Quantitative regulatory genomics - Mirko Francesconi
Addressing big questions with big data
In my lab we address fundamental biological questions using big data integration and modelling, and experimental approaches. We especially focus on genome-wide gene expression dynamics - including at single-cell and single-individual level - as a multidimensional information-rich intermediate phenotype (Francesconi and Lehner 2015) and as a powerful generator of mechanistic hypotheses.
Gene regulation in space and time
Many disease causing mutations do not change gene sequences but when, where and how much genes are expressed. While we understand to a good extent the impact mutations in coding sequences we still do not understand the impact of genetic variation on regulation of gene expression. How can we predict the impact of genetic variation on gene regulation? What are the determinants of gene expression in space and time? These are some of the questions we are addressing in my lab (Francesconi and Lehner 2014).
Why are genetically identical individuals phenotypically different?
Genetically identical individuals are often phenotypically different. For example, identical twins are often discordant for common genetic diseases such as schizophrenia. Beside the genome, one obvious factor that can impact phenotypes, is the environment in which organisms are born and develop. However, studies in genetically identical model organisms, where the environment is carefully controlled, highlight extensive inter-individual phenotypic variation. Understanding the causes, the consequences and the mechanisms underlining this phenotypic variation is therefore is one of the current main open question in biology. And one of the questions we are interested in my lab (Perez, Francesconi et. al, 2017).