Single Cell Transcriptomics – RNA Analysis

Moderator: Steven Potter, Professor, Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center

Day 1 – Thursday, May 22, 2014

8:00 – Single Cell RNA-seq Dissection of Kidney Development

Steven Potter
Professor, Division of Developmental Biology
Cincinnati Children’s Hospital Medical Center

We have used a single cell RNA-seq strategy to dissect the molecular mechanisms of early kidney development. At several stages of kidney development histologically uniform populations of cells give rise to multiple distinct lineages. Single cell analysis allows us to define cellular level heterogeneities that presage distinct developmental decisions…

8:30 – Transcriptome Analysis of Single, Migratory Neural Crest (NC) Cells

Anoja Perera
Senior Laboratory Manager
Stowers Institute for Medical Research

Whole transcriptome analysis of single, migratory neural crest (NC) cells will provide an improved understanding of how individual cells interpret and respond to guidance and differentiation signals within the NC microenvironment. Comprehensive gene expression profiles will help identify genes critical for proper NC migration…

10:15 – Single-Cell Multi-Analyte Analysis in Human Sarcomas

Anders Stahlberg
Postdoctoral resarche fellow
University of Gothenburg

Reverse transcription and the proximity ligation assay were coupled with quantitative PCR and used to quantify any combination of DNA, mRNAs, microRNAs (miRNAs), noncoding RNAs (ncRNAs), and proteins from the same single cell. This method is compatible with most cell-sampling approaches, and generates output for the same parameter for all measured analytes, a feature facilitating comparative data analysis…

10:45 – Driving Genomics to the Single-Cell Level: RNA Expression Profiling Using qPCR and RNAseq

Ken Livak
Senior Scientific Fellow
Fluidigm Corporation

RNAseq clearly provides data on many more genes than qPCR, but the cost of library preparation has been a barrier to obtaining data from a sufficient number of single cells. The C1™ Single-Cell Autoprep System captures up to 96 single cells and performs the processing steps of cell lysis, cDNA synthesis by reverse transcriptase, and initial amplification to generate libraries for qPCR or RNAseq…

11:15 – Single-Cell Transcriptome Analysis of Mouse Cardiomyocytes Derived Progenitor Cells

Charles Wang
Director & Professor, Center for Genomics, Microbiology and Molecular Genetics
School of Medicine
Loma Linda University

To understand the epigenomic reprogramming of mouse CPCs, we integrated single-cell transcriptome and comprehensive high-throughput arrays for relative methylation (CHARM)-based DNA methylation analyses to unravel the molecular signature of mouse CPCs…

1:15 – Unravel the Message in Your Cell(s) with the Power of RNA-Seq and SMART™ Technology

Andrew Farmer
Vice President, Research and Development
Clontech Laboratories

This presentation will cover the application of SMART technology to single cell analysis as well as outline other recent advances in the technology that have extended SMART’s applicability to non-coding RNA and mRNA from degraded samples, such as FFPE, as well as methods to generate strand-specific libraries.

1:45 – Bayesian Approach to Single-Cell Differential Expression Analysis

Peter Kharchenko
Assistant Professor, Center for Biomedical Informatics
Harvard University

We describe a probabilistic model of expression magnitude distortions typical of single-cell RNA sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of stochastic and systematic biases…