Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

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%...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Safety and technical success of transradial access in prostatic artery embolisation: a systematic review and meta-analysis.

Clinical radiology·2026
Same author

Metagenomic global survey and in-depth genomic analyses of Ruminococcus gnavus reveal differences across host lifestyle and health status.

Nature communications·2025
Same author

Sex-related differences in coronary and carotid vessel geometry, plaque composition and shear stress obtained from imaging.

Atherosclerosis·2024
Same author

A modular microfluidic platform to enable complex and customisable <i>in vitro</i> models for neuroscience.

Lab on a chip·2022
Same author

Antigen array for serological diagnosis and novel allergen identification in severe equine asthma.

Scientific reports·2019
Same author

De novo variants in CNOT3 cause a variable neurodevelopmental disorder.

European journal of human genetics : EJHG·2019

Related Experiment Video

Updated: Jun 24, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Methods to detect CNVs in the human genome.

E Aten1, S J White, M E Kalf

  • 1Human and Clinical Genetics and Leiden Genome Technology Center (LGTC), Leiden University Medical Center, Leiden, The Netherlands.

Cytogenetic and Genome Research
|March 17, 2009
PubMed
Summary

Copy Number Variants (CNVs) are crucial in genetic disease. New screening methods enable efficient detection of these genomic DNA changes, improving genetic disorder diagnosis.

More Related Videos

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
11:11

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Related Experiment Videos

Last Updated: Jun 24, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
11:11

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Area of Science:

  • Genomics
  • Molecular Biology
  • Medical Genetics

Background:

  • Copy Number Variants (CNVs) are significant quantitative genomic alterations.
  • CNVs involve numerous genes and are increasingly recognized as causes of genetic diseases.
  • Efficient methods for CNV detection are essential for comprehensive genetic screening.

Purpose of the Study:

  • To review existing and novel methods for detecting Copy Number Variants (CNVs).
  • To discuss the strengths and weaknesses of various CNV detection techniques.
  • To highlight new developments and future directions in CNV screening.

Main Methods:

  • Microscopy
  • Fluorescence in situ hybridization (FISH, fiber-FISH)
  • Southern blotting
  • PCR-based methods (MLPA)
  • Array technology
  • Massive parallel sequencing
  • 1400-plex CNV bead assay
  • Fast-MLPA
  • Melting Curve Analysis

Main Results:

  • A 1400-plex CNV bead assay identified confirmed rearrangements in 9% of 320 patients with mental retardation.
  • New methods like fast-MLPA and Melting Curve Analysis offer improved efficiency and confirmation.
  • The study demonstrates the utility of advanced CNV detection in clinical settings.

Conclusions:

  • Advanced CNV detection methods are vital for understanding genetic diseases.
  • The reviewed techniques provide a range of options for CNV screening from specific loci to genome-wide.
  • Ongoing developments promise more efficient and accessible CNV analysis for diagnostics.