Identification and quantification of chimeric sequencing reads in a highly multiplexed RAD-seq protocol

ChimeraTE: a pipeline to detect chimeric transcripts derived from genes and transposable elements

Transposable elements (TEs) produce structural variants and are considered an important source of genetic diversity. Notably, TE-gene fusion transcripts, i.e. chimeric transcripts, have been associated with adaptation in several species. However, the identification of these chimeras remains hindered due to the lack of detection tools at a transcriptome-wide scale, and to the reliance on a reference genome, even though different individuals/cells/strains have different TE insertions. Therefore, we developed ChimeraTE, a pipeline that uses paired-end RNA-seq reads to identify chimeric transcripts through two different modes. Mode 1 is the reference-guided approach that employs canonical genome alignment, and Mode 2 identifies chimeras derived from fixed or insertionally polymorphic TEs without any reference genome. We have validated both modes using RNA-seq data from four Drosophila melanogaster wild-type strains. We found ∼1.12% of all genes generating chimeric transcripts, most of them from TE-exonized sequences. Approximately ∼23% of all detected chimeras were absent from the reference genome, indicating that TEs belonging to chimeric transcripts may be recent, polymorphic insertions. ChimeraTE is the first pipeline able to automatically uncover chimeric transcripts without a reference genome, consisting of two running Modes that can be used as a tool to investigate the contribution of TEs to transcriptome plasticity.

Developing a Nanopore Sequencing Workflow for Protein Engineering Applications

Sequencing plays a critical role in protein engineering, where the genetic information encoding for a desired mutation can be identified. We evaluated the performance of two commercially available NGS technologies (Illumina NGS and nanopore sequencing) on the available mutant libraries that were either previously constructed for other protein engineering projects or constructed in-house for this study. The sequencing results from Illumina sequencing indicated that a substantial proportion of the reads exhibited strand exchange, which mixed information of different mutants. When nanopore sequencing was used, the occurrence of strand exchange was substantially reduced compared with that of Illumina sequencing. We then developed a new library preparation workflow for nanopore sequencing and were successful in further reducing the incidence of strand exchange. The optimized workflow was successfully used to aid selection of improved alcohol dehydrogenase mutants in cells where their activities were coupled with the cell growth rate. The workflow quantified the enrichment fold change of most mutants in the library (size = 1728) in the growth-based selection passaging. A mutant that was >500% more active than its parent variant was identified based on the fold change data but not with the absolute abundance data (random sampling of the passaged cells), highlighting the usefulness of this rapid and affordable sequencing workflow in protein engineering.