Tandem LTR-retrotransposon structures are common and highly polymorphic in plant genomes

Abstract

Background LTR-retrotransposons (LTR-RT) are a major component of plant genomes and important drivers of genome evolution. Most LTR-RT copies in plant genomes are defective elements found as truncated copies, nested insertions or as part of more complex structures. The recent availability of highly contiguous plant genome assemblies based on long-read sequences now allows to perform detailed characterization of these complex structures and to evaluate their importance for plant genome evolution.

Results The detailed analysis of two rice loci containing complex LTR-RT structures showed that they consist of tandem arrays of LTR copies sharing internal LTRs. Our analyses suggests that these LTR-RT tandems are the result of a single insertion and not of the recombination of two independent LTR-RT elements. Our results also suggest that gypsy elements may be more prone to form these structures. We show that these structures are highly polymorphic in rice and therefore have the potential to generate genetic variability. We have developed a computational pipeline (IDENTAM) that scans genome sequences and identifies tandem LTR-RT candidates. Using this tool, we have detected 266 tandems in a pangenome built from the genomes of 76 accessions of cultivated and wild rice, showing that tandem LTR-RT structures are frequent and highly polymorphic in rice. Running IDENTAM in the Arabidopsis, almond and cotton genomes showed that LTR-RT tandems are frequent in plant genomes of different size, complexity and ploidy level. The complexity of differentiating intra-element variations at the nucleotide level among haplotypes is very high, and we found that graph-based pangenomic methodologies are appropriate to resolve these structures.

Conclusions Our results show that LTR-RT elements can form tandem arrays. These structures are relatively abundant and highly polymorphic in rice and are widespread in the plant kingdom. Future studies will contribute to understanding how these structures originate and whether the variability that they generate has a functional impact.