Clément Goubert

The accelerating pace of genome sequencing throughout the tree of life is driving the need for improved unsupervised annotation of genome components such as transposable elements (TEs). Because the types and sequences of TEs are highly variable across species, automated TE discovery and annotation are challenging and time-consuming tasks. A critical first step is the de novo identification and accurate compilation of sequence models representing all of the unique TE families dispersed in the genome. Here we introduce RepeatModeler2, a pipeline that greatly facilitates this process. This program brings substantial improvements over the original version of RepeatModeler, one of the most widely used tools for TE discovery. In particular, this version incorporates a module for structural discovery of complete long terminal repeat (LTR) retroelements, which are widespread in eukaryotic genomes but recalcitrant to automated identification because of their size and sequence complexity. We benchmarked RepeatModeler2 on three model species with diverse TE landscapes and high-quality, manually curated TE libraries: Drosophila melanogaster (fruit fly), Danio rerio (zebrafish), and Oryza sativa (rice). In these three species, RepeatModeler2 identified approximately 3 times more consensus sequences matching with >95% sequence identity and sequence coverage to the manually curated sequences than the original RepeatModeler. As expected, the greatest improvement is for LTR retroelements. Thus, RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license ( https://github.com/Dfam-consortium/RepeatModeler , http://www.repeatmasker.org/RepeatModeler/ ).

Abstract The accelerating pace of genome sequencing throughout the tree of life is driving the need for improved unsupervised annotation of genome components such as transposable elements (TEs). Because the types and sequences of TEs are highly variable across species, automated TE discovery and annotation are challenging and time-consuming tasks. A critical first step is the de novo identification and accurate compilation of sequence models representing all the unique TE families dispersed in the genome. Here we introduce RepeatModeler2, a new pipeline that greatly facilitates this process. This new program brings substantial improvements over the original version of RepeatModeler, one of the most widely used tools for TE discovery. In particular, this version incorporates a module for structural discovery of complete LTR retroelements, which are widespread in eukaryotic genomes but recalcitrant to automated identification because of their size and sequence complexity. We benchmarked RepeatModeler2 on three model species with diverse TE landscapes and high-quality, manually curated TE libraries: Drosophila melanogaster (fruit fly), Danio rerio (zebrafish), and Oryza sativa (rice). In these three species, RepeatModeler2 identified approximately three times more consensus sequences matching with >95% sequence identity and sequence coverage to the manually curated sequences than the original RepeatModeler. As expected, the greatest improvement is for LTR retroelements. The program had an extremely low false positive rate when applied to simulated genomes devoid of TEs. Thus, RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license ( https://github.com/Dfam-consortium/RepeatModeler , https://github.com/Dfam-consortium/TETools ). Significance Genome sequences are being produced for more and more eukaryotic species. The bulk of these genomes is composed of parasitic, self-mobilizing transposable elements (TEs) that play important roles in organismal evolution. Thus there is a pressing need for developing software that can accurately identify the diverse set of TEs dispersed in genome sequences. Here we introduce RepeatModeler2, an easy-to-use package for the curation of reference TE libraries which can be applied to any eukaryotic species. Through several major improvements over the previous version, RepeatModeler2 is able to produce libraries that recapitulate the known composition of three model species with some of the most complex TE landscapes. Thus RepeatModeler2 will greatly enhance the discovery and annotation of TEs in genome sequences.

Repetitive DNA, including transposable elements (TEs), is found throughout eukaryotic genomes. Annotating and assembling the "repeatome" during genome-wide analysis often poses a challenge. To address this problem, we present dnaPipeTE-a new bioinformatics pipeline that uses a sample of raw genomic reads. It produces precise estimates of repeated DNA content and TE consensus sequences, as well as the relative ages of TE families. We shows that dnaPipeTE performs well using very low coverage sequencing in different genomes, losing accuracy only with old TE families. We applied this pipeline to the genome of the Asian tiger mosquito Aedes albopictus, an invasive species of human health interest, for which the genome size is estimated to be over 1 Gbp. Using dnaPipeTE, we showed that this species harbors a large (50% of the genome) and potentially active repeatome with an overall TE class and order composition similar to that of Aedes aegypti, the yellow fever mosquito. However, intraorder dynamics show clear distinctions between the two species, with differences at the TE family level. Our pipeline's ability to manage the repeatome annotation problem will make it helpful for new or ongoing assembly projects, and our results will benefit future genomic studies of A. albopictus.

BACKGROUND: In the study of transposable elements (TEs), the generation of a high confidence set of consensus sequences that represent the diversity of TEs found in a given genome is a key step in the path to investigate these fascinating genomic elements. Many algorithms and pipelines are available to automatically identify putative TE families present in a genome. Despite the availability of these valuable resources, producing a library of high-quality full-length TE consensus sequences largely remains a process of manual curation. This know-how is often passed on from mentor-to-mentee within research groups, making it difficult for those outside the field to access this highly specialised skill. RESULTS: Our manuscript attempts to fill this gap by providing a set of detailed computer protocols, software recommendations and video tutorials for those aiming to manually curate TEs. Detailed step-by-step protocols, aimed at the complete beginner, are presented in the Supplementary Methods. CONCLUSIONS: The proposed set of programs and tools presented here will make the process of manual curation achievable and amenable to all researchers and in special to those new to the field of TEs.

Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatiotemporal patterns of genetic variation in natural populations have been challenging, as comprehensive sampling is logistically difficult, and sequencing of entire populations costly. Here, we address these issues using a collaborative approach, sequencing 48 pooled population samples from 32 locations, and perform the first continent-wide genomic analysis of genetic variation in European Drosophila melanogaster. Our analyses uncover longitudinal population structure, provide evidence for continent-wide selective sweeps, identify candidate genes for local climate adaptation, and document clines in chromosomal inversion and transposable element frequencies. We also characterize variation among populations in the composition of the fly microbiome, and identify five new DNA viruses in our samples.