We explore the molecular mechanisms underlying nervous system function by finding genes and gene networks that affect behaviour.
The goal of behavioural genomics is to understand the mapping between genome variation and behaviour. However, technology for sequencing and perturbing genomes is advancing more rapidly than our ability to assess all of the consequences of genetic perturbation. To help redress the imbalance between measures of genotype and phenotype, we are developing high-throughput imaging platforms to capture complex behavioural sequences and automated algorithms to interpret them.
Motor behaviour is a useful phenotype because it is the principal output of the nervous system and has previously been used to find genes with roles in synaptic transmission, neural development, and many kinds of sensation among other things. The nematode worm C. elegans is a great model for behavioural genomics in part because of its relatively simple and exceptionally well-characterised nervous system. Its locomotion is sufficiently complex to reliably identify subtle differences between mutants yet simple enough to quantify nearly completely. Well-developed reagents for imaging gene expression and neural activity make for a tight loop between hypothesis generating screens and hypothesis testing functional experiments.
Brown AEX, de Bivort B, Ethology as a physical science, Nature Physics, ISSN:1745-2473, Pages:1-5
et al., An open source platform for analyzing and sharing worm behavior data, Nature Methods, ISSN:1548-7091
Javer A, Ripoll-Sanchez L, Brown AE, Powerful and interpretable behavioural features for quantitative phenotyping of C. elegans, Philosophical Transactions B: Biological Sciences, ISSN:0962-8436
et al., 2018, Glassy worm-like micelles in solvent and shear mediated shape transitions., Soft Matter, Vol:2018, ISSN:1744-683X
Keaveny EE, Brown AEX, 2017, Predicting path from undulations for C. elegans using linear and nonlinear resistive force theory, Physical Biology, Vol:14, ISSN:1478-3967