LocusMasterTE: integrating long-read RNA sequencing improves locus-specific quantification of transposable element expression

Abstract

Transposable elements (TEs) can influence human diseases by disrupting genome integrity, yet their quantification has been challenging due to the repetitive nature of these sequences across the genome. We develop LocusMasterTE, a method that integrates long-read with short-read RNA-seq to increase the accuracy of TE expression quantification. By incorporating fractional transcript per million values from long-read sequencing data into an expectation–maximization algorithm, LocusMasterTE reassigns multi-mapped reads, enhancing accuracy in short-read-based TE quantification. We validate the method with simulated and human datasets. LocusMasterTE may give new insights into TE functions through precise quantification.