Transposable elements (TEs) have been associated with many, frequently detrimental, biological roles. Consequently, the regulations of TEs, e.g. via DNA-methylation and histone modifications, are considered critical for maintaining genomic integrity and other functions. Still, the high-throughput study of TEs is usually limited to the family or consensus-sequence level because of alignment problems prompted by high-sequence similarities and short read lengths. To entirely comprehend the effects and reasons of TE expression, however, it is necessary to assess the TE expression at the level of individual instances. Our simulation study demonstrates that sequence similarities and short read lengths do not rule out the accurate assessment of (differential) expression of TEs at the instance-level. With only slight modifications to existing methods, TE expression analysis works surprisingly well for conventional paired-end sequencing data. We find that SalmonTE and Telescope can accurately tally a considerable amount of TE instances, allowing for differential expression recovery in model and non-model organisms.
Keywords: RNA sequencing; differential expression analysis; simulation; tool comparison; transposable elements.
© The Author(s) 2021. Published by Oxford University Press.