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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

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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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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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Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
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Updated: Nov 16, 2025

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Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural

Jeroen van den Akker1, Lawrence Hon1, Anjana Ondov1

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Rare structural variants (SVs) significantly contribute to hereditary disorders. Advanced sequencing and bioinformatics are crucial for detecting these complex genetic changes, improving diagnostic accuracy for inherited diseases.

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Area of Science:

  • Genetics
  • Genomic Medicine
  • Bioinformatics

Background:

  • Large copy number variants (CNVs) are recognized in hereditary disorders, but rare germline structural variants (SVs) remain understudied.
  • Population sequencing has identified common SVs, yet clinical data on rare germline SVs are limited.

Purpose of the Study:

  • To characterize rare germline SVs in genes linked to hereditary cancer and cardiovascular diseases.
  • To evaluate the efficacy of different sequencing strategies for SV detection.

Main Methods:

  • Targeted next-generation sequencing of 50 genes associated with hereditary disorders.
  • Bioinformatics pipeline modeling for SV detection using read depth analysis.
  • Characterization of various SV types including deletions, duplications, insertions, inversions, and complex rearrangements.

Main Results:

  • Identified 828 unique SVs, with 584 fully characterized, including numerous small CNVs (<5 kb) and single-exon deletions.
  • Genome sequencing (30×) detected 71% of SVs, compared to 53% for targeted panels and <20% for exome sequencing.
  • SVs constituted 14.1% of all unique pathogenic variants identified.

Conclusions:

  • Rare germline SVs play a critical role in hereditary disorders.
  • Robust SV detection necessitates ensemble bioinformatics algorithms utilizing intronic sequencing and diverse data features.
  • Current exome sequencing methods significantly underestimate the contribution of SVs to genetic disease.