A molecular barcoding sequencing kit for highly efficient and accurate single cel
A molecular barcoding sequencing kit for highly efficient and accurate single cel
批准号:
8904694
负责人:
Glenn Fu
金额:
$62.66万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-07-01 至 2016-07-31
关键词:
AgreementAreaBiological AssayBiological SciencesCellsClinicalCollaborationsComplementary DNACustomDNA SequenceDNA amplificationDataData AnalysesDiseaseDrug FormulationsFeedbackGene ExpressionGene Expression ProfilingGenesHealthHuman GenomeIndividualJournalsLabelLibrariesManualsManuscriptsMassive Parallel SequencingMeasurementMeasuresMethodsMolecularOligonucleotidesPeer ReviewPhasePreparationProtocols documentationProviderPublicationsRNARNA SequencesReactionReagentResearchResearch PersonnelReverse TranscriptionRoleSamplingSequence AnalysisSiteTechniquesTestingTranscriptWorkassay developmentcommercializationdigitalimprovedindexingmeetingsproduct developmentprogramsprototypescreeningsoftware developmenttooltranscriptome sequencinguser-friendly
中文摘要
描述(由申请人提供):我们建议开发和商业化高灵敏度和准确的RNA测序试剂盒,适用于在有限的输入样本中测量基因表达,例如单个细胞。在第一阶段,我们提出了使用DNA序列标签形式的分子条形码来标记单个RNA分子(或拷贝)的概念,用于单细胞中的基因表达分析。第一阶段项目被证明是高生产力的,并证明了可行性。对条形码进行计数提供了所表达的转录本数量的绝对数字量化测量。此外,条形码被证明在纠正PCR偏差方面很有用,这在需要DNA扩增协议的小样本中是一个常见的挑战。在目前的单细胞RNA测序样品制备方法中,我们还测定了0.1-3.8%的低RNA表达效率,并证明了使用我们的cDNA扩增和条形码方法,可以获得更准确的测量结果,总得率显著高于其他方法,约为22.5%。这些显着的结果表明,我们的方法可以显着改进现有的技术,这些技术遭受着巨大的损失,并且由于放大失真而引入了不准确的结果。由于基因表达水平的测量在生命科学研究和许多临床环境中都很重要,我们建议的产品如果成功,将极大地促进这些领域的进步。对于第二阶段,我们建议将经过验证的概念扩展到产品开发计划中,以生产高效、用户友好的单细胞RNA测序试剂盒。具体地说,我们将进行分析开发,以生产包括在这些试剂盒中的经过验证的引物集。我们还将优化和验证反应混合配方,以实现对其他方法遗漏的低丰度RNA转录本的高效采样。还将开发用于定制引物组或基因面板的上游选择以及用于测序数据的下游分析的分析工具。
英文摘要
DESCRIPTION (provided by applicant): 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.
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