scholarly journals Quantitative assessment of single-cell whole genome amplification methods for detecting copy number variation using hippocampal neurons

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Luwen Ning ◽  
Zhoufang Li ◽  
Guan Wang ◽  
Wen Hu ◽  
Qingming Hou ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Single Cell ◽  
Copy Number ◽  
Hippocampal Neurons ◽  
Quantitative Assessment ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Genome Amplification ◽  
Number Variation

scholarly journals The comparison of the performance of four whole genome amplification kits on ion proton platform in copy number variation detection

2017 ◽  
Vol 37 (4) ◽  
Author(s):  
Xinyi Zhang ◽  
Bo Liang ◽  
Xiaoyan Xu ◽  
Feifei Zhou ◽  
Lingyin Kong ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Single Cell ◽  
Copy Number ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Genome Amplification ◽  
Single Cell Sequencing ◽  
Ion Proton ◽  
Number Variation ◽  
Copy Number Variation Detection

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.

scholarly journals STR profiling and Copy Number Variation analysis on single, preserved cells using current Whole Genome Amplification methods

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Ann-Sophie Vander Plaetsen ◽  
Lieselot Deleye ◽  
Senne Cornelis ◽  
Laurentijn Tilleman ◽  
Filip Van Nieuwerburgh ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Variation Analysis ◽  
Genome Amplification ◽  
Str Profiling ◽  
Copy Number Variation Analysis ◽  
Number Variation

scholarly journals SCCNV: a software tool for identifying copy number variation from single-cell whole-genome sequencing

2019 ◽  
Author(s):  
Xiao Dong ◽  
Lei Zhang ◽  
Xiaoxiao Hao ◽  
Tao Wang ◽  
Jan Vijg
Keyword(s):  
Copy Number Variation ◽  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
De Novo ◽  
Single Cells ◽  
Software Tool ◽  
Whole Genome ◽  
Number Variation

AbstractBackgroundIdentification of de novo mutations from cell populations requires single-cell whole-genome sequencing (SCWGS). Although many experimental protocols of SCWGS have been developed, few computational tools are available for downstream analysis of different types of somatic mutations, including copy number variation (CNV).ResultsWe developed SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the whole-genome amplification bias.ConclusionsWe demonstrate its performance by analyzing data collected from most of the single-cell amplification methods, including DOP-PCR, MDA, MALBAC and LIANTI. SCCNV is freely available at https://github.com/biosinodx/SCCNV.

scholarly journals Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families

2020 ◽  
Author(s):  
Christopher W. Whelan ◽  
Robert E. Handsaker ◽  
Giulio Genovese ◽  
Seva Kashin ◽  
Monkol Lek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number Variation ◽  
Copy Number ◽  
De Novo ◽  
Whole Genome ◽  
Sequencing Data ◽  
Number Variation ◽  
Structural Mutations ◽  
Or Gene ◽  
Genomic Locations

AbstractTwo intriguing forms of genome structural variation (SV) – dispersed duplications, and de novo rearrangements of complex, multi-allelic loci – have long escaped genomic analysis. We describe a new way to find and characterize such variation by utilizing identity-by-descent (IBD) relationships between siblings together with high-precision measurements of segmental copy number. Analyzing whole-genome sequence data from 706 families, we find hundreds of “IBD-discordant” (IBDD) CNVs: loci at which siblings’ CNV measurements and IBD states are mathematically inconsistent. We found that commonly-IBDD CNVs identify dispersed duplications; we mapped 95 of these common dispersed duplications to their true genomic locations through family-based linkage and population linkage disequilibrium (LD), and found several to be in strong LD with genome-wide association (GWAS) signals for common diseases or gene expression variation at their revealed genomic locations. Other CNVs that were IBDD in a single family appear to involve de novo mutations in complex and multi-allelic loci; we identified 26 de novo structural mutations that had not been previously detected in earlier analyses of the same families by diverse SV analysis methods. These included a de novo mutation of the amylase gene locus and multiple de novo mutations at chromosome 15q14. Combining these complex mutations with more-conventional CNVs, we estimate that segmental mutations larger than 1kb arise in about one per 22 human meioses. These methods are complementary to previous techniques in that they interrogate genomic regions that are home to segmental duplication, high CNV allele frequencies, and multi-allelic CNVs.Author SummaryCopy number variation is an important form of genetic variation in which individuals differ in the number of copies of segments of their genomes. Certain aspects of copy number variation have traditionally been difficult to study using short-read sequencing data. For example, standard analyses often cannot tell whether the duplicated copies of a segment are located near the original copy or are dispersed to other regions of the genome. Another aspect of copy number variation that has been difficult to study is the detection of mutations in the copy number of DNA segments passed down from parents to their children, particularly when the mutations affect genome segments which already display common copy number variation in the population. We develop an analytical approach to solving these problems when sequencing data is available for all members of families with at least two children. This method is based on determining the number of parental haplotypes the two siblings share at each location in their genome, and using that information to determine the possible inheritance patterns that might explain the copy numbers we observe in each family member. We show that dispersed duplications and mutations can be identified by looking for copy number variants that do not follow these expected inheritance patterns. We use this approach to determine the location of 95 common duplications which are dispersed to distant regions of the genome, and demonstrate that these duplications are linked to genetic variants that affect disease risk or gene expression levels. We also identify a set of copy number mutations not detected by previous analyses of sequencing data from a large cohort of families, and show that repetitive and complex regions of the genome undergo frequent mutations in copy number.

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

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.

scholarly journals Whole Genome Survey of Copy Number Variation in the Spontaneously Hypertensive Rat

Hypertension ◽  
2010 ◽  
Vol 55 (5) ◽  
pp. 1231-1238 ◽  
Author(s):  
Fadi J. Charchar ◽  
Michael Kaiser ◽  
Andrew J. Bingham ◽  
Nina Fotinatos ◽  
Fahima Ahmady ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Spontaneously Hypertensive Rat ◽  
Whole Genome ◽  
Spontaneously Hypertensive ◽  
Genome Survey ◽  
Hypertensive Rat ◽  
Number Variation
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