Summary
Social behaviour plays an important role in the survival and development of many species with the most conspicuous and ubiquitous form being collective behaviour – the coordinated action of two or more individuals of the same species. Despite immense interest in collective behaviour in biology, the dynamic relationship between genotypes and phenotypes characterising this phenomenon remains opaque. Understanding this link, however, is crucial to elucidating the mechanisms of collective behaviour and emergence of social structures, and, most importantly, the genetic origins of social behaviour. In this project, I aim to quantify the genotype-phenotype mapping in the social behaviour of the nematode worm Caenorhabditis elegans using quantitative phenotyping and computational modelling. Due to its unique amenability to exhaustive genetic analyses, trackability and rich collective properties (so-called collective feeding), C. elegans is a perfect system to address this question. My project will use high-throughput imaging data of social feeding in hundreds of different C. elegans strains. I will develop a novel dynamic multi-state model based on worm postures and spatial positions, allowing to quantitatively describe nematode social behaviour in a worm density-dependent manner. My research programme will, for the first time, rigorously examine the phenotypic behavioural space in C. elegans and test its tolerance to mutations in a social context, hereby providing insights into the genetic basis of emergent social behaviour. Such a study is extremely timely as it will build on the brand-new nematode data collected at my host university using cutting-edge imaging and tracking techniques. This interdisciplinary project will provide significant amounts of training in modern quantitative and systems biology, including data analysis and modelling, as well as in research project management and networking, and thus be an ideal stepping stone to an independent scientific career.
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| Web resources: | https://cordis.europa.eu/project/id/842860 |
| Start date: | 01-07-2019 |
| End date: | 30-06-2021 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
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Original description
Social behaviour plays an important role in the survival and development of many species with the most conspicuous and ubiquitous form being collective behaviour – the coordinated action of two or more individuals of the same species. Despite immense interest in collective behaviour in biology, the dynamic relationship between genotypes and phenotypes characterising this phenomenon remains opaque. Understanding this link, however, is crucial to elucidating the mechanisms of collective behaviour and emergence of social structures, and, most importantly, the genetic origins of social behaviour. In this project, I aim to quantify the genotype-phenotype mapping in the social behaviour of the nematode worm Caenorhabditis elegans using quantitative phenotyping and computational modelling. Due to its unique amenability to exhaustive genetic analyses, trackability and rich collective properties (so-called collective feeding), C. elegans is a perfect system to address this question. My project will use high-throughput imaging data of social feeding in hundreds of different C. elegans strains. I will develop a novel dynamic multi-state model based on worm postures and spatial positions, allowing to quantitatively describe nematode social behaviour in a worm density-dependent manner. My research programme will, for the first time, rigorously examine the phenotypic behavioural space in C. elegans and test its tolerance to mutations in a social context, hereby providing insights into the genetic basis of emergent social behaviour. Such a study is extremely timely as it will build on the brand-new nematode data collected at my host university using cutting-edge imaging and tracking techniques. This interdisciplinary project will provide significant amounts of training in modern quantitative and systems biology, including data analysis and modelling, as well as in research project management and networking, and thus be an ideal stepping stone to an independent scientific career.Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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