Reproductive behaviours vary greatly, not only between, but also within species. Yet, how specific neural circuits evolve to generate natural behavioural variation within species still remains poorly understood. In particular, the precise genetic changes that modulate cellular and developmental architectures of reproductive systems remain unclear. Here we will focus on the simple egg-laying circuit of the nematode Caenorhabditis elegans as a powerful model system to study natural microevolutionary (intraspecific) variability. Our analysis of 278 natural isolates shows that C. elegans exhibits substantial natural genetic variation in egg-laying behaviour. Hence, past research on the laboratory strain N2 has captured only a fraction of the evolutionary plasticity defining this biological system. In this project, we will ask how partially redundant mechanisms at multiple levels of neural circuit organization – genetic, cellular, electrical, anatomical – evolve and how they translate into behavioural variation. Aim 1 will characterize the molecular basis of natural variation using genome-wide association and linkage mapping to identify natural molecular variants explaining behavioural differences. In Aim 2, we will apply a complementary molecular-cellular approach to gain a more complete overview of natural variability in the egg-laying circuit. Specifically, we will use state-of-the-art genetic (CRISPR-Cas9 gene editing) and quantitative imaging methods to systematically compare neuroanatomy, neuronal signalling and electrical phenotypes in isolates with different behaviours. Finally, in aim 3, we will develop high-resolution quantitative behavioural analyses using innovative video-tracking methods to combine our genetic, cellular, functional and behavioural data into an integrated view of evolutionary variability. This project is based on extensive preliminary data and involves three academic and one industrial partner with highly complementary expertise in evolutionary and developmental genetics, cell biology, neurosciences and behavioural imaging technology. Our results will help to understand the molecular-cellular basis of microevolutionary changes in behaviour to generate much-needed insight into how a cellular signalling network can accommodate natural genetic variation.