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 CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing

2016 ◽  
Author(s):  
Ryan L. Collins ◽  
Matthew R. Stone ◽  
Harrison Brand ◽  
Joseph T. Glessner ◽  
Michael E. Talkowski
Keyword(s):  
Copy Number Variation ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Software Tool ◽  
Whole Genome ◽  
Data Types ◽  
Recent Emergence ◽  
Number Variation ◽  
Population Scale

AbstractSummaryCopy number variation (CNV) is a major component of structural differences between individual genomes. The recent emergence of population-scale whole-genome sequencing (WGS) datasets has enabled genome-wide CNV delineation. However, molecular validation at this scale is impractical, so visualization is an invaluable preliminary screening approach when evaluating CNVs. Standardized tools for visualization of CNVs in large WGS datasets are therefore in wide demand.Methods & ResultsTo address this demand, we developed a software tool, CNView, for normalized visualization, statistical scoring, and annotation of CNVs from population-scale WGS datasets. CNView surmounts challenges of sequencing depth variability between individual libraries by locally adapting to cohort-wide variance in sequencing uniformity at any locus. Importantly, CNView is broadly extensible to any reference genome assembly and most current WGS data types.Availability and ImplementationCNView is written in R, is supported on OS X, MS Windows, and Linux, and is freely distributed under the MIT license. Source code and documentation are available from https://github.com/RCollins13/[email protected]

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.

scholarly journals Effective normalization for copy number variation detection from whole genome sequencing

BMC Genomics ◽  
2012 ◽  
Vol 13 (Suppl 6) ◽  
pp. S16 ◽  
Author(s):  
Angel Janevski ◽  
Vinay Varadan ◽  
Sitharthan Kamalakaran ◽  
Nilanjana Banerjee ◽  
Nevenka Dimitrova
Keyword(s):  
Copy Number Variation ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Whole Genome ◽  
Number Variation ◽  
Copy Number Variation Detection

scholarly journals Identification of Copy Number Variation in Domestic Chicken Using Whole-Genome Sequencing Reveals Evidence of Selection in the Genome

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 809
Author(s):  
Donghyeok Seol ◽  
Byung June Ko ◽  
Bongsang Kim ◽  
Han-Ha Chai ◽  
Dajeong Lim ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Breeding Systems ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Genetic Characteristics ◽  
Red Jungle Fowl ◽  
Number Variation

Copy number variation (CNV) has great significance both functionally and evolutionally. Various CNV studies are in progress to find the cause of human disease and to understand the population structure of livestock. Recent advances in next-generation sequencing (NGS) technology have made CNV detection more reliable and accurate at whole-genome level. However, there is a lack of CNV studies on chickens using NGS. Therefore, we obtained whole-genome sequencing data of 65 chickens including Red Jungle Fowl, Cornish (broiler), Rhode Island Red (hybrid), and White Leghorn (layer) from the public databases for CNV region (CNVR) detection. Using CNVnator, a read-depth based software, a total of 663 domesticated-specific CNVRs were identified across autosomes. Gene ontology analysis of genes annotated in CNVRs showed that mainly enriched terms involved in organ development, metabolism, and immune regulation. Population analysis revealed that CN and RIR are closer to each other than WL, and many genes (LOC772271, OR52R1, RD3, ADH6, TLR2B, PRSS2, TPK1, POPDC3, etc.) with different copy numbers between breeds found. In conclusion, this study has helped to understand the genetic characteristics of domestic chickens at CNV level, which may provide useful information for the development of breeding systems in chickens.

Sign in / Sign up

Export Citation Format

Share Document