A high-throughput and open-source platform for embryo phenomics.
Oliver TillsJohn I SpicerAndrew GrimmerSimone MariniVun Wen JieEllen TullySimon D RundlePublished in: PLoS biology (2018)
Phenomics has the potential to facilitate significant advances in biology but requires the development of high-throughput technologies capable of generating and analysing high-dimensional data. There are significant challenges associated with building such technologies, not least those required for investigating dynamic processes such as embryonic development, during which high rates of temporal, spatial, and functional change are inherently difficult to capture. Here, we present EmbryoPhenomics, an accessible high-throughput platform for phenomics in aquatic embryos comprising an Open-source Video Microscope (OpenVIM) that produces high-resolution videos of multiple embryos under tightly controlled environmental conditions. These videos are then analysed by the Python package Embryo Computer Vision (EmbryoCV), which extracts phenomic data for morphological, physiological, behavioural, and proxy traits during the process of embryonic development. We demonstrate the broad-scale applicability of EmbryoPhenomics in a series of experiments assessing chronic, acute, and multistressor responses to environmental change (temperature and salinity) in >30 million images of >600 embryos of two species with markedly different patterns of development-the pond snail Radix balthica and the marine amphipod Orchestia gammarellus. The challenge of phenomics is significant but so too are the rewards, and it is particularly relevant to the urgent task of assessing complex organismal responses to current rates of environmental change. EmbryoPhenomics can acquire and process data capturing functional, temporal, and spatial responses in the earliest, most dynamic life stages and is potentially game changing for those interested in studying development and phenomics more widely.
Keyphrases
- high throughput
- single cell
- electronic health record
- human health
- high resolution
- big data
- deep learning
- risk assessment
- liver failure
- microbial community
- mass spectrometry
- life cycle
- dna methylation
- genome wide
- genetic diversity
- convolutional neural network
- hepatitis b virus
- respiratory failure
- acute respiratory distress syndrome