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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.
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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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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Related Experiment Video

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Detection of Copy Number Alterations Using Single Cell Sequencing
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Detecting differential copy number variation between groups of samples.

Craig B Lowe1,2, Nicelio Sanchez-Luege1, Timothy R Howes1

  • 1Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA.

Genome Research
|December 13, 2017
PubMed
Summary

We developed a new method to detect copy number variants (CNVs) between sample groups. This approach identified thousands of genomic regions with copy number differences linked to stickleback adaptation to freshwater environments.

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Copy number variants (CNVs) are important drivers of phenotypic variation and adaptation.
  • Detecting CNVs accurately, especially those differing between populations, remains a challenge.

Purpose of the Study:

  • To present a novel statistical method for identifying differentially present copy number variants (CNVs) between two groups of sequenced samples.
  • To apply this method to investigate the genetic basis of postglacial adaptation in threespine stickleback (Gasterosteus aculeatus).

Main Methods:

  • Developed a finite-state transducer model where read depth is conditioned on mappability and GC-content.
  • Modeled read depth as a mixture of binomials, outperforming the negative binomial distribution in simulations.
  • Analyzed all samples simultaneously to preserve uncertainty in CNV breakpoints and magnitudes.

Main Results:

  • Identified 6664 recurrent CNV regions (1.7 Mbp) associated with freshwater adaptation in stickleback.
  • These CNVs include deletions and duplications affecting protein-coding genes and cis-regulatory elements, such as a DCHS1 enhancer.
  • Enriched gene functions near CNVs include immunity, muscle development, and head/limb morphology.

Conclusions:

  • Freshwater stickleback harbor unique CNVs reflecting adaptation, including ancient conserved sequences lost in marine populations due to selective sweeps.
  • The developed method provides a robust framework for detecting differential CNVs in population genomics studies.
  • CNV analysis reveals key genetic changes underlying the transition of stickleback from marine to freshwater environments.