ALBERT

Description: Fanconi anemia (FA) is a chromosome instability syndrome characterized by increased cancer predisposition. Specifically, the FA pathway functions to protect genome stability during DNA replication. The central FA pathway protein, FANCD2, locates to stalled replication forks and recruits homologous recombination (HR) factors such as CtBP interacting protein (CtIP) to promote replication fork restart while suppressing new origin firing. Here, we identify alpha-thalassemia retardation syndrome X-linked (ATRX) as a novel physical and functional interaction partner of FANCD2. ATRX is a chromatin remodeler that forms a complex with Death domain-associated protein 6 (DAXX) to deposit the histone variant H3.3 into specific genomic regions. Intriguingly, ATRX was recently implicated in replication fork recovery; however, the underlying mechanism(s) remained incompletely understood. Our findings demonstrate that ATRX forms a constitutive protein complex with FANCD2 and protects FANCD2 from proteasomal degradation. ATRX and FANCD2 localize to stalled replication forks where they cooperate to recruit CtIP and promote MRE11 exonuclease-dependent fork restart while suppressing the firing of new replication origins. Remarkably, replication restart requires the concerted histone H3 chaperone activities of ATRX/DAXX and FANCD2, demonstrating that coordinated histone H3 variant deposition is a crucial event during the reinitiation of replicative DNA synthesis. Lastly, ATRX also cooperates with FANCD2 to promote the HR-dependent repair of directly induced DNA double-stranded breaks. We propose that ATRX is a novel functional partner of FANCD2 to promote histone deposition-dependent HR mechanisms in S-phase.

Description: 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.

Description: Hypothesis generation is a critical step in research and a cornerstone in the rare disease field. Research is most efficient when those hypotheses are based on the entirety of knowledge known to date. Systematic review articles are commonly used in biomedicine to summarize existing knowledge and contextualize experimental data. But the information contained within review articles is typically only expressed as free-text, which is difficult to use computationally. Researchers struggle to navigate, collect and remix prior knowledge as it is scattered in several silos without seamless integration and access. This lack of a structured information framework hinders research by both experimental and computational scientists. To better organize knowledge and data, we built a structured review article that is specifically focused on NGLY1 Deficiency, an ultra-rare genetic disease first reported in 2012. We represented this structured review as a knowledge graph and then stored this knowledge graph in a Neo4j database to simplify dissemination, querying and visualization of the network. Relative to free-text, this structured review better promotes the principles of findability, accessibility, interoperability and reusability (FAIR). In collaboration with domain experts in NGLY1 Deficiency, we demonstrate how this resource can improve the efficiency and comprehensiveness of hypothesis generation. We also developed a read–write interface that allows domain experts to contribute FAIR structured knowledge to this community resource. In contrast to traditional free-text review articles, this structured review exists as a living knowledge graph that is curated by humans and accessible to computational analyses. Finally, we have generalized this workflow into modular and repurposable components that can be applied to other domain areas. This NGLY1 Deficiency-focused network is publicly available at http://ngly1graph.org/. Availability and implementation Database URL: http://ngly1graph.org/. Network data files are at: https://github.com/SuLab/ngly1-graph and source code at: https://github.com/SuLab/bioknowledge-reviewer. Contact asu@scripps.edu