Program > Browse abstracts by speaker > Orozco-Arias Simon

The number of species with high quality genome sequences continues to increase, in part due to scaling up of multiple large scale biodiversity sequencing projects. While the need to annotate genic sequences in these genomes is widely acknowledged, the parallel need to annotate transposable element sequences that have been shown to alter genome architecture, rewire gene regulatory networks, and contribute to the evolution of host traits is becoming ever more evident. However, accurate genome-wide annotation of transposable element sequences is still technically challenging. Several de novo transposable element identification tools are now available, but manual curation of the libraries produced by these tools is needed to generate high quality genome annotations. Manual curation is time-consuming, and thus impractical for large-scale genomic studies, and lacks reproducibility. In this work, we present the Manual Curator Helper tool MCHelper, which automates the TE library curation process. By leveraging MCHelper's fully automated mode with the outputs from two de novo transposable element identification tools, RepeatModeler2 and REPET, in fruit fly, rice, and zebrafish, we show a substantial improvement in the quality of the transposable element libraries and genome annotations. MCHelper libraries are less redundant, with up to 54% reduction in the number of consensus sequences, have up to 11.4% fewer false positive sequences, and also have up to ∼45% fewer “unclassified/unknown” transposable element consensus sequences. Genome-wide transposable element annotations were also improved, including larger unfragmented insertions. Currently MCHelper includes a module to perform manual inspection of consensus sequences. However, to fully automate the curation process, we designed a post-processing workflow based on deep learning to automate the inspection of the consensus sequences and generate a ready-to-use curated library. MCHelper is a fast, easy to install, and easy to use tool and is available at https://github.com/GonzalezLab/MCHelper.