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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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Single Nucleotide Polymorphisms Caused by Assembly Errors.

Jürgen Kleffe1, Robert Weißmann2, Florian F Schmitzberger3

  • 1Institute of Molecular Biology and Bioinformatics, Charité Berlin, Arnimallee 22, Berlin, Germany.

Genomics Insights
|August 18, 2015
PubMed
Summary
This summary is machine-generated.

Comparing three DNA assemblers revealed significant errors in sequence data. Mathematical sequence assembly algorithms produce erroneous single nucleotide polymorphisms (SNPs), impacting molecular diagnostics and genome variation studies.

Keywords:
SNPgenome comparisongenome variationsequence assemblysingle nucleotide polymorphism

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing generates vast amounts of data requiring sophisticated assembly algorithms.
  • Previous comparisons of assemblers focused on speed and contig count, not assembly content accuracy.
  • Accurate genome assembly is critical for downstream applications like variant detection and clinical diagnostics.

Purpose of the Study:

  • To evaluate the accuracy of de novo genome assembly by comparing the content agreement of three different assembler programs: Celera, Phrap, and Mira2.
  • To estimate the rate of erroneously identified single nucleotide polymorphisms (SNPs) arising solely from the mathematical sequence assembly process.
  • To assess the impact of assembler choice and version on SNP error rates.

Main Methods:

  • Comparison of three assembler programs (Celera, Phrap, Mira2) using a dataset of approximately 100,000 Sanger reads from a bacterial genome.
  • Identification of genome regions consistently assembled by all three programs (threefold consistently assembled regions).
  • Analysis of these consistent regions to quantify erroneous SNPs and insertion/deletions (indels).
  • Re-evaluation using an updated assembler version (Mira3) to assess improvements in error rates.

Main Results:

  • 509 sequence triplets common to all three de novo assemblies were identified, spanning 34% (3.3 Mb) of the bacterial genome.
  • 175 of these regions (approximately 1.5 Mb) contained erroneous SNPs and indels, indicating an average error rate of 1 per 7,155 base pairs.
  • Replacing Mira2 with Mira3 reduced the error rate to 1 per 5,923 base pairs.
  • Consistent errors were observed, suggesting that assembler algorithms themselves introduce inaccuracies.

Conclusions:

  • A substantial number of erroneous SNPs may exist in current sequence data due to assembly algorithms.
  • There is an urgent need for research into the numerical stability of sequence assembly algorithms.
  • Current assemblers, even updated versions, can produce erroneous SNPs dependent on read input order, posing a significant challenge for molecular diagnostics and genome variation studies.