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F. Sedlazeck

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Open access Aug 2026

SALRR: Scalable Analysis of Long-Read RNA-Seq Enables Comprehensive Transcriptome Profiling in Human Brain

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.

C. Kouam, Jackson Mingle, Pilar Álvarez Jerez et al. · 0 citations
Open access Aug 2026

A complete diploid human genome benchmark for personalized genomics

SUMMARY Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of reads, phased variant call sets, and assemblies against a diploid reference. Genome-wide analyses show that de novo assembly resolves 2%–7% more sequence and outperforms variant calling accuracy by an order of magnitude, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji et al. · 6 citations

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