Philippe, N. | Search bioRxiv

bioRxiv2017

Diversity and evolution of the emerging Pandoraviridae family

With DNA genomes up to 2.5 Mb packed in particles of bacterium-like shape and dimension, the first two Acanthamoeba-infecting Pandoraviruses remained the most spectacular viruses since their description in 2013. Our isolation of three new strains from distant locations and environments allowed us to perform the first comparative genomics analysis of the emerging worldwide-distributed Pandoraviridae family. Thorough annotation of the genomes combining transcriptomic, proteomic, and bioinformatic analyses, led to the discovery of many non-coding transcripts while significantly reducing the former set of predicted protein-coding genes. We found that the Pandoraviridae exhibit an open pan genome, the enormous size of which is not adequately explained by gene duplications or horizontal transfers. As most of the strain specific genes have no extant homolog and exhibit statistical features comparable to intergenic regions, we suggests that de novo gene creation is a strong component in the evolution of the giant Pandoravirus genomes.

microbiology↗

bioRxiv2017

Exhaustive capture of biological variation in RNA-seq data through k-mer decomposition

Each individual cell produces its own set of transcripts, which is the combined result of genetic variation, transcription regulation and post-transcriptional processing. Due to this combinatorial nature, obtaining the exhaustive set of full-length transcripts for a given species is a never-ending endeavor. Yet, each RNA deep sequencing experiment produces a variety of transcripts that depart from the reference transcriptome and should be properly identified. To address this challenge, we introduce a k-mer-based software protocol for capturing local RNA variation from a set of standard RNA-seq libraries, independently of a reference genome or transcriptome. Our software, called DE-kupl, analyzes k-mer contents and detects k-mers with differential abundance directly from the raw data files, prior to assembly or mapping. This enables to retrieve the virtually complete set of unannotated variation lying in an RNA-seq dataset. This variation is subsequently assigned to biological events such as differential lincRNAs, antisense RNAs, splice and polyadenylation variants, introns, expressed repeats, and SNV-harboring or exogenous RNA. We applied DE-kupl to public RNA-seq datasets, including an Epythelial-Mensenchymal Transition model and different human tissues. DE-kupl identified abundant novel events and showed excellent reproducibility when applied to independent deep sequencing experiments. DE-kupl is a new paradigm for analyzing differential RNA-seq data with no preconception on target events, which can also provide fresh insights into existing RNA-seq repositories.

bioinformatics↗