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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%...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
Real Time RT-PCR02:57

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...
Karyotyping01:17

Karyotyping

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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

Current analysis platforms and methods for detecting copy number variation.

Wenli Li1, Michael Olivier

  • 1Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.

Physiological Genomics
|November 8, 2012
PubMed
Summary
This summary is machine-generated.

Copy number variation (CNV) is common in human genomes and can affect gene expression and disease. This study reviews methods for detecting CNVs and understanding their impact on health.

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Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • Copy number variation (CNV), arising from DNA duplications or deletions, is prevalent in human genomes.
  • CNVs can alter gene expression and lead to gene fusions, impacting various physiological pathways and disease phenotypes.
  • The full extent and functional significance of CNVs across the genome remain incompletely understood.

Purpose of the Study:

  • To evaluate commonly used and novel analytical methods for detecting genome-wide copy number variations.
  • To discuss the advantages and limitations of different CNV detection technologies for medical researchers.
  • To explore the interplay between genomic structural variation and disease phenotypes.

Main Methods:

  • Review and comparative analysis of established and emerging CNV detection techniques.
  • Assessment of methods for uncovering genome-wide structural variations.
  • Discussion of analytical approaches for linking CNVs to disease phenotypes.

Main Results:

  • The article provides an overview of various genome-wide CNV detection methodologies.
  • It highlights the strengths and weaknesses of different approaches, aiding researchers in method selection.
  • The review underscores the need for advanced analytical tools to fully characterize CNVs and their disease associations.

Conclusions:

  • Accurate detection and analysis of CNVs are crucial for understanding their role in human health and disease.
  • Familiarity with diverse CNV detection technologies is essential for medical researchers.
  • Further development and application of analytical methods are needed to fully elucidate the impact of CNVs on disease phenotypes.