Comparative Analysis of Developmental Systems
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Comparative Analysis of Developmental Systems
2008–present: Group Leader, EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), Barcelona
2006–2008: Postdoctoral Fellow, Laboratory for Development & Evolution, University Museum of Zoology, Cambridge, UK
Principal Investigators: Michael Akam & Nick Monk
Project: A Comparative Gene Circuit Approach to Study the Evolution of Segmentation in Insects
2000–2005: PhD, Graduate Program in Genetics, Stony Brook University, New York, USA
Supervisor: John Reinitz
Thesis: Dynamic Regulatory Analysis of the Gap Gene Network in Drosophila melanogaster
1999–2000: MSc in Holistic Science, Schumacher College, Dartington, Devon, UK
Supervisor: Brian Goodwin
Thesis: A Cellular Oscillator Model of Animal Segmentation.
1997–1999: University Diploma in Biology, Biozentrum, University of Basel, Switzerland
Supervisor: Walter Gehring
Thesis: Apoptosis and Homeosis in the Drosophila Eye Imaginal Disc
"Natural selection may explain the survival of the fittest, but it cannot explain the arrival of the fittest." said the famous geneticist Hugo de Vries in 1904. Today, we still lack a clear idea of why organisms such as plants and animals look exactly the way they do. For example, why are there no back-boned animals with more than four legs? Why do most of these creatures have five or less toes on their feet? Why are there no insects with more than two pairs of wings? Part of these questions can be explained by adaptation of environmental conditions through natural selection. But biological form also depends on how organisms grow and develop. Understanding development is one of the fundamental challenges of modern biology. In our laboratory we try to understand the principles that govern this process, from egg to adult, and how these principles affect the way in which evolution by natural selection shapes the diversity of life.
Our group consists of experimentalists and computational researchers. We perform experiments on three species of flies and midges: the fruit fly (Drosophila melangoaster), a scuttle fly (Megaselia abdita), and a moth midge (Clogmia albipuncata). We study when and where genes are switched on or off during development of these animals. This is done by coloring the chemical products of gene regulation (RNA or protein), and visualizing the resulting patterns of gene expression by microscopy. We then simulate the interactions of these genes (how they regulate each other) using the Mare Nostrum supercomputer of the Barcelona Supercomputing Center (BSC: http://www.bsc.es). This approach is called gene network modeling and allows us to study how genes function in their organismic context and how this function has changed during evolution.
It is now more than 150 years since Darwin published his "Origin of Species", in which he proposed natural selection as the major mechanism for adaptation. Selection acts on phenotypic variability within populations: those individuals who are better adapted to their environment survive longer and have more offspring than less adapted ones. However, we still lack a coherent view of how such variability arises during evolution and development, and how it reflects molecular variation in the genome. In other words, we lack a precise idea of what is being selected.
The relationship between genotype and phenotype is complex and non-linear. Traditional genetic and molecular experimental methods are limited in their ability to keep track of the many factors and regulatory interactions involved. For this reason, we need a systems-biology approach, based on mathematical modeling, to address this question. We are carrying out an integrative, comparative analysis of real evolving developmental gene regulatory networks using a novel reverse-engineering approach (the gene circuit method). Gene circuits are computational tools to extract regulatory information from quantitative spatial gene expression data (Fig. 1). This is achieved by fitting mathematical models of gene networks to data (model optimization). The resulting models give us the structure and dynamics of the regulatory network responsible for the observed patterns, which in turn predict regulatory mechanisms that can be tested experimentally.
We study the evolution of the following networks in dipteran insects (flies, midge, and mosquitoes): the gap gene network involved in pattern formation in the early embryo of dipterans, the gene network underlying muscle and heart development during organogenesis, and the thoracic patterning network responsible for the positioning of mechanosensory bristles on the dorsal cuticle of the animal (Fig. 2A). We are establishing three dipteran species—the fruit fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata—as model systems to experimentally and quantitatively test hypotheses derived from systems-biology approaches to evolutionary developmental biology (Fig. 2B).
Our models allow us to infer the regulatory interactions necessary and sufficient to explain the observed expression patterns by fitting models to data. Models from different species can be compared to reveal which interactions are conserved and which have diverged during evolution. In addition, we study evolutionary transitions between species using an in silico evolution approach. We will test these predictions by using RNA interference (RNAi) in various species and reporter assays in Drosophila. Our approach provides an integrative view of network evolution across multiple levels, from the molecular to the phenotypic. To our knowledge, this has not yet been achieved for any real developmental system.
Our data are available through the following databases:
SuperFly: a database of quantitative Drosophila in situ hybridization patterns.
Diptex: a database for comparative transcriptomics in dipteran species.
FlyEx: a database of quantitative gene expression patterns in the Drosophila blastoderm embryo.
We are collaborating with research groups in Europe and the US:
John Reinitz, University of Chicago, USA
Urs Schmidt-Ott, University of Chicago, USA
Maria Samsonova, St. Petersburg State Polytechnical University, RU
Nick Monk, University of Sheffield, UK
We are co-ordinating the 7th Framework Program consortium called BioPreDyn which is concerned with reverse-engineering and data-driven systems biology modeling. Consortium partners include
Julio Banga, Instituto de Investigaciones Marinas, CSIC, Vigo, ES
Julio Saez Rodrigues, EBI, Hinxton, UK
Jaap Kaandorp, University of Amsterdam, NL
Joke Blom, CWI Amsterdam, NL
Diego di Bernardo, TIGEM Naples, IT
Pedro Mendes, University of Manchester, UK
Neil Lawrence, University of Sheffield, UK
The CoSMo Company, Lyon, FR
Insilico Biotechnology, Stuttgart, DE
Fluxome SA, Stenlose, DK
... and are partners in the EraNET projects MODHEART (Co-ordinated by Laurent Perrin, Marseille, FR) and MOPDEV (Co-ordinated by Jaap Kaandorp, Amsterdam, NL).