{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T16:03:30Z","timestamp":1793721810192,"version":"4.6.1"},"posted":{"date-parts":[[2026,2,12]]},"group-title":"Bioinformatics","reference-count":73,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,2,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>Recent advances in long-read transcriptome sequencing enable high-throughput profiling of full-length RNA isoforms in bulk, single-cell, and single-nucleus samples. However, long-read datasets typically contain a mixture of complete and partial transcripts, leading to pervasive ambiguity in read-to-isoform assignment and complicating accurate isoform identification and quantification, particularly in the absence of reliable reference annotations. These challenges are further amplified in single-cell and single-nucleus samples, where coverage is sparse and transcriptional heterogeneity is high.<\/jats:p>\n                <jats:p>Here, we present the Long Read Alignment Assembler (LRAA), a unified and versatile computational framework for isoform identification and quantification from long-read RNA sequencing data across bulk, single-cell, and single-nucleus transcriptomic samples. LRAA combines splice-graph based structural modeling with expectation maximization based optimization to probabilistically resolve ambiguous read assignments and improve isoform abundance estimation. The framework supports quantification-only, reference-guided, and fully reference-free (de novo) modes of analysis within a single methodological paradigm.<\/jats:p>\n                <jats:p>We benchmarked LRAA using both simulated and genuine long-read datasets spanning sequencing standards and whole transcriptomes. Central to this evaluation is a novel benchmarking strategy based on Multiplexed Overexpression of Regulatory Factors (MORFs), which provides biologically expressed, barcoded isoforms with unambiguous read-level ground truth. Across all benchmarks, including MORFs, synthetic spike-ins, and whole-transcriptome datasets, LRAA consistently outperformed state-of-the-art methods in isoform identification accuracy, sensitivity, and expression quantification.<\/jats:p>\n                <jats:p>\n                  Finally, we demonstrate the biological utility of LRAA by resolving cell-type-specific isoform usage across peripheral blood immune cell populations and by detecting a pathogenic cryptic isoform of\n                  <jats:italic>STMN2<\/jats:italic>\n                  with associated transcriptional changes in single-nucleus RNA-seq data from frontal cortex tissue of an individual with frontotemporal dementia (FTD). Together, these results establish LRAA as a robust and general solution for resolving transcript diversity in complex biological systems, from development to disease.\n                <\/jats:p>","DOI":"10.64898\/2026.02.12.705617","type":"posted-content","created":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:40:53Z","timestamp":1770964853000},"source":"Crossref","is-referenced-by-count":5,"title":["Accurate strand-specific long-read transcript isoform discovery and quantification at bulk, single-cell, and single-nucleus resolution"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5374-2783","authenticated-orcid":false,"given":"Houlin","family":"Yu","sequence":"first","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christophe H.","family":"Georgescu","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akanksha","family":"Khorgade","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghamdan","family":"Al-Eryani","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel A.","family":"Bartlett","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allison","family":"Brookhart","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, 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Alzheimer\u2019s and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangle","family":"Hu","sequence":"additional","affiliation":[{"name":"Center for Alzheimer\u2019s and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah","family":"Bromberek","sequence":"additional","affiliation":[{"name":"Center for Alzheimer\u2019s and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, 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