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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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.
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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,...
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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.
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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Related Experiment Video

Updated: Oct 13, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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Comprehensive characterization of copy number variation (CNV) called from array, long- and short-read data.

Ksenia Lavrichenko1,2, Stefan Johansson3,4, Inge Jonassen5

  • 1Computational Biology Unit, University of Bergen, Bergen, Norway. ksenia.lavrichenko@medisin.uio.no.

BMC Genomics
|November 18, 2021
PubMed
Summary

Long-read sequencing platforms can identify copy number variants (CNVs) in previously inaccessible genomic regions. CNV reproducibility across different pipelines varies and depends on evidence measures, with distinct database frequency profiles for each technology.

Keywords:
CNVGenome in a BottleLong readsMicroarraysShort reads

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Genome-wide high-throughput technologies like SNP arrays, short-read, and long-read sequencing are used to assay copy number variants (CNVs).
  • Each technology has limitations and biases, some of which require further quantification.

Purpose of the Study:

  • To compare the CNV calling capabilities of array, short-read, and long-read technologies.
  • To validate CNV calls using raw data from each technology, rather than relying on a golden standard.

Main Methods:

  • Assembled public datasets of CNV calls and raw data for the Genome in a Bottle individual NA12878.
  • Included data from various methods and pipelines for CNV calling across array, short-read, and long-read technologies.
  • Performed cross-technology comparisons and validated CNV calls using technology-specific raw data.

Main Results:

  • Long-read platforms successfully identified CNVs in genomic regions not covered by arrays or short reads.
  • CNV reproducibility across different pipelines within a technology correlated with CNV evidence measures.
  • Distinct public database frequency profiles were observed for each technology, influenced by the database's underlying data source.

Conclusions:

  • Long-read sequencing expands the scope of CNV detection into previously inaccessible genomic areas.
  • CNV call reproducibility is a critical factor influenced by pipeline choice and evidence measures.
  • The choice of technology significantly impacts CNV frequency profiles in public databases.