1. Developing new technology for spatially resolved transcriptomics

While genome-wide techniques such as RNA sequencing are ideally suited for discovering novel candidate genes, they are unable to yield spatially resolved information in embryos or tissues. Microscopy-based approaches, using for example in situ hybridization, can provide spatial information about gene expression, but are limited to analysing one or a few genes at a time. We recently developed tomo-seq, which is a method where we combined traditional histological techniques with low-input RNA sequencing and mathematical image reconstruction to generate a high-resolution genome-wide 3D atlas of gene expression. Importantly, our technique enables searching for genes that are expressed in specific spatial patterns without manual image annotation. We envision broad applicability of RNA tomography as an accurate and sensitive approach for spatially resolved transcriptomics in tumours.

2. Development of novel experimental and computational methodology for single-cell sequencing

We developed some of the first experimental and computational methods to separate the biological variability from the significant technical variability in single-cell mRNA-seq data. We published the first integrated method to amplify both mRNA and DNA from the same individual cell and we introduced RaceID, which is a strategy to detect rare cells by single-cell mRNA sequencing. This led to the discovery of rare novel cell types in the mammalian intestine. Additionally, we used this approach to infer stem cell states de novo from single-cell transcriptome data (StemID). Most recently we developed the first technology to detect 5-hydroxymethylcytosine (5hmC) in single cells. This method demonstrated large chromosome-wide variability of 5hmC among single cells. Additionally, we demonstrated that this technology is a powerful tool for endogenous lineage reconstruction.

3. Development of new methods to count mRNA molecules in situ

In addition to developing new sequencing-based technology my laboratory also pioneered new imaging-based methods to count individual mRNA and DNA molecules in situ. In 2008 we developed single-molecule FISH (smFISH), a technology that allows the detection of single mRNA molecules in intact single cells. More recently we adapted this approach to detect DNA loci in single cells with high spatial resolution. Additionally the sensitivity of the smFISH technology was optimized to allow allele-specific detection and FACS sorting.

4. Quantitative biology of microRNA regulation

By using a combination of quantitative single cell experiments and models our laboratory made important discoveries that improved our understanding of microRNA regulation. We are particularly interested in how microRNAs can generate thresholds in target gene expression, mediate feedforward and feedback loops in gene networks, and control fluctuations of gene expression.

5. Revealing the origins and sources of stochastic gene expression

The van Oudenaarden has been a pioneering lab in developing the theoretical and experimental tools to develop a quantitative understanding of the origins and sources of stochastic gene expression. Our earlier work was focused on microbial systems but more recently my laboratory started to explore the role of stochastic gene expression in multicellular organisms, stem cells, and cancer.