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bioRxiv · 10.64898/2026.08.12.744438

IsoAtlas: Visual interpretation of known and novel transcript isoforms using population-scale long-read evidence

Zheng, X.·Sedlazeck, F. J.
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Abstract

Long-read RNA sequencing has revealed extensive transcript diversity, but newly observed isoforms remain difficult to interpret beyond their classification as known or novel. Here, we present IsoAtlas, an interactive multispecies database for visual exploration and population-scale interpretation of transcript isoforms using 1, 035 human and 414 mouse uniformly processed long-read RNA-sequencing samples. Users can search annotated genes and transcripts or submit novel transcript models in GTF format, visualize their structures, and examine sample-level support, prevalence, expression, tissue and disease context, and sequencing-platform evidence. IsoAtlas integrates structurally equivalent transcripts across GENCODE, RefSeq and CHESS, consolidating evidence that would otherwise be distributed across annotation-specific identifiers. It further links corresponding human and mouse transcript models, enabling users to assess cross-species conservation and enabling users to assess cross-species conservation and inform the suitability of mouse models for isoform-specific studies. IsoAtlas can also evaluate arbitrary user-supplied transcript structures directly against accumulated long-read evidence. IsoAtlas therefore complements established reference annotations with an extensible evidence layer that connects transcript structure to population prevalence, biological context and cross-species support. IsoAtlas is freely available at https://www.isoatlas.org/. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/744438v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@89bd72org.highwire.dtl.DTLVardef@f48bbforg.highwire.dtl.DTLVardef@102ae37org.highwire.dtl.DTLVardef@fbbc2b_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Zheng, X., Sedlazeck, F. J.. 2026-08-21. IsoAtlas: Visual interpretation of known and novel transcript isoforms using population-scale long-read evidence. https://doi.org/10.64898/2026.08.12.744438

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