
Yee Him Cheung ◽  
Jonathan Bermeo ◽  
Nevenka Dimitrova
Keyword(s):  
Pancreatic Cancer ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Somatic Mosaicism ◽  
Copy Number Variations ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Clonal Heterogeneity ◽  
Limited Effectiveness

e15776 Background: Pancreatic cancer (PDAC) is projected to become the second leading cause of cancer related mortality by 2030. Bulk whole genome sequencing studies of PDAC have characterized the landscape of clonal mutations and highlighted the prominence of copy number alterations (CNAs) in PDAC genomes. However, little is known with regards to the extent of sub-clonal heterogeneity of somatic CNAs and it is hypothesized that this heterogeneity is a contributing factor to the limited effectiveness of existing therapies. Methods: We retrieved absolute copy number information using bulk sparse whole genome sequencing of multi-region sampled PDAC samples as well as matching primary-metastasis tumor samples from over 100 patients. In addition, we analyzed copy number variations in a subset of these samples (n = 15) at single-cell resolution (~1000 cells in total). Results: We describe a detailed picture of sub-clonal CNAs genetic heterogeneity. Our results illustrate, among other findings, (1) extensive sub-clonal diversity of CNAs giving rise to many genetically unique sub-clonal cancer populations, (2) somatic mosaicism of chromosomal amplicons in single-cancer cells, (3) variation in the dosage of cancer genes, including the KRAS oncogene, in different tumor sub-clones and (4) somatic alterations, such as amplification of 8q11 containing the metastasis promoting gene IKBKB, associated with primary PDAC progression to liver metastasis. Conclusions: Our results offer an in-depth view of the sub-clonal heterogeneity of somatic CNAs in pancreatic cancer and illustrate ways in which such heterogeneity could lead to therapeutic resistance.

Prevalence and tissue concordance of BRCA2 copy number loss evaluated by single-cell, shallow whole genome sequencing of circulating tumor cells (CTCs) in castration-resistant prostate cancer (CRPC).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5531-5531
Author(s):  
Ethan Barnett ◽  
Joseph Schonhoft ◽  
Nikolaus D. Schultz ◽  
Jerry Lee ◽  
Samir Zaidi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Whole Genome Sequencing ◽  
Single Cell ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Genome Sequencing ◽  
Copy Number ◽  
Cellular Heterogeneity ◽  
Cancer Tissue ◽  
Whole Genome

5531 Background: Genomic studies have shown that up to 25% of prostate cancer tissue specimens harbor alterations in DNA Damage Repair (DDR) genes, which may sensitize the tumor to poly ADP-ribose polymerase inhibitors (PARPi). Trials evaluating PARPi in patients with DDR deficiencies have shown varied response rates and differences regarding which genomic alterations predict for sensitivity to these agents, with the majority of objective responses seen in BRCA2-altered tumors. These results highlight the need to develop biomarker assays which can predict benefit from PARPi therapy. Tissue and cell-free DNA (cfDNA) have been the most utilized sources of tumor material for analysis in this setting, but success rates of obtaining sufficient tumor for analysis from bone are low and detecting tumor-derived copy number variants (CNVs) in cfDNA is challenging. Circulating tumor cells (CTCs) represent an alternate source of genetic information, for which assays are available to isolate and sequence individual cells in a manner that eliminates background noise from stroma and healthy cells, while capturing inter-cellular heterogeneity. Methods: Blood samples, collected from 138 progressing metastatic CRPC patients within 30 days of a pre-treatment biopsy intended for sequencing using MSK-IMPACT, were sent to EPIC Sciences for CTC analysis. Detected CTCs underwent single cell, low pass whole genome sequencing. Prevalence and concordance of BRCA2 copy-loss, regardless of whether single copy or homozygous, was compared in matched tissue and CTC samples. Results: BRCA2 copy-loss was identified in 21% (23/108) and 50% (58/115) of successfully sequenced tissue and CTC samples, respectively. In the 58 patients with CTC-detected BRCA2 loss, BRCA2 loss was detected in 36% (220/565) of the sequenced CTCs, representing a median of 46% (range 4-100%) of CTCs found in each individual sample. When both sequencing assays were successful, BRCA2 loss was detected in CTCs in 84% (16/19) of the tissue-positive cases, whereas tissue sequencing detected BRCA2 loss in 35% (16/46) of CTC-positive cases. Conclusions: Data from this study supports the notion that single-cell CTC sequencing can detect BRCA2 copy-loss at a high frequency, including cases that were negative in tissue, while also characterizing inter-cellular heterogeneity. Further studies will investigate whether CTC BRCA2 copy-loss can predict the likelihood of response to PARPi.

scholarly journals A Comparison of Tools for Copy-Number Variation Detection in Germline Whole Exome and Whole Genome Sequencing Data

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6283
Author(s):  
Migle Gabrielaite ◽  
Mathias Husted Torp ◽  
Malthe Sebro Rasmussen ◽  
Sergio Andreu-Sánchez ◽  
Filipe Garrett Vieira ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Reference Sample ◽  
Snp Array ◽  
Copy Number Variations ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Standard Reference Sample ◽  
Whole Exome

Copy-number variations (CNVs) have important clinical implications for several diseases and cancers. Relevant CNVs are hard to detect because common structural variations define large parts of the human genome. CNV calling from short-read sequencing would allow single protocol full genomic profiling. We reviewed 50 popular CNV calling tools and included 11 tools for benchmarking in a reference cohort encompassing 39 whole genome sequencing (WGS) samples paired current clinical standard—SNP-array based CNV calling. Additionally, for nine samples we also performed whole exome sequencing (WES), to address the effect of sequencing protocol on CNV calling. Furthermore, we included Gold Standard reference sample NA12878, and tested 12 samples with CNVs confirmed by multiplex ligation-dependent probe amplification (MLPA). Tool performance varied greatly in the number of called CNVs and bias for CNV lengths. Some tools had near-perfect recall of CNVs from arrays for some samples, but poor precision. Several tools had better performance for NA12878, which could be a result of overfitting. We suggest combining the best tools also based on different methodologies: GATK gCNV, Lumpy, DELLY, and cn.MOPS. Reducing the total number of called variants could potentially be assisted by the use of background panels for filtering of frequently called variants.

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