Transcriptomic profiling and differential expression analysis

PRIMARY OUTCOME

differentially expressed transcripts (mRNAs, lncRNAs, miRNAs)

EXPECTED OUTCOMES

## Expected Outcomes ### Primary Outcomes 1. **Inflammation/immune response:** Upregulation of complement components (C1q, C3), cytokines (IL-1β, TNF-α) in APP/PS1 cortex 2. **Synaptic dysfunction:** Downregulation of glutamate receptor subunits (Grin1, Grin2a), synaptic vesicle genes (Snap25, Syn1) 3. **Lipid metabolism alterations:** Changes in cholesterol biosynthesis genes (Hmgcr, Ldlr) and lipid transport genes 4. **Myelin changes:** Altered expression of oligodendrocyte markers (Mbp, Plp1, Mog) ### Secondary Outcomes - Microglial activation signature (Trem2, Cx3cr1, Aif1) - Astrocyte reactivity markers (Gfap, S100b) - Potential early amyloid processing gene changes (App, Bace1, Psen1) ### Null Result Interpretation - At 1 month (pre-symptomatic), changes may be subtle - May need older timepoints (3, 6 months) to capture robust transcriptome changes - Consider cell-type specific approaches (single-cell RNA-seq)

SUCCESS CRITERIA

## Success Criteria ### Primary - [ ] RIN > 8.0, ≥5 µg RNA per sample, 6 biological replicates per group - [ ] ≥30M reads/sample, Q30 > 85%, ≥80% uniquely mapped - [ ] DESeq2: ≥100 significant DEGs (FDR < 0.05) - [ ] GSEA: ≥3 enriched pathways (FDR < 0.05) ### Secondary - [ ] ERCC spike-in recovery within expected range - [ ] Correlation between replicates: r > 0.9 - [ ] Sex-specific DEGs identified and reported ### Technical Quality Gates - [ ] Library complexity: unique fragments > 80% for all libraries - [ ] Ribosomal reads < 5% after cleaning - [ ] Blinded differential expression analysis

PROTOCOL

## Protocol: Transcriptomic Profiling in APP/PS1 AD Mouse Model ### Study Design RNA sequencing analysis of cerebral tissue from 1-month-old APP/PS1 transgenic AD mice vs age-matched WT controls. Identify early transcriptomic changes in Alzheimer's disease pathogenesis. ### Animals and Tissue Collection 1. APP/PS1 transgenic mice (n=6 per group, equal sex distribution) and WT littermates (n=6) 2. Euthanize by rapid decapitation at 1 month (pre-symptomatic stage) 3. Dissect brain region of interest (cerebral cortex) within 2 minutes 4. Flash-freeze tissue in liquid nitrogen 5. Store at -80°C until RNA extraction ### RNA Extraction 1. Homogenize frozen tissue in QIAzol lysis buffer using TissueRuptor 2. Extract total RNA with RNeasy Mini Kit per manufacturer protocol 3. Assess quantity (NanoDrop A260/280 > 1.8) and quality (Bioanalyzer RIN > 8.0) 4. Poly-A selection or rRNA depletion for mRNA capture 5. Prepare mRNAseq libraries using NEBNext Ultra II RNA Library Prep Kit ### Sequencing 1. Sequence on Illumina NovaSeq or equivalent platform 2. Target depth: 30-50 million paired-end 150 bp reads per sample 3. Include spike-in ERCC RNA controls for calibration 4. Assess sequencing quality (Q30 > 85%) ### Bioinformatics Analysis 1. Quality control: FastQC, trim adapters/low-quality bases (Trimmomatic) 2. Alignment: STAR or HISAT2 to mm10 reference genome 3. Quantification: featureCounts or RSEM for gene-level expression 4. Differential expression: DESeq2 or edgeR - Contrast: APP/PS1 vs WT - Significance: FDR < 0.05, |log2FC| > 0.5 5. Pathway analysis: GSEA, KEGG, Reactome enrichment 6. Visualization: volcano plots, heatmaps, IGV browser tracks ### Controls - **Biological replicates:** n=6 per group (minimum for sufficient power) - **ERCC spike-ins:** For calibration of fold-change estimates - **Library complexity:** % mapping > 80%, ribosomal reads < 5% - **Sex as covariate:** Include sex in design matrix ### Expected Outcomes 1. Upregulation of inflammation/immune response genes (e.g., complement components, cytokines) 2. Dysregulation of synaptic transmission genes (glutamate signaling, ion channels) 3. Altered lipid metabolism and cholesterol biosynthesis genes 4. Changes in myelination-related genes (oligodendrocyte function) 5. Potential upregulation of stress response genes (UPR, oxidative stress) ### Success Criteria - [ ] RIN > 8.0 for all samples, ≥ 5 µg total RNA per sample - [ ] ≥30 million reads per sample with Q30 > 85% - [ ] ≥80% reads uniquely mapped to mm10 - [ ] DESeq2 analysis: significant DEGs (FDR < 0.05) identified - [ ] GSEA: ≥3 significantly enriched pathways (FDR < 0.05) - [ ] Technical replicates (library prep duplicates) show correlation r > 0.95

LINKED HYPOTHESES

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