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RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays.
Marioni J, Mason C, Mane S, Stephens M, Gilad Y.
University of Chicago;
Ultra high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and so, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra high-throughput sequencing technology.
RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays.
Marioni J, Mason C, Mane S, Stephens M, Gilad Y.
University of Chicago;
Ultra high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and so, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra high-throughput sequencing technology.