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Pseudogenes transcribed in breast invasive carcinoma show subtype-specific expression and ceRNA potential.
Welch, Joshua D; Baran-Gale, Jeanette; Perou, Charles M; Sethupathy, Praveen; Prins, Jan F.
Afiliación
  • Welch JD; Curriculum in Bioinformatics and Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. jwelch@cs.unc.edu.
  • Baran-Gale J; Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. jwelch@cs.unc.edu.
  • Perou CM; Curriculum in Bioinformatics and Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. jtbaran@email.unc.edu.
  • Sethupathy P; Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. jtbaran@email.unc.edu.
  • Prins JF; Curriculum in Bioinformatics and Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. cperou@med.unc.edu.
BMC Genomics ; 16: 113, 2015 Feb 22.
Article en En | MEDLINE | ID: mdl-25765044
BACKGROUND: Recent studies have shown that some pseudogenes are transcribed and contribute to cancer when dysregulated. In particular, pseudogene transcripts can function as competing endogenous RNAs (ceRNAs). The high similarity of gene and pseudogene nucleotide sequence has hindered experimental investigation of these mechanisms using RNA-seq. Furthermore, previous studies of pseudogenes in breast cancer have not integrated miRNA expression data in order to perform large-scale analysis of ceRNA potential. Thus, knowledge of both pseudogene ceRNA function and the role of pseudogene expression in cancer are restricted to isolated examples. RESULTS: To investigate whether transcribed pseudogenes play a pervasive regulatory role in cancer, we developed a novel bioinformatic method for measuring pseudogene transcription from RNA-seq data. We applied this method to 819 breast cancer samples from The Cancer Genome Atlas (TCGA) project. We then clustered the samples using pseudogene expression levels and integrated sample-paired pseudogene, gene and miRNA expression data with miRNA target prediction to determine whether more pseudogenes have ceRNA potential than expected by chance. CONCLUSIONS: Our analysis identifies with high confidence a set of 440 pseudogenes that are transcribed in breast cancer tissue. Of this set, 309 pseudogenes exhibit significant differential expression among breast cancer subtypes. Hierarchical clustering using only pseudogene expression levels accurately separates tumor samples from normal samples and discriminates the Basal subtype from the Luminal and Her2 subtypes. Correlation analysis shows more positively correlated pseudogene-parent gene pairs and negatively correlated pseudogene-miRNA pairs than expected by chance. Furthermore, 177 transcribed pseudogenes possess binding sites for co-expressed miRNAs that are also predicted to target their parent genes. Taken together, these results increase the catalog of putative pseudogene ceRNAs and suggest that pseudogene transcription in breast cancer may play a larger role than previously appreciated.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcripción Genética / Neoplasias de la Mama / ARN / Seudogenes Límite: Female / Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcripción Genética / Neoplasias de la Mama / ARN / Seudogenes Límite: Female / Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos