Sanita Lima Matheus, Silva Domingues Douglas, Rossi Paschoal Alexandre, Smith David Roy
Department of Biology, Western University, 1151 Richmond Street, London, Ontario N6A 5B7, Canada.
Department of Genetics, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Avenida Padua Dias 11, Piracicaba, SP 13418-900, Brazil.
Brief Funct Genomics. 2024 Dec 6;23(6):695-701. doi: 10.1093/bfgp/elae026.
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.
40年前,细胞器基因组被认为是经过简化的,或许是其原核生物过去遗留下来的平淡无奇的残余物。然而,细胞器基因组学领域揭示了基因组结构(即基因组大小、结构和内容)中存在的无与伦比的多样性。这些奇特基因组的转录过程同样复杂——细胞器基因组被广泛转录为大量的RNA类型。然而,虽然已知细胞器蛋白质编码基因会产生经过大量转录后加工的多顺反子转录本,但细胞器非编码转录组的性质仍未得到很好的解析。在这里,我们回顾了湿实验室实验和第二代测序数据(即短读长)如何有助于确定某些类型的细胞器RNA,特别是非编码RNA。然后,我们解释了第三代(长读长)RNA测序数据如何代表细胞器转录组学的新前沿。我们表明,公共数据库(如NCBI SRA)已经包含了足够的数据用于门间比较研究,并认为细胞器生物学家可以从这些数据中受益。我们讨论了使用公开可用的测序数据进行细胞器重点研究的前景,并审视了这种方法面临的挑战。我们强调,缺乏一个专门致力于细胞器基因组学/转录组学的综合数据库是该领域发展的一个主要障碍,该领域在基础科学和应用科学中都有重要意义。