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Related Concept Videos

Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
RNA-seq03:21

RNA-seq

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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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.

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Related Experiment Video

Updated: Jun 2, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Sequence-specific error profile of Illumina sequencers.

Kensuke Nakamura1, Taku Oshima, Takuya Morimoto

  • 1Graduate School of Information Science, Graduate School of Biological Sciences, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.

Nucleic Acids Research
|May 18, 2011
PubMed
Summary
This summary is machine-generated.

Sequence-specific errors (SSE) in Illumina sequencing arise from inverted repeats and GGC sequences, causing coverage variability and hindering genetic analyses like RNA-seq and SNP calling.

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

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Last Updated: Jun 2, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

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Published on: August 3, 2018

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-generation sequencing technologies, particularly Illumina Genome Analyser (GA), are crucial for genomic research.
  • Accurate base calling and uniform sequence coverage are essential for reliable downstream analyses.
  • Observed biases in population-targeted methods like RNA-seq and ChIP-seq necessitate understanding their root causes.

Purpose of the Study:

  • To identify and characterize sequence-specific errors (SSE) occurring during Illumina sequencing.
  • To elucidate the underlying mechanisms responsible for SSE.
  • To assess the impact of SSE on various genomic applications.

Main Methods:

  • Analysis of miscall patterns in reads from Illumina GA.
  • Identification of specific DNA sequence motifs associated with miscalls.
  • Correlation of miscall patterns with known sequencing process limitations.

Main Results:

  • Identified sequence-specific starting positions of consecutive miscalls.
  • Determined that inverted repeats and GGC sequences are major triggers for SSE.
  • Hypothesized that these sequences inhibit single-base elongation through DNA folding or altered enzyme preference, leading to dephasing.

Conclusions:

  • SSE significantly impacts sequence coverage variability and introduces bias in RNA-seq and ChIP-seq.
  • SSE can lead to false single-nucleotide polymorphism (SNP) calls and impede de novo assembly.
  • Recognizing and understanding SSE mechanisms is vital for improving Illumina sequencer utility.