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The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.

Background Oculocutaneous albinism (OCA) is caused by a group of genetically heterogeneous inherited defects that result in the loss of pigmentation in the eyes, skin and hair. Mutations in the TYR, OCA2, TYRP1 and SLC45A2 genes have been shown to cause isolated OCA. No comprehensive analysis has been conducted to study the spectrum of OCA alleles prevailing in Pakistani albino populations. Methods We enrolled 40 large Pakistani families and screened them for OCA genes and a candidate gene, SLC24A5. Protein function effects were evaluated using in silico prediction algorithms and ex vivo studies in human melanocytes. The effects of splice-site mutations were determined using an exon-trapping assay. Results Screening of the TYR gene revealed four known (p.Arg299His, p.Pro406Leu, p.Gly419Arg, p.Arg278*) and three novel mutations (p.Pro21Leu, p.Cys35Arg, p.Tyr411His) in ten families. Ex vivo studies revealed the retention of an EGFP-tagged mutant (p.Pro21Leu, p.Cys35Arg or p.Tyr411His) tyrosinase in the endoplasmic reticulum (ER) at 37°C, but a significant fraction of p.Cys35Arg and p.Tyr411His left the ER in cells grown at a permissive temperature (31°C). Three novel (p.Asp486Tyr, p.Leu527Arg, c.1045-15 T > G) and two known mutations (p.Pro743Leu, p.Ala787Thr) of OCA2 were found in fourteen families. Exon-trapping assays with a construct containing a novel c.1045-15 T > G mutation revealed an error in splicing. No mutation in TYRP1, SLC45A2, and SLC24A5 was found in the remaining 16 families. Clinical evaluation of the families segregating either TYR or OCA2 mutations showed nystagmus, photophobia, and loss of pigmentation in the skin or hair follicles. Most of the affected individuals had grayish-blue colored eyes. Conclusions Our results show that ten and fourteen families harbored mutations in the TYR and OCA2 genes, respectively. Our findings, along with the results of previous studies, indicate that the p.Cys35Arg, p.Arg278* and p.Gly419Arg alleles of TYR and the p.Asp486Tyr and c.1045-15 T > G alleles of OCA2 are the most common causes of OCA in Pakistani families. To the best of our knowledge, this study represents the first documentation of OCA2 alleles in the Pakistani population. A significant proportion of our cohort did not have mutations in known OCA genes. Overall, our study contributes to the development of genetic testing protocols and genetic counseling for OCA in Pakistani families.

Background High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course of months and years, often without the controls needed to compare directly across the dataset. Few methods are available to facilitate comparisons of high throughput metabolic data generated in batches where explicit in-group controls for normalization are lacking. Results Here we describe MIPHENO (Mutant Identification by Probabilistic High throughput-Enabled Normalization), an approach for post-hoc normalization of quantitative first-pass screening data in the absence of explicit in-group controls. This approach includes a quality control step and facilitates cross-experiment comparisons that decrease the false non-discovery rates, while maintaining the high accuracy needed to limit false positives in first-pass screening. Results from simulation show an improvement in both accuracy and false non-discovery rate over a range of population parameters (p < 2.2 × 10-16) and a modest but significant (p < 2.2 × 10-16) improvement in area under the receiver operator characteristic curve of 0.955 for MIPHENO vs 0.923 for a group-based statistic (z-score). Analysis of the high throughput phenotypic data from the Arabidopsis Chloroplast 2010 Project (http://www.plastid.msu.edu/) showed ~ 4-fold increase in the ability to detect previously described or expected phenotypes over the group based statistic. Conclusions Results demonstrate MIPHENO offers substantial benefit in improving the ability to detect putative mutant phenotypes from post-hoc analysis of large data sets. Additionally, it facilitates data interpretation and permits cross-dataset comparison where group-based controls are missing. MIPHENO is applicable to a wide range of high throughput screenings and the code is freely available as Additional file 1 as well as through an R package in CRAN.