Canalisation and plasticity on the developmental manifold of Caenorhabditis elegans
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Abstract
How do the same mechanisms that faithfully regenerate complex developmental programmes in spite of environmental and genetic perturbations also allow responsiveness to environmental signals, adaptation and genetic evolution? Using the nematode Caenorhabditis elegans as a model, we explore the phenotypic space of growth and development in various genetic and environmental contexts. Our data are growth curves and developmental parameters obtained by automated microscopy. Using these, we show that among the traits that make up the developmental space, correlations within a particular context are predictive of correlations among different contexts. Furthermore, we find that the developmental variability of this animal can be captured on a relatively low‐dimensional phenotypic manifold and that on this manifold, genetic and environmental contributions to plasticity can be deconvolved independently. Our perspective offers a new way of understanding the relationship between robustness and flexibility in complex systems, suggesting that projection and concentration of dimension can naturally align these forces as complementary rather than competing.
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Hi, thanks for the question! For this implementation it a confluence of constraints that results in this sampling rate. There is the mechanical constraint of physical y moving the camera between the wells. Also, because the robot is not 100% precise, drift errors would accumulate over the course of the experiment, to fix this, the camera did a circle detection and re-centering step. Next a series of images were recorded to detect movement in the frame, and then an SVM was applied to the subsection of the image where movement was detected. (in case no movement was detected the images were save for manual curation later). Finally, because there were 40-60 wells that were measured before returning again, this results in the fairly slow frame rate. We could have (and probably should have) recorded a short segment of the behavior upon …
Hi, thanks for the question! For this implementation it a confluence of constraints that results in this sampling rate. There is the mechanical constraint of physical y moving the camera between the wells. Also, because the robot is not 100% precise, drift errors would accumulate over the course of the experiment, to fix this, the camera did a circle detection and re-centering step. Next a series of images were recorded to detect movement in the frame, and then an SVM was applied to the subsection of the image where movement was detected. (in case no movement was detected the images were save for manual curation later). Finally, because there were 40-60 wells that were measured before returning again, this results in the fairly slow frame rate. We could have (and probably should have) recorded a short segment of the behavior upon each visit to the well. At the time I wasn't prioritizing it as I was still in the process of developing some new analytical methods to quantify and compare C. elegans locomotion which weren't quite ready yet. We have recently published some of these methods, and I am excited to be using another setup I built that has 12 parallel cameras that are continuously recording at 15Hz that I am using now to measure development and locomotion simultaneously. For the more high throughput stuff I will definitely start recording short segments of video to measure locomotion from the visits to each well though!
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we designed and constructed a low-cost parallel imaging platform capable of measuring C. elegans growth for 60 individual animals simultaneously over the course of their ≈ 70 hour development at a temporal resolution of 0.001 Hz, resulting in a time series of ≈ 200 observations per animal. In addition to length and area measured automat-ically, egg hatching, and first egg-laying by mature adults are manually recorded.
Is there a reason for the coarse sampling at 0.001 Hz? Mechanical constraints of the XY plotting robot? Data size constraints? Obviously faster sampling would open up locomotion/behavior as a read out of other possibly interesting, orthogonal phenotypes (with their own developmental modes). Given the video data you are already collecting, it seems like if faster sampling is possible this would be a relatively …
we designed and constructed a low-cost parallel imaging platform capable of measuring C. elegans growth for 60 individual animals simultaneously over the course of their ≈ 70 hour development at a temporal resolution of 0.001 Hz, resulting in a time series of ≈ 200 observations per animal. In addition to length and area measured automat-ically, egg hatching, and first egg-laying by mature adults are manually recorded.
Is there a reason for the coarse sampling at 0.001 Hz? Mechanical constraints of the XY plotting robot? Data size constraints? Obviously faster sampling would open up locomotion/behavior as a read out of other possibly interesting, orthogonal phenotypes (with their own developmental modes). Given the video data you are already collecting, it seems like if faster sampling is possible this would be a relatively straightforward - and informative - set of phenotypes to add in?
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