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Comparing Copy Number Variations and SNPs

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

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Related Experiment Video

Updated: Apr 15, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Optimizing sparse sequencing of single cells for highly multiplex copy number profiling.

Timour Baslan¹, Jude Kendall², Brian Ward³

¹Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA; Department of Molecular and Cellular Biology, Stony Brook University, Stony Brook, New York 11790, USA;

Genome Research

|April 11, 2015

Summary

This summary is machine-generated.

This study presents an optimized method for single-cell DNA analysis, enabling affordable genome-wide copy number variation profiling of many cells. This advance aids in understanding genetic heterogeneity and cell lineage in fields like cancer research.

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Detection of Copy Number Alterations Using Single Cell Sequencing

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Published on: February 17, 2017

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Single-cell genome analysis is crucial for understanding cellular heterogeneity in cancer, neurobiology, and development.
Affordable, high-throughput single-cell analysis is needed for transformative impact.
Copy number variation (CNV) detection is feasible with sparse sequencing coverage.

Purpose of the Study:

To develop and optimize a cost-effective method for single-cell DNA amplification and library preparation.
To enable genome-wide CNV profiling of a large number of individual cells using multiplexed sequencing.
To apply the method to cancer research for revealing genetic heterogeneity and clonal evolution.

Main Methods:

Combined bioinformatic and molecular approaches for optimizing single-cell DNA amplification.
Development of a library preparation protocol for highly multiplexed sequencing.
Utilized Illumina HiSeq instrument for high-throughput CNV determination.

Main Results:

Achieved genome-wide CNV profiles for up to 100 single cells per Illumina HiSeq lane.
Demonstrated the method's efficiency, reproducibility, and power in human cancer cell lines and tissues.
Successfully revealed underlying genetic heterogeneity and clonal phylogeny in cancer samples.

Conclusions:

The developed method significantly enhances the capacity for rapid, large-scale single-cell genome profiling.
This approach represents a key advancement in making single-cell profiling an accessible tool for cell lineage studies.
The method's application in cancer research highlights its potential for dissecting complex biological systems.