Systematic discovery of nonobvious human disease models through orthologous phenotypes

Abstract

Biologists have long used model organisms to study human diseases, particularly when the model bears a close resemblance to the disease. We present a method that quantitatively and systematically identifies nonobvious equivalences between mutant phenotypes in different species, based on overlapping sets of orthologous genes from human, mouse, yeast, worm, and plant (212,542 gene-phenotype associations). These orthologous phenotypes, or phenologs, predict unique genes associated with diseases. Our method suggests a yeast model for angiogenesis defects, a worm model for breast cancer, mouse models of autism, and a plant model for the neural crest defects associated with Waardenburg syndrome, among others. Using these models, we show that SOX13 regulates angiogenesis, and that SEC23IP is a likely Waardenburg gene. Phenologs reveal functionally coherent, evolutionarily conserved gene networks-many predating the plant-animal divergence-capable of identifying candidate disease genes.angiogenesis | bioinformatics | evolution | gene-phenotype associations | homology B iochemical and molecular functions of a given protein are generally conserved between organisms; this observation is fundamental to biological research. For example, in x-ray crystallography studies, one can often choose the organism from which the protein is most easily crystallized to facilitate the study of the protein's biochemical function. On the other hand, even with a conserved gene, disruption of function may give rise to radically different phenotypic outcomes in different species. For example, mutating the human RB1 gene leads to retinoblastoma, a cancer of the retina, yet disrupting the nematode ortholog contributes to ectopic vulvae (1, 2). Thus, although a gene's "molecular" functions are conserved, the "organism-level" functions need not be. When a conserved gene is mutated, the resulting organism-level phenotype is an emergent property of the system. This bedrock principle underlying the use of model organisms not only allows us to study important aspects of human biology using mice or frogs, but also permits exploration of inherently multicellular processes, such as cancer, using unicellular organisms like yeast.Within this paradigm, once a molecular function has been discovered in one organism, it should be predictable in other organisms: GSK3 homologs in yeast are kinases, and such GSK3 homologs in every other organism will generally be kinases. In contrast, the emergent organism-level phenotypes are far less predictable between organisms, in part because relationships between genes and phenotypes are many-to-many. Manipulation of GSK3 perturbs nutrient and stress signaling in yeast, anteroposterior patterning and segmentation in insects, dorsoventral patterning in frogs, and craniofacial morphogenesis in mice (3-5). Recognizing functionally equivalent organism-level phenotypes between model organisms can therefore be nonobvious, especially across large evolutionary distances.However, the ability to recognize equivalent phenotypes betwee...

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome

“…41,43 Although the similarities between human and model organism mutant phenotype can be informative, this approach may miss numerous opportunities in which the protein functions are part of conserved pathways among organisms when the orthologous phenotypes are not obviously analogous. 44 For example, a yeast model for angiogenesis 44 and a worm model for breast cancer 44 revealed molecular pathways that contribute to these disorders based on the ''phenology'' concept. Therefore, we adapted a gene-centric rather than phenotypic-centric approach to study gene function by integrating model organism and human data in a single aggregated web-based resource.…”

The need for mouse models in osteoporosis genetics research

“…Genetic mapping research has identified many genes and pathways involving these genes that are responsible for phenotypic outcomes. However, in many cases, the specific genes responsible for the phenotypes may not be conserved between species, 43,44 or even between strains of the same species; however, the pathways perturbed are often conserved across millions of evolutionary years. This suggests that rather than focusing on specific genetic alterations or expression changes in a single gene, research could benefit from considering data at a higher, so called ' systems ' level.…”

An Evolutionary Biology Approach to Understanding Neurological Disorders

“…Proteins sharing a particular functional category cluster in the same location of PPI networks, and are referred to as functional modules, and placement of proteins in PPI networks can be used to inform protein function prediction studies (Dziembowski & Seraphin, 2004;Yook et al, 2004;Makino & Gojobori, 2006). Understanding networks of PPIs can be used to predict additional genes that, when mutated, may cause the same disease as that associated with mutations in interacting partners (McGary et al, 2010), and also explains why so many different mutated genes can cause the same or similar complex disease (Bill & Geschwind, 2009;Bourgeron, 2009;Crespi et al, 2010;Gilman et al, 2011;Guilmatre et al, 2009). Relating to the network-based nature of many gene products is the concept that some proteins interact with multiple other proteins, referred to as 'hub' genes (Fig.…”

“…The reason why model organisms are able to contribute so effectively to our understanding of human diseases lies in the high degree of molecular conservation found between metazoan species, and in the conserved nature of protein-protein, and other, networks (Gandhi et al, 2006). Indeed, even bacteria, plants, protists, and fungi are being exploited to explore differing aspects of biology relevant to human disease (Annesley & Fisher, 2009;Ilievska et al, 2011;McGary et al, 2010;Spradling et al, 2006). …”