Comparison of Methods for Expression Profiling: RNA-Seq by poly(A) Capture, Ribosomal RNA Depletion, and DNA Microarray

Introduction to Gene Expression Profiling

Gene expression profiling is the measurement of the activity (expression) of thousands of genes at once to establish a new global picture of cellular function in the field of molecular biology. These profiles can be used to distinguish between actively dividing cells or to show how cells react to a particular treatment. Many experiments of this type simultaneously measure an entire genome, that is, every gene present in a single cell.

To generate the data needed for analysis, a variety of transcriptomics technologies can be used. The relative activity of previously identified target genes is measured using DNA microarrays. RNA-Seq and other sequence-based techniques provide information on the sequences of genes as well as their expression levels.

Transcriptomics Technologies for Gene Expression Profiling

RNA-Seq by Poly(A) Capture: RNA-sequencing is the development of massively parallel sequencing for use in gene expression profiling (RNA-Seq). The impact of RNA-Seq on gene expression research has been enormous. It provides consistent quantification and exhibits superiority in terms of dynamic range, sampling depth, and independence from pre-existing sequence information when compared to hybridization-based technologies like DNA microarrays. Traditional transcriptome profiling, identification of novel transcripts, identification of expressed SNPs, alternative splicing, and detection of gene fusion events can all be done with RNA-Seq.

Comparison of Methods for Expression Profiling: RNA-Seq by poly(A) Capture, Ribosomal RNA Depletion, and DNA Microarray Figure 1. Biotin poly(A) capture of mRNA sequencing. (Fox-Walsh, 2011)

Before sequencing, highly abundant ribosomal RNAs (rRNAs) must be eliminated from total RNA to allow for mRNAgene detection. Using oligo (dT) primers to enrich for polyadenylated (poly(A)) RNA transcripts (so-called mRNA-Seq), similar to how DNA microarrays are primed, is one standard solution; however, this approach removes all non-poly(A) RNAs in addition to rRNAs. Certain non-polyA RNAs, either non-coding or protein-coding, have been suggested to be functionally important in recent studies.

Ribosomal RNA Depletion: Because the RNAs from FFPE specimens are degraded to a small average size, mRNA-Seq captures partially degraded mRNAs poorly. As a result, it is not the best method to use when the starting materials are from Formalin-Fixed and Paraffin-Embedded (FFPE) samples. Several rRNA depletion protocols have been developed to address these issues. The Ribo-Zero method removes rRNA by capturing it with hybridization and then binding it to magnetic beads for subtraction. Another method is to decimate abundant sequences that reanneal rapidly, such as those derived from highly abundant rRNAs and tRNAs, using Duplex-Specific Nuclease (DSN) degradation using the C0t-kinetics-based normalization method.

DNA Microarray: The simultaneous measurement of the mRNA levels of thousands of genes is possible thanks to DNA microarray technology. This advanced technology can answer many biological questions that were previously unanswerable; however, the massive size of microarray data sets raises issues of experimental design and statistical analysis that many molecular biologists are unfamiliar with. The kind of array utilized, the biological experiment design, the number of experimental replicates, and the statistical method for data analysis should all be premised on the investigator's scientific objectives.


  1. Zhao W, He X, Hoadley KA, et al. Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling. BMC genomics. 2014 Dec;15(1).
  2. Seita J, Sahoo D, Rossi DJ, et al. Gene Expression Commons: an open platform for absolute gene expression profiling. PloS one. 2012 Jul 18;7(7).
  3. Fox-Walsh K, Davis-Turak J, Zhou Y, et al. A multiplex RNA-seq strategy to profile poly (A+) RNA: application to analysis of transcription response and 3' end formation. Genomics. 2011 Oct 1;98(4).
  4. Katagiri F, Glazebrook J. Overview of mRNA expression profiling using DNA microarrays. Current protocols in molecular biology. 2009 Jan;85(1).
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