Research Project
9431112
Project Summary/Abstract The accurate measurement of the transcriptome is essential for most fields of biomedical research and increasingly in genomic medicine. RNA-sequencing (RNA-seq) is a transformative technology that has made measuring the transcriptome more accessible. This has empowered population scale functional genomic analyses, such as expression quantitative trait loci (eQTL) studies, which have yielded insight into the regulatory architecture of the genome. However, current RNA-seq methods are invasive and expensive, which has limited the types and numbers of participants involved in research studies, and more broadly the application of RNA-seq in genomic medicine. The objective of this proposal is to develop a novel RNA-seq based method for measuring the transcriptome that is both non-invasive an order of magnitude cheaper than current methods, and apply it to population scale longitudinal and developmental studies of gene expression and cis-regulatory genetic variation. First I will develop a low cost, non-invasive, RNA-seq based method for transcriptome profiling by borrowing from advances in single genomics and identifying easily sampled tissues that capture relevant gene expression. Second, I will use this method in a human longitudinal eQTL study to determine the degree of cis-regulatory genetic variation effect sharing between non-invasively collected tissues and surgically isolated tissues, and to study the effect of environmental variation on the regulatory landscape. Third, I will collect phenotype, genotype, and expression data in a cohort that spans childhood to produce a map of childhood gene expression, characterize interactions between development and cis-regulatory genetic variation, and identify expression biomarkers of common childhood disease. This may reveal the molecular mechanisms of genetic associations to common disease for processes that occur during development, and have thus far been missed in adult eQTL studies. As a whole, this work will further understanding of the dynamic interaction between cis-regulatory genetic variation, the environment, and development, and will produce a new method that will be of wide use to the biomedical community, empowering future transcriptome studies of vulnerable populations and at massive scales.
