Along with the recent advance of live-imaging technologies, enormous amounts of time-lapse microscopy images are becoming available in public databases. By applying image processing methods, quantitative data such as positions and shapes of nuclei and cells, and their temporal changes can be extracted from the images. Large-scale collections of such data are important resources for computational phenotype analysis. We therefore established a new resource of quantitative data on nuclear division dynamics in C. elegans RNAi-treated embryos by image-processing time-lapse DIC microscopy images in Phenobank. It consists of 1,579 sets of quantitative data from RNAi-treated embryos, including three sets of data for each of 518 genes that exerted defects in early embryogenesis when depleted individually by RNAi. Each data contains the nuclear regions and their temporal changes. The resource will be available in SSBD database (Tohsato et al. 2016;
http://ssbd.qbic.riken.jp). To demonstrate the usefulness of our resource for computational phenotype screening, we calculated the speed of female pronuclear migration in its RNAi-treated embryos. 12 genes showed faster or slower migration than wild-type. Out of the 12 genes, 7 genes reproduced the migration phenotype in our independent RNAi experiments. Among the 7 genes,
sds-22 and F44B9.8 exhibited remarkedly faster and slower migration respectively.
sds-22(RNAi) and F44B9.8(RNAi) embryos expressing GFP::tubulin exhibited larger and smaller microtubule sperm aster respectively, consistent with the nuclear tracking along microtubules mechanism. Convergent cross mapping (CCM) identified a causal effect of the aster size on the migration speed. Since SDS-22 down-regulates ZYG-1 kinase through GSP-1/2 in centrosomal duplications (Peel et al., 2017), we examined RNAi phenotypes of
gsp-1/2 in female pronuclear migration.
gsp-1(RNAi) exhibited faster migration, suggesting that
sds-22 regulates
zyg-1 in pronuclear migrations as well. The roles of F44B9.8, an ortholog of human replication factor C, remain unclear.These results demonstrate that our resource provides new opportunities for computational phenotype screening.