New Technology Enables Single Cell Gene Expression Profiling for Stem Cell Research

Gene expression signatures at the single cell level have the capacity to reveal details about cell fate and they will potentially accelerate the discovery of biomarkers for disease. A new genomic analysis platform represents the first use of such a platform for a hypothesis-neutral, genome-wide survey of expressed genes in individual cells.

Scientists from Applied Biosystems (Foster City, CA, USA presented data on September 17, 2008, at the Connecticut Stem Cell Technology Symposium, held in Farmington, CT, USA, revealing how the company's ultra-high-throughput genomic analysis platform, the SOLiD system, generated genome-wide expression profiling data at the single cell level.

At the symposium, Kai Lao, Ph.D., an Applied Biosystems principal scientist, described how he and his scientific collaborator, Dr. Azim Surani, a professor of physiology and reproduction at the University of Cambridge (UK), used the SOLiD system to determine messenger RNA (mRNA) expression profiles in mouse oocytes during early differentiation. Being able to generate comprehensive profiles of gene activity from single stem cells is expected to reveal clues about molecular variation between genetically identical stem cells and the underlying molecular mechanisms that trigger pluripotent stem cells to differentiate into specific cell types, including cancer cells. Such detailed characterizations of stem cell behavior will give researchers a better understanding of how these cells can be used in regenerative therapies for damaged cells and organs.

"While all embryonic stem cells possess an innate ability to self renew, recent scientific data suggests that undifferentiated embryonic stem cells are heterogeneous and differentially express gene markers,” said Dr. Surani. "Gene expression profiling on the SOLiD system will enable the generation of a precise, whole genome profile of stem cells, including known transcripts and novel genes, at single cell resolution, which will deepen our understanding of the biological mechanisms regulating pluripotency and early differentiation.”

In this study, scientists first isolated individual embryonic cells from mouse oocytes and extracted total RNA using RNA isolation kits from Ambion (Austin, TX, USA), an Applied Biosystems business. Using trace amounts of total RNA, the starting material was converted into cDNA. The resulting libraries were amplified and sequenced using the SOLiD system. Relative expression levels of mRNAs were calculated based on the number of sequence tags generated by the system. With a throughput of up to 240 million tags per run and sensitivity capable of detecting 10-40 picograms of total RNA per cell, the system quantified differential expression patterns of identified mRNAs profiling both known and unknown mRNA species present in the samples, including mRNAs expressed at low levels. To validate the presence of specific mRNA molecules, researchers then used the TaqMan gene expression assays, highly specific assays that quantitate mRNAs present in the samples.

Previous research has shown that by profiling expression patterns of genes and non-coding RNAs, researchers can obtain a more accurate view of the transcriptome by cell or tissue type, which may accelerate the discovery of potential biomarkers to classify different disease types and identify disease susceptibility. This information will help researchers to better understand the nature of diseased cells, such as cancer stem cells, which play a key role in cancer recurrence and tumor metastasis. However, researchers performing these kinds of gene expression analysis applications for stem cell and cancer research often face the challenge of only being able to obtain tiny amounts of RNA from biologic samples, the starting genetic material needed to carry out these investigative studies. The high sensitivity of the SOLiD system enables researchers to generate detailed gene expression profiles from the trace amounts of RNA present in single cell and cancer samples.

In addition to single cell gene expression profiling, other SOLiD system RNA applications include small RNA discovery and screening using the SOLiD Small RNA expression kit, and whole transcriptome discovery and characterization using the SOLiD whole transcriptome kit. This full complement of applications allows researchers to conduct comprehensive RNA-based studies on a single, ultra-high-throughput platform.

The SOLiD system is an end-to-end genomic analysis solution comprised of a sequencing unit, a computing cluster, and data storage. The platform is based on sequencing by oligonucleotide ligation and detection. Unlike polymerase sequencing approaches, the system utilizes a proprietary technology called stepwise ligation, which generates high-quality data for applications including: whole genome sequencing and targeted resequencing, transcriptome analysis, small RNA discovery, gene expression profiling, chromatin immunoprecipitation (ChIP), microbial and eukaryotic resequencing, digital karyotyping, medical sequencing, and genotyping, among others.

Very high throughput, inherent scalability, and unmatched accuracy distinguish the SOLiD system from other next-generation sequencing platforms. The system can be scaled to support a higher density of sequence per slide through bead enrichment. Beads are an integral part of the system's open-slide format architecture, which enables the system to generate greater than six gigabases of sequence data per run.

The SOLiD system has demonstrated runs of nearly 15 billion bases of mappable sequence data per run in customer laboratories, and runs greater than 20 billion bases of mappable sequence data at Applied Biosystems' research and development facilities. The combination of the open-slide format, bead enrichment, and software algorithms provide the infrastructure for allowing it to scale to even higher throughput, without significant changes to the system's current hardware or software. The systems unique two-base encoding provides built-in error checking capability that distinguishes random or systematic errors from true single base changes, or single nucleotide polymorphisms (SNPs). This capability helps researchers to detect SNPs with greater than 99.94 percent sequencing accuracy.

Applied Biosystems, Inc. (formerly known as Applera) is a global leader in the development and marketing of instrument-based systems, consumables, software, and services for academic research, the life science, and commercial industry.

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