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Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays
Daniel Bottomly1, Nicole A R Walter, Jessica Ezzell Hunter
1Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, United States of America. bottomly@ohsu.edu
Plos One
|April 2, 2011
Summary
RNA-Seq offers a more comprehensive approach to gene expression profiling in neuroscience research compared to microarrays. This next-generation sequencing method accurately detects differential gene expression between mouse strains, revealing more genes than traditional hybridization techniques.
Area of Science:
- Neuroscience
- Genomics
- Bioinformatics
Background:
- C57BL/6J (B6) and DBA/2J (D2) are standard inbred mouse strains for neuroscience research.
- Existing mouse genome references and microarray probes are based solely on the B6 strain, limiting cross-strain gene expression comparisons due to genetic variations like single nucleotide polymorphisms (SNPs).
Purpose of the Study:
- To compare the efficacy of RNA-Seq with two microarray platforms (Illumina and Affymetrix) for detecting differential striatal gene expression between B6 and D2 mouse strains.
- To evaluate the concordance and identify advantages of RNA-Seq over hybridization-based methods for gene expression profiling.
Main Methods:
- RNA-Seq (Illumina GA IIx) was performed on 21 striatum samples (10 B6, 11 D2), generating an average of 22 million reads per sample.
- Reads were aligned to the mouse reference genome, and differential gene expression was determined using 'digital mRNA counting' based on exon mapping.
- Results were compared against two microarray platforms: Illumina MouseRef-8 v2.0 and Affymetrix MOE 430 2.0.
Main Results:
- RNA-Seq demonstrated high concordance with both microarray platforms when stringent data processing was applied, with more agreement across both platforms than with a single platform.
- Discordance in the direction of fold change between RNA-Seq and microarrays was infrequent.
- RNA-Seq identified a greater number of genes compared to either microarray platform, with a significant proportion of differentially expressed genes detected exclusively by RNA-Seq.
Conclusions:
- RNA-Seq provides a more sensitive and comprehensive approach for differential gene expression analysis between mouse strains than traditional microarray technologies.
- The increased sensitivity of RNA-Seq is crucial for detecting subtle gene expression changes, particularly in studies with smaller effect sizes, avoiding potential bias from hybridization-based methods.
