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Related Experiment Videos

Evaluating and improving cDNA sequence quality with cQC.

Celine A Hayden1, Travis J Wheeler, Richard A Jorgensen

  • 1Department of Plant Sciences, University of Arizona, Tucson, AZ 85721-0036, USA.

Bioinformatics (Oxford, England)
|October 20, 2005
PubMed
Summary
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Sequence errors are common in complementary DNA (cDNA) collections. A new quality control method revealed significant nucleotide discrepancies and premature termination codons in Arabidopsis and rice cDNA sequences, impacting data reliability.

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Complementary DNA (cDNA) sequences are crucial for gene expression studies.
  • Prevalent errors in cDNA sequences can affect downstream analyses.
  • Systematic evaluation of error frequencies across different cDNA collections is lacking.

Purpose of the Study:

  • To develop and implement a cDNA quality control (cQC) method.
  • To assess the prevalence and types of errors in plant cDNA sequence collections.
  • To revise sequences based on higher quality genomic references.

Main Methods:

  • Developed cDNA quality control (cQC) for evaluating and revising cDNA sequences.
  • Removed contaminants including rRNA, vector, bacterial insertion sequences, and chimeric cDNA.

Related Experiment Videos

  • Compared cDNA sequences against high-quality genomic sequences to identify discrepancies.

    • Main Results:

    • Small-scale nucleotide discrepancies were found in 51% (Arabidopsis 1), 89% (Arabidopsis 2), and 75% (rice) of cDNA sequences.
    • These errors led to premature termination codons in 4% (Arabidopsis 1), 42% (Arabidopsis 2), and 7% (rice) of sequences.

    Conclusions:

    • cDNA sequence collections exhibit significant and variable error rates.
    • The cQC method effectively identifies and quantifies errors impacting coding potential.
    • Ensuring cDNA sequence accuracy is vital for reliable biological interpretation.