SBIR-STTR Award

The study of gene expression is fundamental to our understanding of how cells function. We propose to develop a highly sensitive and precise method to measure global gene expression in single cells. Our novel method is simple, yet is capable of accurately counting individual transcripts across all genes expressed within a single cell. The measurements obtained are absolute numbers of gene transcripts, and represents a significant improvement over modern gene expression techniques which typically only provide relative measurements. Our method is based on the concept of "stochastic labeling" that we recently published where we validated the novel approach by randomly labeling every single copy of fragments of genomic DNA in a sample with a set of molecular barcodes. Once labeled, the original DNA fragments were amplified with PCR and detected by massively parallel sequencing. Counting the number of different barcodes reveals the number of original copies of that DNA fragment, easily distinguishing the plurality of copies of a fragment of identical DNA sequence from additional clones of itself created by PCR replication. We successfully transform the challenging task of counting identical copies of single DNA molecules into the simple process of identifying the number of different barcodes present on identical sequences. Our current objective for phase I is to develop the technique into an application for single cell gene expression analysis where quantitative measurements are especially difficult due to the small amount of starting material present. Another significant challenge in single cell analysis is that the high degree of DNA amplification required creates biases in the gene abundance representation. We circumvent the effects of amplitude distortions by barcoding molecules before any amplification steps, and counting barcodes instead of sequence reads to determine the number of original molecules present. For phase II, we will develop a commercial assay kit containing reagents and protocols to carry out the technique. Our company is comprised of an exceptionally strong team of successful innovators and scientists/engineers with significant achievements in both research and product commercialization settings. Members include an established investigator in the area of single cell/single molecule research, and a key inventor and developer of the most widely used gene expression platform over the past decade. Additionally, we have established collaborations with scientists at the Stanford University Genome Technology Center, giving us access to instruments and expertise available at this world class research facility.

Public Health Relevance Statement:


Public Health Relevance:
To better understand the human genome and its relationship to health and disease, we will develop a technology to enable highly sensitive and accurate global gene expression analysis in single cells.

Project Terms:
Achievement; Area; base; Biological Assay; Cell physiology; Cells; Collaborations; commercialization; Complementary DNA; design; Disease; DNA; DNA amplification; DNA Sequence; Engineering; Gene Expression; Gene Expression Profiling; Genes; Genome; Genomics; Goals; Health; Human Genome; Individual; instrument; Label; Measurement; Measures; member; Messenger RNA; Methodology; Methods; Molecular; novel; novel strategies; Nucleic Acids; Phase; Process; Protocols documentation; public health relevance; Publications; Publishing; Reading; Reagent; Relative (related person); Research; research facility; Research Personnel; Reverse Transcription; Sampling; Scientist; Sequence Analysis; single cell analysis; single molecule; Techniques; Technology; Testing; Transcript; Universities

We propose to develop and commercialize high sensitivity and accuracy RNA sequencing kits suitable for gene expression measurements in limiting input samples, such as single cells. During Phase I, we proposed the concept of using molecular barcodes in the form of DNA sequence tags to label individual molecules (or copies) of RNA for gene expression analysis in single cells. The Phase I project proved to be highly productive, and feasibility was demonstrated. Counting the barcodes provides an absolute, digital quantitative measure of the number of transcripts expressed. In addition, the barcodes are shown to be useful in correcting for PCR bias, a common challenge in small samples requiring DNA amplification protocols. We also determined a low RNA representation efficiency of 0.1-3.8% overall yield in current single cell RNA sequencing sample preparation methods, and demonstrate that with our cDNA amplification and barcoding approach, more accurate measurements are obtained at significantly higher yields of ~22.5%. These remarkable results indicate that our method can significantly improve on current techniques which suffer from large losses and have inaccuracies introduced by amplification distortions. Because measurement of gene expression levels is important in life science research and also in many clinical settings, our proposed product if successful, would contribute greatly to advancements in these areas. For Phase II, we propose to extend the validated concept into a product development program to produce high efficiency, user-friendly single-cell RNA sequencing kits. Specifically, we will perform assay development to produce validated sets of primers for inclusion in these kits. We will also optimize and validate reaction mix formulations to enable the high efficiency sampling of low abundance RNA transcripts that are missed by other methods. Analysis tools for the upstream selection of custom primer sets or gene panels, and for the downstream analysis of sequencing data will also be developed.

Thesaurus Terms:
Agreement;Area;Assay Development;Biological Assay;Biological Sciences;Cells;Clinical;Collaborations;Commercialization;Complementary Dna;Custom;Data;Data Analyses;Digital;Disease;Dna Amplification;Dna Sequence;Drug Formulations;Feedback;Gene Expression;Gene Expression Profiling;Genes;Health;Human Genome;Improved;Indexing;Individual;Journals;Label;Libraries;Manuals;Manuscripts;Massive Parallel Sequencing;Measurement;Measures;Meetings;Methods;Molecular;Oligonucleotides;Peer Review;Phase;Preparation;Product Development;Programs;Protocols Documentation;Prototype;Provider;Public Health Relevance;Publications;Reaction;Reagent;Research;Research Personnel;Reverse Transcription;Rna;Rna Sequences;Role;Sampling;Screening;Sequence Analysis;Site;Software Development;Techniques;Testing;Tool;Transcript;User-Friendly;Work;