Promoting validation and cross-phylogenetic integration in model organism research

Keith C. Cheng, Rebecca D. Burdine, Mary E. Dickinson, Stephen C. Ekker, Alex Y. Lin, K. C.Kent Lloyd, Cathleen M. Lutz, Calum A. MacRae, John H. Morrison, David H. O'Connor, John H. Postlethwait, Crystal D. Rogers, Susan Sanchez, Julie H. Simpson, William S. Talbot, Douglas C. Wallace, Jill M. Weimer, Hugo J. Bellen

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Model organism (MO) research provides a basic understanding of biology and disease due to the evolutionary conservation of the molecular and cellular language of life. MOs have been used to identify and understand the function of orthologous genes, proteins, cells and tissues involved in biological processes, to develop and evaluate techniques and methods, and to perform whole-organismbased chemical screens to test drug efficacy and toxicity. However, a growing richness of datasets and the rising power of computation raise an important question: How do we maximize the value of MOs? In-depth discussions in over 50 virtual presentations organized by the National Institutes of Health across more than 10 weeks yielded important suggestions for improving the rigor, validation, reproducibility and translatability of MO research. The effort clarified challenges and opportunities for developing and integrating tools and resources. Maintenance of critical existing infrastructure and the implementation of suggested improvements will play important roles in maintaining productivity and facilitating the validation of animal models of human biology and disease.

Original languageEnglish (US)
Article numberdmm049600
JournalDMM Disease Models and Mechanisms
Volume15
Issue number9
DOIs
StatePublished - Sep 2022

All Science Journal Classification (ASJC) codes

  • Immunology and Microbiology (miscellaneous)
  • General Biochemistry, Genetics and Molecular Biology
  • Neuroscience (miscellaneous)
  • Medicine (miscellaneous)

Keywords

  • Human diseases
  • Integration
  • Model organisms
  • Omics
  • Phenomics
  • Research resources
  • Technology
  • Validation

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