Transposable Element Annotation in Completely Sequenced Eukaryote Genomes

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.

RepBox: a toolbox for the identification of repetitive elements

BACKGROUND

Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de novo assembled genomes demands new tools to improve the efficiency of this process. For this reason, we developed RepBox, a suite of Python scripts that combine several pre-existing family-specific TE detection methods into a single user-friendly pipeline.

RESULTS

Based on comparisons of RepBox with the standard TE detection software RepeatModeler, we find that RepBox consistently classifies more elements and is also able to identify a more diverse array of TE families than the existing methods in plant genomes.

CONCLUSIONS

The performance of RepBox on two different plant genomes indicates that our toolbox represents a significant improvement over existing TE detection methods, and should facilitate future TE annotation efforts in additional species.

Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes

LTR-retrotransposons are the most abundant repeat sequences in plant genomes and play an important role in evolution and biodiversity. Their characterization is of great importance to understand their dynamics. However, the identification and classification of these elements remains a challenge today. Moreover, current software can be relatively slow (from hours to days), sometimes involve a lot of manual work and do not reach satisfactory levels in terms of precision and sensitivity. Here we present Inpactor2, an accurate and fast application that creates LTR-retrotransposon reference libraries in a very short time. Inpactor2 takes an assembled genome as input and follows a hybrid approach (deep learning and structure-based) to detect elements, filter partial sequences and finally classify intact sequences into superfamilies and, as very few tools do, into lineages. This tool takes advantage of multi-core and GPU architectures to decrease execution times. Using the rice genome, Inpactor2 showed a run time of 5 minutes (faster than other tools) and has the best accuracy and F1-Score of the tools tested here, also having the second best accuracy and specificity only surpassed by EDTA, but achieving 28% higher sensitivity. For large genomes, Inpactor2 is up to seven times faster than other available bioinformatics tools.

TransposonUltimate: software for transposon classification, annotation and detection

Most genomes harbor a large number of transposons, and they play an important role in evolution and gene regulation. They are also of interest to clinicians as they are involved in several diseases, including cancer and neurodegeneration. Although several methods for transposon identification are available, they are often highly specialised towards specific tasks or classes of transposons, and they lack common standards such as a unified taxonomy scheme and output file format. We present TransposonUltimate, a powerful bundle of three modules for transposon classification, annotation, and detection of transposition events. TransposonUltimate comes as a Conda package under the GPL-3.0 licence, is well documented and it is easy to install through https://github.com/DerKevinRiehl/TransposonUltimate. We benchmark the classification module on the large TransposonDB covering 891,051 sequences to demonstrate that it outperforms the currently best existing solutions. The annotation and detection modules combine sixteen existing softwares, and we illustrate its use by annotating Caenorhabditis elegans, Rhizophagus irregularis and Oryza sativa subs. japonica genomes. Finally, we use the detection module to discover 29 554 transposition events in the genomes of 20 wild type strains of C. elegans. Databases, assemblies, annotations and further findings can be downloaded from (https://doi.org/10.5281/zenodo.5518085).

Short interspersed nuclear elements (SINEs) are abundant in Solanaceae and have a family-specific impact on gene structure and genome organization

Short interspersed nuclear elements (SINEs) are highly abundant non-autonomous retrotransposons that are widespread in plants. They are short in size, non-coding, show high sequence diversity, and are therefore mostly not or not correctly annotated in plant genome sequences. Hence, comparative studies on genomic SINE populations are rare. To explore the structural organization and impact of SINEs, we comparatively investigated the genome sequences of the Solanaceae species potato (Solanum tuberosum), tomato (Solanum lycopersicum), wild tomato (Solanum pennellii), and two pepper cultivars (Capsicum annuum). Based on 8.5 Gbp sequence data, we annotated 82 983 SINE copies belonging to 10 families and subfamilies on a base pair level. Solanaceae SINEs are dispersed over all chromosomes with enrichments in distal regions. Depending on the genome assemblies and gene predictions, 30% of all SINE copies are associated with genes, particularly frequent in introns and untranslated regions (UTRs). The close association with genes is family specific. More than 10% of all genes annotated in the Solanaceae species investigated contain at least one SINE insertion, and we found genes harbouring up to 16 SINE copies. We demonstrate the involvement of SINEs in gene and genome evolution including the donation of splice sites, start and stop codons and exons to genes, enlargement of introns and UTRs, generation of tandem-like duplications and transduction of adjacent sequence regions.

Accurate Transposable Element Annotation Is Vital When Analyzing New Genome Assemblies

Transposable elements (TEs) are mobile genetic elements with the ability to replicate themselves throughout the host genome. In some taxa TEs reach copy numbers in hundreds of thousands and can occupy more than half of the genome. The increasing number of reference genomes from nonmodel species has begun to outpace efforts to identify and annotate TE content and methods that are used vary significantly between projects. Here, we demonstrate variation that arises in TE annotations when less than optimal methods are used. We found that across a variety of taxa, the ability to accurately identify TEs based solely on homology decreased as the phylogenetic distance between the queried genome and a reference increased. Next we annotated repeats using homology alone, as is often the case in new genome analyses, and a combination of homology and de novo methods as well as an additional manual curation step. Reannotation using these methods identified a substantial number of new TE subfamilies in previously characterized genomes, recognized a higher proportion of the genome as repetitive, and decreased the average genetic distance within TE families, implying recent TE accumulation. Finally, these finding-increased recognition of younger TEs-were confirmed via an analysis of the postman butterfly (Heliconius melpomene). These observations imply that complete TE annotation relies on a combination of homology and de novo-based repeat identification, manual curation, and classification and that relying on simple, homology-based methods is insufficient to accurately describe the TE landscape of a newly sequenced genome.

A call for benchmarking transposable element annotation methods

DNA derived from transposable elements (TEs) constitutes large parts of the genomes of complex eukaryotes, with major impacts not only on genomic research but also on how organisms evolve and function. Although a variety of methods and tools have been developed to detect and annotate TEs, there are as yet no standard benchmarks-that is, no standard way to measure or compare their accuracy. This lack of accuracy assessment calls into question conclusions from a wide range of research that depends explicitly or implicitly on TE annotation. In the absence of standard benchmarks, toolmakers are impeded in improving their tools, annotators cannot properly assess which tools might best suit their needs, and downstream researchers cannot judge how accuracy limitations might impact their studies. We therefore propose that the TE research community create and adopt standard TE annotation benchmarks, and we call for other researchers to join the authors in making this long-overdue effort a success.