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Newin vitrotesting strategies make it possible to design testing batteries for large numbers of environmental chemicals. Full utilization of the results requires knowledge of the underlying biological networks and the adverse outcome pathways (AOPs) that describe the route from early molecular perturbations to an adverse outcome. Curation of a formal AOP is a time-intensive process and a rate-limiting step to designing these test batteries. Here, we describe a method for integrating publicly available data in order to generate computationally predicted AOP (cpAOP) scaffolds, which can be leveraged by domain experts to shorten the time for formal AOP development. A network-based workflow was used to facilitate the integration of multiple data types to generate cpAOPs. Edges between graph entities were identified through direct experimental or literature information, or computationally inferred using frequent itemset mining. Data from the TG-GATEs and ToxCast programs were used to channel large-scale toxicogenomics information into a cpAOP network (cpAOPnet) of over 20 000 relationships describing connections between chemical treatments, phenotypes, and perturbed pathways as measured by differential gene expression and high-throughput screening targets. The resulting fatty liver cpAOPnet is available as a resource to the community. Subnetworks of cpAOPs for a reference chemical (carbon tetrachloride, CCl4) and outcome (fatty liver) were compared with published mechanistic descriptions. In both cases, the computational approaches approximated the manually curated AOPs. The cpAOPnet can be used for accelerating expert-curated AOP development and to identify pathway targets that lack genomic markers or high-throughput screening tests. It can also facilitate identification of key events for designing test batteries and for classification and grouping of chemicals for follow up testing.

Traditionally, phenotype-driven forward genetic plant mutant studies have been among the most successful approaches to revealing the roles of genes and their products and elucidating biochemical, developmental, and signaling pathways. A limitation is that it is time consuming, and sometimes technically challenging, to discover the gene responsible for a phenotype by map-based cloning or discovery of the insertion element. Reverse genetics is also an excellent way to associate genes with phenotypes, although an absence of detectable phenotypes often results when screening a small number of mutants with a limited range of phenotypic assays. The Arabidopsis Chloroplast 2010 Project (www.plastid.msu.edu) seeks synergy between forward and reverse genetics by screening thousands of sequence-indexed Arabidopsis (Arabidopsis thaliana) T-DNA insertion mutants for a diverse set of phenotypes. Results from this project are discussed that highlight the strengths and limitations of the approach. We describe the discovery of altered fatty acid desaturation phenotypes associated with mutants of At1g10310, previously described as a pterin aldehyde reductase in folate metabolism. Data are presented to show that growth, fatty acid, and chlorophyll fluorescence defects previously associated with antisense inhibition of synthesis of the family of acyl carrier proteins can be attributed to a single gene insertion in Acyl Carrier Protein4 (At4g25050). A variety of cautionary examples associated with the use of sequence-indexed T-DNA mutants are described, including the need to genotype all lines chosen for analysis (even when they number in the thousands) and the presence of tagged and untagged secondary mutations that can lead to the observed phenotypes.