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RNA-seq

Experimental Design Considerations

Replication Strategy

Plan for at least 3 biological replicates per condition, with 5-6 replicates preferred for detecting smaller effect sizes. Technical replicates are generally unnecessary with modern RNA-seq protocols.

Sample Collection and Storage

  • RNA integrity: Target RIN scores >7 for optimal results, though degraded samples (RIN 5-7) can still provide useful data with appropriate analysis adjustments
  • Storage: Flash freeze samples in liquid nitrogen and store at -80°C. Avoid freeze-thaw cycles
  • Batch effects: Randomize sample processing across batches when possible

Library Preparation Considerations

  • Poly(A) selection vs. rRNA depletion: Choose based on research goals - poly(A) for mRNA focus, rRNA depletion for comprehensive transcriptome including non-coding RNAs
  • Strand-specific libraries: Recommended for accurate transcript quantification and novel transcript discovery
  • PCR amplification: Minimize PCR cycles during library preparation to reduce duplication bias. Monitor final library complexity and duplication rates
  • Read length: 75-100bp paired-end reads are standard for most applications

Sequencing Depth

Target 20-30 million paired-end reads per sample for human/mouse samples. Increase depth for: - Novel transcript discovery (50+ million reads) - Low-input samples - Species with large genomes or high transcript diversity

Spike-in Controls

Consider ERCC spike-ins for: - Cross-sample normalization validation - Technical performance assessment - Absolute quantification needs

Quality Control Metrics

Monitor key metrics including: - Mapping rates (>80% for well-annotated genomes) - Duplication rates (<30% for high-quality libraries) - rRNA contamination (<10%)

ENCODE Guidelines

Follow ENCODE RNA-seq standards for experimental design and data processing. Key ENCODE benchmarks include >10 million uniquely mapped reads, <15% duplication rate, and strand-specificity >0.8 for stranded libraries.

Data Processing Workflow

[Link to analysis pipeline documentation]