Transcriptome-guided metabolic modeling implicates cerebellar insulin resistance in transgenic SCA3 mice
Transcriptome profiling of cerebellum from a transgenic SCA3 mouse model (84Q) and wild-type controls (15Q). Spinocerebellar ataxia type 3 (SCA3; Machado-Joseph disease) is a polyglutamine neurodegenerative disorder with prominent cerebellar involvement. To characterize disease-related transcriptional changes and to provide inputs for constraint-based metabolic modeling, we generated bulk RNA-seq from cerebellar tissue of SCA3-84Q mice and 15Q controls. The dataset supports differential expression, pathway enrichment, and integration with genome-scale metabolic models to examine mitochondrial and energy pathways and repair/proteostasis programs.Organism and tissue: Mus musculus, cerebellum.Cohorts and replicates: SCA3-84Q (n = 6) and 15Q controls (n = 6).Age and sex: 18 months; mixed sex (counts provided in sample metadata).Ethics: Institutional IACUC approval CCH-AE-106-017.Library and platform: Strand-specific mRNA libraries prepared with Agilent SureSelect; paired-end 150 bp on Illumina HiSeq 2500.Primary processing (per manuscript):- Read QC: FastQC.- Alignment: HISAT2 to GRCm39 (mm39) with default settings unless otherwise noted.- Post-processing: SAMtools for BAM processing and indexing.- Quantification: StringTie for transcript/gene-level quantification and generation of a count matrix.- RNA-seq QC: RSeQC for mapping and coverage metrics.- Batch correction: SVA in R (details in the manuscript Methods).Data deposited: Raw reads (FASTQ) for all biological replicates, plus a gene-level count matrix, sample metadata (genotype, age, sex, batch), and QC reports.Overall design:Bulk RNA-seq of mouse cerebellum comparing SCA3-84Q and 15Q control cohorts. Total RNA was isolated from cerebellar tissue; strand-specific mRNA libraries were prepared with Agilent SureSelect and sequenced as paired-end 150 bp reads on an Illumina HiSeq 2500. Processing followed the pipeline described in the manuscript: FastQC -> HISAT2 (mm39) -> SAMtools -> StringTie -> RSeQC, with batch correction using SVA. Sample-level metadata (genotype, age, sex, batch) enable reproduction of differential expression and downstream systems-biology analyses.Keywords: SCA3, Machado-Joseph disease, ATXN3, cerebellum, RNA-seq, mouse, polyglutamine, insulin resistance, genome-scale metabolic model, differential expression.