bioRxivGenomicsPreprint
SALRR: Scalable Analysis of Long-Read RNA-Seq Enables Comprehensive Transcriptome Profiling in Human Brain
Cedric KouamiD, Jackson Mingle, Pilar Álvarez JereziD, Allison Evans, Abraham Moller, Breeana BakeriD, Cory A. WelleriD, Kimberly PaquetteiD, Janet BrooksiD, Spencer M. GrantiD, Alexis Ayuketah, Melissa MeredithiD, Joanna PaladeiD, Laksh MalikiD, Kristen Hise, Jessica AndersoniD, Rob Harbert, Yilei FuiD, Xinchang ZhengiD, Sonia García-RuiziD, Emil Karl GustavssoniD, Cornelis BlauwendraatiD, Mina RyteniD, Fritz Joachim SedlazeckiD, Luigi FerrucciiD, , Kimberley J. BillingsleyiD
Abstract
Isoform-resolved transcriptomics is fundamental to decoding the molecular complexity of the human brain, yet population-scale long-read RNA sequencing has remained inaccessible due to labor-intensive library preparation, sensitivity to RNA degradation in postmortem tissue, and the absence of integrated, reproducible analysis pipelines. Here we present SALRR (Scalable Analysis of Long-Read RNA-seq), an integrated wet-lab and computational platform designed to overcome these barriers. Automated ONT long-read cDNA library preparation on the Hamilton Microlab NGS STAR platform reduces hands-on time by 67% and enables 24 libraries per operator per day while maintaining performance across RNA integrity values. A modular, Snakemake-based pipeline performs end-to-end processing from ONT signal data to isoform-level quantification, incorporating SIRV spike-in calibration, multi-stage quality control, and stringent isoform validation. Applied to 10 postmortem frontal cortex samples from the North American Brain Expression Consortium, SALRR identified 31,607 high-confidence isoforms from 10,075 genes, including 8,532 novel splice variants absent from GENCODE v49, and complex splicing events systematically missed by short-read sequencing at neurodegeneration-relevant loci, including GBA1, CCNF, CHCHD10, and TREM2. All protocols and code are openly available, providing a scalable, community-ready framework for isoform-resolved transcriptomics in neurodegeneration, aging, and complex brain disease.
- organism: human
- assay: long-read sequencing
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- Citations
- 0
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