Literature DB >> 9632832

Frame: detection of genomic sequencing errors.

N P Brown1, C Sander, P Bork.   

Abstract

MOTIVATION: The underlying error rate for genomic sequencing sometimes results in the introduction of artificial frameshifts and in-frame stop codons into putative protein encoding genes. Severe errors are then introduced into the inferred transcripts through mis-translation or premature termination.
RESULTS: We describe a system for screening segments of DNA for frameshift and in-frame stop errors in coding regions. The method is based on homology matching using blastx to compare all six reading frames of the query nucleotide sequence against selected protein sequence databases. Fragments of protein matching neighbouring regions of the query DNA are united and extended laterally to define candidate open reading frames, within which, frameshifts and stops are identified. Suitable targets include prokaryotic or other intron-free genomic sequence and complementary DNAs. As an example of its use, we report here two frameshifted ORFs that deviate from the original TIGR sequence annotations for the recently released Helicobacter pylori genome. AVAILABILITY: The tool is accessible via the URL http://www.sander.ebi.ac.uk/frame/. CONTACT: brown@ebi.ac.uk.

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Year:  1998        PMID: 9632832     DOI: 10.1093/bioinformatics/14.4.367

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

1.  Detecting and analyzing DNA sequencing errors: toward a higher quality of the Bacillus subtilis genome sequence.

Authors:  C Médigue; M Rose; A Viari; A Danchin
Journal:  Genome Res       Date:  1999-11       Impact factor: 9.043

2.  FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences.

Authors:  Thomas Schiex; Jérôme Gouzy; Annick Moisan; Yannick de Oliveira
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes.

Authors:  Nitin Gupta; Jamal Benhamida; Vipul Bhargava; Daniel Goodman; Elisabeth Kain; Ian Kerman; Ngan Nguyen; Noah Ollikainen; Jesse Rodriguez; Jian Wang; Mary S Lipton; Margaret Romine; Vineet Bafna; Richard D Smith; Pavel A Pevzner
Journal:  Genome Res       Date:  2008-04-21       Impact factor: 9.043

Review 4.  Functional assignment of metagenomic data: challenges and applications.

Authors:  Tulika Prakash; Todd D Taylor
Journal:  Brief Bioinform       Date:  2012-07-06       Impact factor: 11.622

5.  HMM-FRAME: accurate protein domain classification for metagenomic sequences containing frameshift errors.

Authors:  Yuan Zhang; Yanni Sun
Journal:  BMC Bioinformatics       Date:  2011-05-24       Impact factor: 3.169

6.  ICDS database: interrupted CoDing sequences in prokaryotic genomes.

Authors:  Emmanuel Perrodou; Caroline Deshayes; Jean Muller; Christine Schaeffer; Alain Van Dorsselaer; Raymond Ripp; Olivier Poch; Jean-Marc Reyrat; Odile Lecompte
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

7.  Interrupted coding sequences in Mycobacterium smegmatis: authentic mutations or sequencing errors?

Authors:  Caroline Deshayes; Emmanuel Perrodou; Sebastien Gallien; Daniel Euphrasie; Christine Schaeffer; Alain Van-Dorsselaer; Olivier Poch; Odile Lecompte; Jean-Marc Reyrat
Journal:  Genome Biol       Date:  2007       Impact factor: 13.583

  7 in total

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