Serial Analysis of Gene Expression

Serial analysis of gene expression (SAGE) is a technique used by molecular biologists to produce a snapshot of the messenger RNA population in a sample of interest. The original technique was developed by Dr. Victor Velculescu at the Oncology Center of Johns Hopkins University, and was published in the journal Science in 1995. Several variants have been developed since, most notably a more robust version, LongSAGE (developed by Dr. Saurabh Saha and colleagues at Johns Hopkins University) and the most recent SuperSAGE (by Hideo Matsumura and colleagues) that enables very precise annotation of existing genes and discovery of new genes within genomes because of an increased tag-length of 25-27 bp.

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Overview

Briefly, SAGE experiments proceed as follows:

1. Isolate the mRNA of an input sample (e.g. a tumour).
2. Extract a small chunk of sequence from a defined position of each mRNA molecule.
3. Link these small pieces of sequence together to form a long chain (or concatemer).
4. Clone these chains into a vector which can be taken up by bacteria.
5. Sequence these chains using modern high-throughput DNA sequencers.
6. Process this data with a computer to count the small sequence tags.

A more in-depth, technical explanation of the technique is available here.

Analysis

The output of SAGE is a list of short sequence tags and the number of times it is observed. Using sequence databases a researcher can usually determine, with some confidence, the original mRNA (and therefore which gene) the tag was extracted from.

Statistical methods can be applied to tag and count lists from different samples in order to determine which genes are more highly expressed. For example, a normal tissue sample can be compared against a corresponding tumour to determine which genes tend to be more (or less) active.

Applications

Although SAGE was originally conceived for use in cancer studies, it has been successfully used to describe the transcriptome of other diseases and in a wide variety of organisms.

Comparison to DNA microarrays

The general goal of the technique is similar to the DNA microarray. However, SAGE is a sequence-based sampling technique. Observations are not based on hybridization, which result in more qualitative, analog values. In addition, the mRNA sequences do not need to be known a priori, so genes or gene variants which are not known can be discovered. Microarray experiments are much cheaper to perform, however, so large-scale studies do not typically use SAGE.

Variant Protocols: miRNA cloning

MicroRNAs, or miRNAs for short, are small (~22nt) pieces of RNA which have been found to play a crucial role in gene regulation. One of the most commonly used methods for cloning and identifying miRNAs within a cell or tissue was developed in the Bartel Lab and published in a paper by Lau et al., 2001. Since then, several variant protocols have arisen, but most have the same basic format. The procedure is quite similar to SAGE: The small RNA are isolated, then linkers are added to each, and the RNA is converted to cDNA by RT-PCR. Following this, the linkers, containing internal restriction sites are digested with the appropriate restriction enzyme, and the sticky ends are ligated together into concatamers. Following concatamerization, the fragments are ligated into plasmids and are used to transform bacteria to generate many copies of the plasmid containing the inserts, which may then be sequenced to identify the miRNA present, as well as to observe expression levels of a given miRNA by the number of times it is present in the results, similar to SAGE.

References

• Oncology Centre at Johns Hopkins University
• Velculescu VE, Zhang L, Vogelstein B, and Kinzler KW. 1995. Serial Analysis of Gene Expression. Science 270:484-7 PMID 7570003
• Saha S, Sparks AB, Rago C, Akmaev V, Wang CJ, Vogelstein B, Kinzler KW, Velculescu VE. 2002. Using the transcriptome to annotate the genome. Nat. Biotechnol. 20:508-12 PMID 11981567
• Matsumura H, Ito A, Saitoh H, Winter P, Kahl G, Reuter M, Kruger DH, Terauchi R. 2005. SuperSAGE. Cell Microbiol. 7:11-8 PMID 15617519