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Quantitative regulatory genomics - Mirko Francesconi

Why are individuals different? We address this fundamental question by studying both genetic and non-genetic sources of phenotypic variation, using both genome-wide computational and experimental systems biology approaches in model organisms. In particular, we are interested in understanding how gene expression is regulated in space and time and how perception of ancestral environment contribute to phenotypic variation.

 

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 and as a powerful generator of mechanistic hypotheses (Francesconi and Lehner Molecular BioSystems, 2015). To this end, we develop computational methods to extract hidden phenotypes from gene expression, such as phyisiological age (Bulteau and Francesconi, Nature Methods, 2022).

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, Nature, 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 underlying this phenotypic variation are therefore major goals in biology. We address these important questions using C. elegans nematode as a model system. We previously found that maternal age extensively contributes to phenotypic variation in the next generation (Perez, Francesconi et. al, Nature, 2017).

How does intergenerational memory of the parental environment influence phenotypes and fitness in the next generation ?

More recently, we discovered that sensory information about the social environment perceived by the nervous system of the parents is transmitted to the progeny impacting their germline development and minimum generation time (Perez et al., Current Biology, 2021). This is one of few demonstrated examples where a physiologically relevant sensory information perceived by the nervous system of an animal is transmitted to the progeny impacting their fitness. We are currently investigating the mechanisms of signal transmission and interpretation in the progeny and exploring if other phenotypic traits such as behaviour are impacted by neuronal perception of the environment in the previous generation.