As methods for gene expression measurement have improved, there has been a growing appreciation that biological behavior in single cells can vary dramatically in ways not captured by conventional bulk assays. Single molecule RNA FISH has developed into a powerful and generally applicable method for single cell gene expression analysis, having been adopted by dozens of labs worldwide. However, while it is able to precisely locate individual RNA molecules in single cells, it has not been able to discriminate single base differences on those RNA, thus precluding many potential biological applications. Such applications include differences in expression between the maternal and paternal alleles of a gene, which typically only differ by single nucleotides. These expression differences are relevant in many areas of genetics, including gene imprinting, in which only the maternal or paternal copy of the gene expresses. Many of these issues arise in biological contexts (e.g., complex and heterogeneous tissues such as brain and placenta) that make even single cell biochemical assays problematic because they do not preserve the spatial context of the cells in question. Thus, these biological areas of research have been unable to harness many of the advances that single cell biology has conferred. Recently, we have developed a method that enables us to distinguish individual RNAs based on single base differences. The goal of this proposal is to quantitative validate this method, first in cell lines and then in mouse and human tissues and then applying to specific biological questions that underscore the utility of the approach. Methodologically, we perform a series of experiments aimed at understanding the parameters relevant to our method with the goal of making the method robust, reliable and easily accessible to other researchers.
In aim 1, we will perform these experiments in cell lines to characterize the probes themselves and develop the capability to measure multiple single nucleotide variants simultaneously within single cells.
In aim 2, we will apply our method to tissue sections from mouse and human with the goal of solving common problems specific to tissue, such as RNA degradation and high background. As an application demonstrating the utility of our method, we will study Beckwith-Wiedemann Syndrome, a genetic disorder in which loss of appropriate imprinting leads to a highly varied phenotype. We will study the manifestations of this disorder by examining allele-specific expression in developing mouse tissues and then in de-identified human patient samples, examining how cell-to-cell variability in imprinting leads to the disease phenotype.
Having the ability to directly visualize single mutations within single cells can help us characterize genetic disorders with parent-of-origin effects, such as Beckwith-Wiedemann Syndrome. We aim to take new tools we have developed to make exactly those sorts of measurements and make the methodology robust and broadly applicable. We will use this technology to understand how variability in single cells can lead to the clinical presentation of these types of diseases.
|Symmons, Orsolya; Raj, Arjun (2016) What's Luck Got to Do with It: Single Cells, Multiple Fates, and Biological Nondeterminism. Mol Cell 62:788-802|
|Hsiung, Chris C-S; Bartman, Caroline R; Huang, Peng et al. (2016) A hyperactive transcriptional state marks genome reactivation at the mitosis-G1 transition. Genes Dev 30:1423-39|
|Bartman, Caroline R; Hsu, Sarah C; Hsiung, Chris C-S et al. (2016) Enhancer Regulation of Transcriptional Bursting Parameters Revealed by Forced Chromatin Looping. Mol Cell 62:237-47|
|Ginart, Paul; Kalish, Jennifer M; Jiang, Connie L et al. (2016) Visualizing allele-specific expression in single cells reveals epigenetic mosaicism in an H19 loss-of-imprinting mutant. Genes Dev 30:567-78|
|Kotzin, Jonathan J; Spencer, Sean P; McCright, Sam J et al. (2016) The long non-coding RNA Morrbid regulates Bim and short-lived myeloid cell lifespan. Nature 537:239-243|
|Shaffer, Sydney M; Joshi, Rohan P; Chambers, Benjamin S et al. (2015) Multiplexed detection of viral infections using rapid in situ RNA analysis on a chip. Lab Chip 15:3170-82|
|Mellis, Ian A; Raj, Arjun (2015) Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another? Genome Res 25:1466-72|