Massively Parallel Detection of Variation in Allelic Expression in Single Cells

Differential allelic expression is a major contributor to phenotypic variability that may cause congenital disorders, genetic predispositions for diseases, and other complex traits. Conventional analyses of differences in expression require a population of cells, so they cannot determine whether the phenotype arises from an imbalance of single cells with monoallelic expression or consistently skewed biallelic expression. Although fluorescence-activated cell sorting and image-based methods have been used to assess allelic expression in single cells, these processes are not scalable to allow the analysis of a statistically large set of cells due to the cost of reagents and time required per assay. We present here a surface-based approach to detect variability in allelic expression by probing single nucleotide polymorphisms directly from thousands of single cells in parallel. The resulting array-based format allows the analysis of multiple transcribed genes per cell, and leverages existing equipment and infrastructure for high-throughput gene analysis. The integration of this approach with other massively parallel measurements of lineages and functional activities of the same individual cells will also be discussed.