ReviewBiomolecules2026
Active Human Transposable Elements: Long-Read Sequencing Technologies, Computational Analysis, and Implications for Human Disease.
Review in Biomolecules, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Transposable elements (TEs) account for nearly half of the human genome and shape chromatin organization, gene regulation, and genome evolution. However, their contributions to human physiology and disease remain incompletely understood. The most active elements in humans, LINE-1 (L1), Alu, and SVA, retain some copies with the ability to evade epigenetic repression and mobilize via target-primed reverse transcription (TPRT), whereas copies become inactive through various fragmentations and mutations. TE activity contributes to genomic instability and has been implicated in aging, cancer, neurological disorders, chromatin organization, and epigenetic regulation. Studying TE is challenging due to their repetitive and polymorphic nature. Recent advances in sequencing technologies and short- and long-read sequencing platforms, combined with specialized bioinformatic pipelines, currently enable more comprehensive characterization of TE insertions, deletions, expression, and epigenetic status. Computational approaches vary in sensitivity, specificity, and resource requirements, and their performance is influenced by sequencing modality, coverage, and the reference genome used. Assembly-based and read-based methods, as well as integrating methylation data or single-cell data, provide complementary insights into TE biology. This review summarizes the biology of active human TE, surveys state-of-the-art short- and long-read pipelines for TE analysis, and highlights their applications in studies of aging, cancer, and other complex diseases. We also provide practical guidance for selecting appropriate sequencing strategies and tools for TE-focused projects, and discuss emerging approaches and open questions in the field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.