Long-read RNA sequencing can probe organelle genome pervasive transcription.

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.

Pervasive transcription of plant organelle genomes: functional noncoding transcriptomes?

Plant mitochondrial and plastid genomes typically show pervasive, genome-wide transcription. Little is known, however, about the utility of organelle noncoding RNAs, which often make up most of the transcriptome. Here, we suggest that long-read sequencing data combined with dedicated RNA databases could help identify putative functional organelle noncoding transcripts.

Functional Characterization of ent-Copalyl Diphosphate Synthase and Kaurene Synthase Genes from Coffea arabica L.

The biochemical profile of coffee beans translates directly into quality traits, nutraceutical and health promoting properties of the coffee beverage. Ent-kaurene is the ubiquitous precursor for gibberellin biosynthesis in plants, but it also serves as an intermediate in specialized (i.e., secondary) diterpenoid metabolism that leads to a diversity of more than 1,000 different metabolites. Nutraceutical effects on human health attributed to diterpenes include antioxidant, anticarcinogenic, and anti-inflammatory properties. Cafestol (CAF) and kahweol (KAH) are two diterpenes found exclusively in the Coffea genus. Our objective was to identify and functionally characterize genes involved in the central step of ent-kaurene production. We identified 17 putative terpene synthase genes in the transcriptome of Coffea arabica. Two ent-copalyl diphosphate synthase (CaCPS) and three kaurene synthase (CaKS) were selected and manually annotated. Transcript expression profiles of CaCPS1 and CaKS3 best matched the CAF and KAH metabolite profiles in different tissues. CaCPS1 and CaKS3 proteins were heterologously expressed and functionally characterized. CaCPS1 catalyzes the cyclization of geranylgeranyl diphosphate (GGPP) to ent-copalyl diphosphate (ent-CPP), which is converted to ent-kaurene by CaKS3. Knowledge about the central steps of diterpene formation in coffee provides a foundation for future characterization of the subsequent enzymes involved in CAF and KAH biosynthesis.

Inpactor, Integrated and Parallel Analyzer and Classifier of LTR Retrotransposons and Its Application for Pineapple LTR Retrotransposons Diversity and Dynamics.

One particular class of Transposable Elements (TEs), called Long Terminal Repeats (LTRs), retrotransposons, comprises the most abundant mobile elements in plant genomes. Their copy number can vary from several hundreds to up to a few million copies per genome, deeply affecting genome organization and function. The detailed classification of LTR retrotransposons is an essential step to precisely understand their effect at the genome level, but remains challenging in large-sized genomes, requiring the use of optimized bioinformatics tools that can take advantage of supercomputers. Here, we propose a new tool: Inpactor, a parallel and scalable pipeline designed to classify LTR retrotransposons, to identify autonomous and non-autonomous elements, to perform RT-based phylogenetic trees and to analyze their insertion times using High Performance Computing (HPC) techniques. Inpactor was tested on the classification and annotation of LTR retrotransposons in pineapple, a recently-sequenced genome. The pineapple genome assembly comprises 44% of transposable elements, of which 23% were classified as LTR retrotransposons. Exceptionally, 16.4% of the pineapple genome assembly corresponded to only one lineage of the Gypsy superfamily: Del, suggesting that this particular lineage has undergone a significant increase in its copy numbers. As demonstrated for the pineapple genome, Inpactor provides comprehensive data of LTR retrotransposons' classification and dynamics, allowing a fine understanding of their contribution to genome structure and evolution. Inpactor is available at https://github.com/simonorozcoarias/Inpactor.