Accurate and unambiguous tag-to-gene mapping in serial analysis of gene expression

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dc.article.number487
dc.catalogadoraba
dc.contributor.authorMalig, R.
dc.contributor.authorVarela, C.
dc.contributor.authorAgosin T., Eduardo
dc.contributor.authorMelo Ledermann, Francisco Javier
dc.date.accessioned2025-02-05T19:16:02Z
dc.date.available2025-02-05T19:16:02Z
dc.date.issued2006
dc.description.abstractBackground In this study, we present a robust and reliable computational method for tag-to-gene assignment in serial analysis of gene expression (SAGE). The method relies on current genome information and annotation, incorporation of several new features, and key improvements over alternative methods, all of which are important to determine gene expression levels more accurately. The method provides a complete annotation of potential virtual SAGE tags within a genome, along with an estimation of their confidence for experimental observation that ranks tags that present multiple matches in the genome. Results We applied this method to the Saccharomyces cerevisiae genome, producing the most thorough and accurate annotation of potential virtual SAGE tags that is available today for this organism. The usefulness of this method is exemplified by the significant reduction of ambiguous cases in existing experimental SAGE data. In addition, we report new insights from the analysis of existing SAGE data. First, we found that experimental SAGE tags mapping onto introns, intron-exon boundaries, and non-coding RNA elements are observed in all available SAGE data. Second, a significant fraction of experimental SAGE tags was found to map onto genomic regions currently annotated as intergenic. Third, a significant number of existing experimental SAGE tags for yeast has been derived from truncated cDNAs, which are synthesized through oligo-d(T) priming to internal poly-(A) regions during reverse transcription. Conclusion We conclude that an accurate and unambiguous tag mapping process is essential to increase the quality and the amount of information that can be extracted from SAGE experiments. This is supported by the results obtained here and also by the large impact that the erroneous interpretation of these data could have on downstream applications.
dc.fuente.origenSIPA
dc.identifier.doi10.1186/1471-2105-7-487
dc.identifier.eissn1471-2105
dc.identifier.pubmedid17083742
dc.identifier.pubmedidPMC1637119
dc.identifier.scopusid2-s2.0-33751224464
dc.identifier.urihttps://doi.org/10.1186/1471-2105-7-487
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/102155
dc.identifier.wosidWOS:000242187700002
dc.information.autorucEscuela de Ingeniería; Agosin T., Eduardo; 0000-0003-1656-150X; 99630
dc.information.autorucFacultad de Ciencias Biológicas; Melo Ledermann, Francisco Javier; 0000-0002-0424-5991; 82342
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final18
dc.pagina.inicio1
dc.revistaBMC bioinformatics
dc.rightsacceso abierto
dc.rights.licenseAttribution 2.0 Generic
dc.rights.urihttps://creativecommons.org/licenses/by/2.0/
dc.subjectORF
dc.subjectintron
dc.subjectrRNA
dc.subjecttRNA
dc.subjectsnoRNA
dc.subjectsnRNA
dc.subjectncRNA
dc.subject.ddc570
dc.subject.deweyBiología
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAccurate and unambiguous tag-to-gene mapping in serial analysis of gene expression
dc.typeartículo
dc.volumen7
sipa.codpersvinculados99630
sipa.codpersvinculados82342
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