Effect of RNA quality on transcript intensity levels in microarray analysis of human post-mortem brain tissues

Area of Science:

• Genomics
• Neuroscience
• Bioinformatics

Background:

• Gene expression analysis of post-mortem brain tissue is crucial for understanding psychiatric and neurodegenerative disorders.
• Microarray data analysis presents challenges, particularly with low-quality RNA.

Purpose of the Study:

• To investigate the effects of post-mortem RNA quality on gene expression data.
• To identify strategies for analyzing microarray data from low-quality RNA samples.

Main Methods:

• Analysis of Affymetrix GeneChip data from ten different brain regions.
• Assessment of RNA quality using the 5'/3' ratio of housekeeping genes.
• Development of a linear model to correct for RNA quality effects.

Main Results:

• Post-mortem RNA quality significantly impacts measured transcript abundance, introducing systematic noise.
• RNA quality effects have both random and systematic components, influencing transcript correlations.
• Probe set distribution, mRNA length, and stability are key contributors to systematic noise.

Conclusions:

• RNA quality assessment should be integrated into microarray data preprocessing.
• Inter-gene correlation analysis must account for RNA quality to avoid misleading results.
• Normalization procedures and preprocessing methods (RMA vs. MAS 5.0) have varying sensitivities to RNA quality effects.