Key Difference – Microarray vs RNA Sequencing
Transcriptome represents the whole content of RNA present in a cell including mRNA, rRNA, tRNA, degraded RNA, and, nondegraded RNA. Profiling transcriptome is an important process in order to understand the cell insights. There are several advanced methods for transcriptome profiling. Microarray and RNA sequencing are two types of technologies developed to analyze transcriptome. The key difference between microarray and RNA sequencing is that microarray is based on the hybridization potential of predesigned labeled probes with target cDNA sequences while RNA sequencing is based on the direct sequencing of cDNA strands by advanced sequencing techniques such as NGS. Microarray is performed with the prior knowledge about the sequences and RNA sequencing is performed without the prior knowledge about sequences.
CONTENTS
1. Overview and Key Difference
2. What is Microarray
3. What is RNA Sequencing
4. Side by Side Comparison – Microarray vs RNA Sequencing
5. Summary
What is Microarray?
Microarray is a robust, reliable and high throughput method used for transcriptome profiling by scientists. It is the most popular approach for transcript analysis. It is a low-cost method, which depends on the hybridization probes.
The technique starts with extraction of mRNA from the sample and the construction of cDNA library from total RNA. Then it is mixed with fluorescently labeled predesigned probes on a solid surface (spot matrix). Complementary sequences hybridize with the labeled probes in the microarray. Then microarray is washed and screened, and the image is quantified. Gathered data should be analyzed to get the relative expression profiles.
The intensity of the microarray probes is assumed to be proportional to the quantity of transcripts in the sample. However, the accuracy of the technique depends on the designed probes, prior knowledge of the sequence and the affinity of probes for hybridization. Hence microarray technology has limitations. Microarray technique cannot be performed with low abundance transcripts. It fails to differentiate isoforms and identify genetic variants. Since this method depends on hybridization of probes, some problems related to hybridization such as cross-hybridization, nonspecific hybridization etc. occurs in microarray technique.
Figure 01: Microarray
What is RNA Sequencing?
RNA shotgun sequencing (RNA seq) is a recently developed whole transcriptome sequencing technique. It’s a rapid and high throughput method of transcriptome profiling. It directly quantifies the expression of genes and results in deep investigation of the transcriptome. RNA seq does not depend on predesigned probes or prior knowledge of the sequences. Therefore, RNA seq method has high sensitivity and capability of detecting novel genes and genetic variants.
RNA sequencing method is performed via several steps. Total RNA of the cell must be isolated and fragmented. Then, using reverse transcriptase, a cDNA library must be prepared. Each cDNA strand must be ligated with adaptors. Then the ligated fragments must be amplified and purified. Finally using a NGS method, sequencing of the cDNA must be performed.
Figure 02: RNA Sequencing
What is the difference between Microarray and RNA sequencing?
Microarray vs RNA Sequencing |
|
| Microarray is a robust, reliable, high throughput method. | RNA sequencing is an accurate and high-throughput method. |
| Cost | |
| This is a low-cost method. | This is an expensive method. |
| Analysis of a Large Number of Samples | |
| This facilitates analyzing a large number of samples simultaneously. | This facilitates analyzing a large number of samples. |
| Data Analysis | |
| Data analysis is complex. | More data is generated in this method; hence, the process is more complex. |
| Prior Knowledge of Sequences | |
| This method is based on hybridization probes, so prior knowledge of sequences in required. | This method does not depend on the prior sequence knowledge. |
| Structural Variations and Novel Genes | |
| This method cannot detect structural variations and novel genes. | This method can detect structural variations such as gene fusing, alternative splicing, and novel genes. |
| Sensitivity | |
| This cannot detect differences in expression of isoforms, so this has limited sensitivity. | This has high sensitivity. |
| Outcome | |
| This can only result in relative expression levels. This does not give absolute quantification of gene expression. | It gives absolute and relative expression levels. |
| Data Reanalysis | |
| This needs to be rerun in order to reanalyze. | Sequencing data can be reanalyzed. |
| Need for Specific Personnel and Infrastructure | |
| Specific infrastructure and personnel are not required for microarray. | Specific infrastructure and personnel required by RNA sequencing. |
| Technical Issues | |
| Microarray technique has technical issues such as cross-hybridization, nonspecific hybridization, limited detection rate of individual probes, etc. | RNA seq technique avoids technical issues such as cross-hybridization, nonspecific hybridization, limited detection rate of individual probes, etc. |
| Biases | |
| This is a biased method since it depends on hybridization. | Bias is low compared to microarray. |
Summary – Microarray vs RNA Sequencing
Microarray and RNA sequencing methods are high throughput platforms developed for transcriptome profiling. Both methods produce results which are highly correlated to gene expression profiles. However, RNA sequencing has advantages over microarray for gene expression analysis. RNA sequencing is a more sensitive method for the detection of low abundance transcripts than microarray. RNA sequencing also enables the differentiation between isoforms and identification of gene variants. However, microarray is the common choice of most researchers since RNA sequencing is a new and expensive technique with data storing challenges and complex data analysis.
References:
1.Wang, Zhong, Mark Gerstein, and Michael Snyder. “RNA-Seq: a revolutionary tool for transcriptomics.” Nature reviews. Genetics. U.S. National Library of Medicine, Jan. 2009. Web. 14 Mar. 2017
2.Rogler, Charles E., Tatyana Tchaikovskaya, Raquel Norel, Aldo Massimi, Christopher Plescia, Eugeny Rubashevsky, Paul Siebert, and Leslie E. Rogler. “RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples.” Nucleic Acids Research. Oxford University Press, 01 Jan. 2004. Web. 15 Mar. 2017
3.Zhao, Shanrong, Wai-Ping Fung-Leung, Anton Bittner, Karen Ngo, and Xuejun Liu. “Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells.” PLOS ONE. Public Library of Science, Jan. 2014. Web. 15 Mar. 2017
Image Courtesy:
1. “Journal.pcbi.1004393.g002” By Malachi Griffith, Jason R. Walker, Nicholas C. Spies, Benjamin J. Ainscough, Obi L. Griffith – (CC BY 2.5) via Commons Wikimedia
2. “Microarray” By Bill Branson (Photographer) – National Cancer Institute (Public Domain) via Commons Wikimedia