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Apr 1, 2009 (Vol. 29, No. 7)

Digital Gene-Expression Profiling

Technology Set to Compete with Microarrays in This Application Arena

  • Transcriptome Analysis

    Click Image To Enlarge +
    Companies with Digital Gene Expression Instrumentation

    Compared to microarray-based methods, the paramount advantage of DGE is that the transcripts are counted and “you do not depend on semi-quantitative analysis of light signaling intensity,” says Björn Rotter, head of functional genomics at GenXPro. “You also don’t need to normalize the data to the same extent, and there is no possibility of false positives, resulting in more reliable information,” he adds.

    How DGE is defined depends on who you are talking to. DGE does not describe a technology per se, rather, it is a strategy. In essence, it refers to methods that generate a digital count of gene expression, enabling quantitative differential gene-expression analysis. Initially, DGE was used to describe the SAGE approach, which involves end tagging of cDNA fragments to build an inventory of short sequence tags that can then be sequenced and counted. But the definition of the term has expanded to include methodologies that do not involve end tagging of restriction enzyme digests or require PCR amplification.

    The patented SuperSAGE digital gene-expression platform and SuperTAG technology developed by GenXPro rely on a specific 26-base pair tag for accurate transcriptome analysis. SAGE technology can identify what gene is transcribed, how many times a gene is transcribed, and what transcript isoforms are present by counting the number of sequence-specific tags for each individual mRNA.

    “The longer the tag, the more reliable the annotation,” says Rotter. GenXPro supplements its intellectual property on SuperSAGE with a patented mechanism to avoid PCR-introduced bias. SuperSAGE is designed to work with Illumina’s Genome Analyzer system and the Roche/454 Genome Sequencer instrument, and GenXPro is experimenting with the Applied Biosystems’ SOLiD™ system.

    The main advantage of tag-based gene-expression profiling technology is its open-architecture platform, allowing researchers to detect every transcript present in a sample, including new unexpected transcripts, or antisense transcripts. “It is possible to have a look at rare transcripts, which would get lost in the background noise on microarrays,” Rotter says. In fact, he adds, most of the transcripts in a cell “are rare—present in only one to five copies.”

    Applied Biosystems (ABI), a division of Life Technologies, offers both SAGE and RNASeq kits on its SOLiD system next-generation sequencing platform. The company’s SAGE product incorporates a 27-base pair tag and has a dynamic range of 5 to 6 logs—a 1,000-fold improvement over the typical 2.5 to 3 log readouts achieved with microarrays, according to Roland Wicki, director of SOLiD strategy. That translates to greater sensitivity and the ability to see more targets with SAGE sequencing technology compared to microarray-based methods.

    However, states Wicki, “RNASeq, or a whole transcriptome shotgun RNA sequencing methodology, is the more compelling approach,” and he anticipates that in the future it will likely supplant both microarrays and SAGE methods. The power of whole transcriptome sequencing is defined by what it can enable, including expression analysis of specific exons and detection of splice variants, alternative transcripts, and novel splice junctions. RNASeq can also be used to analyze allele-specific expression and measure the expression levels of heterozygous SNPs. The same strategy and data can yield information on the full spectrum of mutations in a sample and can be used to detect and quantify fusion transcripts.

    “None of this can be done on microarrays— it is all new,” and requires whole transcriptome analysis capability, adds Wicki.

    In a presentation at the Association of Biomolecular Resource Facilities meeting, a team of scientists from ABI and from the University of Cambridge (U.K.), described a method of “Deep Sequencing-Based Whole Transcriptome Analysis of a Single Cell” using the ABI SOLiD System. The researchers combined next-gen sequencing with whole transcriptome amplification to develop a digital gene-expression profiling assay at single-cell resolution.

    They demonstrated that this single-cell cDNA deep-sequencing assay was able to detect expression of thousands more genes than a cDNA microarray technique. Furthermore, for genes detected by both strategies, the sequencing approach yielded novel transcript variants for many of the genes, suggesting that the transcriptome of a single cell is more complex than previously realized.

    In February, ABI began delivering the new SOLiD 3 system to customers. It provides simplified workflows and greater accuracy, according to Wicki. Using two-base encoding—the system reads every base twice, providing a means of internal error correction—it can differentiate between real mutations and misreads by the instrument. The new model also has higher throughput and can analyze 400 million tags, or sequence reads, of 50-mer fragments in a single run. R&D runs have demonstrated the potential of the instrument to process up to one billion tags/run.

Readers' Comments

Posted 04/07/2009 by Real Research

I study the above DGE technique. its amazing technique and i need traning in this technique i request to scientist please help i ever forget your this kind of help.

Research Officer
Ali Mohammad Dahri
Plant tissue culture labs,
PCSIR Labs Complex

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