Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning.

ABSTRACT:

Background

Long terminal repeats (LTRs) represent important parts of LTR retrotransposons and retroviruses found in high copy numbers in a majority of eukaryotic genomes. LTRs contain regulatory sequences essential for the life cycle of the retrotransposon. Previous experimental and sequence studies have provided only limited information about LTR structure and composition, mostly from model systems. To enhance our understanding of these key sequence modules, we focused on the contrasts between LTRs of various retrotransposon families and other genomic regions. Furthermore, this approach can be utilized for the classification and prediction of LTRs.

Results

We used machine learning methods suitable for DNA sequence classification and applied them to a large dataset of plant

SUBMITTER: Horvath J 

PROVIDER: S-EPMC11656987 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature