The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

Abstract

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

The Planarian Anatomy Ontology: A resource to connect data within and across experimental platforms

“…PLANA will be instrumental to the construction and development of additional community resources, such as a planarian phenotype ontology. Notably, PLANA will facilitate the incorporation of a phenotype ontology into Upheno and Monarch (Shefchek et al, 2020), a semantic-based integrative data platform that connects expression and phenotypes with genotypes across species. Interoperability of PLANA with other anatomy ontologies, through Uberon, and of a Smed phenotype ontology with other phenotype ontologies, through Monarch, will facilitate comparative anatomy queries and cross-species genotypic and phenotypic comparisons.…”

Disruption of a Hedgehog-Foxf1-Rspo2 Signaling Axis Leads to Tracheomalacia and a Loss of Sox9+ Tracheal Chondrocytes

“…We next intersected the Gli3R-regulated transcripts with a manually curated list of 61 genes implicated in tracheal chondrogenesis and/or tracheomalacia in mice or humans (Supplemental Table 2). These were identified from a review of the literature (Sinner et al, 2019) (Supplemental Figure 3C) and by searching the Monarchinitiative.org, an online knowledgebase that aggregates human disease and animal model genotype-phenotypes associations (Shefchek et al, 2020). This intersection revealed five genes, all of which were downregulated in Gli3T transgenic embryos ( Figure 5C), consistent with them being direct targets of Gli3 repressor activity.…”

“…Foxg1Gli3T Flag/+ tracheas as determined by Log2FC >|1|, p<0.05. C: Venn diagram intersecting genes differentially expressed in Foxg1Cre;Gli3T Flag/+ mutants with genes known to be involved in human and mouse tracheal chondrogenesis (Shefchek et al, 2020;Sinner et al, 2019). TM = tracheomalaciaassociated genes.…”

Improved characterisation of clinical text through ontology-based vocabulary expansion

“…Therefore, candidate synonyms that contained a colon or underscore were removed. The algorithm also removes labels sourced from GO-PLUS [21], MONDO [22], CCONT [23], and phenX [24], because we found these ontologies consistently produced incorrect synonyms. We also removed labels that include the input label as a substring, as these add no value to NER systems (as the smaller string would match, making the longer string redundant).…”