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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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.
Mismatch Repair01:36

Mismatch Repair

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Related Experiment Video

Updated: May 9, 2026

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

Improving transcriptome assembly through error correction of high-throughput sequence reads.

Matthew D Macmanes1, Michael B Eisen

  • 1California Institute for Quantitative Biosciences, University of California , Berkeley, CA , USA.

Peerj
|August 2, 2013
PubMed
Summary
This summary is machine-generated.

Error correction of sequencing reads significantly improves the accuracy of de novo transcriptome assembly, a crucial step for functional genomics research in non-model organisms. Applying this pre-assembly procedure enhances downstream analyses.

Keywords:
De novo assemblyError correctionIlluminaRNAseqTrinity

More Related Videos

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

Related Experiment Videos

Last Updated: May 9, 2026

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

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

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Functional genomics studies, especially in non-model organisms, rely heavily on transcriptomes and RNA sequencing (RNAseq).
  • De novo transcriptome assembly is a computationally intensive prerequisite for downstream analyses like transcript abundance estimation.
  • The accuracy of the reference transcriptome is critical for the reliability of all subsequent analyses.

Purpose of the Study:

  • To investigate the impact of pre-assembly error correction on the accuracy of de novo transcriptome assembly.
  • To determine if error correction of sequencing reads positively influences transcriptome assembly quality.

Main Methods:

  • Utilized both simulated and empirical datasets for analysis.
  • Applied stand-alone error correction modules to sequencing reads prior to assembly.
  • Evaluated the effect of error correction on the accuracy of the resulting reference transcriptome.

Main Results:

  • Applying error correction to sequencing reads demonstrated significant positive effects on transcriptome assembly accuracy.
  • The study provides evidence that error correction is beneficial for improving reference transcriptome construction.
  • A collection of commands for producing corrected reads is made available.

Conclusions:

  • Error correction of sequencing reads should be applied to all datasets to enhance de novo transcriptome assembly accuracy.
  • This pre-assembly step is vital for improving the quality of functional genomics research.
  • The findings advocate for the routine integration of error correction in RNAseq data processing pipelines.