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Detalle de: Transcriptome Universal Single-isoform COntrol: A Framework for Evaluating Transcriptome reconstruction Quality

Title Transcriptome Universal Single-isoform COntrol: A Framework for Evaluating Transcriptome reconstruction Quality
Abstract

Long-read sequencing (LRS) platforms, such as Oxford Nanopore and Pacific Biosciences, enable comprehensive transcriptome analysis but face challenges such as sequencing errors, sample quality variability, and library preparation biases. Current benchmarking approaches address these issues insufficiently: BUSCO assesses transcriptome completeness using conserved single-copy orthologs but can misinterpret alternative splicing as gene duplications, while spike-ins (SIRVs, ERCCs) oversimplify real- sample complexity, neglecting RNA degradation and RNA extraction artifacts, thus inflating performance metrics. Simulation algorithms are limited to recapitulate this complexity. To overcome these limitations, we introduce the Transcriptome Universal Single-isoform Control (TUSCO), a curated internal reference set of genes lacking alternative isoforms. TUSCO evaluates precision by identifying transcripts deviating from reference annotations and assesses sensitivity by verifying detection completeness in human and mouse samples. Masking TUSCO transcripts—and optionally inserting decoy splice variants—creates a ‘novel- isoform’ challenge that assesses recovery of the true, now-unannotated isoforms. Our validation demonstrates that TUSCO provides accurate and reliable benchmarking without external controls, significantly improving quality control standards for transcriptome reconstruction using LRS.

Apa Reference Liu, T., Paniagua, A., Jetzinger, F., Ferrández-Peral, L., Frankish, A. & Conesa, A. (2025). Transcriptome Universal Single-isoform COntrol: A Framework for Evaluating Transcriptome reconstruction Quality. 10.1101/2025.08.23.671926
Doi 10.1101/2025.08.23.671926
Publication Date 28 Aug 2025
Publication Type Preprint
Researcher Ana Conesa
Ontology Transcriptomics, Benchmarking, Genome Assembly, Computational models and simulations, Molecular evolution, Sequence error correction, Long-read sequencing
Research Groups
Tools

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