Benoit, Matthias, Drost, Hajk-Georg (April 2021) A Predictive Approach to Infer the Activity and Natural Variation of Retrotransposon Families in Plants. Methods in Molecular Biology, 2250. pp. 1-14. ISSN 1064-3745
Abstract
Plant genomes harbor a particularly rich landscape of repetitive sequences. Transposable elements (TEs) represent a major fraction of this diversity and are intimately linked with plasticity and evolution of genomes across the tree of life (Fedoroff, Science 338:758-767, 2012). Amplification of Long Terminal Repeats (LTR) retrotransposons have shaped the genomic landscape by reshuffling genomic regions, altering gene expression, and providing new regulatory sequences, some of which have been instrumental for crop domestication and breeding (Lisch, Nat Rev Genet 14:49-61, 2013; Vitte et al., Brief Funct Genomics 13:276-295, 2014). While many retrotransposon families are still active within plant genomes, the repetitive nature of retrotransposons has hindered accurate annotation and kingdom-wide predictive assessment of their activity and molecular evolution. While it is natural for the first approach towards a genome annotation to characterize all regions of the genome and associate them with known structures such as particular genes, transposable elements, or other types of non-coding regions, such efforts can result in a large proportion of false-positive annotations when seeking for active loci. To overcome this issue, the next round of annotation efforts needs to include functional annotations based on rigorously defined sequence structures and protein domain compositions. In the context of retrotransposons, such a functional annotation can enable efforts to mobilize particular retrotransposon families in species living today and harness their mutagenic potency for crop improvement (Paszkowski, Curr Opin Biotechnol 32:200-206, 2015). For this purpose, we present a predictive analytical approach to infer the activity and natural variation of retrotransposon families in plants. This is achieved by applying a combination of software and molecular biology tools we developed for functional annotation, activity monitoring, and the assessment of the population structure of particular retrotransposon families in multiple plant species.
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