RRC ID 53370
Author San-Miguel A, Kurshan PT, Crane MM, Zhao Y, McGrath PT, Shen K, Lu H.
Title Deep phenotyping unveils hidden traits and genetic relations in subtle mutants.
Journal Nat Commun
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.
Volume 7
Pages 12990
Published 2016-11-23
DOI 10.1038/ncomms12990
PII ncomms12990
PMID 27876787
PMC PMC5122966
MeSH Alleles Animals Caenorhabditis elegans / genetics* Caenorhabditis elegans Proteins / genetics Caenorhabditis elegans Proteins / metabolism* Gene Expression Regulation Gene Regulatory Networks Microfluidic Analytical Techniques Models, Genetic Quantitative Trait Loci
IF 12.121
Times Cited 13
Resource
C.elegans tm648