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Long-read RNA sequencing can probe organelle genome pervasive transcription.
Sanita Lima, Matheus; Silva Domingues, Douglas; Rossi Paschoal, Alexandre; Smith, David Roy.
Afiliação
  • Sanita Lima M; Department of Biology, Western University, 1151 Richmond Street, London, Ontario N6A 5B7, Canada.
  • Silva Domingues D; Department of Genetics, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Avenida Padua Dias 11, Piracicaba, SP 13418-900, Brazil.
  • Rossi Paschoal A; Department of Computer Science, Bioinformatics and Pattern Recognition Group (BIOINFO-CP), Federal University of Technology - Paraná - UTFPR, Avenida Alberto Carazzai 1640, Cornélio Procópio, PR 86300000, Brazil.
  • Smith DR; Department of Biology, Western University, 1151 Richmond Street, London, Ontario N6A 5B7, Canada.
Brief Funct Genomics ; 2024 Jun 17.
Article em En | MEDLINE | ID: mdl-38880995
ABSTRACT
40 years ago, organelle genomes were assumed to be streamlined and, perhaps, unexciting remnants of their prokaryotic past. However, the field of organelle genomics has exposed an unparallel diversity in genome architecture (i.e. genome size, structure, and content). The transcription of these eccentric genomes can be just as elaborate - organelle genomes are pervasively transcribed into a plethora of RNA types. However, while organelle protein-coding genes are known to produce polycistronic transcripts that undergo heavy posttranscriptional processing, the nature of organelle noncoding transcriptomes is still poorly resolved. Here, we review how wet-lab experiments and second-generation sequencing data (i.e. short reads) have been useful to determine certain types of organelle RNAs, particularly noncoding RNAs. We then explain how third-generation (long-read) RNA-Seq data represent the new frontier in organelle transcriptomics. We show that public repositories (e.g. NCBI SRA) already contain enough data for inter-phyla comparative studies and argue that organelle biologists can benefit from such data. We discuss the prospects of using publicly available sequencing data for organelle-focused studies and examine the challenges of such an approach. We highlight that the lack of a comprehensive database dedicated to organelle genomics/transcriptomics is a major impediment to the development of a field with implications in basic and applied science.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article