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Confound-aware lncRNA genomics: Separating biology from abundance, composition, and temporal artefacts.

Created on 24 Aug 2026

Authors

Hidenori Tani

Published in

Biotechnology advances. Pages 109021. Aug 23, 2026. Epub Aug 23, 2026.

Abstract

Long non-coding RNAs (lncRNAs) are nominated at scale as disease biomarkers and as targets for antisense and RNA-targeting therapeutics, yet many fail to replicate - a translational liability: an artefactual target wastes preclinical investment. The reflex explanation is that lncRNA biology is intrinsically hard to measure. This Review argues instead that a large, addressable fraction of the irreproducibility is the signature of three pervasive measurement confounds: low transcript abundance, cell-type composition shifts, and steady-state snapshotting. Abundance is the most recurrent axis across them, but not a universal root cause: composition is causally distinct, driven by cell-type restriction, and snapshotting is a separate identifiability problem. Drawing on the primary literature, I show how apparent class-specific phenomena (noisier half-lives, inflated network centrality, detection deficits) largely dissolve once transcripts are compared at matched abundance, and how composition shifts can manufacture, invert or mask a bulk disease association independently of within-cell regulation. All three are preceded by a transcript-definition problem: lncRNA isoforms can carry opposing functions, and roughly half of lncRNAs are estimated to lack a poly(A) tail, so isoform identity and library chemistry determine what is measured at all. I then distil a portable, confound-aware workflow - a transcript-definition step followed by four analytical gates: abundance-matched nulls, composition adjustment, reliability and leakage flags, and orthogonal or temporal validation - and map it onto the biotechnology pipeline as a low-cost risk-reduction filter for biomarker discovery, drug-target selection, diagnostic design and predictive modelling. Trustworthy measurement is the foundation on which trustworthy lncRNA biotechnology is built.

PMID:
42633884
Bibliographic data and abstract were imported from PubMed on 24 Aug 2026.

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