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- Study Description
The goal of this study is to characterize and understand the variability in the expressed transcriptome of human excitable cells. There are two predominant types of excitable cell in the human body, neurons and muscle cells, including cardiac cells. Many human CNS diseases result from modulation of the electrical responsiveness of neurons while cardiac arrhythmias account for most of heart associated deaths. However, at the level of individual cells there is considerable heterogeneity in function, response, and dysfunction. We hypothesize that there is a many-to-one relationship between transcriptome states and a cell's phenotype. In this relationship the functional molecular ratios of the RNA are determined by the cell systems' stoichiometric constraints, which underdetermine the transcriptome state. Because a broad set of multi-genic combinations support a particular phenotype, changes in the transcriptome state do not necessarily lead to changes in the phenotype potentially explaining cellular heterogeneity in phenotype response to variant conditions such as the application of therapeutic molecules. To test this hypothesis we shall investigate the extent of single cell variation for the whole transcriptome for excitable cells that are in their natural environment using a novel mRNA capture methodology (TIVA-tag), and on a subset of the transcriptome, the mRNAs encoding the therapeutically important and maniputable G protein-coupled receptor (GPRC) pathways. The use of functional genomics techniques developed in the Eberwine and Kim labs (TIPeR) will permit an assessment of the biological role of multigenic transcriptome variation. PUBLIC HEALTH RELEVANCE: The goal of this proposal is to generate a compendium of single cells sequencing data from live human excitable cells that are in contact with endogenous neighboring cells. These sequencing data will be analyzed for variability in gene expression and the biological function of this variability assessed using a novel in vivo functional genomics methodology.
The SCAP-T (PENN) data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 185 single cells from human heart. The second data release includes an additional 157 single cells from human heart. The third data release includes an additional 334 single cells: 297 from human brain and 37 from human heart. The fourth data release did not include any changes to the Penn dataset but rather marked a correction to the USC dataset. The fifth data release includes an additional 188 single cells: 78 from human brain and 110 from human heart. The sixth data release includes an additional 125 single cells: 76 from human brain and 50 from human heart, bringing the total number of single cells available to 990. The seventh data release includes an additional 41 single cells: 24 from human brain and 17 from human heart, bringing the total number of single cells available to 1031. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all these single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.
- Authorized Access
- Publicly Available Data (Public ftp)
- Molecular Data
Type Source Platform Number of Oligos/SNPs SNP Batch Id Comment RNA Sequencing Illumina HiSeq 2500 N/A N/A RNA Sequencing Illumina NextSeq 500 N/A N/A
- Selected Publications
- Diseases/Traits Related to Study (MeSH terms)
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See research articles citing use of the data from this study
- Study Attribution
- James H. Eberwine. University of Pennsylvania, Philadelphia, PA, USA.
- Junhyong Kim. University of Pennsylvania, Philadelphia, PA, USA.
- 1U01MH098953-01. National Institutes of Health, Bethesda, MD, USA.
- Principal Investigators