ArticleProceedings of the National Academy of Sciences of the United States of America2013
Systematic profiling of Caenorhabditis elegans locomotive behaviors reveals additional components in G-protein Gαq signaling.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 32 citations in OpenAlex.
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- Systematic phenomics analysis of autism-associated genes reveals parallel networks underlying reversible impairments in habituation.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Digging deeper: methodologies for high-content phenotyping in Caenorhabditis elegans.Lab animal · 2019Review
- Powerful and interpretable behavioural features for quantitative phenotyping ofPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
- Lipid and Carbohydrate Metabolism inGenetics · 2017Review
- Scalable electrophysiology in intact small animals with nanoscale suspended electrode arrays.Nature nanotechnology · 2017Article
- High-content behavioral profiling reveals neuronal genetic network modulating Drosophila larval locomotor program.BMC genetics · 2017Article
- Locomotion Behavior Is Affected by the GαGenetics · 2017Article
- Inactivity periods and postural change speed can explain atypical postural change patterns of Caenorhabditis elegans mutants.BMC bioinformatics · 2017Article
- A network approach to discerning the identities of C. elegans in a free moving population.Scientific reports · 2016Article
- Hierarchical compression of Caenorhabditis elegans locomotion reveals phenotypic differences in the organization of behaviour.Journal of the Royal Society, Interface · 2016Article
- A Generative Statistical Algorithm for Automatic Detection of Complex Postures.PLoS computational biology · 2015Article
- Genetics of Intraspecies Variation in Avoidance Behavior Induced by a Thermal Stimulus in Caenorhabditis elegans.Genetics · 2015Article
- An automated system for quantitative analysis of Drosophila larval locomotion.BMC developmental biology · 2015Article
- Model-independent phenotyping of C. elegans locomotion using scale-invariant feature transform.PloS one · 2015Article
- WormGender - Open-Source Software for Automatic Caenorhabditis elegans Sex Ratio Measurement.PloS one · 2015Article
- QuantWorm: a comprehensive software package for Caenorhabditis elegans phenotypic assays.PloS one · 2014Article
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7 authors at 3 institutions in 1 country.
Funding
Abstract
Genetic screens have been widely applied to uncover genetic mechanisms of movement disorders. However, most screens rely on human observations of qualitative differences. Here we demonstrate the application of an automatic imaging system to conduct a quantitative screen for genes regulating the locomotive behavior in Caenorhabditis elegans. Two hundred twenty-seven neuronal signaling genes with viable homozygous mutants were selected for this study. We tracked and recorded each animal for 4 min and analyzed over 4,400 animals of 239 genotypes to obtain a quantitative, 10-parameter behavioral profile for each genotype. We discovered 87 genes whose inactivation causes movement defects, including 50 genes that had never been associated with locomotive defects. Computational analysis of the high-content behavioral profiles predicted 370 genetic interactions among these genes. Network partition revealed several functional modules regulating locomotive behaviors, including sensory genes that detect environmental conditions, genes that function in multiple types of excitable cells, and genes in the signaling pathway of the G protein Gαq, a protein that is essential for animal life and behavior. We developed quantitative epistasis analysis methods to analyze the locomotive profiles and validated the prediction of the γ isoform of phospholipase C as a component in the Gαq pathway. These results provided a system-level understanding of how neuronal signaling genes coordinate locomotive behaviors. This study also demonstrated the power of quantitative approaches in genetic studies.
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