title: Deep phenotyping unveils hidden traits and genetic relations in subtle mutants.
abstract: Discovering mechanistic insights from phenotypic information is critical for the understanding of biological processes. For model organisms, unlike in cell culture, this is currently bottlenecked by the non-quantitative nature and perceptive biases of human observations, and the limited number of reporters that can be simultaneously incorporated in live animals. An additional challenge is that isogenic populations exhibit significant phenotypic heterogeneity. These difficulties limit genetic approaches to many biological questions. To overcome these bottlenecks, we developed tools to extract complex phenotypic traits from images of fluorescently labelled subcellular landmarks, using C. elegans synapses as a test case. By population-wide comparisons, we identified subtle but relevant differences inaccessible to subjective conceptualization. Furthermore, the models generated testable hypotheses of how individual alleles relate to known mechanisms or belong to new pathways. We show that our model not only recapitulates current knowledge in synaptic patterning but also identifies novel alleles overlooked by traditional methods.
authors.affiliation: School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Adriana
authors.initials: A
authors.lastname: San-Miguel
authors.affiliation: Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA.
authors.forename: Peri T
authors.initials: PT
authors.lastname: Kurshan
authors.affiliation: Interdisciplinary Program in Bioengineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Matthew M
authors.initials: MM
authors.lastname: Crane
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Yuehui
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Patrick T
authors.initials: PT
authors.lastname: McGrath
authors.affiliation: Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA.
authors.forename: Kang
authors.initials: K
authors.lastname: Shen
authors.affiliation: School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.|Interdisciplinary Program in Bioengineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Hang
authors.initials: H
authors.lastname: Lu
mesh_terms: D000483:Alleles; D000818:Animals; D017173:Caenorhabditis elegans / Q000235:genetics*; D029742:Caenorhabditis elegans Proteins / Q000235:genetics / Q000378:metabolism*; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D046210:Microfluidic Analytical Techniques; D008957:Models, Genetic; D040641:Quantitative Trait Loci
chemical_list: D029742:Caenorhabditis elegans Proteins