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Objective We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. Materials and Methods We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work. Results We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care. Discussion Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. Conclusion By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings. [ABSTRACT FROM AUTHOR]

Despite the availability of thousands of transit peptide (TP) primary sequences, the structural and/or physicochemical properties that determine TP recognition by components of the chloroplast translocon are not well understood. By combining a series of in vitro and in vivo experiments, we reveal that TP recognition is determined by sequence-independent interactions and vectorial-specific recognition domains. Using both native and reversed TPs for two well-studied precursors, small subunit of ribulose-1,5-bis-phosphate carboxylase/oxygenase, and ferredoxin, we exposed these two modes of recognition. Toc34 receptor (34-kD subunit of the translocon of the outer envelope) recognition in vitro, preprotein binding in organellar, precursor binding in vivo, and the recognition of TPs by the major stromal molecular motor Hsp70 are specific for the physicochemical properties of the TP. However, translocation in organellar and in vivo demonstrates strong specificity to recognition domain organization. This organization specificity correlates with the N-terminal placement of a strong Hsp70 recognition element. These results are discussed in light of how individual translocon components sequentially interact with the precursor during binding and translocation and helps explain the apparent lack of sequence conservation in chloroplast TPs. [ABSTRACT FROM AUTHOR]

Motivation: Set-based network similarity metrics are increasingly used to productively analyze genome-wide data. Conventional approaches, such as mean shortest path and clique-based metrics, have been useful but are not well suited to all applications. Computational scientists in other disciplines have developed communicability as a complementary metric. Network communicability considers all paths of all lengths between two network members. Given the success of previous network analyses of protein–protein interactions, we applied the concepts of network communicability to this problem. Here we show that our communicability implementation has advantages over traditional approaches. Overall, analyses suggest network communicability has considerable utility in analysis of large-scale biological networks.Availability and implementation: We provide our method as an R package for use in both human protein–protein interaction network analyses and analyses of arbitrary networks along with a tutorial at http://www.shawlab.org/NetComm/.Contact: cashaw@bcm.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Aggression is a complex social behavior that is widespread in nature. To date, only a limited number of genes that affect aggression have been identified, in large part because the complexity of the phenotype makes screening difficult and time-consuming regardless of the species that is studied. We discovered that aggressive group-housed Drosophila melanogaster males inflict damage on each other’s wings, and show that wing damage negatively affects their ability to fly and mate. Using this wing-damage phenotype, we screened males from ~1400 chemically mutagenized strains and found ~40 mutant strains with substantial wing damage. Five of these mutants also had increased aggressive behavior. To identify the causal mutation in one of our top aggressive strains, we used whole-genome sequencing and genomic duplication rescue strategies.We identified a novel mutation in the voltage-gated potassium channel Shaker (Sh) and show that a nearby previously identified Sh mutation also results in increased aggression. This simple screen can be used to dissect the molecular mechanisms underlying aggression. [ABSTRACT FROM AUTHOR]