Assessment of megabase-scale somatic copy number variation using single-cell sequencing

With the development and clinical application of genomics, more and more concern is focused on single-cell sequencing. In the process of single-cell sequencing, whole genome amplification is a key step to enrich sample DNA. Previous studies have compared the performance of different whole genome amplification (WGA) strategies on Illumina sequencing platforms, but there is no related research aimed at Ion Proton platform, which is also a popular next-generation sequencing platform. Here by amplifying cells from six cell lines with different karyotypes, we estimated the data features of four common commercial WGA kits (PicoPLEX WGA Kit, GenomePlex Single Cell Whole Genome Amplification Kit, MALBAC Single Cell Whole Genome Amplification Kit, and REPLI-g Single Cell Kit), including median absolute pairwise difference, uniformity, reproducibility, and fidelity, and examined their performance of copy number variation detection. The results showed that both MALBAC and PicoPLEX could yield high-quality data and had high reproducibility and fidelity; and as for uniformity, PicoPLEX was slightly superior to MALBAC.

Download Full-text

EPCO-28. SINGLE-CELL RNA SEQUENCING IDENTIFIES INTRATUMORAL HETEROGENEITY AND ACTIVATION OF PRO-INVASIVE PATHWAYS IN NON-FUNCTIONING PITUITARY ADENOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.027 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi8-vi8

Author(s):

Saket Jain ◽

Elaina Wang ◽

Husam Babikir ◽

Karin Shamardani ◽

Aaron Diaz ◽

...

Keyword(s):

Copy Number Variation ◽

Wnt Signaling ◽

Single Cell ◽

Rna Sequencing ◽

Pituitary Adenomas ◽

Copy Number ◽

Variation Analysis ◽

Copy Number Variation Analysis ◽

Single Cell Rna Sequencing ◽

Number Variation

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise 15% of brain neoplasms. Most PAs are histologically benign but can cause significant morbidity. The genetic profile of PAs is poorly understood. We used single-cell RNA sequencing using the 10X genomic platform to investigate cellular heterogeneity in twelve non-functioning pituitary adenoma samples from nine patients including site-specific (core vs edge) samples from three patients. Our analysis identified discrete clusters of cells associated with activation of specific functional pathways including lipid metabolism, angiogenic, and antigen presentation and processing pathways regardless of location within the tumor. MALT1, a lncRNA associated with increased proliferation and metastasis was ubiquitously expressed amongst these samples. Analysis of the core vs edge samples showed two specific clusters with activated invasion-promoting pathways including PI3k/AKT signaling, Wnt signaling (Wnt6 and FZD4), and epithelial-mesenchymal transition (TGFB1, SMAD1, ZEB1, and SNAI2) in the edge of the tumors. The activated Wnt signaling cascade drove a proinflammatory tumor microenvironment induced by the expression of IL-1, IL-17, and Toll-like receptors (TLR6 and TLR7/8) resulting in suppression of Tregs. Copy number variation analysis using the CONICS-CNV algorithm highlighted distinct chromosomal alterations within our samples that led to insight into clonal variations within each tumor with loss of chromosome 2 an early event in tumorigenesis and gain/loss of chromosome 19 as late events. Mapping the copy number variation analysis with the somatic variant analysis using the Vartrix algorithm identified novel driver mutations within these tumors. These findings help define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized for better management of these tumors.

Download Full-text

Single-cell copy number variation detection

Genome Biology ◽

10.1186/gb-2011-12-8-r80 ◽

2011 ◽

Vol 12 (8) ◽

pp. R80 ◽

Cited By ~ 27

Author(s):

Jiqiu Cheng ◽

Evelyne Vanneste ◽

Peter Konings ◽

Thierry Voet ◽

Joris R Vermeesch ◽

...

Keyword(s):

Copy Number Variation ◽

Single Cell ◽

Copy Number ◽

Number Variation ◽

Copy Number Variation Detection

Download Full-text

Single-Cell-Based Platform for Copy Number Variation Profiling through Digital Counting of Amplified Genomic DNA Fragments

ACS Applied Materials & Interfaces ◽

10.1021/acsami.7b03146 ◽

2017 ◽

Vol 9 (16) ◽

pp. 13958-13964 ◽

Cited By ~ 1

Author(s):

Chunmei Li ◽

Zhilong Yu ◽

Yusi Fu ◽

Yuhong Pang ◽

Yanyi Huang

Keyword(s):

Copy Number Variation ◽

Single Cell ◽

Copy Number ◽

Genomic Dna ◽

Dna Fragments ◽

Number Variation ◽

Digital Counting

Download Full-text

Single-Cell, Genome-wide Sequencing Identifies Clonal Somatic Copy-Number Variation in the Human Brain

Cell Reports ◽

10.1016/j.celrep.2014.07.043 ◽

2014 ◽

Vol 8 (5) ◽

pp. 1280-1289 ◽

Cited By ~ 171

Author(s):

Xuyu Cai ◽

Gilad D. Evrony ◽

Hillel S. Lehmann ◽

Princess C. Elhosary ◽

Bhaven K. Mehta ◽

...

Keyword(s):

Copy Number Variation ◽

Human Brain ◽

Single Cell ◽

Copy Number ◽

Genome Wide ◽

Number Variation ◽

Cell Genome ◽

Single Cell Genome

Download Full-text

Single-Cell, Genome-wide Sequencing Identifies Clonal Somatic Copy-Number Variation in the Human Brain

Cell Reports ◽

10.1016/j.celrep.2015.01.028 ◽

2015 ◽

Vol 10 (4) ◽

pp. 645 ◽

Cited By ~ 12

Author(s):

Xuyu Cai ◽

Gilad D. Evrony ◽

Hillel S. Lehmann ◽

Princess C. Elhosary ◽

Bhaven K. Mehta ◽

...

Keyword(s):

Copy Number Variation ◽

Human Brain ◽

Single Cell ◽

Copy Number ◽

Genome Wide ◽

Number Variation ◽

Cell Genome ◽

Single Cell Genome

Download Full-text

scSVAS: CNV clonal visualization online platform for large scale single-cell genomics

10.1101/2021.06.10.437122 ◽

2021 ◽

Author(s):

Lingxi Chen ◽

Yuhao Qing ◽

Ruikang Li ◽

Chaohui Li ◽

Hechen Li ◽

...

Keyword(s):

Copy Number Variation ◽

Single Cell ◽

Real Time ◽

Copy Number ◽

Large Scale ◽

Single Cell Analysis ◽

Interactive Visualization ◽

Cell Analysis ◽

Single Cell Genomics ◽

Number Variation

The recent advance of single-cell copy number variation analysis plays an essential role in addressing intra-tumor heterogeneity, identifying tumor subgroups, and restoring tumor evolving trajectories at single-cell scale. Pleasant visualization of copy number analysis results boosts productive scientific exploration, validation, and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, scSVAS, for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell analysis. Compared with other tools, scSVAS manifests the most comprehensive functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may make scientific discoveries, share interactive visualization, and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing, and publishing single-cell copy number variation profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.

Download Full-text