Uncovering developmental time and tempo using deep learning.

ABSTRACT: During animal development, embryos undergo complex morphological changes over time. Differences in developmental tempo between species are emerging as principal drivers of evolutionary novelty, but accurate description of these processes is very challenging. To address this challenge, we present here an automated and unbiased deep learning approach to analyze the similarity between embryos of different timepoints. Calculation of similarities across stages resulted in complex phenotypic fingerprints, which carry characteristic information about developmental time and tempo. Using this approach, we were able to accurately stage embryos, quantitatively determine temperature-dependent developmental tempo, detect naturally occurring and induced changes in the developmental progression of indivi

SUBMITTER: Toulany N 

PROVIDER: S-EPMC10703695 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature