We are interested in understanding how biological information is encoded in DNA sequences, and how sequence variation among individuals generates phenotypic diversity. Our main focus is on transcriptional control, chromatin structure, and RNA regulation, where we aim to develop quantitative and mechanistic models that integrate the involved components, including DNA sequence, transcription factors, nucleosomes, and binding competition and synergy. To devise and validate our models, we employ several experimental methods to measure DNA binding events and gene expression on a genome-wide scale, at high temporal resolution, across single cells and cell populations, and on both native and synthetically designed regulatory sequences. Ultimately, the ability of our models to accurately explain transcriptional behaviors from DNA sequences should allow us to predict the effect that sequence variation among individuals has on gene expression and thus on more complex phenotypes and disease. Selected papers:
- inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters. Nature Biotechnology, 2012.
- Manipulating nucleosome disfavoring sequences allows fine-tune regulation of gene expression in yeast. Nature Genetics, 2012.
- Genome-wide measurement of RNA secondary structure in yeast. Nature, 2010.
- From DNA sequence to transcriptional behaviour: a quantitative approach.
Nature Reviews Genetics, 2009.
- The DNA-Encoded Nucleosome Organization of a Eukaryotic Genome. Nature, 2009.
- Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature, 2008.
- The role of site accessibility in microRNA target recognition. Nature Genetics, 2007.
- A Genomic Code for Nucleosome Positioning.
Nature, 2006. The New York Times, 2006.