Dataset Information

Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning.

ABSTRACT: Transposable elements are mobile sequences that can move and insert themselves into chromosomes, activating under internal or external stimuli, giving the organism the ability to adapt to the environment. Annotating transposable elements in genomic data is currently considered a crucial task to understand key aspects of organisms such as phenotype variability, species evolution, and genome size, among others. Because of the way they replicate, LTR retrotransposons are the most common transposable elements in plants, accounting in some cases for up to 80% of all DNA information. To annotate these elements, a reference library is usually created, a curation process is performed, eliminating TE fragments and false positives and then annotated in the genome using the homology method. However, the curation process can take weeks, requires extensive manual work and the execution of multiple time-consuming bioinformatics software. Here, we propose a machine learning-based approach to perform this process automatically on plant genomes, obtaining up to 91.18% F1-score. This approach was tested with four plant species, obtaining up to 93.6% F1-score (Oryza granulata) in only 22.61 s, where bioinformatics methods took approximately 6 h. This acceleration demonstrates that the ML-based approach is efficient and could be used in massive sequencing projects.

SUBMITTER: Orozco-Arias S

PROVIDER: S-EPMC9521825 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning.

Orozco-Arias Simon S Candamil-Cortes Mariana S MS Jaimes Paula A PA Valencia-Castrillon Estiven E Tabares-Soto Reinel R Isaza Gustavo G Guyot Romain R

Journal of integrative bioinformatics 20220712 3

Transposable elements are mobile sequences that can move and insert themselves into chromosomes, activating under internal or external stimuli, giving the organism the ability to adapt to the environment. Annotating transposable elements in genomic data is currently considered a crucial task to understand key aspects of organisms such as phenotype variability, species evolution, and genome size, among others. Because of the way they replicate, LTR retrotransposons are the most common transposabl ...[more]

PMID: 35822734

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Project description:BackgroundLTR-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.ResultsThe 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.ConclusionsOur 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.

Dataset Information

Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning.

Publications

Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning.

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