Applied Biosystems removes the bias from gene expression analysis
The new whole transcriptome expression technology will expand the company’s RNA expression analysis portfolio for its SOLiD (Supported Oligonucleotide Ligation and Detection) gene sequencer that was launched last June and will enable researchers to detect all known and unknown RNA transcripts present in a biological sample with no bias towards the known RNA molecules.
Typical global gene expression analysis methods use DNA microarrays that contain oligonucleotide probes that hybridise to the RNA transcripts. However, as the probes have to be predefined, they can only identify those transcripts that the probes code for.
Additionally, microarrays offer a limited dynamic range and are unable to detect RNA transcripts expressed at low levels; two features that are critical for understanding how organisms respond to external stimuli and environmental changes.
According to the firm, the kit is designed to provide greater insights into the biological pathways and molecular mechanisms that regulate cellular by enabling a clearer view of a cell’s transcriptome.
“Global transcriptome analysis is becoming a crucial area of investigation for researchers who strive to have a more complete understanding of the human genome,” said Shaf Yousaf, president of ABI’s molecular and cell biology genomic analysis division.
“The whole transcriptome kit will follow on the recent launch of the SOLiD Small RNA Expression kit, providing the company a broad portfolio of tools for analysis of coding and non-coding RNAs on a genomic analysis platform. Based on the positive reception we received for the small RNA kit, we accelerated our efforts to develop a kit for whole transcriptome analysis based on the same Ambion technology.”
The whole transcriptome kit is expected to reduce the time, cost and experimental variability associated with preparing RNA libraries. Using the multiplexing capability of the kit should further simplify downstream workflows, enabling up to 10 RNA libraries to be sequenced simultaneously, reducing the cost of analysis per sample further still.
The technology also conserves the ‘strandedness’ of cDNA which will enable researchers to discern between overlapping RNAs transcribed from either the sense or antisense strand.
According to Dr John McPherson of the Ontario Institute for Cancer Research (OICR), who is investigating the genetic alterations that occur in different types of cancer “altered expression of genetic variants contributes to the formation of complex diseases such as cancer.”
“Of the various technologies available for detecting expression levels of disease-specific genetic variants where altered expression provides insights into the disease, sequencing-based methods for RNA expression analysis provide the most specific measurement possible, especially for detecting all kinds of alterations that can occur to both coding and non-coding RNA transcripts.”
