Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target–disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive.

One sentence summary: T6P can be targeted through genetic and chemical methods for crop yield 10 improvements in different environments through the effect of T6P on carbon allocation and 11 biosynthetic pathways 12Significant increases in global food security require improving crop yields in favourable and 13 poor conditions alike. However, it is challenging to increase both the crop yield potential and yield 14 resilience simultaneously, since the mechanisms that determine productivity and stress tolerance are 15 typically inversely related. Carbon allocation and use may be amenable to improving yields in a range 16 of conditions. The interaction between trehalose 6-phosphate (T6P) and SnRK1 (SNF1-related/AMPK 17 protein kinases) significantly affects the regulation of carbon allocation and utilisation in plants. 18Targeting T6P appropriately to certain cell types, tissue types, and developmental stages results in an 31 SUCROSE AND TREHALOSE: THE YIN AND YANG OF CROP IMPROVEMENT 32Plants are the only organisms that synthesise both non-reducing disaccharides, trehalose and 33 sucrose. The ubiquity of both pathways in plants has been known for less than 20 years and was a 34 major revelation for those working on carbon metabolism, as well as plant scientists in general, given 35 the range of processes affected by the trehalose pathway. Plant metabolism is highly regulated. Part 36 of this regulation is through trehalose 6-phosphate (T6P) signalling that regulates metabolism in the 37 light of carbon availability and reprograms metabolism between anabolic or catabolic pathways 38 depending on the carbohydrate status of the plant. This discovery is also significant for understanding 39 the regulation of growth and development by carbon supply. Furthermore, the trehalose pathway may 40 widely impact crop improvement. Crops are not yet optimised to maximize their biosynthetic pathways 41 for yield in sinks and growth recovery that are promoted by high T6P, and for mobilisation of reserves 42 and sugar transport which can enable resilience that are promoted by low T6P. 43Both the trehalose and sucrose biosynthesis pathways draw from a pool of core metabolites, 44 from which the carbon skeletons for all cellular components are also made (Paul et al. 2008 procedures to measure the abundance of T6P and trehalose (Lunn et al. 2006; Carillo et al. 2013; 51 Delatte et al. 2009;Mata et al. 2016). The capacity to synthesise trehalose in 52 plants began to become apparent as the associated plant genes were identified (Blazquez et al. 1998; 53 Vogel et al. 1998). Subsequent publication of the Arabidopsis genome showed an abundance of both 54 trehalose phosphate synthase (TPS) and trehalose phosphate phosphatase (TPP) gene families with 55 11 and 10 members respectively (Leyman et al. 2001). 56It is likely that T6P is a specific signal indicating sucrose abundance (Lunn et al. 2006; Nunes 57 et al. 2013a). T6P and sucrose levels are correlated in many tissues e.g. Arabidopsis and wheat 72TPSs have yet to be resolve...

The Open Targets Platform (https://platform.opentargets.org/) is an open source resource to systematically assist drug target identification and prioritisation using publicly available data. Since our last update, we have reimagined, redesigned, and rebuilt the Platform in order to streamline data integration and harmonisation, expand the ways in which users can explore the data, and improve the user experience. The gene–disease causal evidence has been enhanced and expanded to better capture disease causality across rare, common, and somatic diseases. For target and drug annotations, we have incorporated new features that help assess target safety and tractability, including genetic constraint, PROTACtability assessments, and AlphaFold structure predictions. We have also introduced new machine learning applications for knowledge extraction from the published literature, clinical trial information, and drug labels. The new technologies and frameworks introduced since the last update will ease the introduction of new features and the creation of separate instances of the Platform adapted to user requirements. Our new Community forum, expanded training materials, and outreach programme support our users in a range of use cases.