Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2012 Jan;5(1):19-25.
doi: 10.1242/dmm.008334. Epub 2011 Oct 25.

Exploring the Elephant: Histopathology in High-Throughput Phenotyping of Mutant Mice

Affiliations
Free PMC article
Review

Exploring the Elephant: Histopathology in High-Throughput Phenotyping of Mutant Mice

Paul N Schofield et al. Dis Model Mech. .
Free PMC article

Abstract

Recent advances in gene knockout techniques and the in vivo analysis of mutant mice, together with the advent of large-scale projects for systematic mouse mutagenesis and genome-wide phenotyping, have allowed the creation of platforms for the most complete and systematic analysis of gene function ever undertaken in a vertebrate. The development of high-throughput phenotyping pipelines for these and other large-scale projects allows investigators to search and integrate large amounts of directly comparable phenotype data from many mutants, on a genomic scale, to help develop and test new hypotheses about the origins of disease and the normal functions of genes in the organism. Histopathology has a venerable history in the understanding of the pathobiology of human and animal disease, and presents complementary advantages and challenges to in vivo phenotyping. In this review, we present evidence for the unique contribution that histopathology can make to a large-scale phenotyping effort, using examples from past and current programmes at Lexicon Pharmaceuticals and The Jackson Laboratory, and critically assess the role of histopathology analysis in high-throughput phenotyping pipelines.

Figures

Fig. 1.
Fig. 1.
Information content (IC) of mammalian phenotype ontology terms in the OMIM dataset. Blue columns represent all phenotype ontology terms and red columns those terms that are defined using terms from the mammalian pathology ontology (MPATH). Mammalian phenotype ontology terms were used to automatically annotate all OMIM diseases by mapping between the human and mammalian phenotype ontology with PhenomeBlast software (http://bioonto.gen.cam.ac.uk:9090/PhenomeBlast-0.1/). The IC was then calculated as the probability that a given ontology term is used in the annotation of an OMIM disease. For example, abnormal circulating lipid level (MP:0003949) is a relatively undiscriminating measurement because it is found as an annotation to 430 OMIM diseases; thus, the IC for this term is low. By contrast, xanthoma (deposition of cholesterol-rich lipids under the skin; MP:0003692) has a much greater ability to discriminate between diseases because it is only found in 17 diseases in OMIM, and the IC for this term is high. Less than 10% of the phenotype ontology terms are defined using MPATH, but the spectrum of IC values shows that terms defined using MPATH are more informative and therefore more discriminating than the bulk of the phenotype ontology terms.

Similar articles

See all similar articles

Cited by 17 articles

See all "Cited by" articles

References

    1. Abbott A. (2010). Mouse project to find each gene’s role. Nature 465, 410. - PubMed
    1. Acevedo-Arozena A., Wells S., Potter P., Kelly M., Cox R. D., Brown S. D. (2008). ENU mutagenesis, a way forward to understand gene function. Annu. Rev. Genomics Hum. Genet. 9, 49–69 - PubMed
    1. Antony P. M., Diederich N. J., Balling R. (2011). Parkinson’s disease mouse models in translational research. Mamm. Genome 22, 401–409 - PMC - PubMed
    1. Barthold S. W., Borowsky A. D., Brayton C., Bronson R., Cardiff R. D., Griffey S. M., Ince T. A., Nikitin A. Y., Sundberg J. P., Valli V. E., et al. (2007). From whence will they come? A perspective on the acute shortage of pathologists in biomedical research. J. Vet. Diagn. Invest. 19, 455–456 - PubMed
    1. Barton E. R., Wang B. J., Brisson B. K., Sweeney H. L. (2010). Diaphragm displays early and progressive functional deficits in dysferlin-deficient mice. Muscle Nerve 42, 22–29 - PMC - PubMed

Publication types

LinkOut - more resources

Feedback