Unravelling Organelle Genome Transcription Using Publicly Available RNA-Sequencing Data

The study of organelles helped forge theories of genome evolution because of their unconventional genomes and gene expression regimes. The organelle genomics field (~35 years old) has seen the development of next generation sequencing (NGS) techniques and the consequent skyrocketing of genomic and transcriptomic data. However, these data are being underused in the studies of organelle genome transcription. My thesis investigates how NGS has affected the field of organelle genomics at both the DNA and RNA levels. First, I demonstrate that although organelle genomes are being sequenced as never before, they are un-characterized as they are published mostly as “organelle genome reports”. Then, I show that publicly available RNA-sequencing data represent an untapped datasource to study organelle genome transcription. I uncover the widespread pervasive transcription of organelle genomes across eukaryotes and speculate that this mechanism might have influenced the evolution of land plant terrestrialization and trophic mode determination in mixotrophs

P08. Unravelling organelle genome evolution architecture using RNA-sequencing data

Background: Mitochondria genomes vary from 11 Mb to 6 kb, while plastids can vary from 1 Mb to 30 kb. Non-coding DNA accounts for most of this size variation, but the mechanistic and evolutionary reasons for that are still unknown. Next generation sequencing has generated unprecedented amounts of genomic and transcriptomic data that can be used for organelle genome evolution studies. However, most of these data is used only for the study of cell nucleus. Therefore, I decided to use these untapped data source to investigate the transcription of organelle genomes in plastid-bearing protists. Methods: I mapped the transcriptomes over the genomes of 116 protist species using the algorithm Bowtie 2 through the software Geneious. Results/Discussion: 77 out of 116 species had their organelle genomes entirely recovered from transcripts. These genomes come from diverse protists and vary immensely in size and structure, which allowed me to determine the transcriptomic architecture of organelle genomes regardless of their nature. Conclusions: RNA-seq data generated for cell nucleus studies can be used to investigate organelle genome transcription. Even though organelle genomes can exhibit large portions of non-coding DNA, these regions are still transcribed and might play a role in post-transcription regulation. Here, I will argue how RNA-seq data can be used to explore this field and how transcription can interfere in the genome size evolution. Interdisciplinary reflection: My work combines Biodiversity and Molecular Evolution to investigate the evolution of organelle genomes and speciation, which ultimately will help us better manage protist-rich ecosystems

Co-cultivation of Aspergillus nidulans recombinant strains produces an enzymatic cocktail as alternative to alkaline sugarcane bagasse pretreatment

Plant materials represent a strategic energy source because they can give rise to sustainable biofuels through the fermentation of their carbohydrates. A clear example of a plant-derived biofuel resource is the sugar cane bagasse exhibiting 60 % - 80 % of fermentable sugars in its composition. However, the current methods of plant bioconversion employ severe and harmful chemical/physical pretreatments raising biofuel cost production and environmental degradation. Replacing these methods with co-cultivated enzymatic cocktails is an alternative. Here we propose a pretreatment for sugarcane bagasse using a multi-enzymatic cocktail from the co-cultivation of four Aspergillus nidulans recombinant strains. The co-cultivation resulted in the simultaneous production of GH51 arabinofuranosidase (AbfA), GH11 endo-1,4-xylanase (XlnA), GH43 endo-1,5-arabinanase (AbnA) and GH12 xyloglucan specific endo-β-1,4-glucanase (XegA). This core set of recombinant enzymes was more efficient than the alternative alkaline method in maintaining the cellulose integrity and exposing this cellulose to the following saccharification process. Thermogravimetric and differential thermal analysis revealed residual byproducts on the alkali pretreated biomass, which were not found in the enzymatic pretreatment. Therefore, the enzymatic pretreatment was residue-free and seemed to be more efficient than the applied alkaline method, which makes it suitable for bioethanol production