Applied Biosystems will present data at the Stem Cell Technology Symposium revealing how its Solid System generated genome-wide expression profiling data at the single cell level.
Gene expression signatures at the single cell level have the potential to reveal details about cell fate and will potentially accelerate the discovery of biomarkers for disease.
This finding represents the first use of a genomic analysis platform for a hypothesis-neutral, genome-wide survey of expressed genes in individual cells.
Kai Lao, PhD, an Applied Biosystems principal scientist, will unveil data from his presentation entitled 'Whole MiRNA/MRNA Profiling from Single Embryonic Stem Cell and Early Embryos'.
Dr Lao will describe how he and his scientific collaborator, Dr Azim Surani, used the Solid System to determine messenger RNA (MRNA) expression profiles in mouse oocytes - immature egg cells - 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 characterisations of stem cell behaviour 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, 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 Solid 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, which 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 biological 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.
Currently, the most widely used method to analyse global patterns of gene expression is the DNA microarray.
However, microarray technology offers limited sensitivity, requires greater sample input and is unable to detect novel MRNAs.
The Solid System detects DNA sequence tags for expressed genes from starting genetic material that is significantly less than that required by microarray technologies.
Microarrays are hybridisation-based technologies, therefore, they are unable to efficiently detect RNA transcripts expressed at low levels and cannot be used to detect RNA transcripts from repeated sequences.
Additionally, microarrays offer limited dynamic range to detect subtle changes in expression level of target genes, which is critical in understanding biological response to stimuli or environmental changes.
By enabling global, hypothesis-neutral analysis of gene expression profiles, researchers who use the Solid System for this application will be able to detect most known and novel MRNAs present in single cells, with no bias toward known MRNA molecules.
'The ability to evaluate gene activity at the single cell level will allow researchers to begin considering experiments that will bring us closer to understanding the biological basis of complex diseases, such as cancer,' said Shaf Yousaf, president of the molecular and cell biology genomic analysis division at Applied Biosystems.
'As we gain a greater understanding of stem cell behaviour, we are beginning to learn more about how these self-renewing cells contribute to these diseases.' 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, plus whole transcriptome discovery and characterisation using the Solid Whole Transcriptome kit.
These applications allow researchers to conduct comprehensive RNA-based studies on a single, ultra-high throughput platform.
The Stem Cell Symposium takes place on 17 September at the Farmington Marriott, Connecticut.
